From 28ff343201fea5bef07c3e3031400f6d10c175e5 Mon Sep 17 00:00:00 2001 From: JordiManyer Date: Tue, 12 Mar 2024 12:57:20 +1100 Subject: [PATCH 01/90] Added mem leak script --- scripts/_dev/mem_leak.jl | 114 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 114 insertions(+) create mode 100644 scripts/_dev/mem_leak.jl diff --git a/scripts/_dev/mem_leak.jl b/scripts/_dev/mem_leak.jl new file mode 100644 index 00000000..f4fc3270 --- /dev/null +++ b/scripts/_dev/mem_leak.jl @@ -0,0 +1,114 @@ +using Gridap, LevelSetTopOpt + +# FE parameters +order = 1 # Finite element order +xmax=ymax=zmax=1.0 # Domain size +dom = (0,xmax,0,ymax,0,zmax) # Bounding domain +el_size = (40,40,40) # Mesh partition size +prop_Γ_N = 0.4 # Γ_N size parameter +prop_Γ_D = 0.2 # Γ_D size parameter +f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function + (ymax/2-ymax*prop_Γ_N/4 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/4 + eps()) && + (zmax/2-zmax*prop_Γ_N/4 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/4 + eps()) +f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function + (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps()) && + (x[3] <= zmax*prop_Γ_D + eps() || x[3] >= zmax-zmax*prop_Γ_D - eps()) +# FD parameters +γ = 0.1 # HJ equation time step coefficient +γ_reinit = 0.5 # Reinit. equation time step coefficient +max_steps = floor(Int,minimum(el_size)/3) # Max steps for advection +tol = 1/(2order^2)*prod(inv,minimum(el_size)) # Advection tolerance +# Problem parameters +κ = 1 # Diffusivity +g = 1 # Heat flow in +vf = 0.4 # Volume fraction constraint +lsf_func = initial_lsf(4,0.2) # Initial level set function +iter_mod = 10 # Output VTK files every 10th iteration + +# Model +model = CartesianDiscreteModel(dom,el_size); +update_labels!(1,model,f_Γ_D,"Gamma_D") +update_labels!(2,model,f_Γ_N,"Gamma_N") +# Triangulation and measures +Ω = Triangulation(model) +Γ_N = BoundaryTriangulation(model,tags="Gamma_N") +dΩ = Measure(Ω,2*order) +dΓ_N = Measure(Γ_N,2*order) +# Spaces +reffe = ReferenceFE(lagrangian,Float64,order) +V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) +U = TrialFESpace(V,0.0) +V_φ = TestFESpace(model,reffe) +V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) +U_reg = TrialFESpace(V_reg,0) +# Level set and interpolator +φh = interpolate(lsf_func,V_φ) +interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) +I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ +# Weak formulation +a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ +l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N +state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) +# Objective and constraints +J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ +dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ +vol_D = sum(∫(1)dΩ) +C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ +dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ +pcfs = PDEConstrainedFunctionals(J,[C],state_map,analytic_dJ=dJ,analytic_dC=[dC]) +# Velocity extension +α = 4*maximum(get_el_Δ(model)) +a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ +vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) +# Finite difference scheme +scheme = FirstOrderStencil(length(el_size),Float64) +stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) +# Optimiser +optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) +# Solve +for i = 1:10 + LevelSetTopOpt.rrule(state_map,φh) +end + +evaluate!(pcfs,φh); +uh = get_state(state_map) + +GC.gc() +Sys.free_memory() / 2^20 + +for i = 1:10 + begin + u = LevelSetTopOpt.forward_solve!(state_map,φh); + uh = FEFunction(LevelSetTopOpt.get_trial_space(state_map),u); + # LevelSetTopOpt.update_adjoint_caches!(state_map,uh,φh); + end; +end; + +Sys.free_memory() / 2^20 + +GC.gc() +Sys.free_memory() / 2^20 + +for i = 1:10 + begin + # u = LevelSetTopOpt.forward_solve!(state_map,φh); + # uh = FEFunction(LevelSetTopOpt.get_trial_space(state_map),u); + + LevelSetTopOpt.update_adjoint_caches!(state_map,uh,φh); + end; +end; + +Sys.free_memory() / 2^20 + +GC.gc() +Sys.free_memory() / 2^20 + +for i = 1:10 + begin + u = LevelSetTopOpt.forward_solve!(state_map,φh); + uh = FEFunction(LevelSetTopOpt.get_trial_space(state_map),u); + LevelSetTopOpt.update_adjoint_caches!(state_map,uh,φh); + end; +end; + +Sys.free_memory() / 2^20 From ab8127a05a5989eda2d29a4fa5a10b105b7cfdf8 Mon Sep 17 00:00:00 2001 From: JordiManyer Date: Tue, 12 Mar 2024 12:58:22 +1100 Subject: [PATCH 02/90] Minor --- scripts/_dev/mem_leak.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/scripts/_dev/mem_leak.jl b/scripts/_dev/mem_leak.jl index f4fc3270..af9a2b28 100644 --- a/scripts/_dev/mem_leak.jl +++ b/scripts/_dev/mem_leak.jl @@ -4,7 +4,7 @@ using Gridap, LevelSetTopOpt order = 1 # Finite element order xmax=ymax=zmax=1.0 # Domain size dom = (0,xmax,0,ymax,0,zmax) # Bounding domain -el_size = (40,40,40) # Mesh partition size +el_size = (10,10,10) # Mesh partition size prop_Γ_N = 0.4 # Γ_N size parameter prop_Γ_D = 0.2 # Γ_D size parameter f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function @@ -17,7 +17,7 @@ f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator func γ = 0.1 # HJ equation time step coefficient γ_reinit = 0.5 # Reinit. equation time step coefficient max_steps = floor(Int,minimum(el_size)/3) # Max steps for advection -tol = 1/(2order^2)*prod(inv,minimum(el_size)) # Advection tolerance +tol = 1/(2*order^2)*prod(inv,minimum(el_size)) # Advection tolerance # Problem parameters κ = 1 # Diffusivity g = 1 # Heat flow in From 7907edb9fb117f35d5f243cf62fe1368e72c056c Mon Sep 17 00:00:00 2001 From: JordiManyer Date: Tue, 12 Mar 2024 13:03:09 +1100 Subject: [PATCH 03/90] Better gitignores --- .gitignore | 2 -- results/.gitignore | 2 ++ results/empty | 1 - 3 files changed, 2 insertions(+), 3 deletions(-) create mode 100644 results/.gitignore delete mode 100644 results/empty diff --git a/.gitignore b/.gitignore index b8aba4f7..d43b6663 100644 --- a/.gitignore +++ b/.gitignore @@ -19,8 +19,6 @@ deps/src/ # Build artifacts for creating documentation generated by the Documenter package docs/build/ docs/site/ -Results/* -results/* # File generated by Pkg, the package manager, based on a corresponding Project.toml # It records a fixed state of all packages used by the project. As such, it should not be diff --git a/results/.gitignore b/results/.gitignore new file mode 100644 index 00000000..c96a04f0 --- /dev/null +++ b/results/.gitignore @@ -0,0 +1,2 @@ +* +!.gitignore \ No newline at end of file diff --git a/results/empty b/results/empty deleted file mode 100644 index 0519ecba..00000000 --- a/results/empty +++ /dev/null @@ -1 +0,0 @@ - \ No newline at end of file From 7f8003a238675ba42edb085e2aa15dda2fd9fe93 Mon Sep 17 00:00:00 2001 From: JordiManyer Date: Thu, 14 Mar 2024 09:35:59 +1100 Subject: [PATCH 04/90] Bugfix: RepeatingAffineFEMap returned wrong U-assembler --- src/ChainRules.jl | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/src/ChainRules.jl b/src/ChainRules.jl index 900d35db..a3ba34f6 100644 --- a/src/ChainRules.jl +++ b/src/ChainRules.jl @@ -705,10 +705,15 @@ struct RepeatingAffineFEStateMap{A,B,C,D,E,F,G} <: AbstractFEStateMap @check nblocks == length(l) spaces_0 = (U0,V0) + assem_U0 = assem_U + biform = IntegrandWithMeasure(a,dΩ) liforms = map(li -> IntegrandWithMeasure(li,dΩ),l) U, V = repeat_spaces(nblocks,U0,V0) spaces = (U,V,V_φ,U_reg) + assem_U = SparseMatrixAssembler( + get_matrix_type(assem_U0),get_vector_type(assem_V0),U,V,get_assembly_strategy(assem_U0) + ) ## Pullback cache uhd = zero(U0) @@ -802,9 +807,9 @@ function update_adjoint_caches!(φ_to_u::RepeatingAffineFEStateMap,uh,φh) return φ_to_u.adj_caches end -function adjoint_solve!(φ_to_u::RepeatingAffineFEStateMap,du::AbstractVector) +function adjoint_solve!(φ_to_u::RepeatingAffineFEStateMap,du::AbstractBlockVector) adjoint_ns, _, adjoint_x, _ = φ_to_u.adj_caches - map(blocks(adjoint_x),du) do xi, dui + map(blocks(adjoint_x),blocks(du)) do xi, dui solve!(xi,adjoint_ns,dui) end return adjoint_x From 30837bf457cd1e23d1c6079b3185c8044e12d454 Mon Sep 17 00:00:00 2001 From: JordiManyer Date: Thu, 14 Mar 2024 09:47:37 +1100 Subject: [PATCH 05/90] Minor --- scripts/Serial/inverse_homenisation_ALM.jl | 2 +- src/ChainRules.jl | 16 ++++++++-------- 2 files changed, 9 insertions(+), 9 deletions(-) diff --git a/scripts/Serial/inverse_homenisation_ALM.jl b/scripts/Serial/inverse_homenisation_ALM.jl index c480820d..f6b5ccbf 100644 --- a/scripts/Serial/inverse_homenisation_ALM.jl +++ b/scripts/Serial/inverse_homenisation_ALM.jl @@ -25,7 +25,7 @@ function main() α_coeff = 4 vf = 0.5 path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM" - mkdir(path) + !isdir(path) && mkdir(path) ## FE Setup model = CartesianDiscreteModel(dom,el_size,isperiodic=(true,true)) diff --git a/src/ChainRules.jl b/src/ChainRules.jl index a3ba34f6..7a6b0c3f 100644 --- a/src/ChainRules.jl +++ b/src/ChainRules.jl @@ -712,7 +712,7 @@ struct RepeatingAffineFEStateMap{A,B,C,D,E,F,G} <: AbstractFEStateMap U, V = repeat_spaces(nblocks,U0,V0) spaces = (U,V,V_φ,U_reg) assem_U = SparseMatrixAssembler( - get_matrix_type(assem_U0),get_vector_type(assem_V0),U,V,get_assembly_strategy(assem_U0) + get_matrix_type(assem_U0),get_vector_type(assem_U0),U,V,FESpaces.get_assembly_strategy(assem_U0) ) ## Pullback cache @@ -725,12 +725,12 @@ struct RepeatingAffineFEStateMap{A,B,C,D,E,F,G} <: AbstractFEStateMap plb_caches = (dudφ_vec,assem_deriv) ## Forward cache - K = assemble_matrix((u,v) -> biform(u,v,φh),assem_U,U0,V0) + K = assemble_matrix((u,v) -> biform(u,v,φh),assem_U0,U0,V0) b = allocate_in_range(K); fill!(b,zero(eltype(b))) b0 = allocate_in_range(K); fill!(b0,zero(eltype(b0))) x = mortar(map(i -> allocate_in_domain(K), 1:nblocks)); fill!(x,zero(eltype(x))) ns = numerical_setup(symbolic_setup(ls,K),K) - fwd_caches = (ns,K,b,x,uhd,assem_U,b0) + fwd_caches = (ns,K,b,x,uhd,assem_U0,b0,assem_U) ## Adjoint cache adjoint_K = assemble_matrix((u,v)->biform(v,u,φh),assem_adjoint,V0,U0) @@ -764,26 +764,26 @@ end get_state(m::RepeatingAffineFEStateMap) = FEFunction(get_trial_space(m),m.fwd_caches[4]) get_measure(m::RepeatingAffineFEStateMap) = m.biform.dΩ get_spaces(m::RepeatingAffineFEStateMap) = m.spaces -get_assemblers(m::RepeatingAffineFEStateMap) = (m.fwd_caches[6],m.plb_caches[2],m.adj_caches[4]) +get_assemblers(m::RepeatingAffineFEStateMap) = (m.fwd_caches[8],m.plb_caches[2],m.adj_caches[4]) function forward_solve!(φ_to_u::RepeatingAffineFEStateMap,φh) biform, liforms = φ_to_u.biform, φ_to_u.liform U0, V0 = φ_to_u.spaces_0 - ns, K, b, x, uhd, assem_U, b0 = φ_to_u.fwd_caches + ns, K, b, x, uhd, assem_U0, b0, _ = φ_to_u.fwd_caches a_fwd(u,v) = biform(u,v,φh) - assemble_matrix!(a_fwd,K,assem_U,U0,V0) + assemble_matrix!(a_fwd,K,assem_U0,U0,V0) numerical_setup!(ns,K) l0_fwd(v) = a_fwd(uhd,v) - assemble_vector!(l0_fwd,b0,assem_U,V0) + assemble_vector!(l0_fwd,b0,assem_U0,V0) rmul!(b0,-1) v = get_fe_basis(V0) map(blocks(x),liforms) do xi, li copy!(b,b0) vecdata = collect_cell_vector(V0,li(v,φh)) - assemble_vector_add!(b,assem_U,vecdata) + assemble_vector_add!(b,assem_U0,vecdata) solve!(xi,ns,b) end return x From dac40c66a5a322e2b93236b6631b8ca5f4d7d1ae Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 14 Mar 2024 13:19:59 +1000 Subject: [PATCH 06/90] clean up and fix --- scripts/MPI/3d_inverse_homenisation_ALM.jl | 18 +++++++----------- scripts/Serial/inverse_homenisation_ALM.jl | 14 ++++++-------- src/ChainRules.jl | 4 +++- 3 files changed, 16 insertions(+), 20 deletions(-) diff --git a/scripts/MPI/3d_inverse_homenisation_ALM.jl b/scripts/MPI/3d_inverse_homenisation_ALM.jl index af24bfba..b57d1785 100644 --- a/scripts/MPI/3d_inverse_homenisation_ALM.jl +++ b/scripts/MPI/3d_inverse_homenisation_ALM.jl @@ -67,16 +67,12 @@ function main(mesh_partition,distribute,el_size) l = [(v,φ,dΩ) -> ∫(-(I ∘ φ) * C ⊙ εᴹ[i] ⊙ ε(v))dΩ for i in 1:6] ## Optimisation functionals - _C(C,ε_p,ε_q) = C ⊙ ε_p ⊙ ε_q; - - _K(C,u,εᴹ) = (_C(C,ε(u[1])+εᴹ[1],εᴹ[1]) + _C(C,ε(u[2])+εᴹ[2],εᴹ[2]) + _C(C,ε(u[3])+εᴹ[3],εᴹ[3]) + - 2(_C(C,ε(u[1])+εᴹ[1],εᴹ[2]) + _C(C,ε(u[1])+εᴹ[1],εᴹ[3]) + _C(C,ε(u[2])+εᴹ[2],εᴹ[3])))/9 - - _v_K(C,u,εᴹ) = (_C(C,ε(u[1])+εᴹ[1],ε(u[1])+εᴹ[1]) + _C(C,ε(u[2])+εᴹ[2],ε(u[2])+εᴹ[2]) + _C(C,ε(u[3])+εᴹ[3],ε(u[3])+εᴹ[3]) + - 2(_C(C,ε(u[1])+εᴹ[1],ε(u[2])+εᴹ[2]) + _C(C,ε(u[1])+εᴹ[1],ε(u[3])+εᴹ[3]) + _C(C,ε(u[2])+εᴹ[2],ε(u[3])+εᴹ[3])))/9 - - J(u,φ,dΩ) = ∫(-(I ∘ φ)*_K(C,u,εᴹ))dΩ - dJ(q,u,φ,dΩ) = ∫(_v_K(C,u,εᴹ)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + Cᴴ(r,s,u,φ,dΩ) = ∫((I ∘ φ)*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ εᴹ[s]))dΩ + dCᴴ(r,s,q,u,φ,dΩ) = ∫(q*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ (ε(u[s])+εᴹ[s]))*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + κ(u,φ,dΩ) = -1/9*(Cᴴ(1,1,u,φ,dΩ)+Cᴴ(2,2,u,φ,dΩ)+Cᴴ(3,3,u,φ,dΩ)+ + 2*(Cᴴ(1,2,u,φ,dΩ)+Cᴴ(1,3,u,φ,dΩ)+Cᴴ(2,3,u,φ,dΩ))) + dκ(q,u,φ,dΩ) = 1/9*(dCᴴ(1,1,q,u,φ,dΩ)+dCᴴ(2,2,q,u,φ,dΩ)+dCᴴ(3,3,q,u,φ,dΩ)+ + 2*(dCᴴ(1,2,q,u,φ,dΩ)+dCᴴ(1,3,q,u,φ,dΩ)+dCᴴ(2,3,q,u,φ,dΩ))) Vol(u,φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; dVol(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ @@ -95,7 +91,7 @@ function main(mesh_partition,distribute,el_size) assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), ls = solver, adjoint_ls = solver ) - pcfs = PDEConstrainedFunctionals(J,[Vol],state_map;analytic_dJ=dJ,analytic_dC=[dVol]) + pcfs = PDEConstrainedFunctionals(κ,[Vol],state_map;analytic_dJ=dκ,analytic_dC=[dVol]) ## Hilbertian extension-regularisation problems α = α_coeff*maximum(el_Δ) diff --git a/scripts/Serial/inverse_homenisation_ALM.jl b/scripts/Serial/inverse_homenisation_ALM.jl index c480820d..4dcf8b1f 100644 --- a/scripts/Serial/inverse_homenisation_ALM.jl +++ b/scripts/Serial/inverse_homenisation_ALM.jl @@ -24,7 +24,7 @@ function main() η_coeff = 2 α_coeff = 4 vf = 0.5 - path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM" + path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM_new" mkdir(path) ## FE Setup @@ -62,12 +62,10 @@ function main() l = [(v,φ,dΩ) -> ∫(-(I ∘ φ)* C ⊙ εᴹ[i] ⊙ ε(v))dΩ for i in 1:3] ## Optimisation functionals - _C(C,ε_p,ε_q) = C ⊙ ε_p ⊙ ε_q - _K(C,(u1,u2,u3),εᴹ) = (_C(C,ε(u1)+εᴹ[1],εᴹ[1]) + _C(C,ε(u2)+εᴹ[2],εᴹ[2]) + 2*_C(C,ε(u1)+εᴹ[1],εᴹ[2]))/4 - _v_K(C,(u1,u2,u3),εᴹ) = (_C(C,ε(u1)+εᴹ[1],ε(u1)+εᴹ[1]) + _C(C,ε(u2)+εᴹ[2],ε(u2)+εᴹ[2]) + 2*_C(C,ε(u1)+εᴹ[1],ε(u2)+εᴹ[2]))/4 - - J(u,φ,dΩ) = ∫(-(I ∘ φ)*_K(C,u,εᴹ))dΩ - dJ(q,u,φ,dΩ) = ∫(_v_K(C,u,εᴹ)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + Cᴴ(r,s,u,φ,dΩ) = ∫((I ∘ φ)*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ εᴹ[s]))dΩ + dCᴴ(r,s,q,u,φ,dΩ) = ∫(q*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ (ε(u[s])+εᴹ[s]))*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + κ(u,φ,dΩ) = -1/4*(Cᴴ(1,1,u,φ,dΩ)+Cᴴ(2,2,u,φ,dΩ)+2*Cᴴ(1,2,u,φ,dΩ)) + dκ(q,u,φ,dΩ) = 1/4*(dCᴴ(1,1,q,u,φ,dΩ)+dCᴴ(2,2,q,u,φ,dΩ)+2*dCᴴ(1,2,q,u,φ,dΩ)) Vol(u,φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ dVol(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ @@ -76,7 +74,7 @@ function main() ## Setup solver and FE operators state_map = RepeatingAffineFEStateMap(3,a,l,U,V,V_φ,U_reg,φh,dΩ) - pcfs = PDEConstrainedFunctionals(J,[Vol],state_map;analytic_dJ=dJ,analytic_dC=[dVol]) + pcfs = PDEConstrainedFunctionals(κ,[Vol],state_map;analytic_dJ=dκ,analytic_dC=[dVol]) ## Hilbertian extension-regularisation problems α = α_coeff*maximum(el_Δ) diff --git a/src/ChainRules.jl b/src/ChainRules.jl index 900d35db..d9387dbe 100644 --- a/src/ChainRules.jl +++ b/src/ChainRules.jl @@ -49,7 +49,9 @@ function Gridap.gradient(F::IntegrandWithMeasure,uh::Vector,K::Int) local_fields = map(local_views,uh) |> to_parray_of_arrays local_measures = map(local_views,F.dΩ) |> to_parray_of_arrays contribs = map(local_measures,local_fields) do dΩ,lf - _f = u -> F.F(lf[1:K-1]...,u,lf[K+1:end]...,dΩ...) + # TODO: Remove second term below, this is a fix for the problem discussed in + # https://github.com/zjwegert/LSTO_Distributed/issues/46 + _f = u -> F.F(lf[1:K-1]...,u,lf[K+1:end]...,dΩ...) #+ ∑(∫(0)dΩ[i] for i = 1:length(dΩ)) return Gridap.Fields.gradient(_f,lf[K]) end return DistributedDomainContribution(contribs) From 274a03f814381d10c90d5755aa3b6ede091e6779 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 14 Mar 2024 13:28:25 +1000 Subject: [PATCH 07/90] fix name --- scripts/Serial/inverse_homenisation_ALM.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/Serial/inverse_homenisation_ALM.jl b/scripts/Serial/inverse_homenisation_ALM.jl index 4dcf8b1f..5090f339 100644 --- a/scripts/Serial/inverse_homenisation_ALM.jl +++ b/scripts/Serial/inverse_homenisation_ALM.jl @@ -24,7 +24,7 @@ function main() η_coeff = 2 α_coeff = 4 vf = 0.5 - path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM_new" + path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM" mkdir(path) ## FE Setup From f548e1e5d939ae7c4f7857d27689a769fbc9564f Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 14 Mar 2024 14:15:02 +1000 Subject: [PATCH 08/90] fix and add scripts for new issue --- scripts/MPI/3d_inverse_homenisation_ALM.jl | 4 +- scripts/Serial/inverse_homenisation_ALM.jl | 4 +- scripts/_dev/bug_issue_46/thermal_MPI.jl | 91 +++++++++++++++++++++ scripts/_dev/bug_issue_46/thermal_serial.jl | 87 ++++++++++++++++++++ 4 files changed, 182 insertions(+), 4 deletions(-) create mode 100644 scripts/_dev/bug_issue_46/thermal_MPI.jl create mode 100644 scripts/_dev/bug_issue_46/thermal_serial.jl diff --git a/scripts/MPI/3d_inverse_homenisation_ALM.jl b/scripts/MPI/3d_inverse_homenisation_ALM.jl index b57d1785..488ca57e 100644 --- a/scripts/MPI/3d_inverse_homenisation_ALM.jl +++ b/scripts/MPI/3d_inverse_homenisation_ALM.jl @@ -68,10 +68,10 @@ function main(mesh_partition,distribute,el_size) ## Optimisation functionals Cᴴ(r,s,u,φ,dΩ) = ∫((I ∘ φ)*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ εᴹ[s]))dΩ - dCᴴ(r,s,q,u,φ,dΩ) = ∫(q*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ (ε(u[s])+εᴹ[s]))*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + dCᴴ(r,s,q,u,φ,dΩ) = ∫(-q*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ (ε(u[s])+εᴹ[s]))*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ κ(u,φ,dΩ) = -1/9*(Cᴴ(1,1,u,φ,dΩ)+Cᴴ(2,2,u,φ,dΩ)+Cᴴ(3,3,u,φ,dΩ)+ 2*(Cᴴ(1,2,u,φ,dΩ)+Cᴴ(1,3,u,φ,dΩ)+Cᴴ(2,3,u,φ,dΩ))) - dκ(q,u,φ,dΩ) = 1/9*(dCᴴ(1,1,q,u,φ,dΩ)+dCᴴ(2,2,q,u,φ,dΩ)+dCᴴ(3,3,q,u,φ,dΩ)+ + dκ(q,u,φ,dΩ) = -1/9*(dCᴴ(1,1,q,u,φ,dΩ)+dCᴴ(2,2,q,u,φ,dΩ)+dCᴴ(3,3,q,u,φ,dΩ)+ 2*(dCᴴ(1,2,q,u,φ,dΩ)+dCᴴ(1,3,q,u,φ,dΩ)+dCᴴ(2,3,q,u,φ,dΩ))) Vol(u,φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; dVol(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ diff --git a/scripts/Serial/inverse_homenisation_ALM.jl b/scripts/Serial/inverse_homenisation_ALM.jl index 5090f339..d4d60aa8 100644 --- a/scripts/Serial/inverse_homenisation_ALM.jl +++ b/scripts/Serial/inverse_homenisation_ALM.jl @@ -63,9 +63,9 @@ function main() ## Optimisation functionals Cᴴ(r,s,u,φ,dΩ) = ∫((I ∘ φ)*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ εᴹ[s]))dΩ - dCᴴ(r,s,q,u,φ,dΩ) = ∫(q*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ (ε(u[s])+εᴹ[s]))*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + dCᴴ(r,s,q,u,φ,dΩ) = ∫(-q*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ (ε(u[s])+εᴹ[s]))*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ κ(u,φ,dΩ) = -1/4*(Cᴴ(1,1,u,φ,dΩ)+Cᴴ(2,2,u,φ,dΩ)+2*Cᴴ(1,2,u,φ,dΩ)) - dκ(q,u,φ,dΩ) = 1/4*(dCᴴ(1,1,q,u,φ,dΩ)+dCᴴ(2,2,q,u,φ,dΩ)+2*dCᴴ(1,2,q,u,φ,dΩ)) + dκ(q,u,φ,dΩ) = -1/4*(dCᴴ(1,1,q,u,φ,dΩ)+dCᴴ(2,2,q,u,φ,dΩ)+2*dCᴴ(1,2,q,u,φ,dΩ)) Vol(u,φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ dVol(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ diff --git a/scripts/_dev/bug_issue_46/thermal_MPI.jl b/scripts/_dev/bug_issue_46/thermal_MPI.jl new file mode 100644 index 00000000..2e4596ee --- /dev/null +++ b/scripts/_dev/bug_issue_46/thermal_MPI.jl @@ -0,0 +1,91 @@ +using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, + SparseMatricesCSR + +function main(mesh_partition,distribute,use_l::Bool) + ranks = distribute(LinearIndices((prod(mesh_partition),))) + # FE parameters + order = 1 # Finite element order + xmax = ymax = 1.0 # Domain size + dom = (0,xmax,0,ymax) # Bounding domain + el_size = (200,200) # Mesh partition size + prop_Γ_N = 0.2 # Γ_N size parameter + prop_Γ_D = 0.2 # Γ_D size parameter + f_Γ_N(x) = (x[1] ≈ xmax && # Γ_N indicator function + ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0 && # Γ_D indicator function + (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) # @$\lvert\lvert$@ + # FD parameters + γ = 0.1 # HJ eqn time step coeff + γ_reinit = 0.5 # Reinit. eqn time step coeff + max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + tol = 1/(5order^2)/minimum(el_size) # Advection tolerance + # Problem parameters + κ = 1 # Diffusivity + g = 1 # Heat flow in + vf = 0.4 # Volume fraction constraint + lsf_func = initial_lsf(4,0.2) # Initial level set function + iter_mod = 10 # VTK Output modulo + path = "./results/AD_tut1_MPI_lobj_$use_l/" # Output path + i_am_main(ranks) && mkpath(path) # Create path + # Model + model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); + update_labels!(1,model,f_Γ_D,"Gamma_D") + update_labels!(2,model,f_Γ_N,"Gamma_N") + # Triangulation and measures + Ω = Triangulation(model) + Γ_N = BoundaryTriangulation(model,tags="Gamma_N") + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + # Spaces + reffe = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,0.0) + V_φ = TestFESpace(model,reffe) + V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) + U_reg = TrialFESpace(V_reg,0) + # Level set and interpolator + φh = interpolate(lsf_func,V_φ) + interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + # Weak formulation + a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ + l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N + state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) + # Objective and constraints + J(u,φ,dΩ,dΓ_N) = if use_l + ∫(g*u)dΓ_N #+ ∫(0)dΩ + else + ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ + end + dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + vol_D = sum(∫(1)dΩ) + C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C],state_map) + # Velocity extension + α = 4*maximum(get_el_Δ(model)) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ + vel_ext = VelocityExtension(a_hilb, U_reg, V_reg) + # Finite difference scheme + scheme = FirstOrderStencil(length(el_size),Float64) + stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + # Optimiser + optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) + # Solve + for (it,uh,φh) in optimiser + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|nabla(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && (writevtk(Ω,path*"out$it",cellfields=data);GC.gc()) + write_history(path*"/history.txt",get_history(optimiser);ranks) + end + # Final structure + it = get_history(optimiser).niter; uh = get_state(pcfs) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, + "H(φ)"=>(H ∘ φh),"|nabla(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) +end + +with_mpi() do distribute + mesh_partition = (2,2) + main(mesh_partition,distribute,false) + main(mesh_partition,distribute,true) # <- this should crash +end \ No newline at end of file diff --git a/scripts/_dev/bug_issue_46/thermal_serial.jl b/scripts/_dev/bug_issue_46/thermal_serial.jl new file mode 100644 index 00000000..e9c29a6c --- /dev/null +++ b/scripts/_dev/bug_issue_46/thermal_serial.jl @@ -0,0 +1,87 @@ +using LevelSetTopOpt, Gridap + +function main(use_l::Bool) + # FE parameters + order = 1 # Finite element order + xmax = ymax = 1.0 # Domain size + dom = (0,xmax,0,ymax) # Bounding domain + el_size = (200,200) # Mesh partition size + prop_Γ_N = 0.2 # Γ_N size parameter + prop_Γ_D = 0.2 # Γ_D size parameter + f_Γ_N(x) = (x[1] ≈ xmax && # Γ_N indicator function + ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0 && # Γ_D indicator function + (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) + # FD parameters + γ = 0.1 # HJ eqn time step coeff + γ_reinit = 0.5 # Reinit. eqn time step coeff + max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance + # Problem parameters + κ = 1 # Diffusivity + g = 1 # Heat flow in + vf = 0.4 # Volume fraction constraint + lsf_func = initial_lsf(4,0.2) # Initial level set function + iter_mod = 10 # VTK Output modulo + path = "./results/tut1_lobj_$use_l/" # Output path + mkpath(path) # Create path + # Model + model = CartesianDiscreteModel(dom,el_size); + update_labels!(1,model,f_Γ_D,"Gamma_D") + update_labels!(2,model,f_Γ_N,"Gamma_N") + # Triangulation and measures + Ω = Triangulation(model) + Γ_N = BoundaryTriangulation(model,tags="Gamma_N") + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + # Spaces + reffe = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,0.0) + V_φ = TestFESpace(model,reffe) + V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) + U_reg = TrialFESpace(V_reg,0) + # Level set and interpolator + φh = interpolate(lsf_func,V_φ) + interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + # Weak formulation + a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ + l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N + state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) + # Objective and constraints + J(u,φ,dΩ,dΓ_N) = if use_l + ∫(g*u)dΓ_N + else + ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ + end + dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + vol_D = sum(∫(1)dΩ) + C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C],state_map, + analytic_dJ=dJ,analytic_dC=[dC]) + # Velocity extension + α = 4*maximum(get_el_Δ(model)) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ + vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) + # Finite difference scheme + scheme = FirstOrderStencil(length(el_size),Float64) + stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + # Optimiser + optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + γ,γ_reinit,verbose=true,constraint_names=[:Vol]) + # Solve + for (it,uh,φh) in optimiser + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && (writevtk(Ω,path*"out$it",cellfields=data);GC.gc()) + write_history(path*"/history.txt",get_history(optimiser)) + end + # Final structure + it = get_history(optimiser).niter; uh = get_state(pcfs) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, + "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) +end + +main(false) +main(true) \ No newline at end of file From 67922d71f0319e5c673fee425357003f3d4ab88e Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 14 Mar 2024 14:33:31 +1000 Subject: [PATCH 09/90] Added new benchmark --- scripts/Benchmarks/benchmark.jl | 2 +- src/Benchmarks.jl | 19 +++++++++++++++++++ 2 files changed, 20 insertions(+), 1 deletion(-) diff --git a/scripts/Benchmarks/benchmark.jl b/scripts/Benchmarks/benchmark.jl index d91cbe6f..9abd59ee 100644 --- a/scripts/Benchmarks/benchmark.jl +++ b/scripts/Benchmarks/benchmark.jl @@ -439,7 +439,7 @@ with_mpi() do distribute bopt0 = i_am_main(ranks) && zeros(NREPS) end if occursin("bopt1",BMARK_TYPE) - bopt1 = benchmark_optimizer(optim, 1, ranks; nreps=NREPS) + bopt1 = benchmark_single_iteration(optim, ranks; nreps = NREPS) else bopt1 = i_am_main(ranks) && zeros(NREPS) end diff --git a/src/Benchmarks.jl b/src/Benchmarks.jl index d59ff5bd..87cc4a6e 100644 --- a/src/Benchmarks.jl +++ b/src/Benchmarks.jl @@ -79,6 +79,25 @@ function benchmark_optimizer(m::Optimiser, niter, ranks; nreps = 10) return benchmark(f, (m,), ranks; nreps, reset! = opt_reset!) end +""" + benchmark_single_iteration(m::Optimiser, ranks; nreps) + +Given an optimiser `m`, benchmark a single iteration after 0th iteration. +""" +function benchmark_single_iteration(m::Optimiser, ranks; nreps = 10) + _, state = iterate(m) + function f(m) + iterate(m, state) + end + + φ0 = copy(get_free_dof_values(m.φ0)) + function opt_reset!(m::Optimiser) + copy!(get_free_dof_values(m.φ0), φ0) + reset!(get_history(m)) + end + return benchmark(f, (m,), ranks; nreps, reset! = opt_reset!) +end + """ benchmark_forward_problem(m::AbstractFEStateMap, φh, ranks; nreps) From 9508a1c6da1d13bae1bc22a73590ee41c8f7bf1c Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Mon, 18 Mar 2024 14:36:13 +1000 Subject: [PATCH 10/90] Testing --- scripts/MPI/3d_thermal_compliance_ALM.jl | 12 ++++++------ scripts/MPI/inverse_homenisation_ALM.jl | 12 +++++------- scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs | 2 +- 3 files changed, 12 insertions(+), 14 deletions(-) diff --git a/scripts/MPI/3d_thermal_compliance_ALM.jl b/scripts/MPI/3d_thermal_compliance_ALM.jl index d2e4ad12..cae68f2d 100644 --- a/scripts/MPI/3d_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_thermal_compliance_ALM.jl @@ -73,7 +73,7 @@ function main(mesh_partition,distribute,el_size,coef,step) I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(v)dΓ_N + l(v,φ,dΩ,dΓ_N) = ∫(10v)dΓ_N ## Optimisation functionals J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ @@ -126,12 +126,12 @@ with_mpi() do distribute GridapPETSc.with(args=split(all_solver_options)) do main(mesh_partition,distribute,el_size,5,10) - main(mesh_partition,distribute,el_size,2,10) + # main(mesh_partition,distribute,el_size,2,10) - main(mesh_partition,distribute,el_size,5,5) - main(mesh_partition,distribute,el_size,2,5) + # main(mesh_partition,distribute,el_size,5,5) + # main(mesh_partition,distribute,el_size,2,5) - main(mesh_partition,distribute,el_size,5,3) - main(mesh_partition,distribute,el_size,2,3) + # main(mesh_partition,distribute,el_size,5,3) + # main(mesh_partition,distribute,el_size,2,3) end end; \ No newline at end of file diff --git a/scripts/MPI/inverse_homenisation_ALM.jl b/scripts/MPI/inverse_homenisation_ALM.jl index ed9c279f..e5399ae1 100644 --- a/scripts/MPI/inverse_homenisation_ALM.jl +++ b/scripts/MPI/inverse_homenisation_ALM.jl @@ -64,12 +64,10 @@ function main(mesh_partition,distribute,el_size) l = [(v,φ,dΩ) -> ∫(-(I ∘ φ) * C ⊙ εᴹ[i] ⊙ ε(v))dΩ for i in 1:3] ## Optimisation functionals - _C(C,ε_p,ε_q) = C ⊙ ε_p ⊙ ε_q; - _K(C,(u1,u2,u3),εᴹ) = (_C(C,ε(u1)+εᴹ[1],εᴹ[1]) + _C(C,ε(u2)+εᴹ[2],εᴹ[2]) + 2*_C(C,ε(u1)+εᴹ[1],εᴹ[2]))/4 - _v_K(C,(u1,u2,u3),εᴹ) = (_C(C,ε(u1)+εᴹ[1],ε(u1)+εᴹ[1]) + _C(C,ε(u2)+εᴹ[2],ε(u2)+εᴹ[2]) + 2*_C(C,ε(u1)+εᴹ[1],ε(u2)+εᴹ[2]))/4 - - J(u,φ,dΩ) = ∫(-(I ∘ φ)*_K(C,u,εᴹ))dΩ - dJ(q,u,φ,dΩ) = ∫(_v_K(C,u,εᴹ)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; + Cᴴ(r,s,u,φ,dΩ) = ∫((I ∘ φ)*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ εᴹ[s]))dΩ + dCᴴ(r,s,q,u,φ,dΩ) = ∫(-q*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ (ε(u[s])+εᴹ[s]))*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + κ(u,φ,dΩ) = -1/4*(Cᴴ(1,1,u,φ,dΩ)+Cᴴ(2,2,u,φ,dΩ)+2*Cᴴ(1,2,u,φ,dΩ)) + dκ(q,u,φ,dΩ) = -1/4*(dCᴴ(1,1,q,u,φ,dΩ)+dCᴴ(2,2,q,u,φ,dΩ)+2*dCᴴ(1,2,q,u,φ,dΩ)) Vol(u,φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; dVol(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ @@ -88,7 +86,7 @@ function main(mesh_partition,distribute,el_size) assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), ls = solver,adjoint_ls = solver ) - pcfs = PDEConstrainedFunctionals(J,[Vol],state_map;analytic_dJ=dJ,analytic_dC=[dVol]) + pcfs = PDEConstrainedFunctionals(κ,[Vol],state_map;analytic_dJ=dκ,analytic_dC=[dVol]) ## Hilbertian extension-regularisation problems α = α_coeff*maximum(el_Δ) diff --git a/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs b/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs index ef1ff771..d71b2b8f 100644 --- a/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs @@ -4,7 +4,7 @@ #PBS -N 3d_thermal_compliance_ALM #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=200:00:00 +#PBS -l walltime=23:00:00 #PBS -j oe source $HOME/hpc-environments-main/lyra/load-ompi.sh From 45bd1d979c2f1900769170dac44aa4f24c1c4112 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 4 Apr 2024 12:07:18 +1000 Subject: [PATCH 11/90] Add some more docs --- docs/make.jl | 36 +++++++++++++++------------ docs/src/getting-started.md | 39 ++++++++++++++++++++++++++++++ docs/src/index.md | 24 +++++++++++++++--- docs/src/reference/benchmarking.md | 1 + 4 files changed, 81 insertions(+), 19 deletions(-) create mode 100644 docs/src/getting-started.md diff --git a/docs/make.jl b/docs/make.jl index b9f14f4e..fc289362 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -1,3 +1,6 @@ +cd("./docs/") +using Pkg; Pkg.activate(".") + using Documenter using LevelSetTopOpt @@ -5,23 +8,24 @@ makedocs( sitename = "LevelSetTopOpt.jl", format = Documenter.HTML( prettyurls = false, - collapselevel = 1, + # collapselevel = 1, ), modules = [LevelSetTopOpt], pages = [ "Home" => "index.md", - "Usage" => [ - "usage/getting-started.md", - "usage/ad.md", - "usage/petsc.md", - "usage/mpi-mode.md", - ], - "Tutorials" => [ - "tutorials/minimum_thermal_compliance.md", - "tutorials/minimum_elastic_compliance.md", - "tutorials/inverter_mechanism.md", - "tutorials/inverse_homogenisation.md", - ], + "Getting Started" => "getting-started.md", + # "Usage" => [ + # "usage/getting-started.md", + # "usage/ad.md", + # "usage/petsc.md", + # "usage/mpi-mode.md", + # ], + # "Tutorials" => [ + # "tutorials/minimum_thermal_compliance.md", + # "tutorials/minimum_elastic_compliance.md", + # "tutorials/inverter_mechanism.md", + # "tutorials/inverse_homogenisation.md", + # ], "Reference" => [ "reference/optimisers.md", "reference/chainrules.md", @@ -31,9 +35,9 @@ makedocs( "reference/utilities.md", "reference/benchmarking.md" ], - "Developer Notes" => [ - "dev/shape_der.md", - ] + # "Developer Notes" => [ + # "dev/shape_der.md", + # ] ], ) diff --git a/docs/src/getting-started.md b/docs/src/getting-started.md new file mode 100644 index 00000000..5b9eed32 --- /dev/null +++ b/docs/src/getting-started.md @@ -0,0 +1,39 @@ +# Getting started + +## Installation + +`LevelSetTopOpt.jl` and additional dependencies can be installed in an existing Julia environment using the package manager. This can be accessed in the Julia REPL (read-eval–print loop) by pressing `]`. We then add the required packages via: +``` +pkg> add LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, SparseMatricesCSR +``` +Once installed, serial driver scripts can be run immediately, whereas parallel problems also require an MPI installation. + +### MPI +For basic users, [`MPI.jl`](https://github.com/JuliaParallel/MPI.jl) provides such an implementation and a Julia wrapper for `mpiexec` - the MPI executor. This is installed via: +``` +pkg> add MPI +julia> using MPI +julia> MPI.install_mpiexecjl() +``` +Once the `mpiexecjl` wrapper has been added to the system `PATH`, MPI scripts can be executed in a terminal via +``` +mpiexecjl -n P julia main.jl +``` +where `main` is a driver script, `P` denotes the number of processors. + +### PETSc +In `LevelSetTopOpt.jl` we rely on the [`GridapPETSc.jl`](https://github.com/gridap/GridapPETSc.jl) satellite package to interface with the linear and nonlinear solvers provided by the PETSc (Portable, Extensible Toolkit for Scientific Computation) library. For basic users these solvers are provided by `GridapPETSc.jl` with no additional work. + +### Advanced installation +For more advanced installations, such as use of a custom MPI/PETSc installation on a HPC cluster, we refer the reader to the [discussion](https://github.com/gridap/GridapPETSc.jl) for `GridapPETSc.jl` and the [configuration page](https://juliaparallel.org/MPI.jl/stable/configuration/) for `MPI.jl`. + +## Usage and tutorials +In order to get familiar with the library we recommend following the numerical examples described in: + +> Zachary J. Wegert, Jordi M. Fuertes, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. + +More general tutorials for familiarising ones self with Gridap are available via the [Gridap Tutorials](https://gridap.github.io/Tutorials/dev/). + +## Known issues +- PETSc's GAMG preconditioner breaks for split Dirichlet DoFs (e.g., x constrained while y free for a single node). There is no simple fix for this. We recommend instead using MUMPS or another preconditioner for this case. +- Currently, our implementation of automatic differentiation does not support multiplication and division of optimisation functionals. We plan to add this in a future release of `LevelSetTopOpt.jl`. \ No newline at end of file diff --git a/docs/src/index.md b/docs/src/index.md index c26e8171..2a9769a0 100644 --- a/docs/src/index.md +++ b/docs/src/index.md @@ -1,6 +1,24 @@ # LevelSetTopOpt.jl -Welcome to the documentation for LevelSetTopOpt.jl! +Welcome to the documentation for `LevelSetTopOpt.jl`! -# What +## Introduction +`LevelSetTopOpt.jl` is computational toolbox for level set-based topology optimisation implemented in Julia and the Gridap package ecosystem. The core design principle of `LevelSetTopOpt.jl` is to provide an extendable framework for solving optimisation problems in serial or parallel with a high-level programming interface and automatic differentiation. See the following publication for further details: -# Why +> Zachary J. Wegert, Jordi M. Fuertes, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. + +## How to use this documentation + +* The first step for new users is to visit the [Getting Started](getting-started.md) page. + +* A set of tutorials are available as part of the above paper. + +* The detailed documentation is in the Reference section. + +## Julia educational resources + +A basic knowledge of the Julia programming language is needed to use the `LevelSetTopOpt.jl` package. +Here, one can find a list of resources to get started with this programming language. + +* First steps to learn Julia form the [Gridap wiki](https://github.com/gridap/Gridap.jl/wiki/Start-learning-Julia) page. +* Official webpage [docs.julialang.org](https://docs.julialang.org/) +* Official list of learning resources [julialang.org/learning](https://julialang.org/learning/) \ No newline at end of file diff --git a/docs/src/reference/benchmarking.md b/docs/src/reference/benchmarking.md index e5e6d42e..617ee276 100644 --- a/docs/src/reference/benchmarking.md +++ b/docs/src/reference/benchmarking.md @@ -7,6 +7,7 @@ LevelSetTopOpt.benchmark ## Existing benchmark methods ```@docs LevelSetTopOpt.benchmark_optimizer +LevelSetTopOpt.benchmark_single_iteration LevelSetTopOpt.benchmark_forward_problem LevelSetTopOpt.benchmark_advection LevelSetTopOpt.benchmark_reinitialisation From e766580de3c598eb39b0c07b177214bfff8e40e1 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 4 Apr 2024 12:13:58 +1000 Subject: [PATCH 12/90] Update readme --- README.md | 11 +++++++++-- 1 file changed, 9 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 18d66ae5..4be459bc 100755 --- a/README.md +++ b/README.md @@ -1,3 +1,10 @@ -# LevelSetTopOpt.jl +# LevelSetTopOpt -... \ No newline at end of file +[comment]: badges + +LevelSetTopOpt is computational toolbox for level set-based topology optimisation implemented in Julia and the [Gridap](https://github.com/gridap/Gridap.jl) package ecosystem. See the documentation for further details. + +## Documentation + +- [**STABLE**](...) — **Documentation for the most recently tagged version.** +- [**LATEST**](...) — *Documentation for the in-development version.* \ No newline at end of file From 93f33fa935eb56ee884c7f798793ff1b89699acd Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 4 Apr 2024 12:15:54 +1000 Subject: [PATCH 13/90] README update 2 --- README.md | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 4be459bc..1ce80170 100755 --- a/README.md +++ b/README.md @@ -1,8 +1,10 @@ # LevelSetTopOpt -[comment]: badges +| **badges** | -LevelSetTopOpt is computational toolbox for level set-based topology optimisation implemented in Julia and the [Gridap](https://github.com/gridap/Gridap.jl) package ecosystem. See the documentation for further details. +LevelSetTopOpt is computational toolbox for level set-based topology optimisation implemented in Julia and the [Gridap](https://github.com/gridap/Gridap.jl) package ecosystem. See the documentation and following publication for further details: + +> Zachary J. Wegert, Jordi M. Fuertes, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. ## Documentation From a18b6c94ea3f20a4d89ed2a7f81c8df9cc8c6940 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 4 Apr 2024 14:43:40 +1000 Subject: [PATCH 14/90] Add gc call and removed `write_vtk` --- docs/src/reference/io.md | 6 +---- scripts/MPI/3d_elastic_compliance_ALM.jl | 10 ++++--- scripts/MPI/3d_hyperelastic_compliance_ALM.jl | 10 ++++--- .../3d_hyperelastic_compliance_neohook_ALM.jl | 10 ++++--- scripts/MPI/3d_inverse_homenisation_ALM.jl | 10 ++++--- scripts/MPI/3d_inverter_ALM.jl | 8 +++--- scripts/MPI/3d_inverter_HPM.jl | 8 +++--- .../3d_nonlinear_thermal_compliance_ALM.jl | 8 +++--- scripts/MPI/3d_thermal_compliance_ALM.jl | 6 +++-- scripts/MPI/elastic_compliance_ALM.jl | 6 +++-- scripts/MPI/inverse_homenisation_ALM.jl | 6 +++-- scripts/MPI/thermal_compliance_ALM.jl | 6 +++-- scripts/MPI/thermal_compliance_ALM_PETSc.jl | 6 +++-- scripts/Serial/elastic_compliance_ALM.jl | 8 +++--- scripts/Serial/elastic_compliance_HPM.jl | 8 +++--- scripts/Serial/elastic_compliance_LM.jl | 8 +++--- scripts/Serial/hyperelastic_compliance_ALM.jl | 8 +++--- .../hyperelastic_compliance_neohook_ALM.jl | 8 +++--- scripts/Serial/inverse_homenisation_ALM.jl | 8 +++--- scripts/Serial/inverter_ALM.jl | 8 +++--- scripts/Serial/inverter_HPM.jl | 8 +++--- .../nonlinear_thermal_compliance_ALM.jl | 8 +++--- scripts/Serial/thermal_compliance_ALM.jl | 8 +++--- .../_dev/3d_hyperelastic_compliance_ALM.jl | 4 +-- .../inv_hom_block_assem_testing_3D_MPI.jl | 5 ++-- ...inv_hom_block_assem_testing_full_script.jl | 5 ++-- src/LevelSetTopOpt.jl | 1 - src/Optimisers/AugmentedLagrangian.jl | 4 +++ src/Optimisers/HilbertianProjection.jl | 4 +++ src/Utilities.jl | 27 +------------------ 30 files changed, 127 insertions(+), 103 deletions(-) diff --git a/docs/src/reference/io.md b/docs/src/reference/io.md index cc6fccc6..5adc2248 100644 --- a/docs/src/reference/io.md +++ b/docs/src/reference/io.md @@ -1,14 +1,10 @@ # IO -## Optimiser history and visualisation +## Optimiser history ```@docs LevelSetTopOpt.write_history ``` -```@docs -LevelSetTopOpt.write_vtk -``` - ## Object IO in serial ```@docs LevelSetTopOpt.save diff --git a/scripts/MPI/3d_elastic_compliance_ALM.jl b/scripts/MPI/3d_elastic_compliance_ALM.jl index 3e5f6f24..8ae4b8c3 100644 --- a/scripts/MPI/3d_elastic_compliance_ALM.jl +++ b/scripts/MPI/3d_elastic_compliance_ALM.jl @@ -28,7 +28,9 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4 vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_elastic_compliance_ALM" + path = dirname(dirname(@__DIR__))*"/results/3d_elastic_compliance_ALM/" + iter_mod = 10 + i_am_main(ranks) && mkdir(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -98,15 +100,15 @@ function main(mesh_partition,distribute,el_size) ) ## Optimiser - i_am_main(ranks) && mkdir(path) optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history;ranks=ranks) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end with_mpi() do distribute diff --git a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl index 7bb9a0b2..ad197331 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl @@ -24,7 +24,9 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4 vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_hyperelastic_compliance_ALM" + path = dirname(dirname(@__DIR__))*"/results/3d_hyperelastic_compliance_ALM/" + iter_mod = 10 + i_am_main(ranks) && mkdir(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size) @@ -104,15 +106,15 @@ function main(mesh_partition,distribute,el_size) ) ## Optimiser - i_am_main(ranks) && mkdir(path) optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history;ranks=ranks) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end with_mpi() do distribute diff --git a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl index c394a268..0ddd1da4 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl @@ -24,7 +24,9 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4 vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_hyperelastic_compliance_neohook_ALM" + path = dirname(dirname(@__DIR__))*"/results/3d_hyperelastic_compliance_neohook_ALM/" + iter_mod = 10 + i_am_main(ranks) && mkdir(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size) @@ -118,15 +120,15 @@ function main(mesh_partition,distribute,el_size) ) ## Optimiser - i_am_main(ranks) && mkdir(path) optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history;ranks=ranks) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end with_mpi() do distribute diff --git a/scripts/MPI/3d_inverse_homenisation_ALM.jl b/scripts/MPI/3d_inverse_homenisation_ALM.jl index 488ca57e..2769375b 100644 --- a/scripts/MPI/3d_inverse_homenisation_ALM.jl +++ b/scripts/MPI/3d_inverse_homenisation_ALM.jl @@ -26,8 +26,9 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4 vf = 0.5 - path = dirname(dirname(@__DIR__))*"/results/3d_inverse_homenisation_ALM" - i_am_main(ranks) && mkdir(path) + path = dirname(dirname(@__DIR__))*"/results/3d_inverse_homenisation_ALM/" + iter_mod = 10 + i_am_main(ranks) && mkdir(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true,true)) @@ -106,11 +107,12 @@ function main(mesh_partition,distribute,el_size) optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history;ranks=ranks) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))]) end with_mpi() do distribute diff --git a/scripts/MPI/3d_inverter_ALM.jl b/scripts/MPI/3d_inverter_ALM.jl index 4fff7765..1e34d67e 100644 --- a/scripts/MPI/3d_inverter_ALM.jl +++ b/scripts/MPI/3d_inverter_ALM.jl @@ -32,7 +32,8 @@ function main(mesh_partition,distribute,el_size) δₓ=0.5 ks = 0.01 g = VectorValue(1,0,0) - path = dirname(dirname(@__DIR__))*"/results/3d_inverter_ALM" + path = dirname(dirname(@__DIR__))*"/results/3d_inverter_ALM/" + iter_mod = 10 i_am_main(ranks) && mkdir(path) ## FE Setup @@ -120,11 +121,12 @@ function main(mesh_partition,distribute,el_size) optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol,:UΓ_out]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history;ranks=ranks) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end with_mpi() do distribute diff --git a/scripts/MPI/3d_inverter_HPM.jl b/scripts/MPI/3d_inverter_HPM.jl index ad041a18..1e051812 100644 --- a/scripts/MPI/3d_inverter_HPM.jl +++ b/scripts/MPI/3d_inverter_HPM.jl @@ -32,7 +32,8 @@ function main(mesh_partition,distribute,el_size) δₓ=0.5 ks = 0.01 g = VectorValue(1,0,0) - path = dirname(dirname(@__DIR__))*"/results/3d_inverter_HPM" + path = dirname(dirname(@__DIR__))*"/results/3d_inverter_HPM/" + iter_mod = 10 i_am_main(ranks) && mkdir(path) ## FE Setup @@ -121,11 +122,12 @@ function main(mesh_partition,distribute,el_size) optimiser = HilbertianProjection(pcfs,stencil,vel_ext,φh;γ,γ_reinit,ls_enabled,α_min=0.7, ls_γ_max=0.05,verbose=i_am_main(ranks),constraint_names=[:Vol,:UΓ_out]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history;ranks=ranks) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end with_mpi() do distribute diff --git a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl index 2fb8ce00..19598021 100644 --- a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl @@ -31,7 +31,8 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4 vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_nonlinear_thermal_compliance_ALM" + path = dirname(dirname(@__DIR__))*"/results/3d_nonlinear_thermal_compliance_ALM/" + iter_mod = 10 i_am_main(ranks) && mkdir(path) ## FE Setup @@ -108,11 +109,12 @@ function main(mesh_partition,distribute,el_size) optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history;ranks=ranks) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end with_mpi() do distribute diff --git a/scripts/MPI/3d_thermal_compliance_ALM.jl b/scripts/MPI/3d_thermal_compliance_ALM.jl index cae68f2d..d9da92ff 100644 --- a/scripts/MPI/3d_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_thermal_compliance_ALM.jl @@ -38,6 +38,7 @@ function main(mesh_partition,distribute,el_size,coef,step) α_coeff = 4 vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/3d_thermal_compliance_ALM_Nx$(el_size[1])_Coef$(coef)_Step$(step)" + iter_mod = 10 i_am_main(ranks) && mkdir(path) ## FE Setup @@ -111,11 +112,12 @@ function main(mesh_partition,distribute,el_size,coef,step) optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history;ranks=ranks) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end with_mpi() do distribute diff --git a/scripts/MPI/elastic_compliance_ALM.jl b/scripts/MPI/elastic_compliance_ALM.jl index 5be16714..49f97724 100644 --- a/scripts/MPI/elastic_compliance_ALM.jl +++ b/scripts/MPI/elastic_compliance_ALM.jl @@ -29,6 +29,7 @@ function main(mesh_partition,distribute,el_size) α_coeff = 4 vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_ALM_MPI" + iter_mod = 10 i_am_main(ranks) && mkdir(path) ## FE Setup @@ -100,11 +101,12 @@ function main(mesh_partition,distribute,el_size) optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history;ranks=ranks) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end with_mpi() do distribute diff --git a/scripts/MPI/inverse_homenisation_ALM.jl b/scripts/MPI/inverse_homenisation_ALM.jl index e5399ae1..4b866b5f 100644 --- a/scripts/MPI/inverse_homenisation_ALM.jl +++ b/scripts/MPI/inverse_homenisation_ALM.jl @@ -27,6 +27,7 @@ function main(mesh_partition,distribute,el_size) α_coeff = 4 vf = 0.5 path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM_MPI" + iter_mod = 10 i_am_main(ranks) && mkdir(path) ## FE Setup @@ -101,11 +102,12 @@ function main(mesh_partition,distribute,el_size) optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history;ranks=ranks) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))]) end with_mpi() do distribute diff --git a/scripts/MPI/thermal_compliance_ALM.jl b/scripts/MPI/thermal_compliance_ALM.jl index f4208c11..b4f316e2 100644 --- a/scripts/MPI/thermal_compliance_ALM.jl +++ b/scripts/MPI/thermal_compliance_ALM.jl @@ -29,6 +29,7 @@ function main(mesh_partition,distribute) α_coeff = 4 vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM_MPI" + iter_mod = 10 i_am_main(ranks) && mkdir(path) ## FE Setup @@ -86,11 +87,12 @@ function main(mesh_partition,distribute) optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history;ranks=ranks) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end with_mpi() do distribute diff --git a/scripts/MPI/thermal_compliance_ALM_PETSc.jl b/scripts/MPI/thermal_compliance_ALM_PETSc.jl index a39f1a6a..8c032c04 100644 --- a/scripts/MPI/thermal_compliance_ALM_PETSc.jl +++ b/scripts/MPI/thermal_compliance_ALM_PETSc.jl @@ -29,6 +29,7 @@ function main(mesh_partition,distribute,el_size) α_coeff = 4 vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM_MPI+PETSc" + iter_mod = 10 i_am_main(ranks) && mkdir(path) ## FE Setup @@ -100,11 +101,12 @@ function main(mesh_partition,distribute,el_size) optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history;ranks=ranks) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end with_mpi() do distribute diff --git a/scripts/Serial/elastic_compliance_ALM.jl b/scripts/Serial/elastic_compliance_ALM.jl index a193d39b..c1f780db 100644 --- a/scripts/Serial/elastic_compliance_ALM.jl +++ b/scripts/Serial/elastic_compliance_ALM.jl @@ -26,7 +26,8 @@ function main() α_coeff = 4 vf = 0.4 g = VectorValue(0,-1) - path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_ALM" + path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_ALM/" + iter_mod = 10 mkdir(path) ## FE Setup @@ -85,11 +86,12 @@ function main() optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end main() \ No newline at end of file diff --git a/scripts/Serial/elastic_compliance_HPM.jl b/scripts/Serial/elastic_compliance_HPM.jl index 825e92f9..4e620db2 100644 --- a/scripts/Serial/elastic_compliance_HPM.jl +++ b/scripts/Serial/elastic_compliance_HPM.jl @@ -26,7 +26,8 @@ function main() α_coeff = 4 vf = 0.4 g = VectorValue(0,-1) - path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_HPM" + path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_HPM/" + iter_mod = 10 mkdir(path) ## FE Setup @@ -86,11 +87,12 @@ function main() optimiser = HilbertianProjection(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end main(); \ No newline at end of file diff --git a/scripts/Serial/elastic_compliance_LM.jl b/scripts/Serial/elastic_compliance_LM.jl index 64b04677..b1be54a6 100644 --- a/scripts/Serial/elastic_compliance_LM.jl +++ b/scripts/Serial/elastic_compliance_LM.jl @@ -24,7 +24,8 @@ function main() η_coeff = 2 α_coeff = 4 g = VectorValue(0,-1) - path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_LM" + path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_LM/" + iter_mod = 10 mkdir(path) ## FE Setup @@ -81,11 +82,12 @@ function main() ## Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end main(); \ No newline at end of file diff --git a/scripts/Serial/hyperelastic_compliance_ALM.jl b/scripts/Serial/hyperelastic_compliance_ALM.jl index f2117446..e6b801dc 100644 --- a/scripts/Serial/hyperelastic_compliance_ALM.jl +++ b/scripts/Serial/hyperelastic_compliance_ALM.jl @@ -17,7 +17,8 @@ function main() η_coeff = 2 α_coeff = 4 vf = 0.6 - path = dirname(dirname(@__DIR__))*"/results/hyperelastic_compliance_ALM" + path = dirname(dirname(@__DIR__))*"/results/hyperelastic_compliance_ALM/" + iter_mod = 10 mkdir(path) ## FE Setup @@ -85,11 +86,12 @@ function main() optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end main() \ No newline at end of file diff --git a/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl b/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl index 0ebae329..1a10577c 100644 --- a/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl @@ -17,7 +17,8 @@ function main() η_coeff = 2 α_coeff = 4 vf = 0.6 - path = dirname(dirname(@__DIR__))*"/results/hyperelastic_compliance_neohook_ALM" + path = dirname(dirname(@__DIR__))*"/results/hyperelastic_compliance_neohook_ALM/" + iter_mod = 10 mkdir(path) ## FE Setup @@ -99,11 +100,12 @@ function main() optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end main() \ No newline at end of file diff --git a/scripts/Serial/inverse_homenisation_ALM.jl b/scripts/Serial/inverse_homenisation_ALM.jl index d4d60aa8..7ac70885 100644 --- a/scripts/Serial/inverse_homenisation_ALM.jl +++ b/scripts/Serial/inverse_homenisation_ALM.jl @@ -24,7 +24,8 @@ function main() η_coeff = 2 α_coeff = 4 vf = 0.5 - path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM" + path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM/" + iter_mod = 10 mkdir(path) ## FE Setup @@ -85,11 +86,12 @@ function main() optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))]) end main() \ No newline at end of file diff --git a/scripts/Serial/inverter_ALM.jl b/scripts/Serial/inverter_ALM.jl index 85b28d89..9b1e4879 100644 --- a/scripts/Serial/inverter_ALM.jl +++ b/scripts/Serial/inverter_ALM.jl @@ -30,7 +30,8 @@ function main() δₓ = 0.2 ks = 0.1 g = VectorValue(0.5,0) - path = dirname(dirname(@__DIR__))*"/results/inverter_ALM" + path = dirname(dirname(@__DIR__))*"/results/inverter_ALM/" + iter_mod = 10 mkdir(path) ## FE Setup @@ -100,11 +101,12 @@ function main() optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol,:UΓ_out]) for (it,uh,φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end main() \ No newline at end of file diff --git a/scripts/Serial/inverter_HPM.jl b/scripts/Serial/inverter_HPM.jl index f79ca7e9..4f22c0f3 100644 --- a/scripts/Serial/inverter_HPM.jl +++ b/scripts/Serial/inverter_HPM.jl @@ -30,7 +30,8 @@ function main() δₓ = 0.2 ks = 0.1 g = VectorValue(0.5,0) - path = dirname(dirname(@__DIR__))*"/results/inverter_HPM_osc" + path = dirname(dirname(@__DIR__))*"/results/inverter_HPM/" + iter_mod = 10 mkdir(path) ## FE Setup @@ -102,11 +103,12 @@ function main() optimiser = HilbertianProjection(pcfs,stencil,vel_ext,φh; γ,γ_reinit,α_min=0.4,ls_enabled,verbose=true,constraint_names=[:Vol,:UΓ_out]) for (it,uh,φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end main() \ No newline at end of file diff --git a/scripts/Serial/nonlinear_thermal_compliance_ALM.jl b/scripts/Serial/nonlinear_thermal_compliance_ALM.jl index 270eedcf..ba3f8d74 100644 --- a/scripts/Serial/nonlinear_thermal_compliance_ALM.jl +++ b/scripts/Serial/nonlinear_thermal_compliance_ALM.jl @@ -27,7 +27,8 @@ function main() η_coeff = 2 α_coeff = 4 vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/nonlinear_thermal_compliance_ALM" + path = dirname(dirname(@__DIR__))*"/results/nonlinear_thermal_compliance_ALM/" + iter_mod = 10 mkdir(path) ## FE Setup @@ -88,11 +89,12 @@ function main() optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it, uh, φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end main() \ No newline at end of file diff --git a/scripts/Serial/thermal_compliance_ALM.jl b/scripts/Serial/thermal_compliance_ALM.jl index 171d8d49..425a63d5 100644 --- a/scripts/Serial/thermal_compliance_ALM.jl +++ b/scripts/Serial/thermal_compliance_ALM.jl @@ -26,7 +26,8 @@ function main() vf = 0.4 η_coeff = 2 α_coeff = 4 - path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM" + path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM/" + iter_mod = 10 mkdir(path) ## FE Setup @@ -86,11 +87,12 @@ function main() optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",optimiser.history) end it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end main() \ No newline at end of file diff --git a/scripts/_dev/3d_hyperelastic_compliance_ALM.jl b/scripts/_dev/3d_hyperelastic_compliance_ALM.jl index 8066e3e6..2565536b 100644 --- a/scripts/_dev/3d_hyperelastic_compliance_ALM.jl +++ b/scripts/_dev/3d_hyperelastic_compliance_ALM.jl @@ -73,7 +73,7 @@ function main(mesh_partition,distribute,el_size,δₓ) ## Optimiser u = LevelSetTopOpt.forward_solve!(state_map,φh) uh = FEFunction(U,u) - write_vtk(Ω,path*"/struc_$δₓ",0,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"/struc_$δₓ",cellfields=["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end function main_alt(mesh_partition,distribute,el_size,gz) @@ -173,7 +173,7 @@ function main_alt(mesh_partition,distribute,el_size,gz) ## Optimiser u = LevelSetTopOpt.forward_solve!(state_map,φh) uh = FEFunction(U,u) - write_vtk(Ω,path*"/struc_neohook_$gz",0,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + writevtk(Ω,path*"/struc_neohook_$gz",cellfields=["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end with_mpi() do distribute diff --git a/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl b/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl index aa2d019e..4ab969a6 100644 --- a/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl +++ b/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl @@ -136,13 +136,14 @@ function main(mesh_partition,distribute,el_size,diag_assem::Bool) λi = optimiser.λ; Λi = optimiser.Λ print_history(it,["J"=>Ji,"C"=>Ci,"L"=>Li,"λ"=>λi,"Λ"=>Λi];ranks=ranks) write_history(history,path*"/history.csv";ranks=ranks) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))] + iszero(it % 10) && writevtk(Ω,path*"out$it",cellfields=data) end it,Ji,Ci,Li = last(optimiser.history) λi = optimiser.λ; Λi = optimiser.Λ print_history(it,["J"=>Ji,"C"=>Ci,"L"=>Li,"λ"=>λi,"Λ"=>Λi];ranks=ranks) write_history(optimiser.history,path*"/history.csv";ranks=ranks) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))];iter_mod=1) + writevtk(Ω,path*"/out$it",cellfields=["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))]) end # RUN: mpiexecjl --project=. -n 8 julia ./scripts/inv_hom_block_assem_testing_3D_MPI.jl diff --git a/scripts/_dev/inv_hom_block_assem_testing_full_script.jl b/scripts/_dev/inv_hom_block_assem_testing_full_script.jl index 75018ee6..f3c31fc2 100644 --- a/scripts/_dev/inv_hom_block_assem_testing_full_script.jl +++ b/scripts/_dev/inv_hom_block_assem_testing_full_script.jl @@ -115,13 +115,14 @@ function main(diag_block) λi = optimiser.λ; Λi = optimiser.Λ print_history(it,["J"=>Ji,"C"=>Ci,"L"=>Li,"λ"=>λi,"Λ"=>Λi]) write_history(history,path*"/history.csv") - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))]) + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))] + iszero(it % 10) && writevtk(Ω,path*"out$it",cellfields=data) end it,Ji,Ci,Li = last(optimiser.history) λi = optimiser.λ; Λi = optimiser.Λ print_history(it,["J"=>Ji,"C"=>Ci,"L"=>Li,"λ"=>λi,"Λ"=>Λi]) write_history(optimiser.history,path*"/history.csv") - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))];iter_mod=1) + writevtk(Ω,path*"/out$it",cellfields=["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))]) end using LinearAlgebra diff --git a/src/LevelSetTopOpt.jl b/src/LevelSetTopOpt.jl index 39917e95..7b6ebc4d 100644 --- a/src/LevelSetTopOpt.jl +++ b/src/LevelSetTopOpt.jl @@ -51,7 +51,6 @@ export update_labels! export initial_lsf export get_el_Δ export isotropic_elast_tensor -export write_vtk include("Advection.jl") export AdvectionStencil diff --git a/src/Optimisers/AugmentedLagrangian.jl b/src/Optimisers/AugmentedLagrangian.jl index fb9d74fe..b2380686 100644 --- a/src/Optimisers/AugmentedLagrangian.jl +++ b/src/Optimisers/AugmentedLagrangian.jl @@ -178,6 +178,10 @@ function Base.iterate(m::AugmentedLagrangian,state) update_mod, reinit_mod, ζ, Λ_max, γ_reinit, os_γ_mult = params.update_mod, params.reinit_mod, params.ζ, params.Λ_max, params.γ_reinit, params.os_γ_mult + ## Periodicially call GC + iszero(it % 50) && GC.gc(); + + ## Check stopping criteria if finished(m) return nothing end diff --git a/src/Optimisers/HilbertianProjection.jl b/src/Optimisers/HilbertianProjection.jl index c64a9d7f..9cb75952 100644 --- a/src/Optimisers/HilbertianProjection.jl +++ b/src/Optimisers/HilbertianProjection.jl @@ -321,6 +321,10 @@ function Base.iterate(m::HilbertianProjection,state) it, J, C, θ, dJ, dC, uh, φh, vel, φ_tmp, γ, os_it = state history, params = m.history, m.params + ## Periodicially call GC + iszero(it % 50) && GC.gc(); + + ## Check stopping criteria if finished(m) return nothing end diff --git a/src/Utilities.jl b/src/Utilities.jl index 82ba9f0f..aede0bd2 100644 --- a/src/Utilities.jl +++ b/src/Utilities.jl @@ -212,29 +212,4 @@ function isotropic_elast_tensor(D::Int,E::Number,v::Number) else @notimplemented end -end - -""" - write_vtk(Ω,path,it,entries::Vector{<:Pair};iter_mod=10) - -Write a VTK file to `path`. This functions in a similar way to -Gridap's `writevtk` function except we - -!!! note - This may be removed in future and replaced by - - ```(isone(it) || iszero(it % iter_mod)) && writevtk(Ω,path,cellfields=entries)``` - - or - - ```iszero(it-1 % iter_mod) && writevtk(Ω,path,cellfields=entries)``` -""" -function write_vtk(Ω,path,it,entries::Vector{<:Pair};iter_mod=10) # TODO: Rename to writevtk? - if isone(it) || iszero(it % iter_mod) - writevtk(Ω,path,cellfields=entries) - end - - if iszero(it % 10*iter_mod) - GC.gc() # TODO: Test in Julia 1.10.0 and check if fixed. - end -end +end \ No newline at end of file From d1633a91bc4ccc7d2d71202c6abd8c9508101480 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 4 Apr 2024 15:32:49 +1000 Subject: [PATCH 15/90] Added paper scripts to later go in supplementary --- .../3d_hyperelastic_compliance_neohook_ALM.jl | 4 +- ...relastic_compliance_neohook_ALM_COMPARE.jl | 193 ----------------- scripts/_dev/Added_for_paper/thermal_MPI.jl | 88 -------- .../elast_comp_MPI_3D.jl} | 201 +++++++++--------- .../Paper_scripts/hyperelast_comp_MPI_3D.jl | 118 ++++++++++ .../_dev/Paper_scripts/inverse_hom_MPI_3D.jl | 108 ++++++++++ scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 114 ++++++++++ .../Paper_scripts/jobs/elast_comp_MPI_3D.pbs | 16 ++ .../jobs/hyperelast_comp_MPI_3D.pbs | 16 ++ .../Paper_scripts/jobs/inverse_hom_MPI_3D.pbs | 16 ++ .../Paper_scripts/jobs/inverter_MPI_3D.pbs | 16 ++ .../Paper_scripts/jobs/therm_comp_MPI_3D.pbs | 17 ++ .../therm_comp_MPI.jl} | 17 +- .../therm_comp_MPI_3D.jl} | 20 +- .../therm_comp_serial.jl} | 6 +- 15 files changed, 547 insertions(+), 403 deletions(-) delete mode 100644 scripts/_dev/Added_for_paper/hyperelastic_compliance_neohook_ALM_COMPARE.jl delete mode 100644 scripts/_dev/Added_for_paper/thermal_MPI.jl rename scripts/_dev/{Added_for_paper/thermal_PETSc.jl => Paper_scripts/elast_comp_MPI_3D.jl} (50%) create mode 100644 scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl create mode 100644 scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl create mode 100644 scripts/_dev/Paper_scripts/inverter_MPI_3D.jl create mode 100644 scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs create mode 100644 scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs create mode 100644 scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs create mode 100644 scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs create mode 100644 scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs rename scripts/_dev/{Added_for_paper/thermal_MPI_PETSc.jl => Paper_scripts/therm_comp_MPI.jl} (86%) rename scripts/_dev/{Added_for_paper/thermal_MPI_PETSc_3D.jl => Paper_scripts/therm_comp_MPI_3D.jl} (87%) rename scripts/_dev/{Added_for_paper/thermal_serial.jl => Paper_scripts/therm_comp_serial.jl} (93%) diff --git a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl index 0ddd1da4..cc428534 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl @@ -61,9 +61,9 @@ function main(mesh_partition,distribute,el_size) I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ ## Material properties - _E = 1000 + E = 1000 ν = 0.3 - μ, λ = _E/(2*(1 + ν)), _E*ν/((1 + ν)*(1 - 2*ν)) + μ, λ = E/(2*(1 + ν)), E*ν/((1 + ν)*(1 - 2*ν)) g = VectorValue(0,0,-100) ## Neohookean hyperelastic material diff --git a/scripts/_dev/Added_for_paper/hyperelastic_compliance_neohook_ALM_COMPARE.jl b/scripts/_dev/Added_for_paper/hyperelastic_compliance_neohook_ALM_COMPARE.jl deleted file mode 100644 index 673ae38c..00000000 --- a/scripts/_dev/Added_for_paper/hyperelastic_compliance_neohook_ALM_COMPARE.jl +++ /dev/null @@ -1,193 +0,0 @@ -using Gridap, LevelSetTopOpt - -""" - (Serial) Minimum hyperelastic (neohookean) compliance with augmented Lagrangian method in 2D. -""" -function main() - ## Parameters - order = 1 - xmax,ymax=2.0,1.0 - prop_Γ_N = 0.2 - dom = (0,xmax,0,ymax) - el_size = (400,200) - γ = 0.1 - γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) - tol = 1/(5order^2)/minimum(el_size) - η_coeff = 2 - α_coeff = 4 - vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/highres_hyperelastic_compliance_neohook_ALM" - mkdir(path) - - ## FE Setup - model = CartesianDiscreteModel(dom,el_size); - el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0) - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - vol_D = sum(∫(1)dΩ) - - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,VectorValue(0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - - ## Create FE functions - φh = interpolate(initial_lsf(4,0.2),V_φ) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - ## Material properties - _E = 1000 - ν = 0.3 - μ, λ = _E/(2*(1 + ν)), _E*ν/((1 + ν)*(1 - 2*ν)) - g = VectorValue(0,-10) - - ## Neohookean hyperelastic material - # Deformation gradient - F(∇u) = one(∇u) + ∇u' - J(F) = sqrt(det(C(F))) - - # Derivative of green Strain - dE(∇du,∇u) = 0.5*( ∇du⋅F(∇u) + (∇du⋅F(∇u))' ) - - # Right Caughy-green deformation tensor - C(F) = (F')⋅F - - # Constitutive law (Neo hookean) - function S(∇u) - Cinv = inv(C(F(∇u))) - μ*(one(∇u)-Cinv) + λ*log(J(F(∇u)))*Cinv - end - - # Cauchy stress tensor and residual - σ(∇u) = (1.0/J(F(∇u)))*F(∇u)⋅S(∇u)⋅(F(∇u))' - res(u,v,φ,dΩ,dΓ_N) = ∫( (I ∘ φ)*((dE∘(∇(v),∇(u))) ⊙ (S∘∇(u))) )*dΩ - ∫(g⋅v)dΓ_N - - ## Optimisation functionals - Obj(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*((dE∘(∇(u),∇(u))) ⊙ (S∘∇(u))))dΩ - Vol(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; - dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - - ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) - - ## Setup solver and FE operators - state_map = NonlinearFEStateMap(res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) - pcfs = PDEConstrainedFunctionals(Obj,[Vol],state_map,analytic_dC=[dVol]) - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(el_Δ) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - - ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; - γ,γ_reinit,verbose=true,constraint_names=[:Vol]) - for (it,uh,φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) - write_history(path*"/history.txt",optimiser.history) - end - it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) -end - -main() - -function main_LE_comparison() - ## Parameters - order = 1 - xmax,ymax=(2.0,1.0) - prop_Γ_N = 0.2 - dom = (0,xmax,0,ymax) - el_size = (400,200) - γ = 0.1 - γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) - tol = 1/(5order^2)/minimum(el_size) - C = isotropic_elast_tensor(2,1000,0.3) - η_coeff = 2 - α_coeff = 4 - vf = 0.4 - g = VectorValue(0,-10) - path = dirname(dirname(@__DIR__))*"/results/highres_LE_comparison" - mkdir(path) - - ## FE Setup - model = CartesianDiscreteModel(dom,el_size) - el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0) - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - vol_D = sum(∫(1)dΩ) - - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,VectorValue(0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - - ## Create FE functions - φh = interpolate(initial_lsf(4,0.2),V_φ) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(v⋅g)dΓ_N - - ## Optimisation functionals - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(u)))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫((C ⊙ ε(u) ⊙ ε(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; - Vol(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; - dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - - ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) - - ## Setup solver and FE operators - state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) - pcfs = PDEConstrainedFunctionals(J,[Vol],state_map,analytic_dJ=dJ,analytic_dC=[dVol]) - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(el_Δ) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; - vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - - ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; - γ,γ_reinit,verbose=true,constraint_names=[:Vol]) - for (it,uh,φh) in optimiser - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) - write_history(path*"/history.txt",optimiser.history) - end - it = get_history(optimiser).niter; uh = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) -end - -main_LE_comparison() \ No newline at end of file diff --git a/scripts/_dev/Added_for_paper/thermal_MPI.jl b/scripts/_dev/Added_for_paper/thermal_MPI.jl deleted file mode 100644 index 446c0a54..00000000 --- a/scripts/_dev/Added_for_paper/thermal_MPI.jl +++ /dev/null @@ -1,88 +0,0 @@ -using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, - SparseMatricesCSR - -function main(mesh_partition,distribute) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - # FE parameters - order = 1 # Finite element order - xmax = ymax = 1.0 # Domain size - dom = (0,xmax,0,ymax) # Bounding domain - el_size = (200,200) # Mesh partition size - prop_Γ_N = 0.2 # Γ_N size parameter - prop_Γ_D = 0.2 # Γ_D size parameter - f_Γ_N(x) = (x[1] ≈ xmax && # Γ_N indicator function - ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0 && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) # @$\lvert\lvert$@ - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Advection tolerance - # Problem parameters - κ = 1 # Diffusivity - g = 1 # Heat flow in - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - iter_mod = 10 # VTK Output modulo - path = "./results/tut1_MPI_FIXEDSign/" # Output path - i_am_main(ranks) && mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe) - V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N - solver = PETScLinearSolver() - state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - vol_D = sum(∫(1)dΩ) - C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C],state_map, - analytic_dJ=dJ,analytic_dC=[dC]) - # Velocity extension - α = 4*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension(a_hilb, U_reg, V_reg) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; - γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) - # Solve - for (it,uh,φh) in optimiser - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|nabla(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && (writevtk(Ω,path*"out$it",cellfields=data);GC.gc()) - write_history(path*"/history.txt",get_history(optimiser);ranks) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, - "H(φ)"=>(H ∘ φh),"|nabla(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -with_mpi() do distribute - mesh_partition = (2,2) - main(mesh_partition,distribute) -end \ No newline at end of file diff --git a/scripts/_dev/Added_for_paper/thermal_PETSc.jl b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl similarity index 50% rename from scripts/_dev/Added_for_paper/thermal_PETSc.jl rename to scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl index 9b1383cf..b3bd339d 100644 --- a/scripts/_dev/Added_for_paper/thermal_PETSc.jl +++ b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl @@ -1,99 +1,104 @@ -using LevelSetTopOpt, Gridap, GridapPETSc, SparseMatricesCSR - -function main() - # FE parameters - order = 1 # Finite element order - xmax = ymax = 1.0 # Domain size - dom = (0,xmax,0,ymax) # Bounding domain - el_size = (200,200) # Mesh partition size - prop_Γ_N = 0.2 # Γ_N size parameter - prop_Γ_D = 0.2 # Γ_D size parameter - f_Γ_N(x) = (x[1] ≈ xmax && # Γ_N indicator function - ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0 && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance - # Problem parameters - κ = 1 # Diffusivity - g = 1 # Heat flow in - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - iter_mod = 10 # VTK Output modulo - path = "./results/tut1_PETSc/" # Output path - mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe) - V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - solver = PETScLinearSolver() - state_map = AffineFEStateMap( - a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver,adjoint_ls = solver - ) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - vol_D = sum(∫(1)dΩ) - C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C],state_map, - analytic_dJ=dJ,analytic_dC=[dC]) - # Velocity extension - α = 4*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = solver - ) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; - γ,γ_reinit,verbose=true,constraint_names=[:Vol]) - # Solve - for (it,uh,φh) in optimiser - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && (writevtk(Ω,path*"out$it",cellfields=data);GC.gc()) - write_history(path*"/history.txt",get_history(optimiser)) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, - "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" -GridapPETSc.with(args=split(solver_options)) do - main() +using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, + SparseMatricesCSR + +function main(mesh_partition,distribute) + ranks = distribute(LinearIndices((prod(mesh_partition),))) + # FE parameters + order = 1 # Finite element order + xmax,ymax,zmax = (2.0,1.0,1.0) # Domain size + dom = (0,xmax,0,ymax,0,zmax) # Bounding domain + el_size = (160,80,80) # Mesh partition size + prop_Γ_N = 0.2 # Γ_N size parameter + f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function + (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& + (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0) # Γ_D indicator function + # FD parameters + γ = 0.1 # HJ eqn time step coeff + γ_reinit = 0.5 # Reinit. eqn time step coeff + max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance + # Problem parameters + C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor + g = VectorValue(0,0,-1) # Applied load on Γ_N + vf = 0.4 # Volume fraction constraint + lsf_func = initial_lsf(4,0.2) # Initial level set function + iter_mod = 10 # VTK Output modulo + path = "./results/elast_comp_MPI_3D/" # Output path + i_am_main(ranks) && mkpath(path) # Create path + # Model + model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); + update_labels!(1,model,f_Γ_D,"Gamma_D") + update_labels!(2,model,f_Γ_N,"Gamma_N") + # Triangulation and measures + Ω = Triangulation(model) + Γ_N = BoundaryTriangulation(model,tags="Gamma_N") + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + # Spaces + reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) + V_φ = TestFESpace(model,reffe_scalar) + V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) + U_reg = TrialFESpace(V_reg,0) + # Level set and interpolator + φh = interpolate(lsf_func,V_φ) + interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + # Weak formulation + a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ + l(v,φ,dΩ,dΓ_N) = ∫(v⋅g)dΓ_N + Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} + Tv = Vector{PetscScalar} + solver = ElasticitySolver(V) + state_map = AffineFEStateMap( + a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; + assem_U = SparseMatrixAssembler(Tm,Tv,U,V), + assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), + assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), + ls = solver,adjoint_ls = solver + ) + # Objective and constraints + J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(u)))dΩ + dJ(q,u,φ,dΩ,dΓ_N) = ∫((C ⊙ ε(u) ⊙ ε(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + vol_D = sum(∫(1)dΩ) + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C1],state_map, + analytic_dJ=dJ,analytic_dC=[dC1]) + # Velocity extension + α = 4*maximum(get_el_Δ(model)) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ + vel_ext = VelocityExtension( + a_hilb, U_reg, V_reg; + assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), + ls = PETScLinearSolver() + ) + # Finite difference scheme + scheme = FirstOrderStencil(length(el_size),Float64) + stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + # Optimiser + optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + verbose=i_am_main(ranks)) + # Solve + for (it,uh,φh) in optimiser + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) + write_history(path*"/history.txt",get_history(optimiser);ranks) + end + # Final structure + it = get_history(optimiser).niter; uh = get_state(pcfs) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, + "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) +end + +with_mpi() do distribute + mesh_partition = (5,5,5) + solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + -ksp_converged_reason -ksp_rtol 1.0e-12" + GridapPETSc.with(args=split(solver_options)) do + main(mesh_partition,distribute) + end end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl new file mode 100644 index 00000000..919e046e --- /dev/null +++ b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl @@ -0,0 +1,118 @@ +using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, + SparseMatricesCSR + +function main(mesh_partition,distribute) + ranks = distribute(LinearIndices((prod(mesh_partition),))) + # FE parameters + order = 1 # Finite element order + xmax,ymax,zmax = (2.0,1.0,1.0) # Domain size + dom = (0,xmax,0,ymax,0,zmax) # Bounding domain + el_size = (160,80,80) # Mesh partition size + prop_Γ_N = 0.2 # Γ_N size parameter + f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function + (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& + (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0) # Γ_D indicator function + # FD parameters + γ = 0.1 # HJ eqn time step coeff + γ_reinit = 0.5 # Reinit. eqn time step coeff + max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance + # Problem parameters + E = 1000 # Young's modulus + ν = 0.3 # Poisson's ratio + μ, λ = E/(2*(1 + ν)), E*ν/((1 + ν)*(1 - 2*ν)) # Lame constants + g = VectorValue(0,0,-1) # Applied load on Γ_N + vf = 0.4 # Volume fraction constraint + lsf_func = initial_lsf(4,0.2) # Initial level set function + iter_mod = 10 # VTK Output modulo + path = "./results/hyperelast_comp_MPI_3D/" # Output path + i_am_main(ranks) && mkpath(path) # Create path + # Model + model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); + update_labels!(1,model,f_Γ_D,"Gamma_D") + update_labels!(2,model,f_Γ_N,"Gamma_N") + # Triangulation and measures + Ω = Triangulation(model) + Γ_N = BoundaryTriangulation(model,tags="Gamma_N") + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + # Spaces + reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) + V_φ = TestFESpace(model,reffe_scalar) + V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) + U_reg = TrialFESpace(V_reg,0) + # Level set and interpolator + φh = interpolate(lsf_func,V_φ) + interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + # Weak formulation + ## Piola-Kirchhoff tensor + function S(∇u) + Cinv = inv(C(F(∇u))) + μ*(one(∇u)-Cinv) + λ*log(J(F(∇u)))*Cinv + end + ## Derivative of Green strain + dE(∇du,∇u) = 0.5*( ∇du⋅F(∇u) + (∇du⋅F(∇u))' ) + ## Right Cauchy-Green deformation tensor + C(F) = (F')⋅F + ## Deformation gradient tensor + F(∇u) = one(∇u) + ∇u' + ## Volume change + J(F) = sqrt(det(C(F))) + ## Residual + res(u,v,φ,dΩ,dΓ_N) = ∫( (I ∘ φ)*((dE ∘ (∇(v),∇(u))) ⊙ (S ∘ ∇(u))) )*dΩ - ∫(g⋅v)dΓ_N + Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} + Tv = Vector{PetscScalar} + lin_solver = ElasticitySolver(V) + nl_solver = NewtonSolver(lin_solver;maxiter=50,rtol=10^-8,verbose=i_am_main(ranks)) + state_map = NonlinearFEStateMap( + res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; + assem_U = SparseMatrixAssembler(Tm,Tv,U,V), + assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), + assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), + nls = nl_solver, adjoint_ls = lin_solver + ) + # Objective and constraints + J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*((dE ∘ (∇(u),∇(u))) ⊙ (S ∘ ∇(u))))dΩ + vol_D = sum(∫(1)dΩ) + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C1],state_map,analytic_dC=[dC1]) + # Velocity extension + α = 4*maximum(get_el_Δ(model)) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ + vel_ext = VelocityExtension( + a_hilb, U_reg, V_reg; + assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), + ls = PETScLinearSolver() + ) + # Finite difference scheme + scheme = FirstOrderStencil(length(el_size),Float64) + stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + # Optimiser + optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + verbose=i_am_main(ranks)) + # Solve + for (it,uh,φh) in optimiser + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) + write_history(path*"/history.txt",get_history(optimiser);ranks) + end + # Final structure + it = get_history(optimiser).niter; uh = get_state(pcfs) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, + "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) +end + +with_mpi() do distribute + mesh_partition = (5,5,5) + solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + -ksp_converged_reason -ksp_rtol 1.0e-12" + GridapPETSc.with(args=split(solver_options)) do + main(mesh_partition,distribute) + end +end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl new file mode 100644 index 00000000..eab453d0 --- /dev/null +++ b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl @@ -0,0 +1,108 @@ +using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, + SparseMatricesCSR + +function main(mesh_partition,distribute) + ranks = distribute(LinearIndices((prod(mesh_partition),))) + # FE parameters + order = 1 # Finite element order + xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size + dom = (0,xmax,0,ymax,0,zmax) # Bounding domain + el_size = (100,100,100) # Mesh partition size + f_Γ_D(x) = iszero(x) # Γ_D indicator function + # FD parameters + γ = 0.1 # HJ eqn time step coeff + γ_reinit = 0.5 # Reinit. eqn time step coeff + max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance + # Problem parameters + C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor + g = VectorValue(0,0,-1) # Applied load on Γ_N + vf = 0.4 # Volume fraction constraint + lsf_func(x) = cos(2π*x[1]) + cos(2π*x[2]) + # Initial level set function + cos(2π*x[3]) + iter_mod = 10 # VTK Output modulo + path = "./results/inverse_hom_MPI_3D/" # Output path + i_am_main(ranks) && mkpath(path) # Create path + # Model + model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true,true)); + update_labels!(1,model,f_Γ_D,"origin") + # Triangulation and measures + Ω = Triangulation(model) + dΩ = Measure(Ω,2*order) + # Spaces + reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["origin"]) + U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) + V_φ = TestFESpace(model,reffe_scalar) + V_reg = TestFESpace(model,reffe_scalar) + U_reg = TrialFESpace(V_reg) + # Level set and interpolator + φh = interpolate(lsf_func,V_φ) + interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + # Weak formulation + εᴹ = (TensorValue(1.,0.,0.,0.,0.,0.,0.,0.,0.), + TensorValue(0.,0.,0.,0.,1.,0.,0.,0.,0.), + TensorValue(0.,0.,0.,0.,0.,0.,0.,0.,1.), + TensorValue(0.,0.,0.,0.,0.,1/2,0.,1/2,0.), + TensorValue(0.,0.,1/2,0.,0.,0.,1/2,0.,0.), + TensorValue(0.,1/2,0.,1/2,0.,0.,0.,0.,0.)) + a(u,v,φ,dΩ) = ∫((I ∘ φ) * C ⊙ ε(u) ⊙ ε(v))dΩ + l = [(v,φ,dΩ) -> ∫(-(I ∘ φ) * C ⊙ εᴹ[i] ⊙ ε(v))dΩ for i in 1:6] + Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} + Tv = Vector{PetscScalar} + solver = ElasticitySolver(V) + state_map = RepeatingAffineFEStateMap( + 6,a,l,U,V,V_φ,U_reg,φh,dΩ; + assem_U = SparseMatrixAssembler(Tm,Tv,U,V), + assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), + assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), + ls = solver, adjoint_ls = solver + ) + # Objective and constraints + Cᴴ(r,s,u,φ,dΩ) = ∫((I ∘ φ)*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ εᴹ[s]))dΩ + dCᴴ(r,s,q,u,φ,dΩ) = ∫(-q*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ (ε(u[s])+εᴹ[s]))*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + κ(u,φ,dΩ) = -1/9*(Cᴴ(1,1,u,φ,dΩ)+Cᴴ(2,2,u,φ,dΩ)+Cᴴ(3,3,u,φ,dΩ)+ + 2*(Cᴴ(1,2,u,φ,dΩ)+Cᴴ(1,3,u,φ,dΩ)+Cᴴ(2,3,u,φ,dΩ))) + dκ(q,u,φ,dΩ) = -1/9*(dCᴴ(1,1,q,u,φ,dΩ)+dCᴴ(2,2,q,u,φ,dΩ)+dCᴴ(3,3,q,u,φ,dΩ)+ + 2*(dCᴴ(1,2,q,u,φ,dΩ)+dCᴴ(1,3,q,u,φ,dΩ)+dCᴴ(2,3,q,u,φ,dΩ))) + vol_D = sum(∫(1)dΩ) + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(κ,[C1],state_map, + analytic_dJ=dκ,analytic_dC=[dC1]) + # Velocity extension + α = 4*maximum(get_el_Δ(model)) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ + vel_ext = VelocityExtension( + a_hilb, U_reg, V_reg; + assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), + ls = PETScLinearSolver() + ) + # Finite difference scheme + scheme = FirstOrderStencil(length(el_size),Float64) + stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + # Optimiser + optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + verbose=i_am_main(ranks)) + # Solve + for (it,uh,φh) in optimiser + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) + write_history(path*"/history.txt",get_history(optimiser);ranks) + end + # Final structure + it = get_history(optimiser).niter; uh = get_state(pcfs) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, + "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))]) +end + +with_mpi() do distribute + mesh_partition = (5,5,5) + solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + -ksp_converged_reason -ksp_rtol 1.0e-12" + GridapPETSc.with(args=split(solver_options)) do + main(mesh_partition,distribute) + end +end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl new file mode 100644 index 00000000..0dbac675 --- /dev/null +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -0,0 +1,114 @@ +using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, + SparseMatricesCSR + +function main(mesh_partition,distribute) + ranks = distribute(LinearIndices((prod(mesh_partition),))) + # FE parameters + order = 1 # Finite element order + xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size + dom = (0,xmax,0,ymax,0,zmax) # Bounding domain + el_size = (100,100,100) # Mesh partition size + f_Γ_in(x) = (x[1] ≈ 0.0) && # Γ_in indicator function + (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) + f_Γ_out(x) = (x[1] ≈ 1.0) && # Γ_out indicator function + (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function + (x[2] <= 0.1 || x[2] >= 0.9) && (x[3] <= 0.1 || x[3] >= 0.9) + # FD parameters + γ = 0.1 # HJ eqn time step coeff + γ_reinit = 0.5 # Reinit. eqn time step coeff + max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance + # Problem parameters + C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor + g = VectorValue(0,0,-1) # Applied load on Γ_N + vf = 0.4 # Volume fraction constraint + sphere(x,(xc,yc,zc)) = -sqrt((x[1]-xc)^2+(x[2]-yc)^2+(x[3]-zc)^2) + 0.2 + lsf_func(x) = max(initial_lsf(4,0.2)(x), # Initial level set function + sphere(x,(1,0,0)),sphere(x,(1,0,1)),sphere(x,(1,1,0)),sphere(x,(1,1,1))) + lsf_func = initial_lsf(4,0.2) # Initial level set function + iter_mod = 10 # VTK Output modulo + path = "./results/inverter_MPI_3D/" # Output path + i_am_main(ranks) && mkpath(path) # Create path + # Model + model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); + update_labels!(1,model,f_Γ_in,"Gamma_in") + update_labels!(2,model,f_Γ_out,"Gamma_out") + update_labels!(4,model,f_Γ_D,"Gamma_D") + # Triangulation and measures + Ω = Triangulation(model) + Γ_in = BoundaryTriangulation(model,tags="Gamma_in") + Γ_out = BoundaryTriangulation(model,tags="Gamma_out") + dΩ = Measure(Ω,2*order) + dΓ_in = Measure(Γ_in,2*order) + dΓ_out = Measure(Γ_out,2*order) + # Spaces + reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) + V_φ = TestFESpace(model,reffe_scalar) + V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_in","Gamma_out"]) + U_reg = TrialFESpace(V_reg,0) + # Level set and interpolator + φh = interpolate(lsf_func,V_φ); + interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + # Weak formulation + a(u,v,φ,dΩ,dΓ_in,dΓ_out) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ + ∫(ks*(u⋅v))dΓ_out + l(v,φ,dΩ,dΓ_in,dΓ_out) = ∫(v⋅g)dΓ_in + Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} + Tv = Vector{PetscScalar} + solver = ElasticitySolver(V) + state_map = AffineFEStateMap( + a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; + assem_U = SparseMatrixAssembler(Tm,Tv,U,V), + assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), + assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), + ls = solver,adjoint_ls = solver + ) + # Objective and constraints + e₁ = VectorValue(1,0,0) + vol_Γ_in = sum(∫(1)dΓ_in) + vol_Γ_out = sum(∫(1)dΓ_out) + vol_D = sum(∫(1)dΩ) + J(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅e₁)/vol_Γ_in)dΓ_in + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + C2(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out + pcfs = PDEConstrainedFunctionals(J,[C1,C2],state_map, + analytic_dJ=dJ,analytic_dC=[dC1,nothing]) + # Velocity extension + α = 4*maximum(get_el_Δ(model)) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ + vel_ext = VelocityExtension( + a_hilb, U_reg, V_reg; + assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), + ls = PETScLinearSolver() + ) + # Finite difference scheme + scheme = FirstOrderStencil(length(el_size),Float64) + stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + # Optimiser + optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + verbose=i_am_main(ranks)) + # Solve + for (it,uh,φh) in optimiser + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) + write_history(path*"/history.txt",get_history(optimiser);ranks) + end + # Final structure + it = get_history(optimiser).niter; uh = get_state(pcfs) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, + "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) +end + +with_mpi() do distribute + mesh_partition = (5,5,5) + solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + -ksp_converged_reason -ksp_rtol 1.0e-12" + GridapPETSc.with(args=split(solver_options)) do + main(mesh_partition,distribute) + end +end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs new file mode 100644 index 00000000..38e3aaa8 --- /dev/null +++ b/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs @@ -0,0 +1,16 @@ +#!/bin/bash -l +#PBS -P LSTO +#PBS -N elast_comp_MPI_3D + +#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 +#PBS -l walltime=50:00:00 +#PBS -j oe + +source $HOME/hpc-environments-main/lyra/load-ompi.sh +PROJECT_DIR=$HOME/LevelSetTopOpt/ + +julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" + +mpirun --hostfile $PBS_NODEFILE \ + julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs new file mode 100644 index 00000000..a9c89845 --- /dev/null +++ b/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs @@ -0,0 +1,16 @@ +#!/bin/bash -l +#PBS -P LSTO +#PBS -N hyperelast_comp_MPI_3D + +#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 +#PBS -l walltime=50:00:00 +#PBS -j oe + +source $HOME/hpc-environments-main/lyra/load-ompi.sh +PROJECT_DIR=$HOME/LevelSetTopOpt/ + +julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" + +mpirun --hostfile $PBS_NODEFILE \ + julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs new file mode 100644 index 00000000..d1a72278 --- /dev/null +++ b/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs @@ -0,0 +1,16 @@ +#!/bin/bash -l +#PBS -P LSTO +#PBS -N inverse_hom_MPI_3D + +#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 +#PBS -l walltime=50:00:00 +#PBS -j oe + +source $HOME/hpc-environments-main/lyra/load-ompi.sh +PROJECT_DIR=$HOME/LevelSetTopOpt/ + +julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" + +mpirun --hostfile $PBS_NODEFILE \ + julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs new file mode 100644 index 00000000..aeeada29 --- /dev/null +++ b/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs @@ -0,0 +1,16 @@ +#!/bin/bash -l +#PBS -P LSTO +#PBS -N inverter_MPI_3D + +#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 +#PBS -l walltime=50:00:00 +#PBS -j oe + +source $HOME/hpc-environments-main/lyra/load-ompi.sh +PROJECT_DIR=$HOME/LevelSetTopOpt/ + +julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" + +mpirun --hostfile $PBS_NODEFILE \ + julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs new file mode 100644 index 00000000..795dc33d --- /dev/null +++ b/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs @@ -0,0 +1,17 @@ +#!/bin/bash -l + +#PBS -P LSTO +#PBS -N therm_comp_MPI_3D + +#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 +#PBS -l walltime=23:00:00 +#PBS -j oe + +source $HOME/hpc-environments-main/lyra/load-ompi.sh +PROJECT_DIR=$HOME/LevelSetTopOpt/ + +julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" + +mpirun --hostfile $PBS_NODEFILE \ + julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl \ No newline at end of file diff --git a/scripts/_dev/Added_for_paper/thermal_MPI_PETSc.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI.jl similarity index 86% rename from scripts/_dev/Added_for_paper/thermal_MPI_PETSc.jl rename to scripts/_dev/Paper_scripts/therm_comp_MPI.jl index ef08aa72..a0b1afeb 100644 --- a/scripts/_dev/Added_for_paper/thermal_MPI_PETSc.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_MPI.jl @@ -5,7 +5,7 @@ function main(mesh_partition,distribute) ranks = distribute(LinearIndices((prod(mesh_partition),))) # FE parameters order = 1 # Finite element order - xmax = ymax = 1.0 # Domain size + xmax,ymax = (1.0,1.0) # Domain size dom = (0,xmax,0,ymax) # Bounding domain el_size = (200,200) # Mesh partition size prop_Γ_N = 0.2 # Γ_N size parameter @@ -25,7 +25,7 @@ function main(mesh_partition,distribute) vf = 0.4 # Volume fraction constraint lsf_func = initial_lsf(4,0.2) # Initial level set function iter_mod = 10 # VTK Output modulo - path = "./results/tut1_MPI_PETSc/" # Output path + path = "./results/therm_comp_MPI/" # Output path i_am_main(ranks) && mkpath(path) # Create path # Model model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -64,10 +64,10 @@ function main(mesh_partition,distribute) J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ vol_D = sum(∫(1)dΩ) - C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C],state_map, - analytic_dJ=dJ,analytic_dC=[dC]) + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C1],state_map, + analytic_dJ=dJ,analytic_dC=[dC1]) # Velocity extension α = 4*maximum(get_el_Δ(model)) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ @@ -80,12 +80,11 @@ function main(mesh_partition,distribute) scheme = FirstOrderStencil(length(el_size),Float64) stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; - γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) + optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=i_am_main(ranks)) # Solve for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && (writevtk(Ω,path*"out$it",cellfields=data);GC.gc()) + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",get_history(optimiser);ranks) end # Final structure diff --git a/scripts/_dev/Added_for_paper/thermal_MPI_PETSc_3D.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl similarity index 87% rename from scripts/_dev/Added_for_paper/thermal_MPI_PETSc_3D.jl rename to scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl index 90addf1d..0fb2889c 100644 --- a/scripts/_dev/Added_for_paper/thermal_MPI_PETSc_3D.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl @@ -5,8 +5,8 @@ function main(mesh_partition,distribute) ranks = distribute(LinearIndices((prod(mesh_partition),))) # FE parameters order = 1 # Finite element order - xmax = ymax = 1.0 # Domain size - dom = (0,xmax,0,ymax) # Bounding domain + xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size + dom = (0,xmax,0,ymax,0,zmax) # Bounding domain el_size = (150,150,150) # Mesh partition size prop_Γ_N = 0.2 # Γ_N size parameter prop_Γ_D = 0.2 # Γ_D size parameter @@ -27,7 +27,7 @@ function main(mesh_partition,distribute) vf = 0.4 # Volume fraction constraint lsf_func = initial_lsf(4,0.2) # Initial level set function iter_mod = 10 # VTK Output modulo - path = "./results/tut1_MPI_PETSc_3D/" # Output path + path = "./results/therm_comp_MPI_3D/" # Output path i_am_main(ranks) && mkpath(path) # Create path # Model model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -66,10 +66,10 @@ function main(mesh_partition,distribute) J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ vol_D = sum(∫(1)dΩ) - C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C],state_map, - analytic_dJ=dJ,analytic_dC=[dC]) + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C1],state_map, + analytic_dJ=dJ,analytic_dC=[dC1]) # Velocity extension α = 4*maximum(get_el_Δ(model)) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ @@ -82,12 +82,12 @@ function main(mesh_partition,distribute) scheme = FirstOrderStencil(length(el_size),Float64) stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; - γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) + optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + verbose=i_am_main(ranks)) # Solve for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && (writevtk(Ω,path*"out$it",cellfields=data);GC.gc()) + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",get_history(optimiser);ranks) end # Final structure diff --git a/scripts/_dev/Added_for_paper/thermal_serial.jl b/scripts/_dev/Paper_scripts/therm_comp_serial.jl similarity index 93% rename from scripts/_dev/Added_for_paper/thermal_serial.jl rename to scripts/_dev/Paper_scripts/therm_comp_serial.jl index 115e1b5e..055f5ad9 100644 --- a/scripts/_dev/Added_for_paper/thermal_serial.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_serial.jl @@ -23,7 +23,7 @@ function main() vf = 0.4 # Volume fraction constraint lsf_func = initial_lsf(4,0.2) # Initial level set function iter_mod = 10 # VTK Output modulo - path = "./results/tut1/" # Output path + path = "./results/therm_comp_serial/" # Output path mkpath(path) # Create path # Model model = CartesianDiscreteModel(dom,el_size); @@ -65,8 +65,8 @@ function main() scheme = FirstOrderStencil(length(el_size),Float64) stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; - γ,γ_reinit,verbose=true,constraint_names=[:Vol]) + optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + verbose=true) # Solve for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] From dbb13b0f62dd298b1f5ba4d61ef3dff15f85c165 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 4 Apr 2024 15:39:26 +1000 Subject: [PATCH 16/90] Consistency --- scripts/_dev/Paper_scripts/therm_comp_serial.jl | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/scripts/_dev/Paper_scripts/therm_comp_serial.jl b/scripts/_dev/Paper_scripts/therm_comp_serial.jl index 055f5ad9..6c657510 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_serial.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_serial.jl @@ -53,10 +53,10 @@ function main() J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ vol_D = sum(∫(1)dΩ) - C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C],state_map, - analytic_dJ=dJ,analytic_dC=[dC]) + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C1],state_map, + analytic_dJ=dJ,analytic_dC=[dC1]) # Velocity extension α = 4*maximum(get_el_Δ(model)) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ From 7253fc4ec1916758b3b814e4b592633fde42ac81 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sat, 6 Apr 2024 10:32:23 +1000 Subject: [PATCH 17/90] typo fix --- src/Advection.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/Advection.jl b/src/Advection.jl index ebd31306..241af032 100644 --- a/src/Advection.jl +++ b/src/Advection.jl @@ -74,7 +74,7 @@ function reinit!(::FirstOrderStencil{2,T},φ_new,φ,vel,Δt,Δx,isperiodic,cache # Sign approximation ∇⁺ .= @. (D⁺ʸ - D⁻ʸ)/(2Δy); ~yperiodic ? ∇⁺[:,[1,end]] .= zero(T) : 0; ∇⁻ .= @. (D⁺ˣ - D⁻ˣ)/(2Δx); ~xperiodic ? ∇⁻[[1,end],:] .= zero(T) : 0; - ϵₛ = maximum((Δx,Δy)) + ϵₛ = minimum((Δx,Δy)) vel .= @. φ/sqrt(φ^2 + ϵₛ^2*(∇⁺^2+∇⁻^2)) # Forward (+) & Backward (-) D⁺ʸ .= @. (D⁺ʸ - φ)/Δy; ~yperiodic ? D⁺ʸ[:,end] .= zero(T) : 0; @@ -129,7 +129,7 @@ function reinit!(::FirstOrderStencil{3,T},φ_new,φ,vel,Δt,Δx,isperiodic,cache ∇⁻ .= @. (D⁺ˣ - D⁻ˣ)/(2Δx); ~xperiodic ? ∇⁻[[1,end],:,:] .= zero(T) : 0; ∇⁺ .= @. ∇⁺^2+∇⁻^2 # |∇φ|² (partially computed) ∇⁻ .= @. (D⁺ᶻ - D⁻ᶻ)/(2Δz); ~xperiodic ? ∇⁻[:,:,[1,end]] .= zero(T) : 0; - ϵₛ = maximum((Δx,Δy)) + ϵₛ = minimum((Δx,Δy,Δz)) vel .= @. φ/sqrt(φ^2 + ϵₛ^2*(∇⁺+∇⁻^2)) # Forward (+) & Backward (-) D⁺ʸ .= (D⁺ʸ - φ)/Δy; ~yperiodic ? D⁺ʸ[:,end,:] .= zero(T) : 0; From 2d613e52a04204009972ca741dd2b5baf667a2d3 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sun, 7 Apr 2024 10:10:24 +1000 Subject: [PATCH 18/90] Several script tuning changes --- scripts/MPI/3d_elastic_compliance_ALM.jl | 15 ++- scripts/MPI/3d_hyperelastic_compliance_ALM.jl | 18 +-- .../3d_hyperelastic_compliance_neohook_ALM.jl | 18 +-- scripts/MPI/3d_inverse_homenisation_ALM.jl | 15 ++- scripts/MPI/3d_inverter_ALM.jl | 15 ++- scripts/MPI/3d_inverter_HPM.jl | 15 ++- .../3d_nonlinear_thermal_compliance_ALM.jl | 15 ++- scripts/MPI/3d_thermal_compliance_ALM.jl | 22 ++-- scripts/MPI/elastic_compliance_ALM.jl | 4 +- scripts/MPI/inverse_homenisation_ALM.jl | 4 +- .../MPI/jobs/3d_elastic_compliance_ALM.pbs | 13 ++- .../jobs/3d_hyperelastic_compliance_ALM.pbs | 13 ++- ...3d_hyperelastic_compliance_neohook_ALM.pbs | 13 ++- .../MPI/jobs/3d_inverse_homenisation_ALM.pbs | 13 ++- scripts/MPI/jobs/3d_inverter_ALM.pbs | 14 ++- scripts/MPI/jobs/3d_inverter_HPM.pbs | 14 ++- .../3d_nonlinear_thermal_compliance_ALM.pbs | 14 ++- .../MPI/jobs/3d_thermal_compliance_ALM.pbs | 20 ++-- scripts/MPI/thermal_compliance_ALM.jl | 4 +- scripts/MPI/thermal_compliance_ALM_PETSc.jl | 4 +- scripts/Serial/elastic_compliance_ALM.jl | 4 +- scripts/Serial/elastic_compliance_HPM.jl | 4 +- scripts/Serial/elastic_compliance_LM.jl | 4 +- scripts/Serial/hyperelastic_compliance_ALM.jl | 4 +- .../hyperelastic_compliance_neohook_ALM.jl | 4 +- scripts/Serial/inverse_homenisation_ALM.jl | 4 +- scripts/Serial/inverter_ALM.jl | 4 +- scripts/Serial/inverter_HPM.jl | 4 +- .../nonlinear_thermal_compliance_ALM.jl | 4 +- scripts/Serial/thermal_compliance_ALM.jl | 6 +- .../thermal_compliance_ALM_higherorderlsf.jl | 104 ++++++++++++++++++ .../_dev/Paper_scripts/elast_comp_MPI_3D.jl | 4 +- .../Paper_scripts/hyperelast_comp_MPI_3D.jl | 4 +- .../_dev/Paper_scripts/inverse_hom_MPI_3D.jl | 4 +- scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 4 +- .../Paper_scripts/jobs/elast_comp_MPI_3D.pbs | 3 +- .../jobs/hyperelast_comp_MPI_3D.pbs | 3 +- .../Paper_scripts/jobs/inverse_hom_MPI_3D.pbs | 3 +- .../Paper_scripts/jobs/inverter_MPI_3D.pbs | 3 +- scripts/_dev/Paper_scripts/therm_comp_MPI.jl | 4 +- .../_dev/Paper_scripts/therm_comp_MPI_3D.jl | 4 +- .../_dev/Paper_scripts/therm_comp_serial.jl | 6 +- src/Optimisers/AugmentedLagrangian.jl | 6 +- 43 files changed, 320 insertions(+), 137 deletions(-) create mode 100644 scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl diff --git a/scripts/MPI/3d_elastic_compliance_ALM.jl b/scripts/MPI/3d_elastic_compliance_ALM.jl index 8ae4b8c3..8bf651f1 100644 --- a/scripts/MPI/3d_elastic_compliance_ALM.jl +++ b/scripts/MPI/3d_elastic_compliance_ALM.jl @@ -1,6 +1,13 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) + """ (MPI) Minimum elastic compliance with augmented Lagrangian method in 3D. @@ -21,12 +28,12 @@ function main(mesh_partition,distribute,el_size) dom = (0,xmax,0,ymax,0,zmax) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/5) tol = 1/(5order^2)/minimum(el_size) C = isotropic_elast_tensor(3,1.,0.3) g = VectorValue(0,0,-1) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/3d_elastic_compliance_ALM/" iter_mod = 10 @@ -112,8 +119,8 @@ function main(mesh_partition,distribute,el_size) end with_mpi() do distribute - mesh_partition = (5,5,5) - el_size = (160,80,80) + mesh_partition = (Px,Py,Pz) + el_size = (elx,ely,elz) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" diff --git a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl index ad197331..8c24bbcb 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl @@ -3,11 +3,15 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, using GridapSolvers: NewtonSolver +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) + """ (MPI) Minimum hyperelastic compliance with augmented Lagrangian method in 3D. - - Optimisation problem: - ... """ function main(mesh_partition,distribute,el_size) ranks = distribute(LinearIndices((prod(mesh_partition),))) @@ -19,10 +23,10 @@ function main(mesh_partition,distribute,el_size) dom = (0,xmax,0,ymax,0,zmax) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/3d_hyperelastic_compliance_ALM/" iter_mod = 10 @@ -118,8 +122,8 @@ function main(mesh_partition,distribute,el_size) end with_mpi() do distribute - mesh_partition = (5,5,5) - el_size = (160,80,80) + mesh_partition = (Px,Py,Pz) + el_size = (elx,ely,elz) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" diff --git a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl index cc428534..662071b7 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl @@ -3,11 +3,15 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, using GridapSolvers: NewtonSolver +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) + """ (MPI) Minimum hyperelastic compliance with augmented Lagrangian method in 3D. - - Optimisation problem: - ... """ function main(mesh_partition,distribute,el_size) ranks = distribute(LinearIndices((prod(mesh_partition),))) @@ -19,10 +23,10 @@ function main(mesh_partition,distribute,el_size) dom = (0,xmax,0,ymax,0,zmax) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/3d_hyperelastic_compliance_neohook_ALM/" iter_mod = 10 @@ -132,8 +136,8 @@ function main(mesh_partition,distribute,el_size) end with_mpi() do distribute - mesh_partition = (5,5,5) - el_size = (160,80,80) + mesh_partition = (Px,Py,Pz) + el_size = (elx,ely,elz) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" diff --git a/scripts/MPI/3d_inverse_homenisation_ALM.jl b/scripts/MPI/3d_inverse_homenisation_ALM.jl index 2769375b..a0df9c4b 100644 --- a/scripts/MPI/3d_inverse_homenisation_ALM.jl +++ b/scripts/MPI/3d_inverse_homenisation_ALM.jl @@ -1,6 +1,13 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) + """ (MPI) Maximum bulk modulus inverse homogenisation with augmented Lagrangian method in 3D. @@ -20,11 +27,11 @@ function main(mesh_partition,distribute,el_size) dom = (0,xmax,0,ymax,0,zmax) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) C = isotropic_elast_tensor(3,1.,0.3) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.5 path = dirname(dirname(@__DIR__))*"/results/3d_inverse_homenisation_ALM/" iter_mod = 10 @@ -116,8 +123,8 @@ function main(mesh_partition,distribute,el_size) end with_mpi() do distribute - mesh_partition = (5,5,5) - el_size = (100,100,100) + mesh_partition = (Px,Py,Pz) + el_size = (elx,ely,elz) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" diff --git a/scripts/MPI/3d_inverter_ALM.jl b/scripts/MPI/3d_inverter_ALM.jl index 1e34d67e..fde12b40 100644 --- a/scripts/MPI/3d_inverter_ALM.jl +++ b/scripts/MPI/3d_inverter_ALM.jl @@ -1,6 +1,13 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) + """ (MPI) Inverter mechanism with Hilbertian projection method in 3D. @@ -23,11 +30,11 @@ function main(mesh_partition,distribute,el_size) dom = (0,1,0,1,0,1) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) C = isotropic_elast_tensor(3,1.0,0.3) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf=0.4 δₓ=0.5 ks = 0.01 @@ -130,8 +137,8 @@ function main(mesh_partition,distribute,el_size) end with_mpi() do distribute - mesh_partition = (5,5,5) - el_size = (100,100,100) + mesh_partition = (Px,Py,Pz) + el_size = (elx,ely,elz) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" diff --git a/scripts/MPI/3d_inverter_HPM.jl b/scripts/MPI/3d_inverter_HPM.jl index 1e051812..b645ab9c 100644 --- a/scripts/MPI/3d_inverter_HPM.jl +++ b/scripts/MPI/3d_inverter_HPM.jl @@ -1,6 +1,13 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) + """ (MPI) Inverter mechanism with Hilbertian projection method in 3D. @@ -23,11 +30,11 @@ function main(mesh_partition,distribute,el_size) dom = (0,1,0,1,0,1) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) C = isotropic_elast_tensor(3,1.0,0.3) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf=0.4 δₓ=0.5 ks = 0.01 @@ -131,8 +138,8 @@ function main(mesh_partition,distribute,el_size) end with_mpi() do distribute - mesh_partition = (5,5,5) - el_size = (100,100,100) + mesh_partition = (Px,Py,Pz) + el_size = (elx,ely,elz) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" diff --git a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl index 19598021..8aab7ed2 100644 --- a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl @@ -3,6 +3,13 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, using GridapSolvers: NewtonSolver +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) + """ (MPI) Minimum thermal compliance with augmented Lagrangian method in 3D with nonlinear diffusivity. @@ -26,10 +33,10 @@ function main(mesh_partition,distribute,el_size) dom = (0,xmax,0,ymax,0,zmax) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/3d_nonlinear_thermal_compliance_ALM/" iter_mod = 10 @@ -118,8 +125,8 @@ function main(mesh_partition,distribute,el_size) end with_mpi() do distribute - mesh_partition = (5,5,5) - el_size = (150,150,150) + mesh_partition = (Px,Py,Pz) + el_size = (elx,ely,elz) options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" diff --git a/scripts/MPI/3d_thermal_compliance_ALM.jl b/scripts/MPI/3d_thermal_compliance_ALM.jl index d9da92ff..eded269d 100644 --- a/scripts/MPI/3d_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_thermal_compliance_ALM.jl @@ -1,14 +1,12 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR -using GridapSolvers: NewtonSolver - -# global elx = parse(Int,ARGS[1]) -# global ely = parse(Int,ARGS[2]) -# global elz = parse(Int,ARGS[3]) -# global Px = parse(Int,ARGS[4]) -# global Py = parse(Int,ARGS[5]) -# global Pz = parse(Int,ARGS[6]) +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) """ (MPI) Minimum thermal compliance with augmented Lagrangian method in 3D. @@ -31,11 +29,11 @@ function main(mesh_partition,distribute,el_size,coef,step) dom = (0,xmax,0,ymax,0,zmax) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/step) + max_steps = floor(Int,order*minimum(el_size)/step) tol = 1/(coef*order^2)/minimum(el_size) κ = 1 η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/3d_thermal_compliance_ALM_Nx$(el_size[1])_Coef$(coef)_Step$(step)" iter_mod = 10 @@ -121,8 +119,8 @@ function main(mesh_partition,distribute,el_size,coef,step) end with_mpi() do distribute - mesh_partition = (5,5,5)#(Px,Py,Pz) - el_size = (150,150,150)#(elx,ely,elz) + mesh_partition = (Px,Py,Pz) + el_size = (elx,ely,elz) all_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" diff --git a/scripts/MPI/elastic_compliance_ALM.jl b/scripts/MPI/elastic_compliance_ALM.jl index 49f97724..21f8ce9a 100644 --- a/scripts/MPI/elastic_compliance_ALM.jl +++ b/scripts/MPI/elastic_compliance_ALM.jl @@ -21,12 +21,12 @@ function main(mesh_partition,distribute,el_size) dom = (0,xmax,0,ymax) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) C = isotropic_elast_tensor(2,1.,0.3) g = VectorValue(0,-1) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_ALM_MPI" iter_mod = 10 diff --git a/scripts/MPI/inverse_homenisation_ALM.jl b/scripts/MPI/inverse_homenisation_ALM.jl index 4b866b5f..e9a736db 100644 --- a/scripts/MPI/inverse_homenisation_ALM.jl +++ b/scripts/MPI/inverse_homenisation_ALM.jl @@ -20,11 +20,11 @@ function main(mesh_partition,distribute,el_size) dom = (0,xmax,0,ymax) γ = 0.05 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) C = isotropic_elast_tensor(2,1.,0.3) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.5 path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM_MPI" iter_mod = 10 diff --git a/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs b/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs index 3d6df3ef..81d10175 100644 --- a/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs @@ -3,7 +3,7 @@ #PBS -N 3d_elastic_compliance_ALM #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=50:00:00 +#PBS -l walltime=23:00:00 #PBS -j oe source $HOME/hpc-environments-main/lyra/load-ompi.sh @@ -11,6 +11,11 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_elastic_compliance_ALM.jl +mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/MPI/3d_elastic_compliance_ALM.jl \ + 160 \ + 80 \ + 80 \ + 5 \ + 5 \ + 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs b/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs index 19e1bde9..9a9d94c6 100644 --- a/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs @@ -3,7 +3,7 @@ #PBS -N 3d_hyperelastic_compliance_ALM #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=50:00:00 +#PBS -l walltime=23:00:00 #PBS -j oe source $HOME/hpc-environments-main/lyra/load-ompi.sh @@ -11,6 +11,11 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_hyperelastic_compliance_ALM.jl +mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/MPI/3d_hyperelastic_compliance_ALM.jl \ + 160 \ + 80 \ + 80 \ + 5 \ + 5 \ + 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs b/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs index e100e2e4..5b7ef3f7 100644 --- a/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs +++ b/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs @@ -3,7 +3,7 @@ #PBS -N 3d_hyperelastic_compliance_neohook_ALM #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=50:00:00 +#PBS -l walltime=23:00:00 #PBS -j oe source $HOME/hpc-environments-main/lyra/load-ompi.sh @@ -11,6 +11,11 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl +mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl \ + 160 \ + 80 \ + 80 \ + 5 \ + 5 \ + 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs b/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs index 111cb9a1..bf1e09f4 100644 --- a/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs +++ b/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs @@ -3,7 +3,7 @@ #PBS -N 3d_inverse_homenisation_ALM #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=50:00:00 +#PBS -l walltime=23:00:00 #PBS -j oe source $HOME/hpc-environments-main/lyra/load-ompi.sh @@ -11,6 +11,11 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_inverse_homenisation_ALM.jl +mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/MPI/3d_inverse_homenisation_ALM.jl \ + 100 \ + 100 \ + 100 \ + 5 \ + 5 \ + 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_inverter_ALM.pbs b/scripts/MPI/jobs/3d_inverter_ALM.pbs index 7499fd5a..5e80b93d 100644 --- a/scripts/MPI/jobs/3d_inverter_ALM.pbs +++ b/scripts/MPI/jobs/3d_inverter_ALM.pbs @@ -1,9 +1,10 @@ #!/bin/bash -l + #PBS -P LSTO #PBS -N 3d_inverter_ALM #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=50:00:00 +#PBS -l walltime=23:00:00 #PBS -j oe source $HOME/hpc-environments-main/lyra/load-ompi.sh @@ -11,6 +12,11 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_inverter_ALM.jl +mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/MPI/3d_inverter_ALM.jl \ + 100 \ + 100 \ + 100 \ + 5 \ + 5 \ + 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_inverter_HPM.pbs b/scripts/MPI/jobs/3d_inverter_HPM.pbs index b4092519..c95b0423 100644 --- a/scripts/MPI/jobs/3d_inverter_HPM.pbs +++ b/scripts/MPI/jobs/3d_inverter_HPM.pbs @@ -1,9 +1,10 @@ #!/bin/bash -l + #PBS -P LSTO #PBS -N 3d_inverter_HPM #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=50:00:00 +#PBS -l walltime=23:00:00 #PBS -j oe source $HOME/hpc-environments-main/lyra/load-ompi.sh @@ -11,6 +12,11 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_inverter_HPM.jl +mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/MPI/3d_inverter_HPM.jl \ + 100 \ + 100 \ + 100 \ + 5 \ + 5 \ + 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs b/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs index acbc4a6c..3b8774a6 100644 --- a/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs @@ -1,9 +1,10 @@ #!/bin/bash -l + #PBS -P LSTO #PBS -N 3d_nonlinear_thermal_compliance_ALM #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=50:00:00 +#PBS -l walltime=23:00:00 #PBS -j oe source $HOME/hpc-environments-main/lyra/load-ompi.sh @@ -11,6 +12,11 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl +mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl \ + 100 \ + 100 \ + 100 \ + 5 \ + 5 \ + 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs b/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs index d71b2b8f..5451c039 100644 --- a/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs @@ -12,15 +12,11 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_thermal_compliance_ALM.jl - -# mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ -# $PROJECT_DIR/scripts/MPI/3d_thermal_compliance_ALM.jl \ -# 150 \ -# 150 \ -# 150 \ -# 5 \ -# 5 \ -# 5 \ No newline at end of file +mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ + $PROJECT_DIR/scripts/MPI/3d_thermal_compliance_ALM.jl \ + 150 \ + 150 \ + 150 \ + 5 \ + 5 \ + 5 \ No newline at end of file diff --git a/scripts/MPI/thermal_compliance_ALM.jl b/scripts/MPI/thermal_compliance_ALM.jl index b4f316e2..9b807c90 100644 --- a/scripts/MPI/thermal_compliance_ALM.jl +++ b/scripts/MPI/thermal_compliance_ALM.jl @@ -22,11 +22,11 @@ function main(mesh_partition,distribute) el_size = (200,200) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) κ = 1 η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM_MPI" iter_mod = 10 diff --git a/scripts/MPI/thermal_compliance_ALM_PETSc.jl b/scripts/MPI/thermal_compliance_ALM_PETSc.jl index 8c032c04..8a3ce6d5 100644 --- a/scripts/MPI/thermal_compliance_ALM_PETSc.jl +++ b/scripts/MPI/thermal_compliance_ALM_PETSc.jl @@ -22,11 +22,11 @@ function main(mesh_partition,distribute,el_size) dom = (0,xmax,0,ymax) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) κ = 1 η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM_MPI+PETSc" iter_mod = 10 diff --git a/scripts/Serial/elastic_compliance_ALM.jl b/scripts/Serial/elastic_compliance_ALM.jl index c1f780db..c313ef68 100644 --- a/scripts/Serial/elastic_compliance_ALM.jl +++ b/scripts/Serial/elastic_compliance_ALM.jl @@ -19,11 +19,11 @@ function main() el_size = (200,100) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) C = isotropic_elast_tensor(2,1.,0.3) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 g = VectorValue(0,-1) path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_ALM/" diff --git a/scripts/Serial/elastic_compliance_HPM.jl b/scripts/Serial/elastic_compliance_HPM.jl index 4e620db2..e7fe84c8 100644 --- a/scripts/Serial/elastic_compliance_HPM.jl +++ b/scripts/Serial/elastic_compliance_HPM.jl @@ -19,11 +19,11 @@ function main() el_size = (200,100) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) C = isotropic_elast_tensor(2,1.,0.3) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 g = VectorValue(0,-1) path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_HPM/" diff --git a/scripts/Serial/elastic_compliance_LM.jl b/scripts/Serial/elastic_compliance_LM.jl index b1be54a6..004e2119 100644 --- a/scripts/Serial/elastic_compliance_LM.jl +++ b/scripts/Serial/elastic_compliance_LM.jl @@ -18,11 +18,11 @@ function main() el_size = (200,100) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) C = isotropic_elast_tensor(2,1.,0.3) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ g = VectorValue(0,-1) path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_LM/" iter_mod = 10 diff --git a/scripts/Serial/hyperelastic_compliance_ALM.jl b/scripts/Serial/hyperelastic_compliance_ALM.jl index e6b801dc..fe45ee8e 100644 --- a/scripts/Serial/hyperelastic_compliance_ALM.jl +++ b/scripts/Serial/hyperelastic_compliance_ALM.jl @@ -12,10 +12,10 @@ function main() el_size = (200,200) γ = 0.05 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.6 path = dirname(dirname(@__DIR__))*"/results/hyperelastic_compliance_ALM/" iter_mod = 10 diff --git a/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl b/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl index 1a10577c..c212f0ef 100644 --- a/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl @@ -12,10 +12,10 @@ function main() el_size = (200,200) γ = 0.05 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.6 path = dirname(dirname(@__DIR__))*"/results/hyperelastic_compliance_neohook_ALM/" iter_mod = 10 diff --git a/scripts/Serial/inverse_homenisation_ALM.jl b/scripts/Serial/inverse_homenisation_ALM.jl index 7ac70885..7779b851 100644 --- a/scripts/Serial/inverse_homenisation_ALM.jl +++ b/scripts/Serial/inverse_homenisation_ALM.jl @@ -18,11 +18,11 @@ function main() el_size = (200,200) γ = 0.05 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) C = isotropic_elast_tensor(2,1.,0.3) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.5 path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM/" iter_mod = 10 diff --git a/scripts/Serial/inverter_ALM.jl b/scripts/Serial/inverter_ALM.jl index 9b1e4879..d1144e2f 100644 --- a/scripts/Serial/inverter_ALM.jl +++ b/scripts/Serial/inverter_ALM.jl @@ -21,11 +21,11 @@ function main() el_size = (200,100) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) C = isotropic_elast_tensor(2,1.0,0.3) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 δₓ = 0.2 ks = 0.1 diff --git a/scripts/Serial/inverter_HPM.jl b/scripts/Serial/inverter_HPM.jl index 4f22c0f3..ae21a683 100644 --- a/scripts/Serial/inverter_HPM.jl +++ b/scripts/Serial/inverter_HPM.jl @@ -21,11 +21,11 @@ function main() el_size = (200,100) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) C = isotropic_elast_tensor(2,1.0,0.3) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 δₓ = 0.2 ks = 0.1 diff --git a/scripts/Serial/nonlinear_thermal_compliance_ALM.jl b/scripts/Serial/nonlinear_thermal_compliance_ALM.jl index ba3f8d74..edbc0b1b 100644 --- a/scripts/Serial/nonlinear_thermal_compliance_ALM.jl +++ b/scripts/Serial/nonlinear_thermal_compliance_ALM.jl @@ -22,10 +22,10 @@ function main() el_size = (200,200) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5order^2)/minimum(el_size) η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ vf = 0.4 path = dirname(dirname(@__DIR__))*"/results/nonlinear_thermal_compliance_ALM/" iter_mod = 10 diff --git a/scripts/Serial/thermal_compliance_ALM.jl b/scripts/Serial/thermal_compliance_ALM.jl index 425a63d5..44903c27 100644 --- a/scripts/Serial/thermal_compliance_ALM.jl +++ b/scripts/Serial/thermal_compliance_ALM.jl @@ -11,7 +11,7 @@ using Gridap, LevelSetTopOpt ⎣∫ κ*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. """ function main() - ## Parameters| + ## Parameters order = 1 xmax=ymax=1.0 prop_Γ_N = 0.2 @@ -20,12 +20,12 @@ function main() el_size = (200,200) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5*order^2)/minimum(el_size) κ = 1 vf = 0.4 η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM/" iter_mod = 10 mkdir(path) diff --git a/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl b/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl new file mode 100644 index 00000000..9123a832 --- /dev/null +++ b/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl @@ -0,0 +1,104 @@ +using Gridap, LevelSetTopOpt + +""" + (Serial) Minimum thermal compliance with augmented Lagrangian method in 2D. + + This problem uses a higher order level set function than the FE solution for + the state equation. In future, second order upwind schemes will require a + higher order FE function. + + Optimisation problem: + Min J(Ω) = ∫ κ*∇(u)⋅∇(u) dΩ + Ω + s.t., Vol(Ω) = vf, + ⎡u∈V=H¹(Ω;u(Γ_D)=0), + ⎣∫ κ*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. +""" +function main() + ## Parameters + fe_order = 1 + order = 2 + xmax=ymax=1.0 + prop_Γ_N = 0.2 + prop_Γ_D = 0.2 + dom = (0,xmax,0,ymax) + el_size = (200,200) + γ = 0.1 + γ_reinit = 0.5 + max_steps = floor(Int,order*minimum(el_size)/10) + tol = 1/(5*order^2)/minimum(el_size) + κ = 1 + vf = 0.4 + η_coeff = 2 + α_coeff = 4max_steps*γ + path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM_higherorderlsf/" + iter_mod = 10 + mkdir(path) + + ## FE Setup + model = CartesianDiscreteModel(dom,el_size); + el_Δ = get_el_Δ(model) + f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || + x[2] >= ymax-ymax*prop_Γ_D - eps())) + f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= + ymax/2+ymax*prop_Γ_N/2 + eps()) + update_labels!(1,model,f_Γ_D,"Gamma_D") + update_labels!(2,model,f_Γ_N,"Gamma_N") + + ## Triangulations and measures + Ω = Triangulation(model) + Γ_N = BoundaryTriangulation(model,tags="Gamma_N") + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + vol_D = sum(∫(1)dΩ) + + ## Spaces + reffe = ReferenceFE(lagrangian,Float64,fe_order) + lsf_reffe = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,0.0) + V_φ = TestFESpace(model,lsf_reffe) + V_reg = TestFESpace(model,lsf_reffe;dirichlet_tags=["Gamma_N"]) + U_reg = TrialFESpace(V_reg,0) + + ## Create FE functions + φh = interpolate(initial_lsf(4,0.2),V_φ) + + ## Interpolation and weak form + interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + + a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ + l(v,φ,dΩ,dΓ_N) = ∫(v)dΓ_N + + ## Optimisation functionals + J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ + dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; + Vol(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; + dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + + ## Finite difference solver and level set function + stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + + ## Setup solver and FE operators + state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) + pcfs = PDEConstrainedFunctionals(J,[Vol],state_map,analytic_dJ=dJ,analytic_dC=[dVol]) + + ## Hilbertian extension-regularisation problems + α = α_coeff*maximum(el_Δ) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; + vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) + + ## Optimiser + optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + γ,γ_reinit,verbose=true,constraint_names=[:Vol]) + for (it,uh,φh) in optimiser + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) + write_history(path*"/history.txt",optimiser.history) + end + it = get_history(optimiser).niter; uh = get_state(pcfs) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) +end + +main() \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl index b3bd339d..52871792 100644 --- a/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl @@ -16,7 +16,7 @@ function main(mesh_partition,distribute) # FD parameters γ = 0.1 # HJ eqn time step coeff γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance # Problem parameters C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor @@ -69,7 +69,7 @@ function main(mesh_partition,distribute) pcfs = PDEConstrainedFunctionals(J,[C1],state_map, analytic_dJ=dJ,analytic_dC=[dC1]) # Velocity extension - α = 4*maximum(get_el_Δ(model)) + α = 4max_steps*γ*maximum(get_el_Δ(model)) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension( a_hilb, U_reg, V_reg; diff --git a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl index 919e046e..5b4730c5 100644 --- a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl @@ -16,7 +16,7 @@ function main(mesh_partition,distribute) # FD parameters γ = 0.1 # HJ eqn time step coeff γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance # Problem parameters E = 1000 # Young's modulus @@ -83,7 +83,7 @@ function main(mesh_partition,distribute) dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ pcfs = PDEConstrainedFunctionals(J,[C1],state_map,analytic_dC=[dC1]) # Velocity extension - α = 4*maximum(get_el_Δ(model)) + α = 4max_steps*γ*maximum(get_el_Δ(model)) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension( a_hilb, U_reg, V_reg; diff --git a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl index eab453d0..d15c424c 100644 --- a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl @@ -12,7 +12,7 @@ function main(mesh_partition,distribute) # FD parameters γ = 0.1 # HJ eqn time step coeff γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance # Problem parameters C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor @@ -73,7 +73,7 @@ function main(mesh_partition,distribute) pcfs = PDEConstrainedFunctionals(κ,[C1],state_map, analytic_dJ=dκ,analytic_dC=[dC1]) # Velocity extension - α = 4*maximum(get_el_Δ(model)) + α = 4max_steps*γ*maximum(get_el_Δ(model)) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension( a_hilb, U_reg, V_reg; diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl index 0dbac675..b9f3269c 100644 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -17,7 +17,7 @@ function main(mesh_partition,distribute) # FD parameters γ = 0.1 # HJ eqn time step coeff γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance # Problem parameters C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor @@ -79,7 +79,7 @@ function main(mesh_partition,distribute) pcfs = PDEConstrainedFunctionals(J,[C1,C2],state_map, analytic_dJ=dJ,analytic_dC=[dC1,nothing]) # Velocity extension - α = 4*maximum(get_el_Δ(model)) + α = 4max_steps*γ*maximum(get_el_Δ(model)) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension( a_hilb, U_reg, V_reg; diff --git a/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs index 38e3aaa8..f0e6a8e1 100644 --- a/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs @@ -1,9 +1,10 @@ #!/bin/bash -l + #PBS -P LSTO #PBS -N elast_comp_MPI_3D #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=50:00:00 +#PBS -l walltime=23:00:00 #PBS -j oe source $HOME/hpc-environments-main/lyra/load-ompi.sh diff --git a/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs index a9c89845..2e765a8a 100644 --- a/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs @@ -1,9 +1,10 @@ #!/bin/bash -l + #PBS -P LSTO #PBS -N hyperelast_comp_MPI_3D #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=50:00:00 +#PBS -l walltime=23:00:00 #PBS -j oe source $HOME/hpc-environments-main/lyra/load-ompi.sh diff --git a/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs index d1a72278..6b5f5c2c 100644 --- a/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs @@ -1,9 +1,10 @@ #!/bin/bash -l + #PBS -P LSTO #PBS -N inverse_hom_MPI_3D #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=50:00:00 +#PBS -l walltime=23:00:00 #PBS -j oe source $HOME/hpc-environments-main/lyra/load-ompi.sh diff --git a/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs index aeeada29..29179f69 100644 --- a/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs @@ -1,9 +1,10 @@ #!/bin/bash -l + #PBS -P LSTO #PBS -N inverter_MPI_3D #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=50:00:00 +#PBS -l walltime=23:00:00 #PBS -j oe source $HOME/hpc-environments-main/lyra/load-ompi.sh diff --git a/scripts/_dev/Paper_scripts/therm_comp_MPI.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI.jl index a0b1afeb..9b76c455 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_MPI.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_MPI.jl @@ -17,7 +17,7 @@ function main(mesh_partition,distribute) # FD parameters γ = 0.1 # HJ eqn time step coeff γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + max_steps = floor(Int,order*minimum(el_size)/10)# Max steps for advection tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance # Problem parameters κ = 1 # Diffusivity @@ -69,7 +69,7 @@ function main(mesh_partition,distribute) pcfs = PDEConstrainedFunctionals(J,[C1],state_map, analytic_dJ=dJ,analytic_dC=[dC1]) # Velocity extension - α = 4*maximum(get_el_Δ(model)) + α = 4max_steps*γ*maximum(get_el_Δ(model)) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension( a_hilb, U_reg, V_reg; diff --git a/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl index 0fb2889c..99be6ec8 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl @@ -19,7 +19,7 @@ function main(mesh_partition,distribute) # FD parameters γ = 0.1 # HJ eqn time step coeff γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance # Problem parameters κ = 1 # Diffusivity @@ -71,7 +71,7 @@ function main(mesh_partition,distribute) pcfs = PDEConstrainedFunctionals(J,[C1],state_map, analytic_dJ=dJ,analytic_dC=[dC1]) # Velocity extension - α = 4*maximum(get_el_Δ(model)) + α = 4max_steps*γ*maximum(get_el_Δ(model)) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension( a_hilb, U_reg, V_reg; diff --git a/scripts/_dev/Paper_scripts/therm_comp_serial.jl b/scripts/_dev/Paper_scripts/therm_comp_serial.jl index 6c657510..78cd651c 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_serial.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_serial.jl @@ -15,7 +15,7 @@ function main() # FD parameters γ = 0.1 # HJ eqn time step coeff γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection + max_steps = floor(Int,order*minimum(el_size)/10)# Max steps for advection tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance # Problem parameters κ = 1 # Diffusivity @@ -58,7 +58,7 @@ function main() pcfs = PDEConstrainedFunctionals(J,[C1],state_map, analytic_dJ=dJ,analytic_dC=[dC1]) # Velocity extension - α = 4*maximum(get_el_Δ(model)) + α = 4max_steps*γ*maximum(get_el_Δ(model)) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme @@ -70,7 +70,7 @@ function main() # Solve for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && (writevtk(Ω,path*"out$it",cellfields=data);GC.gc()) + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) write_history(path*"/history.txt",get_history(optimiser)) end # Final structure diff --git a/src/Optimisers/AugmentedLagrangian.jl b/src/Optimisers/AugmentedLagrangian.jl index b2380686..ec9823f5 100644 --- a/src/Optimisers/AugmentedLagrangian.jl +++ b/src/Optimisers/AugmentedLagrangian.jl @@ -124,8 +124,8 @@ end function default_al_converged( m::AugmentedLagrangian; - L_tol = 0.05*maximum(m.stencil.params.Δ), - C_tol = 0.001 + L_tol = 0.01*maximum(m.stencil.params.Δ), + C_tol = 0.01 ) h = m.history it = get_last_iteration(h) @@ -134,7 +134,7 @@ function default_al_converged( end Li, Ci = h[:L,it], h[:C,it] - L_prev = h[:L,it-10:it-1] + L_prev = h[:L,it-5:it-1] A = all(L -> abs(Li - L)/abs(Li) < L_tol, L_prev) B = all(C -> abs(C) < C_tol,Ci) return A && B From 8e5695ed222c98edccf2460f47de17a642d9dbd1 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sun, 7 Apr 2024 10:11:52 +1000 Subject: [PATCH 19/90] Adjust ALM Lambda update --- src/Optimisers/AugmentedLagrangian.jl | 10 +++++++--- 1 file changed, 7 insertions(+), 3 deletions(-) diff --git a/src/Optimisers/AugmentedLagrangian.jl b/src/Optimisers/AugmentedLagrangian.jl index b2380686..f462c6ff 100644 --- a/src/Optimisers/AugmentedLagrangian.jl +++ b/src/Optimisers/AugmentedLagrangian.jl @@ -79,7 +79,7 @@ struct AugmentedLagrangian{N,O} <: Optimiser stencil :: AdvectionStencil{O}, vel_ext :: VelocityExtension, φ0; - Λ_max = 5.0, ζ = 1.1, update_mod = 5, reinit_mod = 1, γ = 0.1, γ_reinit = 0.5, + Λ_max = 10^10, ζ = 1.1, update_mod = 5, reinit_mod = 1, γ = 0.1, γ_reinit = 0.5, os_γ_mult = 0.75, maxiter = 1000, verbose=false, constraint_names = map(i -> Symbol("C_$i"),1:N), converged::Function = default_al_converged, debug = false, has_oscillations::Function = default_has_oscillations, @@ -209,8 +209,12 @@ function Base.iterate(m::AugmentedLagrangian,state) ## Augmented Lagrangian method λ .= λ .- Λ .* C - if iszero(it % update_mod) - Λ .= @.(min(Λ*ζ,Λ_max)) + if iszero(it % update_mod) + for i = 1:length(C) + if abs(C[i])>0.01 + Λ[i] = min(Λ[i]*ζ,Λ_max) + end + end end ## Compute dL and it's projection From 4c759189a073114a5783c1ef0e31c4e4be457c7d Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Mon, 8 Apr 2024 08:37:09 +1000 Subject: [PATCH 20/90] start iteration option in default_has_oscillations --- src/Optimisers/AugmentedLagrangian.jl | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/src/Optimisers/AugmentedLagrangian.jl b/src/Optimisers/AugmentedLagrangian.jl index 9b903b05..3a44ea75 100644 --- a/src/Optimisers/AugmentedLagrangian.jl +++ b/src/Optimisers/AugmentedLagrangian.jl @@ -100,10 +100,11 @@ end get_history(m::AugmentedLagrangian) = m.history -function default_has_oscillations(m::AugmentedLagrangian,os_it;itlength=25,algo=:zerocrossing) +function default_has_oscillations(m::AugmentedLagrangian,os_it;itlength=25, + itstart=2itlength,algo=:zerocrossing) h = m.history it = get_last_iteration(h) - if it < 2itlength || it < os_it + itlength + 1 + if it < itstart || it < os_it + itlength + 1 return false end From 3f8ea5315665d3cf56fd6bdfe18e72ab33f94475 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Mon, 8 Apr 2024 09:36:42 +1000 Subject: [PATCH 21/90] update benchmarks --- scripts/Benchmarks/benchmark.jl | 346 ++++++++---------- .../Benchmarks/generate_benchmark_scripts.jl | 18 +- 2 files changed, 165 insertions(+), 199 deletions(-) diff --git a/scripts/Benchmarks/benchmark.jl b/scripts/Benchmarks/benchmark.jl index 9abd59ee..3c0fe455 100644 --- a/scripts/Benchmarks/benchmark.jl +++ b/scripts/Benchmarks/benchmark.jl @@ -18,35 +18,36 @@ global VERBOSE = parse(Int,ARGS[8]) global NREPS = parse(Int,ARGS[9]) function nl_elast(mesh_partition,ranks,el_size,order,verbose) - ## Parameters - xmax=ymax=zmax=1.0 - prop_Γ_N = 0.2 - dom = (0,xmax,0,ymax,0,zmax) - γ = 0.05 - γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/3) - tol = 1/(2order^2)/minimum(el_size) - vf = 0.5 - η_coeff = 2 - α_coeff = 4 - - ## FE Setup - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size) - el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0) - f_Γ_N(x) = (x[1] ≈ xmax) && (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) && - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) + # FE parameters + xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size + dom = (0,xmax,0,ymax,0,zmax) # Bounding domain + prop_Γ_N = 0.2 # Γ_N size parameter + f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function + (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& + (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0) # Γ_D indicator function + # FD parameters + γ = 0.1 # HJ eqn time step coeff + γ_reinit = 0.5 # Reinit. eqn time step coeff + max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection + tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance + # Problem parameters + E = 1000 # Young's modulus + ν = 0.3 # Poisson's ratio + μ, λ = E/(2*(1 + ν)), E*ν/((1 + ν)*(1 - 2*ν)) # Lame constants + g = VectorValue(0,0,-1) # Applied load on Γ_N + vf = 0.4 # Volume fraction constraint + lsf_func = initial_lsf(4,0.2) # Initial level set function + # Model + model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); update_labels!(1,model,f_Γ_D,"Gamma_D") update_labels!(2,model,f_Γ_N,"Gamma_N") - - ## Triangulations and measures + # Triangulation and measures Ω = Triangulation(model) Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - vol_D = sum(∫(1)dΩ) - - ## Spaces + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + # Spaces reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) reffe_scalar = ReferenceFE(lagrangian,Float64,order) V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) @@ -54,55 +55,30 @@ function nl_elast(mesh_partition,ranks,el_size,order,verbose) V_φ = TestFESpace(model,reffe_scalar) V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) U_reg = TrialFESpace(V_reg,0) - - ## Create FE functions - φh = interpolate(initial_lsf(4,0.2),V_φ) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) + # Level set and interpolator + φh = interpolate(lsf_func,V_φ) + interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - ## Material properties - _E = 1000 - nu = 0.3 - μ, λ = _E/(2*(1 + nu)), _E*nu/((1 + nu)*(1 - 2*nu)) - g = VectorValue(0,0,-100) - - ## Neohookean hyperelastic material - # Deformation gradient - F(∇u) = one(∇u) + ∇u' - J(F) = sqrt(det(C(F))) - - # Derivative of green Strain - dE(∇du,∇u) = 0.5*( ∇du⋅F(∇u) + (∇du⋅F(∇u))' ) - - # Right Caughy-green deformation tensor - C(F) = (F')⋅F - - # Constitutive law (Neo hookean) + # Weak formulation + ## Piola-Kirchhoff tensor function S(∇u) Cinv = inv(C(F(∇u))) μ*(one(∇u)-Cinv) + λ*log(J(F(∇u)))*Cinv end - - # Cauchy stress tensor and residual - σ(∇u) = (1.0/J(F(∇u)))*F(∇u)⋅S(∇u)⋅(F(∇u))' - res(u,v,φ,dΩ,dΓ_N) = ∫( (I ∘ φ)*((dE∘(∇(v),∇(u))) ⊙ (S∘∇(u))) )*dΩ - ∫(g⋅v)dΓ_N - - ## Optimisation functionals - Obj(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*((dE∘(∇(u),∇(u))) ⊙ (S∘∇(u))))dΩ - Vol(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - - ## Finite difference solver - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) - - ## Setup solver and FE operators + ## Derivative of Green strain + dE(∇du,∇u) = 0.5*( ∇du⋅F(∇u) + (∇du⋅F(∇u))' ) + ## Right Cauchy-Green deformation tensor + C(F) = (F')⋅F + ## Deformation gradient tensor + F(∇u) = one(∇u) + ∇u' + ## Volume change + J(F) = sqrt(det(C(F))) + ## Residual + res(u,v,φ,dΩ,dΓ_N) = ∫( (I ∘ φ)*((dE ∘ (∇(v),∇(u))) ⊙ (S ∘ ∇(u))) )*dΩ - ∫(g⋅v)dΓ_N Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} Tv = Vector{PetscScalar} lin_solver = ElasticitySolver(V) - nl_solver = NewtonSolver(lin_solver;maxiter=50,rtol=10^-8,verbose=verbose) - + nl_solver = NewtonSolver(lin_solver;maxiter=50,rtol=10^-8,verbose) state_map = NonlinearFEStateMap( res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), @@ -110,82 +86,75 @@ function nl_elast(mesh_partition,ranks,el_size,order,verbose) assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), nls = nl_solver, adjoint_ls = lin_solver ) - pcfs = PDEConstrainedFunctionals(Obj,[Vol],state_map,analytic_dC=[dVol]) - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(el_Δ) - a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; + # Objective and constraints + J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*((dE ∘ (∇(u),∇(u))) ⊙ (S ∘ ∇(u))))dΩ + vol_D = sum(∫(1)dΩ) + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C1],state_map,analytic_dC=[dC1]) + # Velocity extension + α = 4max_steps*γ*maximum(get_el_Δ(model)) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension( - a_hilb,U_reg,V_reg; + a_hilb, U_reg, V_reg; assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), ls = PETScLinearSolver() ) - - ## Optimiser - return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=verbose) + # Finite difference scheme + scheme = FirstOrderStencil(length(el_size),Float64) + stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + # Optimiser + return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose) end function therm(mesh_partition,ranks,el_size,order,verbose) - ## Parameters - xmax=ymax=zmax=1.0 - prop_Γ_N = 0.2 - prop_Γ_D = 0.2 - dom = (0,xmax,0,ymax,0,zmax) - γ = 0.05 - γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/3) - tol = 1/(2order^2)/minimum(el_size) - D = 1 - η_coeff = 2 - α_coeff = 4 - - ## FE Setup - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0) && (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps()) && - (x[3] <= zmax*prop_Γ_D + eps() || x[3] >= zmax-zmax*prop_Γ_D - eps()) - f_Γ_N(x) = (x[1] ≈ xmax) && (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) && + # FE parameters + xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size + dom = (0,xmax,0,ymax,0,zmax) # Bounding domain + prop_Γ_N = 0.2 # Γ_N size parameter + prop_Γ_D = 0.2 # Γ_D size parameter + f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function + (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function + (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps()) && + (x[3] <= zmax*prop_Γ_D + eps() || x[3] >= zmax-zmax*prop_Γ_D - eps()) + # FD parameters + γ = 0.1 # HJ eqn time step coeff + γ_reinit = 0.5 # Reinit. eqn time step coeff + max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection + tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance + # Problem parameters + κ = 1 # Diffusivity + g = 1 # Heat flow in + vf = 0.4 # Volume fraction constraint + lsf_func = initial_lsf(4,0.2) # Initial level set function + # Model + model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); update_labels!(1,model,f_Γ_D,"Gamma_D") update_labels!(2,model,f_Γ_N,"Gamma_N") - - ## Triangulations and measures + # Triangulation and measures Ω = Triangulation(model) Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - - ## Spaces - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_D"]) + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + # Spaces + reffe = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) + V_φ = TestFESpace(model,reffe) + V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) U_reg = TrialFESpace(V_reg,0) - - ## Create FE functions - φh = interpolate(initial_lsf(4,0.2),V_φ); - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) + # Level set and interpolator + φh = interpolate(lsf_func,V_φ) + interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*D*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(v)dΓ_N - - ## Optimisation functionals - ξ = 0.1 - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*D*∇(u)⋅∇(u) + ξ*(ρ ∘ φ))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫((-ξ+D*∇(u)⋅∇(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - - ## Finite difference solver - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) - - ## Setup solver and FE operators + # Weak formulation + a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ + l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} Tv = Vector{PetscScalar} solver = PETScLinearSolver() - state_map = AffineFEStateMap( a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), @@ -193,53 +162,58 @@ function therm(mesh_partition,ranks,el_size,order,verbose) assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), ls = solver,adjoint_ls = solver ) - pcfs = PDEConstrainedFunctionals(J,state_map,analytic_dJ=dJ) - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(el_Δ) - a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; + # Objective and constraints + J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ + dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + vol_D = sum(∫(1)dΩ) + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C1],state_map, + analytic_dJ=dJ,analytic_dC=[dC1]) + # Velocity extension + α = 4max_steps*γ*maximum(get_el_Δ(model)) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension( a_hilb, U_reg, V_reg; assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), ls = solver ) - - ## Optimiser - return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=verbose) + # Finite difference scheme + scheme = FirstOrderStencil(length(el_size),Float64) + stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + # Optimiser + return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose) end function elast(mesh_partition,ranks,el_size,order,verbose) - ## Parameters - xmax=ymax=zmax=1.0 - prop_Γ_N = 0.2 - dom = (0,xmax,0,ymax,0,zmax) - γ = 0.05 - γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/3) - tol = 1/(2order^2)/minimum(el_size) - C = isotropic_elast_tensor(3,1.,0.3) - g = VectorValue(0,0,-1) - η_coeff = 2 - α_coeff = 4 - vf = 0.5 - - ## FE Setup + # FE parameters + xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size + dom = (0,xmax,0,ymax,0,zmax) # Bounding domain + prop_Γ_N = 0.2 # Γ_N size parameter + f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function + (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& + (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0) # Γ_D indicator function + # FD parameters + γ = 0.1 # HJ eqn time step coeff + γ_reinit = 0.5 # Reinit. eqn time step coeff + max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection + tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance + # Problem parameters + C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor + g = VectorValue(0,0,-1) # Applied load on Γ_N + vf = 0.4 # Volume fraction constraint + lsf_func = initial_lsf(4,0.2) # Initial level set function + # Model model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0) - f_Γ_N(x) = (x[1] ≈ xmax) && (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) && - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) update_labels!(1,model,f_Γ_D,"Gamma_D") update_labels!(2,model,f_Γ_N,"Gamma_N") - - ## Triangulations and measures + # Triangulation and measures Ω = Triangulation(model) Γ_N = BoundaryTriangulation(model,tags="Gamma_N") dΩ = Measure(Ω,2*order) dΓ_N = Measure(Γ_N,2*order) - vol_D = sum(∫(1)dΩ) - - ## Spaces + # Spaces reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) reffe_scalar = ReferenceFE(lagrangian,Float64,order) V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) @@ -247,51 +221,44 @@ function elast(mesh_partition,ranks,el_size,order,verbose) V_φ = TestFESpace(model,reffe_scalar) V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) U_reg = TrialFESpace(V_reg,0) - - ## Create FE functions - φh = interpolate(initial_lsf(4,0.2),V_φ) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) + # Level set and interpolator + φh = interpolate(lsf_func,V_φ) + interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - + # Weak formulation a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ l(v,φ,dΩ,dΓ_N) = ∫(v⋅g)dΓ_N - - ## Optimisation functionals - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(u)))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫((C ⊙ ε(u) ⊙ ε(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - Vol(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - - ## Finite difference solver - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) - - ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} Tv = Vector{PetscScalar} solver = ElasticitySolver(V) - state_map = AffineFEStateMap( a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver, adjoint_ls = solver + ls = solver,adjoint_ls = solver ) - pcfs = PDEConstrainedFunctionals(J,[Vol],state_map;analytic_dJ=dJ,analytic_dC=[dVol]) - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(el_Δ) - a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; + # Objective and constraints + J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(u)))dΩ + dJ(q,u,φ,dΩ,dΓ_N) = ∫((C ⊙ ε(u) ⊙ ε(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + vol_D = sum(∫(1)dΩ) + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C1],state_map, + analytic_dJ=dJ,analytic_dC=[dC1]) + # Velocity extension + α = 4max_steps*γ*maximum(get_el_Δ(model)) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension( - a_hilb,U_reg,V_reg; + a_hilb, U_reg, V_reg; assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), ls = PETScLinearSolver() ) - - ## Optimiser - return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=verbose) + # Finite difference scheme + scheme = FirstOrderStencil(length(el_size),Float64) + stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + # Optimiser + return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose) end function inverter_HPM(mesh_partition,ranks,el_size,order,verbose) @@ -399,8 +366,7 @@ with_mpi() do distribute verbose = Bool(VERBOSE) ? i_am_main(ranks) : false; if PROB_TYPE == "NLELAST" options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" + -ksp_converged_reason -ksp_rtol 1.0e-12" opt = nl_elast elseif PROB_TYPE == "THERM" options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true @@ -408,13 +374,11 @@ with_mpi() do distribute opt = therm elseif PROB_TYPE == "ELAST" options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" + -ksp_converged_reason -ksp_rtol 1.0e-12" opt = elast elseif PROB_TYPE == "INVERTER_HPM" options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" + -ksp_converged_reason -ksp_rtol 1.0e-12" opt = inverter_HPM else error("Problem not defined") diff --git a/scripts/Benchmarks/generate_benchmark_scripts.jl b/scripts/Benchmarks/generate_benchmark_scripts.jl index 257fdf4c..4214f36e 100644 --- a/scripts/Benchmarks/generate_benchmark_scripts.jl +++ b/scripts/Benchmarks/generate_benchmark_scripts.jl @@ -19,7 +19,7 @@ function generate( ) ncpus = n_mesh_partition^3 - wallhr = occursin("STRONG",name) && n_mesh_partition <= 3 ? 50 : wallhr + wallhr = occursin("STRONG",name) && n_mesh_partition <= 3 ? 100 : wallhr mem = occursin("STRONG",name) && n_mesh_partition == 1 ? 256 : occursin("STRONG",name) && n_mesh_partition == 2 ? 32 : gb_per_cpu; @@ -29,14 +29,16 @@ function generate( end function generate_jobs(template,phys_type,ndof_per_node,bmark_types) - strong = (N).^3; - weak_el_x = @. floor(Int,(dofs_per_proc*strong/ndof_per_node)^(1/3)-1); - dof_sanity_check = @.(floor(Int,ndof_per_node*(weak_el_x+1)^3/strong)), - maximum(abs,@. ndof_per_node*(weak_el_x+1)^3/strong/dofs_per_proc - 1) + npart = (N).^3; + weak_el_x = @. floor(Int,(dofs_per_proc*npart/ndof_per_node)^(1/3)-1); + dof_sanity_check = @.(floor(Int,ndof_per_node*(weak_el_x+1)^3/npart)), + maximum(abs,@. ndof_per_node*(weak_el_x+1)^3/npart/dofs_per_proc - 1) sname(phys_type,ndof_per_node,n,elx) = "STRONG_$(phys_type)_dof$(ndof_per_node)_N$(n)_elx$(elx)" wname(phys_type,ndof_per_node,n,elx) = "WEAK_$(phys_type)_dof$(ndof_per_node)_N$(n)_elx$(elx)" + strong_el_x = ceil(Int,(strong_dof/ndof_per_node)^(1/3)); + strong_jobs = map(n->(sname(phys_type,ndof_per_node,n,strong_el_x), generate(template,sname(phys_type,ndof_per_node,n,strong_el_x),phys_type,bmark_types, cputype,wallhr,n,strong_el_x,fe_order,verbose,dir_name,write_dir,nreps)),N) @@ -63,14 +65,14 @@ dir_name= "LevelSetTopOpt"; write_dir = "\$HOME/$dir_name/results/benchmarks/" N = 1:10; # Number of partitions in x-axis -strong_el_x=100; # Number of elements in x-axis (strong scaling) +strong_dof=(150+1)^3*3; # Number of dofs for strong scaling # Phys type and number of dofs per node, and what to benchmark phys_types = [ ("THERM",1,"bopt0,bopt1,bfwd,badv,breinit,bvelext"), - ("ELAST",3,"bopt0,bopt1,bfwd"), + ("ELAST",3,"bopt0,bopt1,bfwd,badv,breinit,bvelext"), ("NLELAST",3,"bopt0,bopt1,bfwd"), - ("INVERTER_HPM",3,"bhpm"), + # ("INVERTER_HPM",3,"bhpm"), ]; # Template From b23c411dc49b00400094aa8e5f4b5d20e242ea5a Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Mon, 8 Apr 2024 14:16:45 +1000 Subject: [PATCH 22/90] Cleanup --- docs/make.jl | 5 +++-- scripts/MPI/3d_elastic_compliance_ALM.jl | 5 ++--- scripts/MPI/3d_hyperelastic_compliance_ALM.jl | 5 ++--- .../MPI/3d_hyperelastic_compliance_neohook_ALM.jl | 5 ++--- scripts/MPI/3d_inverse_homenisation_ALM.jl | 5 ++--- scripts/MPI/3d_inverter_ALM.jl | 5 ++--- scripts/MPI/3d_inverter_HPM.jl | 5 ++--- scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl | 2 +- scripts/MPI/3d_thermal_compliance_ALM.jl | 13 +++---------- 9 files changed, 19 insertions(+), 31 deletions(-) diff --git a/docs/make.jl b/docs/make.jl index fc289362..67bba876 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -1,5 +1,6 @@ -cd("./docs/") -using Pkg; Pkg.activate(".") +## Local generate +# cd("./docs/") +# using Pkg; Pkg.activate(".") using Documenter using LevelSetTopOpt diff --git a/scripts/MPI/3d_elastic_compliance_ALM.jl b/scripts/MPI/3d_elastic_compliance_ALM.jl index 8bf651f1..58836523 100644 --- a/scripts/MPI/3d_elastic_compliance_ALM.jl +++ b/scripts/MPI/3d_elastic_compliance_ALM.jl @@ -35,7 +35,7 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_elastic_compliance_ALM/" + path = dirname(dirname(@__DIR__))*"/results/3d_elastic_compliance_ALM_Nx$(el_size[1])/" iter_mod = 10 i_am_main(ranks) && mkdir(path) @@ -122,8 +122,7 @@ with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" + -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(hilb_solver_options)) do main(mesh_partition,distribute,el_size) diff --git a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl index 8c24bbcb..6064ae61 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl @@ -28,7 +28,7 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_hyperelastic_compliance_ALM/" + path = dirname(dirname(@__DIR__))*"/results/3d_hyperelastic_compliance_ALM_Nx$(el_size[1])/" iter_mod = 10 i_am_main(ranks) && mkdir(path) @@ -125,8 +125,7 @@ with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" + -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(hilb_solver_options)) do main(mesh_partition,distribute,el_size) diff --git a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl index 662071b7..7b02dd0c 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl @@ -28,7 +28,7 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_hyperelastic_compliance_neohook_ALM/" + path = dirname(dirname(@__DIR__))*"/results/3d_hyperelastic_compliance_neohook_ALM_Nx$(el_size[1])/" iter_mod = 10 i_am_main(ranks) && mkdir(path) @@ -139,8 +139,7 @@ with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" + -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(hilb_solver_options)) do main(mesh_partition,distribute,el_size) diff --git a/scripts/MPI/3d_inverse_homenisation_ALM.jl b/scripts/MPI/3d_inverse_homenisation_ALM.jl index a0df9c4b..ec6f7872 100644 --- a/scripts/MPI/3d_inverse_homenisation_ALM.jl +++ b/scripts/MPI/3d_inverse_homenisation_ALM.jl @@ -33,7 +33,7 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.5 - path = dirname(dirname(@__DIR__))*"/results/3d_inverse_homenisation_ALM/" + path = dirname(dirname(@__DIR__))*"/results/3d_inverse_homenisation_ALM_Nx$(el_size[1])/" iter_mod = 10 i_am_main(ranks) && mkdir(path) @@ -126,8 +126,7 @@ with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" + -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(hilb_solver_options)) do main(mesh_partition,distribute,el_size) diff --git a/scripts/MPI/3d_inverter_ALM.jl b/scripts/MPI/3d_inverter_ALM.jl index fde12b40..0b600003 100644 --- a/scripts/MPI/3d_inverter_ALM.jl +++ b/scripts/MPI/3d_inverter_ALM.jl @@ -39,7 +39,7 @@ function main(mesh_partition,distribute,el_size) δₓ=0.5 ks = 0.01 g = VectorValue(1,0,0) - path = dirname(dirname(@__DIR__))*"/results/3d_inverter_ALM/" + path = dirname(dirname(@__DIR__))*"/results/3d_inverter_ALM_Nx$(el_size[1])/" iter_mod = 10 i_am_main(ranks) && mkdir(path) @@ -140,8 +140,7 @@ with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" + -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(hilb_solver_options)) do main(mesh_partition,distribute,el_size) diff --git a/scripts/MPI/3d_inverter_HPM.jl b/scripts/MPI/3d_inverter_HPM.jl index b645ab9c..bd6d16e9 100644 --- a/scripts/MPI/3d_inverter_HPM.jl +++ b/scripts/MPI/3d_inverter_HPM.jl @@ -39,7 +39,7 @@ function main(mesh_partition,distribute,el_size) δₓ=0.5 ks = 0.01 g = VectorValue(1,0,0) - path = dirname(dirname(@__DIR__))*"/results/3d_inverter_HPM/" + path = dirname(dirname(@__DIR__))*"/results/3d_inverter_HPM_Nx$(el_size[1])/" iter_mod = 10 i_am_main(ranks) && mkdir(path) @@ -141,8 +141,7 @@ with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" + -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(hilb_solver_options)) do main(mesh_partition,distribute,el_size) diff --git a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl index 8aab7ed2..f4f110d6 100644 --- a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl @@ -38,7 +38,7 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_nonlinear_thermal_compliance_ALM/" + path = dirname(dirname(@__DIR__))*"/results/3d_nonlinear_thermal_compliance_ALM_Nx$(el_size[1])/" iter_mod = 10 i_am_main(ranks) && mkdir(path) diff --git a/scripts/MPI/3d_thermal_compliance_ALM.jl b/scripts/MPI/3d_thermal_compliance_ALM.jl index eded269d..9d0366f6 100644 --- a/scripts/MPI/3d_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_thermal_compliance_ALM.jl @@ -18,7 +18,7 @@ global Pz = parse(Int,ARGS[6]) ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. """ -function main(mesh_partition,distribute,el_size,coef,step) +function main(mesh_partition,distribute,el_size) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -35,7 +35,7 @@ function main(mesh_partition,distribute,el_size,coef,step) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_thermal_compliance_ALM_Nx$(el_size[1])_Coef$(coef)_Step$(step)" + path = dirname(dirname(@__DIR__))*"/results/3d_thermal_compliance_ALM_Nx$(el_size[1])" iter_mod = 10 i_am_main(ranks) && mkdir(path) @@ -125,13 +125,6 @@ with_mpi() do distribute -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(all_solver_options)) do - main(mesh_partition,distribute,el_size,5,10) - # main(mesh_partition,distribute,el_size,2,10) - - # main(mesh_partition,distribute,el_size,5,5) - # main(mesh_partition,distribute,el_size,2,5) - - # main(mesh_partition,distribute,el_size,5,3) - # main(mesh_partition,distribute,el_size,2,3) + main(mesh_partition,distribute,el_size) end end; \ No newline at end of file From 6e1d718c4d01a57fa328069576520b7c40ab714b Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 09:30:20 +1000 Subject: [PATCH 23/90] fix paths --- scripts/MPI/3d_thermal_compliance_ALM.jl | 2 +- scripts/MPI/elastic_compliance_ALM.jl | 2 +- scripts/MPI/inverse_homenisation_ALM.jl | 2 +- scripts/MPI/thermal_compliance_ALM.jl | 2 +- scripts/MPI/thermal_compliance_ALM_PETSc.jl | 2 +- 5 files changed, 5 insertions(+), 5 deletions(-) diff --git a/scripts/MPI/3d_thermal_compliance_ALM.jl b/scripts/MPI/3d_thermal_compliance_ALM.jl index 9d0366f6..0fa01deb 100644 --- a/scripts/MPI/3d_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_thermal_compliance_ALM.jl @@ -35,7 +35,7 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_thermal_compliance_ALM_Nx$(el_size[1])" + path = dirname(dirname(@__DIR__))*"/results/3d_thermal_compliance_ALM_Nx$(el_size[1])/" iter_mod = 10 i_am_main(ranks) && mkdir(path) diff --git a/scripts/MPI/elastic_compliance_ALM.jl b/scripts/MPI/elastic_compliance_ALM.jl index 21f8ce9a..fcfb451f 100644 --- a/scripts/MPI/elastic_compliance_ALM.jl +++ b/scripts/MPI/elastic_compliance_ALM.jl @@ -28,7 +28,7 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_ALM_MPI" + path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_ALM_MPI/" iter_mod = 10 i_am_main(ranks) && mkdir(path) diff --git a/scripts/MPI/inverse_homenisation_ALM.jl b/scripts/MPI/inverse_homenisation_ALM.jl index e9a736db..7a068021 100644 --- a/scripts/MPI/inverse_homenisation_ALM.jl +++ b/scripts/MPI/inverse_homenisation_ALM.jl @@ -26,7 +26,7 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.5 - path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM_MPI" + path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM_MPI/" iter_mod = 10 i_am_main(ranks) && mkdir(path) diff --git a/scripts/MPI/thermal_compliance_ALM.jl b/scripts/MPI/thermal_compliance_ALM.jl index 9b807c90..8bb1e9aa 100644 --- a/scripts/MPI/thermal_compliance_ALM.jl +++ b/scripts/MPI/thermal_compliance_ALM.jl @@ -28,7 +28,7 @@ function main(mesh_partition,distribute) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM_MPI" + path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM_MPI/" iter_mod = 10 i_am_main(ranks) && mkdir(path) diff --git a/scripts/MPI/thermal_compliance_ALM_PETSc.jl b/scripts/MPI/thermal_compliance_ALM_PETSc.jl index 8a3ce6d5..39bd0271 100644 --- a/scripts/MPI/thermal_compliance_ALM_PETSc.jl +++ b/scripts/MPI/thermal_compliance_ALM_PETSc.jl @@ -28,7 +28,7 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM_MPI+PETSc" + path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM_MPI+PETSc/" iter_mod = 10 i_am_main(ranks) && mkdir(path) From 4b94785e030ac2bc69ac58700b517ed5ea938ec6 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 10:43:19 +1000 Subject: [PATCH 24/90] Create LevelSetEvolution abstract type --- .../HamiltonJacobiEvolution.jl | 351 ++++++++++++++++++ src/LevelSetEvolution/LevelSetEvolution.jl | 39 ++ src/LevelSetEvolution/SpatialStencil.jl | 175 +++++++++ 3 files changed, 565 insertions(+) create mode 100644 src/LevelSetEvolution/HamiltonJacobiEvolution.jl create mode 100644 src/LevelSetEvolution/LevelSetEvolution.jl create mode 100644 src/LevelSetEvolution/SpatialStencil.jl diff --git a/src/LevelSetEvolution/HamiltonJacobiEvolution.jl b/src/LevelSetEvolution/HamiltonJacobiEvolution.jl new file mode 100644 index 00000000..8e86f07a --- /dev/null +++ b/src/LevelSetEvolution/HamiltonJacobiEvolution.jl @@ -0,0 +1,351 @@ +""" + struct HamiltonJacobiEvolution{O} + +A standard forward Euler in time finite difference method for solving the +Hamilton-Jacobi evolution equation and reinitialisation equation +on order `O` finite elements in serial or parallel. + +Based on the scheme by Osher and Fedkiw ([link](https://doi.org/10.1007/b98879)). + +# Parameters + +- `stencil::SpatialStencil`: Spatial finite difference stencil for a single step HJ + equation and reinitialisation equation. +- `model`: A `CartesianDiscreteModel`. +- `space`: FE space for level-set function +- `perm`: A permutation vector +- `params`: Tuple of additional params +- `cache`: SpatialStencil cache +""" +struct HamiltonJacobiEvolution{O} <: LevelSetEvolution + stencil :: SpatialStencil + model + space + perm + params + cache +end + +""" + HamiltonJacobiEvolution(stencil::SpatialStencil,model,space,tol,max_steps,max_steps_reinit) + +Create an instance of `HamiltonJacobiEvolution` given a stencil, model, FE space, and +additional optional arguments. This automatically creates the DoF permutation +to handle high-order finite elements. +""" +function HamiltonJacobiEvolution( + stencil::SpatialStencil, + model, + space, + tol=1.e-3, + max_steps=100, + max_steps_reinit=2000 +) + # Parameters + order, isperiodic, Δ, ndof = get_stencil_params(model,space) + params = (;isperiodic,Δ,ndof,max_steps,max_steps_reinit,tol) + + # Check that we have sufficient order + check_order(stencil,order) + + # Dof permutation + perm = create_dof_permutation(model,space,order) + + # Caches + φ, vel = zero_free_values(space), zero_free_values(space) + cache = allocate_caches(stencil,φ,vel,perm,order,ndof) + + return HamiltonJacobiEvolution{order}(stencil,model,space,perm,params,cache) +end + +""" + get_dof_Δ(::HamiltonJacobiEvolution) + +Return the distance betweem degree of freedom +""" +function get_dof_Δ(m::HamiltonJacobiEvolution) + return m.params.Δ +end + +""" + compute_Δt(::HamiltonJacobiEvolution,φ,vel) + +Compute the time step for the `HamiltonJacobiEvolution`. +""" +function compute_Δt(::HamiltonJacobiEvolution,Δ,γ,φ,vel) + T = eltype(γ) + v_norm = maximum(abs,vel) + return γ * min(Δ...) / (eps(T)^2 + v_norm) +end + +""" + evolve!(s::HamiltonJacobiEvolution{O},φ,vel,γ) where O + +Solve the Hamilton-Jacobi evolution equation using the `HamiltonJacobiEvolution`. + +# Hamilton-Jacobi evolution equation +``\\frac{\\partial\\phi}{\\partial t} + V(\\boldsymbol{x})\\lVert\\boldsymbol{\\nabla}\\phi\\rVert = 0,`` + +with ``\\phi(0,\\boldsymbol{x})=\\phi_0(\\boldsymbol{x})`` and ``\\boldsymbol{x}\\in D,~t\\in(0,T)``. + +# Arguments + +- `s::HamiltonJacobiEvolution{O}`: Method +- `φ`: level set function as a vector of degrees of freedom +- `vel`: the normal velocity as a vector of degrees of freedom +- `γ`: coeffient on the time step size. +""" +function evolve!(s::HamiltonJacobiEvolution{O},φ::PVector,vel::PVector,γ) where O + _, _, perm_caches, stencil_cache = s.cache + Δ, isperiodic, = s.params.Δ, s.params.isperiodic + ndof, max_steps = s.params.ndof, s.params.max_steps + + _φ = (O >= 2) ? permute!(perm_caches[1],φ,s.perm) : φ + _vel = (O >= 2) ? permute!(perm_caches[2],vel,s.perm) : vel + + ## CFL Condition (requires γ≤1.0) + Δt = compute_Δt(s,Δ,γ,φ,vel) + for _ in 1:max_steps + # Apply operations across partitions + map(local_views(_φ),local_views(_vel),stencil_cache,ndof) do _φ,_vel,stencil_cache,S + φ_mat = reshape(_φ,S) + vel_mat = reshape(_vel,S) + evolve!(s.stencil,φ_mat,vel_mat,Δt,Δ,isperiodic,stencil_cache) + end + # Update ghost nodes + consistent!(_φ) |> fetch + end + φ = (O >= 2) ? permute_inv!(φ,_φ,s.perm) : _φ + return φ +end + +function evolve!(s::HamiltonJacobiEvolution{O},φ::Vector,vel::Vector,γ) where O + _, _, perm_caches, stencil_cache = s.cache + Δ, isperiodic, = s.params.Δ, s.params.isperiodic + ndof, max_steps = s.params.ndof, s.params.max_steps + + _φ = (O >= 2) ? permute!(perm_caches[1],φ,s.perm) : φ + _vel = (O >= 2) ? permute!(perm_caches[2],vel,s.perm) : vel + + ## CFL Condition (requires γ≤1.0) + Δt = compute_Δt(s,Δ,γ,φ,vel) + for _ in 1:max_steps + φ_mat = reshape(_φ,ndof) + vel_mat = reshape(_vel,ndof) + evolve!(s.stencil,φ_mat,vel_mat,Δt,Δ,isperiodic,stencil_cache) + end + φ = (O >= 2) ? permute_inv!(φ,_φ,s.perm) : _φ + return φ +end + +function evolve!(s::HamiltonJacobiEvolution,φh,args...) + evolve!(s,get_free_dof_values(φh),args...) +end + +""" + reinit!(s::HamiltonJacobiEvolution{O},φ,γ) where O + +Solve the reinitialisation equation using the `HamiltonJacobiEvolution`. + +# Reinitialisation equation +``\\frac{\\partial\\phi}{\\partial t} + \\mathrm{sign}(\\phi_0)(\\lVert\\boldsymbol{\\nabla}\\phi\\rVert-1) = 0,`` + +with ``\\phi(0,\\boldsymbol{x})=\\phi_0(\\boldsymbol{x})`` and ``\\boldsymbol{x}\\in D,~t\\in(0,T)``. + +# Arguments + +- `s::HamiltonJacobiEvolution{O}`: Method +- `φ`: level set function as a vector of degrees of freedom +- `γ`: coeffient on the time step size. +""" +function reinit!(s::HamiltonJacobiEvolution{O},φ::PVector,γ) where O + φ_tmp, vel_tmp, perm_caches, stencil_cache = s.cache + Δ, isperiodic, ndof = s.params.Δ, s.params.isperiodic, s.params.ndof + tol, max_steps = s.params.tol, s.params.max_steps_reinit + + _φ = (O >= 2) ? permute!(perm_caches[1],φ,s.perm) : φ + + ## CFL Condition (requires γ≤0.5). Note infnorm(S) = 1.0 + Δt = compute_Δt(s,Δ,γ,_φ,1.0) + + # Apply operations across partitions + step = 1; err = maximum(abs,φ); fill!(φ_tmp,0.0) + while (err > tol) && (step <= max_steps) + # Step of 1st order upwind reinitialisation equation + map(local_views(φ_tmp),local_views(_φ),local_views(vel_tmp),stencil_cache,ndof) do φ_tmp,_φ,vel_tmp,stencil_cache,S + φ_tmp_mat = reshape(φ_tmp,S) + φ_mat = reshape(_φ,S) + vel_tmp_mat = reshape(vel_tmp,S) + reinit!(s.stencil,φ_tmp_mat,φ_mat,vel_tmp_mat,Δt,Δ,isperiodic,stencil_cache) + end + + # Compute error + _φ .-= φ_tmp # φ - φ_tmp + err = maximum(abs,_φ) + step += 1 + + # Update φ + copy!(_φ,φ_tmp) + consistent!(_φ) |> fetch # We exchange ghosts here! + end + φ = (O >= 2) ? permute_inv!(φ,_φ,s.perm) : _φ + return φ +end + +function reinit!(s::HamiltonJacobiEvolution{O},φ::Vector,γ) where O + φ_tmp, vel_tmp, perm_caches, stencil_cache = s.cache + Δ, isperiodic, ndof = s.params.Δ, s.params.isperiodic, s.params.ndof + tol, max_steps = s.params.tol, s.params.max_steps_reinit + + _φ = (O >= 2) ? permute!(perm_caches[1],φ,s.perm) : φ + + ## CFL Condition (requires γ≤0.5) + Δt = compute_Δt(s,Δ,γ,_φ,1.0) + + # Apply operations across partitions + step = 1; err = maximum(abs,φ); fill!(φ_tmp,0.0) + while (err > tol) && (step <= max_steps) + # Step of 1st order upwind reinitialisation equation + φ_tmp_mat = reshape(φ_tmp,ndof) + φ_mat = reshape(_φ,ndof) + vel_tmp_mat = reshape(vel_tmp,ndof) + reinit!(s.stencil,φ_tmp_mat,φ_mat,vel_tmp_mat,Δt,Δ,isperiodic,stencil_cache) + + # Compute error + _φ .-= φ_tmp + err = maximum(abs,_φ) + step += 1 + + # Update φ + copy!(_φ,φ_tmp) + end + φ = (O >= 2) ? permute_inv!(φ,_φ,s.perm) : _φ + return φ +end + +function reinit!(s::HamiltonJacobiEvolution,φh,args...) + reinit!(s,get_free_dof_values(φh),args...) +end + +## Utilities +function get_stencil_params(model::CartesianDiscreteModel,space::FESpace) + order = get_order(first(Gridap.CellData.get_data(get_fe_basis(space)))) + desc = get_cartesian_descriptor(model) + isperiodic = desc.isperiodic + ndof = order .* desc.partition .+ 1 .- isperiodic + Δ = desc.sizes ./ order + return order, isperiodic, Δ, ndof +end + +function get_stencil_params(model::DistributedDiscreteModel,space::DistributedFESpace) + order, isperiodic, Δ, ndof = map(local_views(model),local_views(space)) do model, space + get_stencil_params(model,space) + end |> PartitionedArrays.tuple_of_arrays + + isperiodic = getany(isperiodic) + order = getany(order) + Δ = getany(Δ) + return order, isperiodic, Δ, ndof +end + +Gridap.ReferenceFEs.get_order(f::Gridap.Fields.LinearCombinationFieldVector) = get_order(f.fields) + +# Create dof permutation vector to enable finite differences on +# higher order Lagrangian finite elements on a Cartesian mesh. +function create_dof_permutation(model::CartesianDiscreteModel{Dc}, + space::UnconstrainedFESpace, + order::Integer) where Dc + function get_terms(poly::Polytope, orders) + _nodes, facenodes = Gridap.ReferenceFEs._compute_nodes(poly, orders) + terms = Gridap.ReferenceFEs._coords_to_terms(_nodes, orders) + return terms + end + desc = get_cartesian_descriptor(model) + + periodic = desc.isperiodic + ncells = desc.partition + ndofs = order .* ncells .+ 1 .- periodic + @check prod(ndofs) == num_free_dofs(space) + + new_dof_ids = CircularArray(LinearIndices(ndofs)) + n2o_dof_map = fill(-1,num_free_dofs(space)) + + terms = get_terms(first(get_polytopes(model)), fill(order,Dc)) + cell_dof_ids = get_cell_dof_ids(space) + cache_cell_dof_ids = array_cache(cell_dof_ids) + for (iC,cell) in enumerate(CartesianIndices(ncells)) + first_new_dof = order .* (Tuple(cell) .- 1) .+ 1 + new_dofs_range = map(i -> i:i+order,first_new_dof) + new_dofs = view(new_dof_ids,new_dofs_range...) + + cell_dofs = getindex!(cache_cell_dof_ids,cell_dof_ids,iC) + for (iDof, dof) in enumerate(cell_dofs) + t = terms[iDof] + #o2n_dof_map[dof] = new_dofs[t] + n2o_dof_map[new_dofs[t]] = dof + end + end + + return n2o_dof_map +end + +function create_dof_permutation(model::GridapDistributed.DistributedDiscreteModel, + space::GridapDistributed.DistributedFESpace, + order::Integer) + local_perms = map(local_views(model),local_views(space)) do model, space + create_dof_permutation(model,space,order) + end + return local_perms +end + +function PartitionedArrays.permute_indices(indices::LocalIndices,perm) + id = part_id(indices) + n_glob = global_length(indices) + l2g = view(local_to_global(indices),perm) + l2o = view(local_to_owner(indices),perm) + return LocalIndices(n_glob,id,l2g,l2o) +end + +function allocate_caches(s::SpatialStencil,φ::Vector,vel::Vector,perm,order,ndofs) + stencil_caches = allocate_caches(s,reshape(φ,ndofs),reshape(vel,ndofs)) + φ_tmp = similar(φ) + vel_tmp = similar(vel) + perm_caches = (order >= 2) ? (similar(φ), similar(vel)) : nothing + return φ_tmp, vel_tmp, perm_caches, stencil_caches +end + +function allocate_caches(s::SpatialStencil,φ::PVector,vel::PVector,perm,order,local_ndofs) + local_stencil_caches = map(local_views(φ),local_views(vel),local_views(local_ndofs)) do φ,vel,ndofs + allocate_caches(s,reshape(φ,ndofs),reshape(vel,ndofs)) + end + + perm_indices = map(permute_indices,partition(axes(φ,1)),perm) + perm_caches = (order >= 2) ? (pfill(0.0,perm_indices),pfill(0.0,perm_indices)) : nothing + + φ_tmp = (order >= 2) ? pfill(0.0,perm_indices) : similar(φ) + vel_tmp = (order >= 2) ? pfill(0.0,perm_indices) : similar(vel) + return φ_tmp, vel_tmp, perm_caches, local_stencil_caches +end + +function permute!(x_out,x_in,perm) + for (i_new,i_old) in enumerate(perm) + x_out[i_new] = x_in[i_old] + end + return x_out +end + +function permute!(x_out::PVector,x_in::PVector,perm) + map(permute!,partition(x_out),partition(x_in),perm) + return x_out +end + +function permute_inv!(x_out,x_in,perm) + for (i_new,i_old) in enumerate(perm) + x_out[i_old] = x_in[i_new] + end + return x_out +end +function permute_inv!(x_out::PVector,x_in::PVector,perm) + map(permute_inv!,partition(x_out),partition(x_in),perm) + return x_out +end \ No newline at end of file diff --git a/src/LevelSetEvolution/LevelSetEvolution.jl b/src/LevelSetEvolution/LevelSetEvolution.jl new file mode 100644 index 00000000..d6a743f4 --- /dev/null +++ b/src/LevelSetEvolution/LevelSetEvolution.jl @@ -0,0 +1,39 @@ +""" + abstract type LevelSetEvolution + +Your own evolution method can be implemented by implementing +concrete functionality of the below. +""" +abstract type LevelSetEvolution end + +""" + evolve!(::LevelSetEvolution,φ,args...) + +Evolve the level set function φ according to an evolution +method LevelSetEvolution. +""" +function evolve!(::LevelSetEvolution,φ,args...) + @abstractmethod +end + +""" + reinit!(::LevelSetEvolution,φ,args...) + +Reinitialise the level set function φ according to an +evolution method LevelSetEvolution. +""" +function reinit!(::LevelSetEvolution,φ,args...) + @abstractmethod +end + +""" + get_dof_Δ(::LevelSetEvolution) + +Return the distance betweem degree of freedom +""" +function get_dof_Δ(::LevelSetEvolution) + @abstractmethod +end + +include("SpatialStencil.jl") +include("HamiltonJacobiEvolution.jl") \ No newline at end of file diff --git a/src/LevelSetEvolution/SpatialStencil.jl b/src/LevelSetEvolution/SpatialStencil.jl new file mode 100644 index 00000000..12dd6469 --- /dev/null +++ b/src/LevelSetEvolution/SpatialStencil.jl @@ -0,0 +1,175 @@ +""" + abstract type SpatialStencil + +Finite difference stencil for a single step of the Hamilton-Jacobi +evolution equation and reinitialisation equation. + +Your own stencil can be implemented by extending the methods below. +""" +abstract type SpatialStencil end + +""" + allocate_caches(::SpatialStencil,φ,vel) + +Allocate caches for a given `SpatialStencil`. +""" +function allocate_caches(::SpatialStencil,φ,vel) + nothing # By default, no caches are required. +end + +""" + check_order(::SpatialStencil,order) + +Throw error if insufficient reference element order +to implement stencil in parallel. +""" +function check_order(::SpatialStencil,order) + @abstractmethod +end + +""" + reinit!(::SpatialStencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) -> φ + +Single finite difference step of the reinitialisation equation for a given `SpatialStencil`. +""" +function reinit!(::SpatialStencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) + @abstractmethod +end + +""" + evolve!(::SpatialStencil,φ,vel,Δt,Δx,isperiodic,caches) -> φ + +Single finite difference step of the Hamilton-Jacobi evoluation equation for a given +`SpatialStencil`. +""" +function evolve!(::SpatialStencil,φ,vel,Δt,Δx,isperiodic,caches) + @abstractmethod +end + +""" + struct FirstOrderStencil{D,T} <: SpatialStencil end + +A first order Godunov upwind difference scheme based on Osher and Fedkiw +([link](https://doi.org/10.1007/b98879)). +""" +struct FirstOrderStencil{D,T} <: SpatialStencil + function FirstOrderStencil(D::Integer,::Type{T}) where T<:Real + new{D,T}() + end +end + +function check_order(::FirstOrderStencil,order) + @check order >= 1 "FirstOrderStencil requires reference element to have order >= 1" +end + +function allocate_caches(::FirstOrderStencil{2},φ,vel) + D⁺ʸ = similar(φ); D⁺ˣ = similar(φ) + D⁻ʸ = similar(φ); D⁻ˣ = similar(φ) + ∇⁺ = similar(φ); ∇⁻ = similar(φ) + return D⁺ʸ, D⁺ˣ, D⁻ʸ, D⁻ˣ, ∇⁺, ∇⁻ +end + +function reinit!(::FirstOrderStencil{2,T},φ_new,φ,vel,Δt,Δx,isperiodic,caches) where T + D⁺ʸ, D⁺ˣ, D⁻ʸ, D⁻ˣ, ∇⁺, ∇⁻ = caches + Δx, Δy = Δx + xperiodic,yperiodic = isperiodic + # Prepare shifted lsf + circshift!(D⁺ʸ,φ,(0,-1)); circshift!(D⁻ʸ,φ,(0,1)) + circshift!(D⁺ˣ,φ,(-1,0)); circshift!(D⁻ˣ,φ,(1,0)) + # Sign approximation + ∇⁺ .= @. (D⁺ʸ - D⁻ʸ)/(2Δy); ~yperiodic ? ∇⁺[:,[1,end]] .= zero(T) : 0; + ∇⁻ .= @. (D⁺ˣ - D⁻ˣ)/(2Δx); ~xperiodic ? ∇⁻[[1,end],:] .= zero(T) : 0; + ϵₛ = minimum((Δx,Δy)) + vel .= @. φ/sqrt(φ^2 + ϵₛ^2*(∇⁺^2+∇⁻^2)) + # Forward (+) & Backward (-) + D⁺ʸ .= @. (D⁺ʸ - φ)/Δy; ~yperiodic ? D⁺ʸ[:,end] .= zero(T) : 0; + D⁺ˣ .= @. (D⁺ˣ - φ)/Δx; ~xperiodic ? D⁺ˣ[end,:] .= zero(T) : 0; + D⁻ʸ .= @. (φ - D⁻ʸ)/Δy; ~yperiodic ? D⁻ʸ[:,1] .= zero(T) : 0; + D⁻ˣ .= @. (φ - D⁻ˣ)/Δx; ~xperiodic ? D⁻ˣ[1,:] .= zero(T) : 0; + # Operators + ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2); + ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2); + # Update + φ_new .= @. φ - Δt*(max(vel,0)*∇⁺ + min(vel,0)*∇⁻ - vel) + return φ_new +end + +function evolve!(::FirstOrderStencil{2,T},φ,vel,Δt,Δx,isperiodic,caches) where T + D⁺ʸ, D⁺ˣ, D⁻ʸ, D⁻ˣ, ∇⁺, ∇⁻ = caches + Δx, Δy = Δx + xperiodic,yperiodic = isperiodic + # Prepare shifted lsf + circshift!(D⁺ʸ,φ,(0,-1)); circshift!(D⁻ʸ,φ,(0,1)) + circshift!(D⁺ˣ,φ,(-1,0)); circshift!(D⁻ˣ,φ,(1,0)) + # Forward (+) & Backward (-) + D⁺ʸ .= @. (D⁺ʸ - φ)/Δy; ~yperiodic ? D⁺ʸ[:,end] .= zero(T) : 0; + D⁺ˣ .= @. (D⁺ˣ - φ)/Δx; ~xperiodic ? D⁺ˣ[end,:] .= zero(T) : 0; + D⁻ʸ .= @. (φ - D⁻ʸ)/Δy; ~yperiodic ? D⁻ʸ[:,1] .= zero(T) : 0; + D⁻ˣ .= @. (φ - D⁻ˣ)/Δx; ~xperiodic ? D⁻ˣ[1,:] .= zero(T) : 0; + # Operators + ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2) + ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2) + # Update + φ .= @. φ - Δt*(max(vel,0)*∇⁺ + min(vel,0)*∇⁻) + return φ +end + +function allocate_caches(::FirstOrderStencil{3},φ,vel) + D⁺ᶻ = similar(φ); D⁺ʸ = similar(φ); D⁺ˣ = similar(φ) + D⁻ᶻ = similar(φ); D⁻ʸ = similar(φ); D⁻ˣ = similar(φ) + ∇⁺ = similar(φ); ∇⁻ = similar(φ) + return D⁺ᶻ, D⁺ʸ, D⁺ˣ, D⁻ᶻ, D⁻ʸ, D⁻ˣ, ∇⁺, ∇⁻ +end + +function reinit!(::FirstOrderStencil{3,T},φ_new,φ,vel,Δt,Δx,isperiodic,caches) where T + D⁺ᶻ, D⁺ʸ, D⁺ˣ, D⁻ᶻ, D⁻ʸ, D⁻ˣ, ∇⁺, ∇⁻=caches + Δx, Δy, Δz = Δx + xperiodic,yperiodic,zperiodic = isperiodic + # Prepare shifted lsf + circshift!(D⁺ʸ,φ,(0,-1,0)); circshift!(D⁻ʸ,φ,(0,1,0)) + circshift!(D⁺ˣ,φ,(-1,0,0)); circshift!(D⁻ˣ,φ,(1,0,0)) + circshift!(D⁺ᶻ,φ,(0,0,-1)); circshift!(D⁻ᶻ,φ,(0,0,1)) + # Sign approximation + ∇⁺ .= @. (D⁺ʸ - D⁻ʸ)/(2Δy); ~yperiodic ? ∇⁺[:,[1,end],:] .= zero(T) : 0; + ∇⁻ .= @. (D⁺ˣ - D⁻ˣ)/(2Δx); ~xperiodic ? ∇⁻[[1,end],:,:] .= zero(T) : 0; + ∇⁺ .= @. ∇⁺^2+∇⁻^2 # |∇φ|² (partially computed) + ∇⁻ .= @. (D⁺ᶻ - D⁻ᶻ)/(2Δz); ~xperiodic ? ∇⁻[:,:,[1,end]] .= zero(T) : 0; + ϵₛ = minimum((Δx,Δy,Δz)) + vel .= @. φ/sqrt(φ^2 + ϵₛ^2*(∇⁺+∇⁻^2)) + # Forward (+) & Backward (-) + D⁺ʸ .= (D⁺ʸ - φ)/Δy; ~yperiodic ? D⁺ʸ[:,end,:] .= zero(T) : 0; + D⁺ˣ .= (D⁺ˣ - φ)/Δx; ~xperiodic ? D⁺ˣ[end,:,:] .= zero(T) : 0; + D⁺ᶻ .= (D⁺ᶻ - φ)/Δz; ~zperiodic ? D⁺ᶻ[:,:,end] .= zero(T) : 0; + D⁻ʸ .= (φ - D⁻ʸ)/Δy; ~yperiodic ? D⁻ʸ[:,1,:] .= zero(T) : 0; + D⁻ˣ .= (φ - D⁻ˣ)/Δx; ~xperiodic ? D⁻ˣ[1,:,:] .= zero(T) : 0; + D⁻ᶻ .= (φ - D⁻ᶻ)/Δz; ~zperiodic ? D⁻ᶻ[:,:,1] .= zero(T) : 0; + # Operators + ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2 + max(D⁻ᶻ,0)^2 + min(D⁺ᶻ,0)^2) + ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2 + max(D⁺ᶻ,0)^2 + min(D⁻ᶻ,0)^2) + # Update + φ_new .= @. φ - Δt*(max(vel,0)*∇⁺ + min(vel,0)*∇⁻ - vel) + return φ_new +end + +function evolve!(::FirstOrderStencil{3,T},φ,vel,Δt,Δx,isperiodic,caches) where T + D⁺ᶻ, D⁺ʸ, D⁺ˣ, D⁻ᶻ, D⁻ʸ, D⁻ˣ, ∇⁺, ∇⁻=caches + Δx, Δy, Δz = Δx + xperiodic,yperiodic,zperiodic = isperiodic + # Prepare shifted lsf + circshift!(D⁺ʸ,φ,(0,-1,0)); circshift!(D⁻ʸ,φ,(0,1,0)) + circshift!(D⁺ˣ,φ,(-1,0,0)); circshift!(D⁻ˣ,φ,(1,0,0)) + circshift!(D⁺ᶻ,φ,(0,0,-1)); circshift!(D⁻ᶻ,φ,(0,0,1)) + # Forward (+) & Backward (-) + D⁺ʸ .= (D⁺ʸ - φ)/Δy; ~yperiodic ? D⁺ʸ[:,end,:] .= zero(T) : 0; + D⁺ˣ .= (D⁺ˣ - φ)/Δx; ~xperiodic ? D⁺ˣ[end,:,:] .= zero(T) : 0; + D⁺ᶻ .= (D⁺ᶻ - φ)/Δz; ~zperiodic ? D⁺ᶻ[:,:,end] .= zero(T) : 0; + D⁻ʸ .= (φ - D⁻ʸ)/Δy; ~yperiodic ? D⁻ʸ[:,1,:] .= zero(T) : 0; + D⁻ˣ .= (φ - D⁻ˣ)/Δx; ~xperiodic ? D⁻ˣ[1,:,:] .= zero(T) : 0; + D⁻ᶻ .= (φ - D⁻ᶻ)/Δz; ~zperiodic ? D⁻ᶻ[:,:,1] .= zero(T) : 0; + # Operators + ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2 + max(D⁻ᶻ,0)^2 + min(D⁺ᶻ,0)^2) + ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2 + max(D⁺ᶻ,0)^2 + min(D⁻ᶻ,0)^2) + # Update + φ .= @. φ - Δt*(max(vel,0)*∇⁺ + min(vel,0)*∇⁻) + return φ +end \ No newline at end of file From 3d0539e083f46e4f4f56263cc896688d0669c962 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 10:43:45 +1000 Subject: [PATCH 25/90] Update includes and exports --- src/LevelSetTopOpt.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/LevelSetTopOpt.jl b/src/LevelSetTopOpt.jl index 7b6ebc4d..cc30a752 100644 --- a/src/LevelSetTopOpt.jl +++ b/src/LevelSetTopOpt.jl @@ -52,8 +52,8 @@ export initial_lsf export get_el_Δ export isotropic_elast_tensor -include("Advection.jl") -export AdvectionStencil +include("LevelSetEvolution/LevelSetEvolution.jl") +export HamiltonJacobiEvolution export FirstOrderStencil export advect! export reinit! From 8850dfa052c64bdf4178f469203b44873c7b8444 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 10:46:14 +1000 Subject: [PATCH 26/90] Update Benchmark.jl --- src/Benchmarks.jl | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/src/Benchmarks.jl b/src/Benchmarks.jl index 87cc4a6e..afffef2d 100644 --- a/src/Benchmarks.jl +++ b/src/Benchmarks.jl @@ -116,13 +116,13 @@ function benchmark_forward_problem(m::AbstractFEStateMap, φh, ranks; nreps = 10 end """ - benchmark_advection(stencil::AdvectionStencil, φ0, v0, γ, ranks; nreps) + benchmark_advection(stencil::LevelSetEvolution, φ0, v0, γ, ranks; nreps) Benchmark solving the Hamilton-Jacobi evolution equation given a `stencil`, level-set function `φ0`, velocity function `v0`, and time step coefficient `γ`. See [`advect!`](@ref) for input types. """ -function benchmark_advection(stencil::AdvectionStencil, φ0, v0, γ, ranks; nreps = 10) +function benchmark_advection(stencil::LevelSetEvolution, φ0, v0, γ, ranks; nreps = 10) function f(stencil,φ,v,γ) advect!(stencil,φ,v,γ) end @@ -136,12 +136,12 @@ function benchmark_advection(stencil::AdvectionStencil, φ0, v0, γ, ranks; nrep end """ - benchmark_reinitialisation(stencil::AdvectionStencil, φ0, γ_reinit, ranks; nreps) + benchmark_reinitialisation(stencil::LevelSetEvolution, φ0, γ_reinit, ranks; nreps) Benchmark solving the reinitialisation equation given a `stencil`, level-set function `φ0`, and time step coefficient `γ`. See [`reinit!`](@ref) for input types. """ -function benchmark_reinitialisation(stencil::AdvectionStencil, φ0, γ_reinit, ranks; nreps = 10) +function benchmark_reinitialisation(stencil::LevelSetEvolution, φ0, γ_reinit, ranks; nreps = 10) function f(stencil,φ,γ_reinit) reinit!(stencil,φ,γ_reinit) end From 8b60442857aa7e78aeddd64f47ba0ff2d14b4609 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 11:08:07 +1000 Subject: [PATCH 27/90] Rename advect! --- src/Benchmarks.jl | 4 ++-- src/LevelSetTopOpt.jl | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/Benchmarks.jl b/src/Benchmarks.jl index afffef2d..0c052a44 100644 --- a/src/Benchmarks.jl +++ b/src/Benchmarks.jl @@ -120,11 +120,11 @@ end Benchmark solving the Hamilton-Jacobi evolution equation given a `stencil`, level-set function `φ0`, velocity function `v0`, and time step coefficient `γ`. -See [`advect!`](@ref) for input types. +See [`evolve!`](@ref) for input types. """ function benchmark_advection(stencil::LevelSetEvolution, φ0, v0, γ, ranks; nreps = 10) function f(stencil,φ,v,γ) - advect!(stencil,φ,v,γ) + evolve!(stencil,φ,v,γ) end function reset!(stencil,φ,v,γ) copy!(φ,φ0) diff --git a/src/LevelSetTopOpt.jl b/src/LevelSetTopOpt.jl index cc30a752..5de30155 100644 --- a/src/LevelSetTopOpt.jl +++ b/src/LevelSetTopOpt.jl @@ -55,7 +55,7 @@ export isotropic_elast_tensor include("LevelSetEvolution/LevelSetEvolution.jl") export HamiltonJacobiEvolution export FirstOrderStencil -export advect! +export evolve! export reinit! include("Solvers.jl") From 489f886c96d485e9070e6221bbc7ecab97a7751a Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 11:22:10 +1000 Subject: [PATCH 28/90] Update src/Optimisers/.. --- src/Optimisers/AugmentedLagrangian.jl | 45 ++++++++++++-------------- src/Optimisers/HilbertianProjection.jl | 37 +++++++++++---------- 2 files changed, 39 insertions(+), 43 deletions(-) diff --git a/src/Optimisers/AugmentedLagrangian.jl b/src/Optimisers/AugmentedLagrangian.jl index 3a44ea75..1c879508 100644 --- a/src/Optimisers/AugmentedLagrangian.jl +++ b/src/Optimisers/AugmentedLagrangian.jl @@ -1,5 +1,5 @@ """ - struct AugmentedLagrangian{N,O} <: Optimiser + struct AugmentedLagrangian <: Optimiser An augmented Lagrangian method based on Nocedal and Wright, 2006 ([link](https://doi.org/10.1007/978-0-387-40065-5)). Note that @@ -8,9 +8,8 @@ are defined in `problem::PDEConstrainedFunctionals`. # Parameters -- `problem::PDEConstrainedFunctionals{N}`: The objective and constraint setup. -- `stencil::AdvectionStencil{O}`: The finite difference stencil for - solving the evolution and reinitisation equations. +- `problem::PDEConstrainedFunctionals`: The objective and constraint setup. +- `ls_evolver::LevelSetEvolution`: Solver for the evolution and reinitisation equations. - `vel_ext::VelocityExtension`: The velocity-extension method for extending shape sensitivities onto the computational domain. - `history::OptimiserHistory{Float64}`: Historical information for optimisation problem. @@ -22,9 +21,9 @@ The `has_oscillations` function has been added to avoid oscillations in the iteration history. By default this uses a mean zero crossing algorithm as implemented in ChaosTools. Oscillations checking can be disabled by taking `has_oscillations = (args...) -> false`. """ -struct AugmentedLagrangian{N,O} <: Optimiser - problem :: PDEConstrainedFunctionals{N} - stencil :: AdvectionStencil{O} +struct AugmentedLagrangian <: Optimiser + problem :: PDEConstrainedFunctionals + ls_evolver :: LevelSetEvolution vel_ext :: VelocityExtension history :: OptimiserHistory{Float64} converged :: Function @@ -34,9 +33,9 @@ struct AugmentedLagrangian{N,O} <: Optimiser @doc """ AugmentedLagrangian( - problem :: PDEConstrainedFunctionals{N}, - stencil :: AdvectionStencil{O}, - vel_ext :: VelocityExtension, + problem :: PDEConstrainedFunctionals{N}, + ls_evolver :: LevelSetEvolution, + vel_ext :: VelocityExtension, φ0; Λ_max = 5.0, ζ = 1.1, update_mod = 5, γ = 0.1, γ_reinit = 0.5, os_γ_mult = 0.75, maxiter = 1000, verbose=false, constraint_names = map(i -> Symbol("C_\$i"),1:N), @@ -48,9 +47,8 @@ struct AugmentedLagrangian{N,O} <: Optimiser # Required - - `problem::PDEConstrainedFunctionals{N}`: The objective and constraint setup. - - `stencil::AdvectionStencil{O}`: The finite difference stencil for - solving the evolution and reinitisation equations. + - `problem::PDEConstrainedFunctionals`: The objective and constraint setup. + - `ls_evolver::LevelSetEvolution`: Solver for the evolution and reinitisation equations. - `vel_ext::VelocityExtension`: The velocity-extension method for extending shape sensitivities onto the computational domain. - `φ0`: An initial level-set function defined as a FEFunction or GridapDistributed equivilent. @@ -75,16 +73,16 @@ struct AugmentedLagrangian{N,O} <: Optimiser - `debug = false`: Debug flag. """ function AugmentedLagrangian( - problem :: PDEConstrainedFunctionals{N}, - stencil :: AdvectionStencil{O}, - vel_ext :: VelocityExtension, + problem :: PDEConstrainedFunctionals{N}, + ls_evolver :: LevelSetEvolution, + vel_ext :: VelocityExtension, φ0; Λ_max = 10^10, ζ = 1.1, update_mod = 5, reinit_mod = 1, γ = 0.1, γ_reinit = 0.5, os_γ_mult = 0.75, maxiter = 1000, verbose=false, constraint_names = map(i -> Symbol("C_$i"),1:N), converged::Function = default_al_converged, debug = false, has_oscillations::Function = default_has_oscillations, initial_parameters::Function = default_al_init_params - ) where {N,O} + ) where N constraint_names = map(Symbol,constraint_names) λ_names = map(i -> Symbol("λ$i"),1:N) @@ -94,7 +92,7 @@ struct AugmentedLagrangian{N,O} <: Optimiser history = OptimiserHistory(Float64,al_keys,al_bundles,maxiter,verbose) params = (;Λ_max,ζ,update_mod,reinit_mod,γ,γ_reinit,os_γ_mult,debug,initial_parameters) - new{N,O}(problem,stencil,vel_ext,history,converged,has_oscillations,params,φ0) + new(problem,ls_evolver,vel_ext,history,converged,has_oscillations,params,φ0) end end @@ -125,7 +123,7 @@ end function default_al_converged( m::AugmentedLagrangian; - L_tol = 0.01*maximum(m.stencil.params.Δ), + L_tol = 0.01*maximum(get_dof_Δ(m.ls_evolver)), C_tol = 0.01 ) h = m.history @@ -145,7 +143,7 @@ function Base.iterate(m::AugmentedLagrangian) φh, history, params = m.φ0, m.history, m.params ## Reinitialise as SDF - reinit!(m.stencil,φh,params.γ_reinit) + reinit!(m.ls_evolver,φh,params.γ_reinit) ## Compute FE problem and shape derivatives J, C, dJ, dC = evaluate!(m.problem,φh) @@ -176,8 +174,7 @@ end function Base.iterate(m::AugmentedLagrangian,state) it, L, J, C, dL, dJ, dC, uh, φh, vel, λ, Λ, γ, os_it = state params, history = m.params, m.history - update_mod, reinit_mod, ζ, Λ_max, γ_reinit, os_γ_mult = params.update_mod, - params.reinit_mod, params.ζ, params.Λ_max, params.γ_reinit, params.os_γ_mult + Λ_max,ζ,update_mod,reinit_mod,_,γ_reinit,os_γ_mult,_,_ = params ## Periodicially call GC iszero(it % 50) && GC.gc(); @@ -197,8 +194,8 @@ function Base.iterate(m::AugmentedLagrangian,state) U_reg = get_deriv_space(m.problem.state_map) V_φ = get_aux_space(m.problem.state_map) interpolate!(FEFunction(U_reg,dL),vel,V_φ) - advect!(m.stencil,φh,vel,γ) - iszero(it % reinit_mod) && reinit!(m.stencil,φh,γ_reinit) + evolve!(m.ls_evolver,φh,vel,γ) + iszero(it % reinit_mod) && reinit!(m.ls_evolver,φh,γ_reinit) ## Calculate objective, constraints, and shape derivatives J, C, dJ, dC = evaluate!(m.problem,φh) diff --git a/src/Optimisers/HilbertianProjection.jl b/src/Optimisers/HilbertianProjection.jl index 9cb75952..b4f18628 100644 --- a/src/Optimisers/HilbertianProjection.jl +++ b/src/Optimisers/HilbertianProjection.jl @@ -124,7 +124,7 @@ function compute_α(C,dC_orthog,dC,normsq,K,P,λ,α_min,α_max) end """ - struct HilbertianProjection{T,N} <: Optimiser + struct HilbertianProjection <: Optimiser A Hilbertian projection method as described by Wegert et al., 2023 ([link](https://doi.org/10.1007/s00158-023-03663-0)). @@ -132,8 +132,7 @@ A Hilbertian projection method as described by Wegert et al., 2023 # Parameters - `problem::PDEConstrainedFunctionals{N}`: The objective and constraint setup. -- `stencil::AdvectionStencil{O}`: The finite difference stencil for - solving the evolution and reinitisation equations. +- `ls_evolver::LevelSetEvolution`: Solver for the evolution and reinitisation equations. - `vel_ext::VelocityExtension`: The velocity-extension method for extending shape sensitivities onto the computational domain. - `projector::HilbertianProjectionMap`: Sensitivity information projector @@ -142,9 +141,9 @@ A Hilbertian projection method as described by Wegert et al., 2023 - `has_oscillations::Function`: A function to check for oscillations. - `params::NamedTuple`: Optimisation parameters. """ -struct HilbertianProjection{T,N} <: Optimiser - problem :: PDEConstrainedFunctionals{N} - stencil :: AdvectionStencil +struct HilbertianProjection <: Optimiser + problem :: PDEConstrainedFunctionals + ls_evolver :: LevelSetEvolution vel_ext :: VelocityExtension projector :: HilbertianProjectionMap history :: OptimiserHistory{Float64} @@ -156,7 +155,7 @@ struct HilbertianProjection{T,N} <: Optimiser @doc """ HilbertianProjection( problem :: PDEConstrainedFunctionals{N}, - stencil :: AdvectionStencil, + ls_evolver :: LevelSetEvolution, vel_ext :: VelocityExtension, φ0; orthog = HPModifiedGramSchmidt(), @@ -174,8 +173,7 @@ struct HilbertianProjection{T,N} <: Optimiser # Required - `problem::PDEConstrainedFunctionals{N}`: The objective and constraint setup. - - `stencil::AdvectionStencil{O}`: The finite difference stencil for - solving the evolution and reinitisation equations. + - `ls_evolver::LevelSetEvolution`: Solver for the evolution and reinitisation equations. - `vel_ext::VelocityExtension`: The velocity-extension method for extending shape sensitivities onto the computational domain. - `φ0`: An initial level-set function defined as a FEFunction or GridapDistributed equivilent. @@ -221,9 +219,9 @@ struct HilbertianProjection{T,N} <: Optimiser disabling the line search via `ls_enabled = false` will enable oscillation detection. """ function HilbertianProjection( - problem :: PDEConstrainedFunctionals{N}, - stencil :: AdvectionStencil, - vel_ext :: VelocityExtension, + problem :: PDEConstrainedFunctionals{N}, + ls_evolver :: LevelSetEvolution, + vel_ext :: VelocityExtension, φ0; orthog = HPModifiedGramSchmidt(), λ=0.5, α_min=0.1, α_max=1.0, γ=0.1, γ_reinit=0.5, reinit_mod = 1, @@ -234,7 +232,9 @@ struct HilbertianProjection{T,N} <: Optimiser converged::Function = default_hp_converged, debug = false, has_oscillations::Function = (ls_enabled ? (args...)->false : default_has_oscillations), os_γ_mult = 0.5 - ) where {N} + ) where N + + @assert α_min <= α_max "We require α_min <= α_max" constraint_names = map(Symbol,constraint_names) al_keys = [:J,constraint_names...,:γ] @@ -244,8 +244,7 @@ struct HilbertianProjection{T,N} <: Optimiser projector = HilbertianProjectionMap(N,orthog,vel_ext;λ,α_min,α_max,debug) params = (;debug,γ,γ_reinit,reinit_mod,ls_enabled,ls_max_iters,ls_δ_inc,ls_δ_dec,ls_ξ, ls_ξ_reduce_coef,ls_ξ_reduce_abs_tol,ls_γ_min,ls_γ_max,os_γ_mult) - T = typeof(orthog) - new{T,N}(problem,stencil,vel_ext,projector,history,converged, + new(problem,ls_evolver,vel_ext,projector,history,converged, has_oscillations,params,φ0) end end @@ -258,7 +257,7 @@ end function default_hp_converged( m::HilbertianProjection; - J_tol = 0.2*maximum(m.stencil.params.Δ), + J_tol = 0.2*maximum(get_dof_Δ(m.ls_evolver)), C_tol = 0.001 ) h = m.history @@ -296,7 +295,7 @@ function Base.iterate(m::HilbertianProjection) φh = m.φ0 ## Reinitialise as SDF - reinit!(m.stencil,φh,params.γ_reinit) + reinit!(m.ls_evolver,φh,params.γ_reinit) ## Compute FE problem and shape derivatives J, C, dJ, dC = Gridap.evaluate!(m.problem,φh) @@ -351,8 +350,8 @@ function Base.iterate(m::HilbertianProjection,state) φ = get_free_dof_values(φh); copy!(φ_tmp,φ) while !done && (ls_it <= ls_max_iters) # Advect & Reinitialise - advect!(m.stencil,φ,vel,γ) - iszero(it % reinit_mod) && reinit!(m.stencil,φ,params.γ_reinit) + evolve!(m.ls_evolver,φ,vel,γ) + iszero(it % reinit_mod) && reinit!(m.ls_evolver,φ,params.γ_reinit) ~ls_enabled && break From bea8cf2be9c0e989b4d711e1f674668912f45982 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 11:25:22 +1000 Subject: [PATCH 29/90] Update scripts --- scripts/Benchmarks/benchmark.jl | 8 ++++---- scripts/MPI/3d_elastic_compliance_ALM.jl | 2 +- scripts/MPI/3d_hyperelastic_compliance_ALM.jl | 2 +- scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl | 2 +- scripts/MPI/3d_inverse_homenisation_ALM.jl | 2 +- scripts/MPI/3d_inverter_ALM.jl | 2 +- scripts/MPI/3d_inverter_HPM.jl | 2 +- scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl | 2 +- scripts/MPI/3d_thermal_compliance_ALM.jl | 2 +- scripts/MPI/elastic_compliance_ALM.jl | 2 +- scripts/MPI/inverse_homenisation_ALM.jl | 2 +- scripts/MPI/thermal_compliance_ALM.jl | 2 +- scripts/MPI/thermal_compliance_ALM_PETSc.jl | 2 +- scripts/Serial/elastic_compliance_ALM.jl | 2 +- scripts/Serial/elastic_compliance_HPM.jl | 2 +- scripts/Serial/elastic_compliance_LM.jl | 2 +- scripts/Serial/hyperelastic_compliance_ALM.jl | 2 +- scripts/Serial/hyperelastic_compliance_neohook_ALM.jl | 2 +- scripts/Serial/inverse_homenisation_ALM.jl | 2 +- scripts/Serial/inverter_ALM.jl | 2 +- scripts/Serial/inverter_HPM.jl | 2 +- scripts/Serial/nonlinear_thermal_compliance_ALM.jl | 2 +- scripts/Serial/thermal_compliance_ALM.jl | 2 +- scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl | 2 +- scripts/_dev/3d_hyperelastic_compliance_ALM.jl | 2 +- scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl | 2 +- scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl | 2 +- scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl | 2 +- scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 2 +- scripts/_dev/Paper_scripts/therm_comp_MPI.jl | 2 +- scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl | 2 +- scripts/_dev/Paper_scripts/therm_comp_serial.jl | 2 +- .../_dev/benchmark_tests/MPI_benchmark_test_2D_themal.jl | 2 +- .../_dev/benchmark_tests/MPI_benchmark_test_3D_themal.jl | 2 +- scripts/_dev/benchmark_tests/serial_benchmark_test.jl | 2 +- scripts/_dev/bug_issue_46/thermal_MPI.jl | 2 +- scripts/_dev/bug_issue_46/thermal_serial.jl | 2 +- scripts/_dev/full_piezo_script.jl | 2 +- scripts/_dev/inv_hom_block_assem_testing.jl | 2 +- scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl | 2 +- scripts/_dev/inv_hom_block_assem_testing_full_script.jl | 2 +- scripts/_dev/mem_leak.jl | 2 +- scripts/_dev/nonlinear_adjoint_MWE.jl | 2 +- .../minimum_thermal_compliance_implementation.jl | 2 +- .../minimum_thermal_compliance_implementation_3d.jl | 2 +- .../minimum_thermal_compliance_implementation_3d_petsc.jl | 2 +- ...imum_thermal_compliance_implementation_3d_petsc_mpi.jl | 2 +- ...minimum_thermal_compliance_implementation_nonlinear.jl | 2 +- 48 files changed, 51 insertions(+), 51 deletions(-) diff --git a/scripts/Benchmarks/benchmark.jl b/scripts/Benchmarks/benchmark.jl index 3c0fe455..759bf6e0 100644 --- a/scripts/Benchmarks/benchmark.jl +++ b/scripts/Benchmarks/benchmark.jl @@ -102,7 +102,7 @@ function nl_elast(mesh_partition,ranks,el_size,order,verbose) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose) end @@ -180,7 +180,7 @@ function therm(mesh_partition,ranks,el_size,order,verbose) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose) end @@ -256,7 +256,7 @@ function elast(mesh_partition,ranks,el_size,order,verbose) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose) end @@ -329,7 +329,7 @@ function inverter_HPM(mesh_partition,ranks,el_size,order,verbose) UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out ## Finite difference solver - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} diff --git a/scripts/MPI/3d_elastic_compliance_ALM.jl b/scripts/MPI/3d_elastic_compliance_ALM.jl index 58836523..d44fdff3 100644 --- a/scripts/MPI/3d_elastic_compliance_ALM.jl +++ b/scripts/MPI/3d_elastic_compliance_ALM.jl @@ -81,7 +81,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} diff --git a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl index 6064ae61..c103beab 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl @@ -83,7 +83,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} diff --git a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl index 7b02dd0c..1a9fe02e 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl @@ -97,7 +97,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} diff --git a/scripts/MPI/3d_inverse_homenisation_ALM.jl b/scripts/MPI/3d_inverse_homenisation_ALM.jl index ec6f7872..2fed57d8 100644 --- a/scripts/MPI/3d_inverse_homenisation_ALM.jl +++ b/scripts/MPI/3d_inverse_homenisation_ALM.jl @@ -85,7 +85,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} diff --git a/scripts/MPI/3d_inverter_ALM.jl b/scripts/MPI/3d_inverter_ALM.jl index 0b600003..5d270952 100644 --- a/scripts/MPI/3d_inverter_ALM.jl +++ b/scripts/MPI/3d_inverter_ALM.jl @@ -99,7 +99,7 @@ function main(mesh_partition,distribute,el_size) UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} diff --git a/scripts/MPI/3d_inverter_HPM.jl b/scripts/MPI/3d_inverter_HPM.jl index bd6d16e9..f1684cf0 100644 --- a/scripts/MPI/3d_inverter_HPM.jl +++ b/scripts/MPI/3d_inverter_HPM.jl @@ -99,7 +99,7 @@ function main(mesh_partition,distribute,el_size) UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} diff --git a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl index f4f110d6..126309d5 100644 --- a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl @@ -85,7 +85,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} diff --git a/scripts/MPI/3d_thermal_compliance_ALM.jl b/scripts/MPI/3d_thermal_compliance_ALM.jl index 0fa01deb..e0cea609 100644 --- a/scripts/MPI/3d_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_thermal_compliance_ALM.jl @@ -81,7 +81,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} diff --git a/scripts/MPI/elastic_compliance_ALM.jl b/scripts/MPI/elastic_compliance_ALM.jl index fcfb451f..6fa7a17c 100644 --- a/scripts/MPI/elastic_compliance_ALM.jl +++ b/scripts/MPI/elastic_compliance_ALM.jl @@ -74,7 +74,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} diff --git a/scripts/MPI/inverse_homenisation_ALM.jl b/scripts/MPI/inverse_homenisation_ALM.jl index 7a068021..ec4d8886 100644 --- a/scripts/MPI/inverse_homenisation_ALM.jl +++ b/scripts/MPI/inverse_homenisation_ALM.jl @@ -73,7 +73,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} diff --git a/scripts/MPI/thermal_compliance_ALM.jl b/scripts/MPI/thermal_compliance_ALM.jl index 8bb1e9aa..bce212f1 100644 --- a/scripts/MPI/thermal_compliance_ALM.jl +++ b/scripts/MPI/thermal_compliance_ALM.jl @@ -72,7 +72,7 @@ function main(mesh_partition,distribute) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) diff --git a/scripts/MPI/thermal_compliance_ALM_PETSc.jl b/scripts/MPI/thermal_compliance_ALM_PETSc.jl index 39bd0271..cfe2acd6 100644 --- a/scripts/MPI/thermal_compliance_ALM_PETSc.jl +++ b/scripts/MPI/thermal_compliance_ALM_PETSc.jl @@ -72,7 +72,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} diff --git a/scripts/Serial/elastic_compliance_ALM.jl b/scripts/Serial/elastic_compliance_ALM.jl index c313ef68..7cd20e1a 100644 --- a/scripts/Serial/elastic_compliance_ALM.jl +++ b/scripts/Serial/elastic_compliance_ALM.jl @@ -71,7 +71,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) diff --git a/scripts/Serial/elastic_compliance_HPM.jl b/scripts/Serial/elastic_compliance_HPM.jl index e7fe84c8..50964928 100644 --- a/scripts/Serial/elastic_compliance_HPM.jl +++ b/scripts/Serial/elastic_compliance_HPM.jl @@ -72,7 +72,7 @@ function main() dVol = (q,u,φ,dΩ,dΓ_N) -> ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) diff --git a/scripts/Serial/elastic_compliance_LM.jl b/scripts/Serial/elastic_compliance_LM.jl index 004e2119..0517ef1b 100644 --- a/scripts/Serial/elastic_compliance_LM.jl +++ b/scripts/Serial/elastic_compliance_LM.jl @@ -68,7 +68,7 @@ function main() dJ = (q,u,φ,dΩ,dΓ_N) -> ∫((- ξ + C ⊙ ε(u) ⊙ ε(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) diff --git a/scripts/Serial/hyperelastic_compliance_ALM.jl b/scripts/Serial/hyperelastic_compliance_ALM.jl index fe45ee8e..c455de7b 100644 --- a/scripts/Serial/hyperelastic_compliance_ALM.jl +++ b/scripts/Serial/hyperelastic_compliance_ALM.jl @@ -71,7 +71,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = NonlinearFEStateMap(res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) diff --git a/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl b/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl index c212f0ef..03ea9f55 100644 --- a/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl @@ -85,7 +85,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = NonlinearFEStateMap(res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) diff --git a/scripts/Serial/inverse_homenisation_ALM.jl b/scripts/Serial/inverse_homenisation_ALM.jl index 7779b851..c079c08c 100644 --- a/scripts/Serial/inverse_homenisation_ALM.jl +++ b/scripts/Serial/inverse_homenisation_ALM.jl @@ -71,7 +71,7 @@ function main() dVol(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = RepeatingAffineFEStateMap(3,a,l,U,V,V_φ,U_reg,φh,dΩ) diff --git a/scripts/Serial/inverter_ALM.jl b/scripts/Serial/inverter_ALM.jl index d1144e2f..2774a9ea 100644 --- a/scripts/Serial/inverter_ALM.jl +++ b/scripts/Serial/inverter_ALM.jl @@ -86,7 +86,7 @@ function main() UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out) diff --git a/scripts/Serial/inverter_HPM.jl b/scripts/Serial/inverter_HPM.jl index ae21a683..f2587eec 100644 --- a/scripts/Serial/inverter_HPM.jl +++ b/scripts/Serial/inverter_HPM.jl @@ -87,7 +87,7 @@ function main() UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out) diff --git a/scripts/Serial/nonlinear_thermal_compliance_ALM.jl b/scripts/Serial/nonlinear_thermal_compliance_ALM.jl index edbc0b1b..51597244 100644 --- a/scripts/Serial/nonlinear_thermal_compliance_ALM.jl +++ b/scripts/Serial/nonlinear_thermal_compliance_ALM.jl @@ -74,7 +74,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = NonlinearFEStateMap(res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) diff --git a/scripts/Serial/thermal_compliance_ALM.jl b/scripts/Serial/thermal_compliance_ALM.jl index 44903c27..6ddf66cc 100644 --- a/scripts/Serial/thermal_compliance_ALM.jl +++ b/scripts/Serial/thermal_compliance_ALM.jl @@ -72,7 +72,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) diff --git a/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl b/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl index 9123a832..0b076760 100644 --- a/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl +++ b/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl @@ -78,7 +78,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) diff --git a/scripts/_dev/3d_hyperelastic_compliance_ALM.jl b/scripts/_dev/3d_hyperelastic_compliance_ALM.jl index 2565536b..de79e6fc 100644 --- a/scripts/_dev/3d_hyperelastic_compliance_ALM.jl +++ b/scripts/_dev/3d_hyperelastic_compliance_ALM.jl @@ -153,7 +153,7 @@ function main_alt(mesh_partition,distribute,el_size,gz) res(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*((T ∘ ∇(u)) ⊙ ∇(v)))dΩ - ∫(g⋅v)dΓ_N ## Finite difference solver and level set function - # stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + # stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) # reinit!(stencil,φh,γ_reinit) ## Setup solver and FE operators diff --git a/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl index 52871792..c903951a 100644 --- a/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl @@ -78,7 +78,7 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks)) diff --git a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl index 5b4730c5..6f463318 100644 --- a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl @@ -92,7 +92,7 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks)) diff --git a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl index d15c424c..657b35c4 100644 --- a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl @@ -82,7 +82,7 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks)) diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl index b9f3269c..75163cb0 100644 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -88,7 +88,7 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks)) diff --git a/scripts/_dev/Paper_scripts/therm_comp_MPI.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI.jl index 9b76c455..8320ff76 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_MPI.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_MPI.jl @@ -78,7 +78,7 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=i_am_main(ranks)) # Solve diff --git a/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl index 99be6ec8..3cb4f8ba 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl @@ -80,7 +80,7 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks)) diff --git a/scripts/_dev/Paper_scripts/therm_comp_serial.jl b/scripts/_dev/Paper_scripts/therm_comp_serial.jl index 78cd651c..9e7e2342 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_serial.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_serial.jl @@ -63,7 +63,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, verbose=true) diff --git a/scripts/_dev/benchmark_tests/MPI_benchmark_test_2D_themal.jl b/scripts/_dev/benchmark_tests/MPI_benchmark_test_2D_themal.jl index e4a309ad..2d09b546 100644 --- a/scripts/_dev/benchmark_tests/MPI_benchmark_test_2D_themal.jl +++ b/scripts/_dev/benchmark_tests/MPI_benchmark_test_2D_themal.jl @@ -62,7 +62,7 @@ function main(mesh_partition,el_size,ranks) dJ(q,u,φ,dΩ,dΓ_N) = ∫((-ξ+D*∇(u)⋅∇(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) reinit!(stencil,φh,γ_reinit) ## Setup solver and FE operators diff --git a/scripts/_dev/benchmark_tests/MPI_benchmark_test_3D_themal.jl b/scripts/_dev/benchmark_tests/MPI_benchmark_test_3D_themal.jl index 37b149c8..5842ead6 100644 --- a/scripts/_dev/benchmark_tests/MPI_benchmark_test_3D_themal.jl +++ b/scripts/_dev/benchmark_tests/MPI_benchmark_test_3D_themal.jl @@ -68,7 +68,7 @@ function main(mesh_partition,distribute,el_size) dJ(q,u,φ,dΩ,dΓ_N) = ∫((ξ-D*∇(u)⋅∇(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) reinit!(stencil,φh,γ_reinit) ## Setup solver and FE operators diff --git a/scripts/_dev/benchmark_tests/serial_benchmark_test.jl b/scripts/_dev/benchmark_tests/serial_benchmark_test.jl index 8de90168..0f8a784a 100644 --- a/scripts/_dev/benchmark_tests/serial_benchmark_test.jl +++ b/scripts/_dev/benchmark_tests/serial_benchmark_test.jl @@ -56,7 +56,7 @@ function main() dJ(q,u,φ,dΩ,dΓ_N) = ∫((ξ-D*∇(u)⋅∇(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) reinit!(stencil,φh,γ_reinit) ## Setup solver and FE operators diff --git a/scripts/_dev/bug_issue_46/thermal_MPI.jl b/scripts/_dev/bug_issue_46/thermal_MPI.jl index 2e4596ee..176e7b05 100644 --- a/scripts/_dev/bug_issue_46/thermal_MPI.jl +++ b/scripts/_dev/bug_issue_46/thermal_MPI.jl @@ -68,7 +68,7 @@ function main(mesh_partition,distribute,use_l::Bool) vel_ext = VelocityExtension(a_hilb, U_reg, V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) diff --git a/scripts/_dev/bug_issue_46/thermal_serial.jl b/scripts/_dev/bug_issue_46/thermal_serial.jl index e9c29a6c..b94a4d09 100644 --- a/scripts/_dev/bug_issue_46/thermal_serial.jl +++ b/scripts/_dev/bug_issue_46/thermal_serial.jl @@ -67,7 +67,7 @@ function main(use_l::Bool) vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) diff --git a/scripts/_dev/full_piezo_script.jl b/scripts/_dev/full_piezo_script.jl index 7cb7c149..49dc507a 100644 --- a/scripts/_dev/full_piezo_script.jl +++ b/scripts/_dev/full_piezo_script.jl @@ -92,7 +92,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ) = ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) reinit!(stencil,φh,γ_reinit) ## Setup solver and FE operators diff --git a/scripts/_dev/inv_hom_block_assem_testing.jl b/scripts/_dev/inv_hom_block_assem_testing.jl index acd4c897..d8623a05 100644 --- a/scripts/_dev/inv_hom_block_assem_testing.jl +++ b/scripts/_dev/inv_hom_block_assem_testing.jl @@ -74,7 +74,7 @@ Vol = (u,φ,dΩ) -> ∫(((ρ ∘ φ) - 0.5)/vol_D)dΩ; dVol = (q,u,φ,dΩ) -> ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function -stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol); +stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol); reinit!(stencil,φ,γ_reinit) ## Initialise op diff --git a/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl b/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl index 4ab969a6..d0317914 100644 --- a/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl +++ b/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl @@ -86,7 +86,7 @@ function main(mesh_partition,distribute,el_size,diag_assem::Bool) dVol = (q,u,φ,dΩ) -> ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(3,Float64),model,V_φ,el_size./order,max_steps,tol) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,el_size./order,max_steps,tol) reinit!(stencil,φ,γ_reinit) ## Setup solver and FE operators diff --git a/scripts/_dev/inv_hom_block_assem_testing_full_script.jl b/scripts/_dev/inv_hom_block_assem_testing_full_script.jl index f3c31fc2..13da1a00 100644 --- a/scripts/_dev/inv_hom_block_assem_testing_full_script.jl +++ b/scripts/_dev/inv_hom_block_assem_testing_full_script.jl @@ -77,7 +77,7 @@ function main(diag_block) dVol = (q,u,φ,dΩ) -> ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol) reinit!(stencil,φ,γ_reinit) ## Setup solver and FE operators diff --git a/scripts/_dev/mem_leak.jl b/scripts/_dev/mem_leak.jl index af9a2b28..2865affb 100644 --- a/scripts/_dev/mem_leak.jl +++ b/scripts/_dev/mem_leak.jl @@ -62,7 +62,7 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) +stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve diff --git a/scripts/_dev/nonlinear_adjoint_MWE.jl b/scripts/_dev/nonlinear_adjoint_MWE.jl index a84705a2..082e78e0 100644 --- a/scripts/_dev/nonlinear_adjoint_MWE.jl +++ b/scripts/_dev/nonlinear_adjoint_MWE.jl @@ -70,7 +70,7 @@ function main() J = (u,φ,dΩ,dΓ_N) -> ∫((I ∘ φ)*(D ∘ u)*∇(u)⋅∇(u) + ξ*(ρ ∘ φ))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol) reinit!(stencil,φ,γ_reinit) ## Setup solver and FE operators diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation.jl index 6867340e..c9f05eca 100644 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation.jl +++ b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation.jl @@ -61,7 +61,7 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) +stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d.jl index 0f167337..f6db4233 100644 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d.jl +++ b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d.jl @@ -63,7 +63,7 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) +stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc.jl index a8db1de4..b41760df 100644 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc.jl +++ b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc.jl @@ -77,7 +77,7 @@ function main() ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc_mpi.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc_mpi.jl index d9fde797..7ea63770 100644 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc_mpi.jl +++ b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc_mpi.jl @@ -78,7 +78,7 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_nonlinear.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_nonlinear.jl index 058f1f4f..69c03024 100644 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_nonlinear.jl +++ b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_nonlinear.jl @@ -59,7 +59,7 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) +stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve From a8d2e265f673d33db34ead5aaa07a8e71f50e2dd Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 11:27:40 +1000 Subject: [PATCH 30/90] Update warmup script --- compile/warmup.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/compile/warmup.jl b/compile/warmup.jl index c79ecbd1..70adbc03 100644 --- a/compile/warmup.jl +++ b/compile/warmup.jl @@ -70,7 +70,7 @@ function main(mesh_partition,distribute) dJ = (q,u,φ,dΩ,dΓ_N) -> ∫((ξ-D*∇(u)⋅∇(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,Δ./order,max_steps,tol) + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,Δ./order,max_steps,tol) reinit!(stencil,φ,γ_reinit) ## Setup solver and FE operators From 6358a6febfb2ff65730a388640b5e8ca45dacd61 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 11:34:29 +1000 Subject: [PATCH 31/90] Started updating docs --- docs/make.jl | 2 +- .../{advection.md => levelsetevolution.md} | 8 ++++---- docs/src/tutorials/minimum_thermal_compliance.md | 14 +++++++------- 3 files changed, 12 insertions(+), 12 deletions(-) rename docs/src/reference/{advection.md => levelsetevolution.md} (64%) diff --git a/docs/make.jl b/docs/make.jl index 67bba876..6edb2324 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -30,7 +30,7 @@ makedocs( "Reference" => [ "reference/optimisers.md", "reference/chainrules.md", - "reference/advection.md", + "reference/levelsetevolution.md", "reference/velext.md", "reference/io.md", "reference/utilities.md", diff --git a/docs/src/reference/advection.md b/docs/src/reference/levelsetevolution.md similarity index 64% rename from docs/src/reference/advection.md rename to docs/src/reference/levelsetevolution.md index 46166d58..a9ba77e4 100644 --- a/docs/src/reference/advection.md +++ b/docs/src/reference/levelsetevolution.md @@ -1,9 +1,9 @@ -# Advection +# LevelSetEvolution (NEED TO UPDATE THIS) -## `AdvectionStencil` +## `HamiltonJacobiEvolution` ```@docs -LevelSetTopOpt.AdvectionStencil -LevelSetTopOpt.AdvectionStencil(stencil::LevelSetTopOpt.Stencil,model,space,tol=1.e-3,max_steps=100,max_steps_reinit=2000) +LevelSetTopOpt.HamiltonJacobiEvolution +LevelSetTopOpt.HamiltonJacobiEvolution(stencil::LevelSetTopOpt.Stencil,model,space,tol=1.e-3,max_steps=100,max_steps_reinit=2000) LevelSetTopOpt.advect! LevelSetTopOpt.reinit! ``` diff --git a/docs/src/tutorials/minimum_thermal_compliance.md b/docs/src/tutorials/minimum_thermal_compliance.md index ddbb4337..5d1f4452 100644 --- a/docs/src/tutorials/minimum_thermal_compliance.md +++ b/docs/src/tutorials/minimum_thermal_compliance.md @@ -346,10 +346,10 @@ Both of these equations can be solved numerically on a Cartesian mesh using a fi ```julia # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) +stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) ``` -In the above we first build an object [`FirstOrderStencil`](@ref) that represents a finite difference stencil for a single step of the Hamilton-Jacobi evolution equation and reinitialisation equation. We use `length(el_size)` to indicate the dimension of the problem. We then create an [`AdvectionStencil`](@ref) which enables finite differencing on order `O` finite elements in serial or parallel. The [`AdvectionStencil`](@ref) object provides two important methods [`advect!`](@ref) and [`reinit!`](@ref) that correspond to solving the Hamilton-Jacobi evolution equation and reinitialisation equation, respectively. +In the above we first build an object [`FirstOrderStencil`](@ref) that represents a finite difference stencil for a single step of the Hamilton-Jacobi evolution equation and reinitialisation equation. We use `length(el_size)` to indicate the dimension of the problem. We then create an [`HamiltonJacobiEvolution`](@ref) which enables finite differencing on order `O` finite elements in serial or parallel. The [`HamiltonJacobiEvolution`](@ref) object provides two important methods [`advect!`](@ref) and [`reinit!`](@ref) that correspond to solving the Hamilton-Jacobi evolution equation and reinitialisation equation, respectively. ### Optimiser, visualisation and IO @@ -461,7 +461,7 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) +stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve @@ -604,7 +604,7 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) +stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve @@ -754,7 +754,7 @@ function main() ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve @@ -918,7 +918,7 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) + stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) @@ -1070,7 +1070,7 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = AdvectionStencil(scheme,model,V_φ,tol,max_steps) +stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve From 29e628029cbd79d5b34152bfd6a000f56adac3d8 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 11:50:08 +1000 Subject: [PATCH 32/90] Remove src/Advection.jl and ALM converge change --- src/Advection.jl | 501 -------------------------- src/Optimisers/AugmentedLagrangian.jl | 4 +- 2 files changed, 2 insertions(+), 503 deletions(-) delete mode 100644 src/Advection.jl diff --git a/src/Advection.jl b/src/Advection.jl deleted file mode 100644 index 241af032..00000000 --- a/src/Advection.jl +++ /dev/null @@ -1,501 +0,0 @@ -""" - abstract type Stencil - -Finite difference stencil for a single step of the Hamilton-Jacobi -evolution equation and reinitialisation equation. - -Your own stencil can be implemented by extending the methods below. -""" -abstract type Stencil end - -""" - allocate_caches(::Stencil,φ,vel) - -Allocate caches for a given `Stencil`. -""" -function allocate_caches(::Stencil,φ,vel) - nothing # By default, no caches are required. -end - -""" - reinit!(::Stencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) -> φ - -Single finite difference step of the reinitialisation equation for a given `Stencil`. -""" -function reinit!(::Stencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) - @abstractmethod -end - -""" - advect!(::Stencil,φ,vel,Δt,Δx,isperiodic,caches) -> φ - -Single finite difference step of the Hamilton-Jacobi evoluation equation for a given -`Stencil`. -""" -function advect!(::Stencil,φ,vel,Δt,Δx,isperiodic,caches) - @abstractmethod -end - -""" - compute_Δt(::Stencil,φ,vel) - -Compute the time step for the `Stencil`. -""" -function compute_Δt(::Stencil,φ,vel) - @abstractmethod -end - -""" - struct FirstOrderStencil{D,T} <: Stencil end - -A first order Godunov upwind difference scheme based on Osher and Fedkiw -([link](https://doi.org/10.1007/b98879)). -""" -struct FirstOrderStencil{D,T} <: Stencil - function FirstOrderStencil(D::Integer,::Type{T}) where T<:Real - new{D,T}() - end -end - -function allocate_caches(::FirstOrderStencil{2},φ,vel) - D⁺ʸ = similar(φ); D⁺ˣ = similar(φ) - D⁻ʸ = similar(φ); D⁻ˣ = similar(φ) - ∇⁺ = similar(φ); ∇⁻ = similar(φ) - return D⁺ʸ, D⁺ˣ, D⁻ʸ, D⁻ˣ, ∇⁺, ∇⁻ -end - -function reinit!(::FirstOrderStencil{2,T},φ_new,φ,vel,Δt,Δx,isperiodic,caches) where T - D⁺ʸ, D⁺ˣ, D⁻ʸ, D⁻ˣ, ∇⁺, ∇⁻ = caches - Δx, Δy = Δx - xperiodic,yperiodic = isperiodic - # Prepare shifted lsf - circshift!(D⁺ʸ,φ,(0,-1)); circshift!(D⁻ʸ,φ,(0,1)) - circshift!(D⁺ˣ,φ,(-1,0)); circshift!(D⁻ˣ,φ,(1,0)) - # Sign approximation - ∇⁺ .= @. (D⁺ʸ - D⁻ʸ)/(2Δy); ~yperiodic ? ∇⁺[:,[1,end]] .= zero(T) : 0; - ∇⁻ .= @. (D⁺ˣ - D⁻ˣ)/(2Δx); ~xperiodic ? ∇⁻[[1,end],:] .= zero(T) : 0; - ϵₛ = minimum((Δx,Δy)) - vel .= @. φ/sqrt(φ^2 + ϵₛ^2*(∇⁺^2+∇⁻^2)) - # Forward (+) & Backward (-) - D⁺ʸ .= @. (D⁺ʸ - φ)/Δy; ~yperiodic ? D⁺ʸ[:,end] .= zero(T) : 0; - D⁺ˣ .= @. (D⁺ˣ - φ)/Δx; ~xperiodic ? D⁺ˣ[end,:] .= zero(T) : 0; - D⁻ʸ .= @. (φ - D⁻ʸ)/Δy; ~yperiodic ? D⁻ʸ[:,1] .= zero(T) : 0; - D⁻ˣ .= @. (φ - D⁻ˣ)/Δx; ~xperiodic ? D⁻ˣ[1,:] .= zero(T) : 0; - # Operators - ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2); - ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2); - # Update - φ_new .= @. φ - Δt*(max(vel,0)*∇⁺ + min(vel,0)*∇⁻ - vel) - return φ_new -end - -function advect!(::FirstOrderStencil{2,T},φ,vel,Δt,Δx,isperiodic,caches) where T - D⁺ʸ, D⁺ˣ, D⁻ʸ, D⁻ˣ, ∇⁺, ∇⁻ = caches - Δx, Δy = Δx - xperiodic,yperiodic = isperiodic - # Prepare shifted lsf - circshift!(D⁺ʸ,φ,(0,-1)); circshift!(D⁻ʸ,φ,(0,1)) - circshift!(D⁺ˣ,φ,(-1,0)); circshift!(D⁻ˣ,φ,(1,0)) - # Forward (+) & Backward (-) - D⁺ʸ .= @. (D⁺ʸ - φ)/Δy; ~yperiodic ? D⁺ʸ[:,end] .= zero(T) : 0; - D⁺ˣ .= @. (D⁺ˣ - φ)/Δx; ~xperiodic ? D⁺ˣ[end,:] .= zero(T) : 0; - D⁻ʸ .= @. (φ - D⁻ʸ)/Δy; ~yperiodic ? D⁻ʸ[:,1] .= zero(T) : 0; - D⁻ˣ .= @. (φ - D⁻ˣ)/Δx; ~xperiodic ? D⁻ˣ[1,:] .= zero(T) : 0; - # Operators - ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2) - ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2) - # Update - φ .= @. φ - Δt*(max(vel,0)*∇⁺ + min(vel,0)*∇⁻) - return φ -end - -function allocate_caches(::FirstOrderStencil{3},φ,vel) - D⁺ᶻ = similar(φ); D⁺ʸ = similar(φ); D⁺ˣ = similar(φ) - D⁻ᶻ = similar(φ); D⁻ʸ = similar(φ); D⁻ˣ = similar(φ) - ∇⁺ = similar(φ); ∇⁻ = similar(φ) - return D⁺ᶻ, D⁺ʸ, D⁺ˣ, D⁻ᶻ, D⁻ʸ, D⁻ˣ, ∇⁺, ∇⁻ -end - -function reinit!(::FirstOrderStencil{3,T},φ_new,φ,vel,Δt,Δx,isperiodic,caches) where T - D⁺ᶻ, D⁺ʸ, D⁺ˣ, D⁻ᶻ, D⁻ʸ, D⁻ˣ, ∇⁺, ∇⁻=caches - Δx, Δy, Δz = Δx - xperiodic,yperiodic,zperiodic = isperiodic - # Prepare shifted lsf - circshift!(D⁺ʸ,φ,(0,-1,0)); circshift!(D⁻ʸ,φ,(0,1,0)) - circshift!(D⁺ˣ,φ,(-1,0,0)); circshift!(D⁻ˣ,φ,(1,0,0)) - circshift!(D⁺ᶻ,φ,(0,0,-1)); circshift!(D⁻ᶻ,φ,(0,0,1)) - # Sign approximation - ∇⁺ .= @. (D⁺ʸ - D⁻ʸ)/(2Δy); ~yperiodic ? ∇⁺[:,[1,end],:] .= zero(T) : 0; - ∇⁻ .= @. (D⁺ˣ - D⁻ˣ)/(2Δx); ~xperiodic ? ∇⁻[[1,end],:,:] .= zero(T) : 0; - ∇⁺ .= @. ∇⁺^2+∇⁻^2 # |∇φ|² (partially computed) - ∇⁻ .= @. (D⁺ᶻ - D⁻ᶻ)/(2Δz); ~xperiodic ? ∇⁻[:,:,[1,end]] .= zero(T) : 0; - ϵₛ = minimum((Δx,Δy,Δz)) - vel .= @. φ/sqrt(φ^2 + ϵₛ^2*(∇⁺+∇⁻^2)) - # Forward (+) & Backward (-) - D⁺ʸ .= (D⁺ʸ - φ)/Δy; ~yperiodic ? D⁺ʸ[:,end,:] .= zero(T) : 0; - D⁺ˣ .= (D⁺ˣ - φ)/Δx; ~xperiodic ? D⁺ˣ[end,:,:] .= zero(T) : 0; - D⁺ᶻ .= (D⁺ᶻ - φ)/Δz; ~zperiodic ? D⁺ᶻ[:,:,end] .= zero(T) : 0; - D⁻ʸ .= (φ - D⁻ʸ)/Δy; ~yperiodic ? D⁻ʸ[:,1,:] .= zero(T) : 0; - D⁻ˣ .= (φ - D⁻ˣ)/Δx; ~xperiodic ? D⁻ˣ[1,:,:] .= zero(T) : 0; - D⁻ᶻ .= (φ - D⁻ᶻ)/Δz; ~zperiodic ? D⁻ᶻ[:,:,1] .= zero(T) : 0; - # Operators - ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2 + max(D⁻ᶻ,0)^2 + min(D⁺ᶻ,0)^2) - ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2 + max(D⁺ᶻ,0)^2 + min(D⁻ᶻ,0)^2) - # Update - φ_new .= @. φ - Δt*(max(vel,0)*∇⁺ + min(vel,0)*∇⁻ - vel) - return φ_new -end - -function advect!(::FirstOrderStencil{3,T},φ,vel,Δt,Δx,isperiodic,caches) where T - D⁺ᶻ, D⁺ʸ, D⁺ˣ, D⁻ᶻ, D⁻ʸ, D⁻ˣ, ∇⁺, ∇⁻=caches - Δx, Δy, Δz = Δx - xperiodic,yperiodic,zperiodic = isperiodic - # Prepare shifted lsf - circshift!(D⁺ʸ,φ,(0,-1,0)); circshift!(D⁻ʸ,φ,(0,1,0)) - circshift!(D⁺ˣ,φ,(-1,0,0)); circshift!(D⁻ˣ,φ,(1,0,0)) - circshift!(D⁺ᶻ,φ,(0,0,-1)); circshift!(D⁻ᶻ,φ,(0,0,1)) - # Forward (+) & Backward (-) - D⁺ʸ .= (D⁺ʸ - φ)/Δy; ~yperiodic ? D⁺ʸ[:,end,:] .= zero(T) : 0; - D⁺ˣ .= (D⁺ˣ - φ)/Δx; ~xperiodic ? D⁺ˣ[end,:,:] .= zero(T) : 0; - D⁺ᶻ .= (D⁺ᶻ - φ)/Δz; ~zperiodic ? D⁺ᶻ[:,:,end] .= zero(T) : 0; - D⁻ʸ .= (φ - D⁻ʸ)/Δy; ~yperiodic ? D⁻ʸ[:,1,:] .= zero(T) : 0; - D⁻ˣ .= (φ - D⁻ˣ)/Δx; ~xperiodic ? D⁻ˣ[1,:,:] .= zero(T) : 0; - D⁻ᶻ .= (φ - D⁻ᶻ)/Δz; ~zperiodic ? D⁻ᶻ[:,:,1] .= zero(T) : 0; - # Operators - ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2 + max(D⁻ᶻ,0)^2 + min(D⁺ᶻ,0)^2) - ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2 + max(D⁺ᶻ,0)^2 + min(D⁻ᶻ,0)^2) - # Update - φ .= @. φ - Δt*(max(vel,0)*∇⁺ + min(vel,0)*∇⁻) - return φ -end - -function compute_Δt(::FirstOrderStencil{D,T},Δ,γ,φ,vel) where {D,T} - v_norm = maximum(abs,vel) - return γ * min(Δ...) / (eps(T)^2 + v_norm) -end - -""" - struct AdvectionStencil{O} - -Wrapper to enable finite differencing to solve the -Hamilton-Jacobi evolution equation and reinitialisation equation -on order `O` finite elements in serial or parallel. - -# Parameters - -- `stencil::Stencil`: Finite difference stencil for a single step HJ - equation and reinitialisation equation. -- `model`: A `CartesianDiscreteModel`. -- `space`: FE space for level-set function -- `perm`: A permutation vector -- `params`: Tuple of additional params -- `cache`: Stencil cache -""" -struct AdvectionStencil{O} - stencil :: Stencil - model - space - perm - params - cache -end - -""" - AdvectionStencil(stencil::Stencil,model,space,tol,max_steps,max_steps_reinit) - -Create an instance of `AdvectionStencil` given a stencil, model, FE space, and -additional optional arguments. This automatically creates the DoF permutation -to handle high-order finite elements. -""" -function AdvectionStencil( - stencil::Stencil, - model, - space, - tol=1.e-3, - max_steps=100, - max_steps_reinit=2000 -) - # Parameters - order, isperiodic, Δ, ndof = get_stencil_params(model,space) - params = (;isperiodic,Δ,ndof,max_steps,max_steps_reinit,tol) - - # Dof permutation - perm = create_dof_permutation(model,space,order) - - # Caches - φ, vel = zero_free_values(space), zero_free_values(space) - cache = allocate_caches(stencil,φ,vel,perm,order,ndof) - - return AdvectionStencil{order}(stencil,model,space,perm,params,cache) -end - -function get_stencil_params(model::CartesianDiscreteModel,space::FESpace) - order = get_order(first(Gridap.CellData.get_data(get_fe_basis(space)))) - desc = get_cartesian_descriptor(model) - isperiodic = desc.isperiodic - ndof = order .* desc.partition .+ 1 .- isperiodic - Δ = desc.sizes ./ order - return order, isperiodic, Δ, ndof -end - -function get_stencil_params(model::DistributedDiscreteModel,space::DistributedFESpace) - order, isperiodic, Δ, ndof = map(local_views(model),local_views(space)) do model, space - get_stencil_params(model,space) - end |> PartitionedArrays.tuple_of_arrays - - isperiodic = getany(isperiodic) - order = getany(order) - Δ = getany(Δ) - return order, isperiodic, Δ, ndof -end - -Gridap.ReferenceFEs.get_order(f::Gridap.Fields.LinearCombinationFieldVector) = get_order(f.fields) - -# Create dof permutation vector to enable finite differences on -# higher order Lagrangian finite elements on a Cartesian mesh. -function create_dof_permutation(model::CartesianDiscreteModel{Dc}, - space::UnconstrainedFESpace, - order::Integer) where Dc - function get_terms(poly::Polytope, orders) - _nodes, facenodes = Gridap.ReferenceFEs._compute_nodes(poly, orders) - terms = Gridap.ReferenceFEs._coords_to_terms(_nodes, orders) - return terms - end - desc = get_cartesian_descriptor(model) - - periodic = desc.isperiodic - ncells = desc.partition - ndofs = order .* ncells .+ 1 .- periodic - @check prod(ndofs) == num_free_dofs(space) - - new_dof_ids = CircularArray(LinearIndices(ndofs)) - n2o_dof_map = fill(-1,num_free_dofs(space)) - - terms = get_terms(first(get_polytopes(model)), fill(order,Dc)) - cell_dof_ids = get_cell_dof_ids(space) - cache_cell_dof_ids = array_cache(cell_dof_ids) - for (iC,cell) in enumerate(CartesianIndices(ncells)) - first_new_dof = order .* (Tuple(cell) .- 1) .+ 1 - new_dofs_range = map(i -> i:i+order,first_new_dof) - new_dofs = view(new_dof_ids,new_dofs_range...) - - cell_dofs = getindex!(cache_cell_dof_ids,cell_dof_ids,iC) - for (iDof, dof) in enumerate(cell_dofs) - t = terms[iDof] - #o2n_dof_map[dof] = new_dofs[t] - n2o_dof_map[new_dofs[t]] = dof - end - end - - return n2o_dof_map -end - -function create_dof_permutation(model::GridapDistributed.DistributedDiscreteModel, - space::GridapDistributed.DistributedFESpace, - order::Integer) - local_perms = map(local_views(model),local_views(space)) do model, space - create_dof_permutation(model,space,order) - end - return local_perms -end - -function PartitionedArrays.permute_indices(indices::LocalIndices,perm) - id = part_id(indices) - n_glob = global_length(indices) - l2g = view(local_to_global(indices),perm) - l2o = view(local_to_owner(indices),perm) - return LocalIndices(n_glob,id,l2g,l2o) -end - -function allocate_caches(s::Stencil,φ::Vector,vel::Vector,perm,order,ndofs) - stencil_caches = allocate_caches(s,reshape(φ,ndofs),reshape(vel,ndofs)) - φ_tmp = similar(φ) - vel_tmp = similar(vel) - perm_caches = (order >= 2) ? (similar(φ), similar(vel)) : nothing - return φ_tmp, vel_tmp, perm_caches, stencil_caches -end - -function allocate_caches(s::Stencil,φ::PVector,vel::PVector,perm,order,local_ndofs) - local_stencil_caches = map(local_views(φ),local_views(vel),local_views(local_ndofs)) do φ,vel,ndofs - allocate_caches(s,reshape(φ,ndofs),reshape(vel,ndofs)) - end - - perm_indices = map(permute_indices,partition(axes(φ,1)),perm) - perm_caches = (order >= 2) ? (pfill(0.0,perm_indices),pfill(0.0,perm_indices)) : nothing - - φ_tmp = (order >= 2) ? pfill(0.0,perm_indices) : similar(φ) - vel_tmp = (order >= 2) ? pfill(0.0,perm_indices) : similar(vel) - return φ_tmp, vel_tmp, perm_caches, local_stencil_caches -end - -function permute!(x_out,x_in,perm) - for (i_new,i_old) in enumerate(perm) - x_out[i_new] = x_in[i_old] - end - return x_out -end - -function permute!(x_out::PVector,x_in::PVector,perm) - map(permute!,partition(x_out),partition(x_in),perm) - return x_out -end - -function permute_inv!(x_out,x_in,perm) - for (i_new,i_old) in enumerate(perm) - x_out[i_old] = x_in[i_new] - end - return x_out -end -function permute_inv!(x_out::PVector,x_in::PVector,perm) - map(permute_inv!,partition(x_out),partition(x_in),perm) - return x_out -end - -function advect!(s::AdvectionStencil,φh,args...) - advect!(s,get_free_dof_values(φh),args...) -end - -""" - advect!(s::AdvectionStencil{O},φ,vel,γ) where O - -Solve the Hamilton-Jacobi evolution equation using the `AdvectionStencil`. - -# Hamilton-Jacobi evolution equation -``\\frac{\\partial\\phi}{\\partial t} + V(\\boldsymbol{x})\\lVert\\boldsymbol{\\nabla}\\phi\\rVert = 0,`` - -with ``\\phi(0,\\boldsymbol{x})=\\phi_0(\\boldsymbol{x})`` and ``\\boldsymbol{x}\\in D,~t\\in(0,T)``. - -# Arguments - -- `s::AdvectionStencil{O}`: Stencil for computation -- `φ`: level set function as a vector of degrees of freedom -- `vel`: the normal velocity as a vector of degrees of freedom -- `γ`: coeffient on the time step size. -""" -function advect!(s::AdvectionStencil{O},φ::PVector,vel::PVector,γ) where O - _, _, perm_caches, stencil_cache = s.cache - Δ, isperiodic, = s.params.Δ, s.params.isperiodic - ndof, max_steps = s.params.ndof, s.params.max_steps - - _φ = (O >= 2) ? permute!(perm_caches[1],φ,s.perm) : φ - _vel = (O >= 2) ? permute!(perm_caches[2],vel,s.perm) : vel - - ## CFL Condition (requires γ≤1.0) - Δt = compute_Δt(s.stencil,Δ,γ,φ,vel) - for _ in 1:max_steps - # Apply operations across partitions - map(local_views(_φ),local_views(_vel),stencil_cache,ndof) do _φ,_vel,stencil_cache,S - φ_mat = reshape(_φ,S) - vel_mat = reshape(_vel,S) - advect!(s.stencil,φ_mat,vel_mat,Δt,Δ,isperiodic,stencil_cache) - end - # Update ghost nodes - consistent!(_φ) |> fetch - end - φ = (O >= 2) ? permute_inv!(φ,_φ,s.perm) : _φ - return φ -end - -function advect!(s::AdvectionStencil{O},φ::Vector,vel::Vector,γ) where O - _, _, perm_caches, stencil_cache = s.cache - Δ, isperiodic, = s.params.Δ, s.params.isperiodic - ndof, max_steps = s.params.ndof, s.params.max_steps - - _φ = (O >= 2) ? permute!(perm_caches[1],φ,s.perm) : φ - _vel = (O >= 2) ? permute!(perm_caches[2],vel,s.perm) : vel - - ## CFL Condition (requires γ≤1.0) - Δt = compute_Δt(s.stencil,Δ,γ,φ,vel) - for _ in 1:max_steps - φ_mat = reshape(_φ,ndof) - vel_mat = reshape(_vel,ndof) - advect!(s.stencil,φ_mat,vel_mat,Δt,Δ,isperiodic,stencil_cache) - end - φ = (O >= 2) ? permute_inv!(φ,_φ,s.perm) : _φ - return φ -end - -function reinit!(s::AdvectionStencil,φh,args...) - reinit!(s,get_free_dof_values(φh),args...) -end - -""" - reinit!(s::AdvectionStencil{O},φ,γ) where O - -Solve the reinitialisation equation using the `AdvectionStencil`. - -# Reinitialisation equation -``\\frac{\\partial\\phi}{\\partial t} + \\mathrm{sign}(\\phi_0)(\\lVert\\boldsymbol{\\nabla}\\phi\\rVert-1) = 0,`` - -with ``\\phi(0,\\boldsymbol{x})=\\phi_0(\\boldsymbol{x})`` and ``\\boldsymbol{x}\\in D,~t\\in(0,T)``. - -# Arguments - -- `s::AdvectionStencil{O}`: Stencil for computation -- `φ`: level set function as a vector of degrees of freedom -- `γ`: coeffient on the time step size. -""" -function reinit!(s::AdvectionStencil{O},φ::PVector,γ) where O - φ_tmp, vel_tmp, perm_caches, stencil_cache = s.cache - Δ, isperiodic, ndof = s.params.Δ, s.params.isperiodic, s.params.ndof - tol, max_steps = s.params.tol, s.params.max_steps_reinit - - _φ = (O >= 2) ? permute!(perm_caches[1],φ,s.perm) : φ - - ## CFL Condition (requires γ≤0.5). Note inform(vel_tmp) = 1.0 - Δt = compute_Δt(s.stencil,Δ,γ,_φ,1.0) - - # Apply operations across partitions - step = 1; err = maximum(abs,φ); fill!(φ_tmp,0.0) - while (err > tol) && (step <= max_steps) - # Step of 1st order upwind reinitialisation equation - map(local_views(φ_tmp),local_views(_φ),local_views(vel_tmp),stencil_cache,ndof) do φ_tmp,_φ,vel_tmp,stencil_cache,S - φ_tmp_mat = reshape(φ_tmp,S) - φ_mat = reshape(_φ,S) - vel_tmp_mat = reshape(vel_tmp,S) - reinit!(s.stencil,φ_tmp_mat,φ_mat,vel_tmp_mat,Δt,Δ,isperiodic,stencil_cache) - end - - # Compute error - _φ .-= φ_tmp # φ - φ_tmp - err = maximum(abs,_φ) - step += 1 - - # Update φ - copy!(_φ,φ_tmp) - consistent!(_φ) |> fetch # We exchange ghosts here! - end - φ = (O >= 2) ? permute_inv!(φ,_φ,s.perm) : _φ - return φ -end - -function reinit!(s::AdvectionStencil{O},φ::Vector,γ) where O - φ_tmp, vel_tmp, perm_caches, stencil_cache = s.cache - Δ, isperiodic, ndof = s.params.Δ, s.params.isperiodic, s.params.ndof - tol, max_steps = s.params.tol, s.params.max_steps_reinit - - _φ = (O >= 2) ? permute!(perm_caches[1],φ,s.perm) : φ - - ## CFL Condition (requires γ≤0.5) - Δt = compute_Δt(s.stencil,Δ,γ,_φ,1.0) - - # Apply operations across partitions - step = 1; err = maximum(abs,φ); fill!(φ_tmp,0.0) - while (err > tol) && (step <= max_steps) - # Step of 1st order upwind reinitialisation equation - φ_tmp_mat = reshape(φ_tmp,ndof) - φ_mat = reshape(_φ,ndof) - vel_tmp_mat = reshape(vel_tmp,ndof) - reinit!(s.stencil,φ_tmp_mat,φ_mat,vel_tmp_mat,Δt,Δ,isperiodic,stencil_cache) - - # Compute error - _φ .-= φ_tmp - err = maximum(abs,_φ) - step += 1 - - # Update φ - copy!(_φ,φ_tmp) - end - φ = (O >= 2) ? permute_inv!(φ,_φ,s.perm) : _φ - return φ -end diff --git a/src/Optimisers/AugmentedLagrangian.jl b/src/Optimisers/AugmentedLagrangian.jl index 1c879508..6c2d48b5 100644 --- a/src/Optimisers/AugmentedLagrangian.jl +++ b/src/Optimisers/AugmentedLagrangian.jl @@ -37,7 +37,7 @@ struct AugmentedLagrangian <: Optimiser ls_evolver :: LevelSetEvolution, vel_ext :: VelocityExtension, φ0; - Λ_max = 5.0, ζ = 1.1, update_mod = 5, γ = 0.1, γ_reinit = 0.5, os_γ_mult = 0.75, + Λ_max = 10^10, ζ = 1.1, update_mod = 5, γ = 0.1, γ_reinit = 0.5, os_γ_mult = 0.75, maxiter = 1000, verbose=false, constraint_names = map(i -> Symbol("C_\$i"),1:N), converged::Function = default_al_converged, debug = false, has_oscillations::Function = default_has_oscillations @@ -123,7 +123,7 @@ end function default_al_converged( m::AugmentedLagrangian; - L_tol = 0.01*maximum(get_dof_Δ(m.ls_evolver)), + L_tol = 0.01*maximum(get_dof_Δ(m.ls_evolver))/(length(get_dof_Δ(m.ls_evolver))-1), C_tol = 0.01 ) h = m.history From f142cd5e5b9b4b8d506ababf381815b5229018c9 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 14:29:56 +1000 Subject: [PATCH 33/90] Update docs --- docs/src/reference/levelsetevolution.md | 34 +++++++++++++------ docs/src/reference/optimisers.md | 2 +- .../tutorials/minimum_thermal_compliance.md | 2 +- .../HamiltonJacobiEvolution.jl | 8 ++--- src/LevelSetEvolution/SpatialStencil.jl | 6 ++-- 5 files changed, 31 insertions(+), 21 deletions(-) diff --git a/docs/src/reference/levelsetevolution.md b/docs/src/reference/levelsetevolution.md index a9ba77e4..3fd8ebf4 100644 --- a/docs/src/reference/levelsetevolution.md +++ b/docs/src/reference/levelsetevolution.md @@ -1,25 +1,39 @@ -# LevelSetEvolution (NEED TO UPDATE THIS) +# LevelSetEvolution +In LevelSetTopOpt, the level set is evolved and reinitialised using a `LevelSetEvolution` method. The most standard of these is the Hamilton-Jacobi evolution equation solved using a first order upwind finite difference scheme. A forward Euler in time method is provided below via `HamiltonJacobiEvolution <: LevelSetEvolution` along with an upwind finite difference stencil for the spatial discretisation via `FirstOrderStencil`. + +This can be extended in several ways. For example, higher order spatial stencils can be implemented by extending the `SpatialStencil` interface below. In addition, more advanced ODE solvers could be implemented (e.g., Runge–Kutta methods) or entirely different level set evolution methods by extending the `LevelSetEvolution` interface below. ## `HamiltonJacobiEvolution` ```@docs LevelSetTopOpt.HamiltonJacobiEvolution -LevelSetTopOpt.HamiltonJacobiEvolution(stencil::LevelSetTopOpt.Stencil,model,space,tol=1.e-3,max_steps=100,max_steps_reinit=2000) -LevelSetTopOpt.advect! +LevelSetTopOpt.HamiltonJacobiEvolution(stencil::LevelSetTopOpt.SpatialStencil,model,space,tol=1.e-3,max_steps=100,max_steps_reinit=2000) +LevelSetTopOpt.evolve! LevelSetTopOpt.reinit! +LevelSetTopOpt.get_dof_Δ(m::HamiltonJacobiEvolution) ``` -## Stencils +## Spatial stencils for `HamiltonJacobiEvolution` ```@docs LevelSetTopOpt.FirstOrderStencil ``` -## Custom `Stencil` +## Custom `SpatialStencil` + +```@docs +LevelSetTopOpt.SpatialStencil +LevelSetTopOpt.evolve!(::LevelSetTopOpt.SpatialStencil,φ,vel,Δt,Δx,isperiodic,caches) +LevelSetTopOpt.reinit!(::LevelSetTopOpt.SpatialStencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) +LevelSetTopOpt.allocate_caches(::LevelSetTopOpt.SpatialStencil,φ,vel) +LevelSetTopOpt.check_order +``` + +## Custom `LevelSetEvolution` +To implement a custom level set evolution method, we can extend the methods below. For example, one could consider Reaction-Diffusion-based evolution of the level set function. This can be solved with a finite element method and so we can implement a new type that inherits from `LevelSetEvolution` independently of the `SpatialStencil` types. ```@docs -LevelSetTopOpt.Stencil -LevelSetTopOpt.advect!(::LevelSetTopOpt.Stencil,φ,vel,Δt,Δx,isperiodic,caches) -LevelSetTopOpt.reinit!(::LevelSetTopOpt.Stencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) -LevelSetTopOpt.compute_Δt(::LevelSetTopOpt.Stencil,φ,vel) -LevelSetTopOpt.allocate_caches(::LevelSetTopOpt.Stencil,φ,vel) +LevelSetTopOpt.LevelSetEvolution +LevelSetTopOpt.evolve!(::LevelSetTopOpt.LevelSetEvolution,φ,args...) +LevelSetTopOpt.reinit!(::LevelSetTopOpt.LevelSetEvolution,φ,args...) +LevelSetTopOpt.get_dof_Δ(::LevelSetTopOpt.LevelSetEvolution) ``` \ No newline at end of file diff --git a/docs/src/reference/optimisers.md b/docs/src/reference/optimisers.md index f886ccf2..502759d3 100644 --- a/docs/src/reference/optimisers.md +++ b/docs/src/reference/optimisers.md @@ -23,7 +23,7 @@ LevelSetTopOpt.OptimiserHistory LevelSetTopOpt.OptimiserHistorySlice ``` -## Custom optimiser +## Custom `Optimiser` ```@docs LevelSetTopOpt.Optimiser LevelSetTopOpt.iterate(::LevelSetTopOpt.Optimiser) diff --git a/docs/src/tutorials/minimum_thermal_compliance.md b/docs/src/tutorials/minimum_thermal_compliance.md index 5d1f4452..0839f6e7 100644 --- a/docs/src/tutorials/minimum_thermal_compliance.md +++ b/docs/src/tutorials/minimum_thermal_compliance.md @@ -349,7 +349,7 @@ scheme = FirstOrderStencil(length(el_size),Float64) stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) ``` -In the above we first build an object [`FirstOrderStencil`](@ref) that represents a finite difference stencil for a single step of the Hamilton-Jacobi evolution equation and reinitialisation equation. We use `length(el_size)` to indicate the dimension of the problem. We then create an [`HamiltonJacobiEvolution`](@ref) which enables finite differencing on order `O` finite elements in serial or parallel. The [`HamiltonJacobiEvolution`](@ref) object provides two important methods [`advect!`](@ref) and [`reinit!`](@ref) that correspond to solving the Hamilton-Jacobi evolution equation and reinitialisation equation, respectively. +In the above we first build an object [`FirstOrderStencil`](@ref) that represents a finite difference stencil for a single step of the Hamilton-Jacobi evolution equation and reinitialisation equation. We use `length(el_size)` to indicate the dimension of the problem. We then create an [`HamiltonJacobiEvolution`](@ref) which enables finite differencing on order `O` finite elements in serial or parallel. The [`HamiltonJacobiEvolution`](@ref) object provides two important methods [`evolve!`](@ref) and [`reinit!`](@ref) that correspond to solving the Hamilton-Jacobi evolution equation and reinitialisation equation, respectively. ### Optimiser, visualisation and IO diff --git a/src/LevelSetEvolution/HamiltonJacobiEvolution.jl b/src/LevelSetEvolution/HamiltonJacobiEvolution.jl index 8e86f07a..f8052495 100644 --- a/src/LevelSetEvolution/HamiltonJacobiEvolution.jl +++ b/src/LevelSetEvolution/HamiltonJacobiEvolution.jl @@ -59,7 +59,7 @@ function HamiltonJacobiEvolution( end """ - get_dof_Δ(::HamiltonJacobiEvolution) + get_dof_Δ(m::HamiltonJacobiEvolution) Return the distance betweem degree of freedom """ @@ -67,11 +67,7 @@ function get_dof_Δ(m::HamiltonJacobiEvolution) return m.params.Δ end -""" - compute_Δt(::HamiltonJacobiEvolution,φ,vel) - -Compute the time step for the `HamiltonJacobiEvolution`. -""" +# Compute the time step for the `HamiltonJacobiEvolution`. function compute_Δt(::HamiltonJacobiEvolution,Δ,γ,φ,vel) T = eltype(γ) v_norm = maximum(abs,vel) diff --git a/src/LevelSetEvolution/SpatialStencil.jl b/src/LevelSetEvolution/SpatialStencil.jl index 12dd6469..f306442f 100644 --- a/src/LevelSetEvolution/SpatialStencil.jl +++ b/src/LevelSetEvolution/SpatialStencil.jl @@ -1,10 +1,10 @@ """ abstract type SpatialStencil -Finite difference stencil for a single step of the Hamilton-Jacobi +Spatial finite difference stencil for a single step of the Hamilton-Jacobi evolution equation and reinitialisation equation. -Your own stencil can be implemented by extending the methods below. +Your own spatial stencil can be implemented by extending the methods below. """ abstract type SpatialStencil end @@ -49,7 +49,7 @@ end """ struct FirstOrderStencil{D,T} <: SpatialStencil end -A first order Godunov upwind difference scheme based on Osher and Fedkiw +A first order upwind difference scheme based on Osher and Fedkiw ([link](https://doi.org/10.1007/b98879)). """ struct FirstOrderStencil{D,T} <: SpatialStencil From 02321bc923529c2f75707d283ee2ff26db5ef52c Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 14:31:18 +1000 Subject: [PATCH 34/90] Fix precompile bug for SmoothErsatzMaterialInterpolation --- src/Utilities.jl | 25 ++++++++++++++++--------- 1 file changed, 16 insertions(+), 9 deletions(-) diff --git a/src/Utilities.jl b/src/Utilities.jl index aede0bd2..25f6ab57 100644 --- a/src/Utilities.jl +++ b/src/Utilities.jl @@ -22,17 +22,24 @@ function ``\\varphi`` and ``I`` is an indicator function. - To update η and/or ϵ in an instance `m`, take `m.η .= `. - A conviencence constructor is provided to create an instance given `η<:Number` and `ϵ<:Number`. """ -Base.@kwdef struct SmoothErsatzMaterialInterpolation{M<:Vector{<:Number},N<:Vector{<:Number}} +struct SmoothErsatzMaterialInterpolation{M<:Vector{<:Number},N<:Vector{<:Number}} η::M ϵ::N - H = x -> H_η(x,first(η)) - DH = x -> DH_η(x,first(η)) - I = φ -> (1 - H(φ)) + first(ϵ)*H(φ) - ρ = φ -> 1 - H(φ) -end - -function SmoothErsatzMaterialInterpolation(;η::M,ϵ::N=10^-3) where {M<:Number,N<:Number} - return SmoothErsatzMaterialInterpolation{Vector{M},Vector{N}}(η=[η],ϵ=[ϵ]) + H + DH + I + ρ + function SmoothErsatzMaterialInterpolation(; + η::M, + ϵ::N = 10^-3, + H = x -> H_η(x,first(η)), + DH = x -> DH_η(x,first(η)), + I = φ -> (1 - H(φ)) + first(ϵ)*H(φ), + ρ = φ -> 1 - H(φ) + ) where {M<:Number,N<:Number} + + new{Vector{M},Vector{N}}([η],[ϵ],H,DH,I,ρ) + end end function H_η(t,η) From 51b6cd15d85315fea102020b1365344911f48330 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Wed, 10 Apr 2024 14:35:35 +1000 Subject: [PATCH 35/90] Update stop --- src/Optimisers/AugmentedLagrangian.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/Optimisers/AugmentedLagrangian.jl b/src/Optimisers/AugmentedLagrangian.jl index 3a44ea75..20bcfd19 100644 --- a/src/Optimisers/AugmentedLagrangian.jl +++ b/src/Optimisers/AugmentedLagrangian.jl @@ -38,7 +38,7 @@ struct AugmentedLagrangian{N,O} <: Optimiser stencil :: AdvectionStencil{O}, vel_ext :: VelocityExtension, φ0; - Λ_max = 5.0, ζ = 1.1, update_mod = 5, γ = 0.1, γ_reinit = 0.5, os_γ_mult = 0.75, + Λ_max = 10^10, ζ = 1.1, update_mod = 5, γ = 0.1, γ_reinit = 0.5, os_γ_mult = 0.75, maxiter = 1000, verbose=false, constraint_names = map(i -> Symbol("C_\$i"),1:N), converged::Function = default_al_converged, debug = false, has_oscillations::Function = default_has_oscillations @@ -125,7 +125,7 @@ end function default_al_converged( m::AugmentedLagrangian; - L_tol = 0.01*maximum(m.stencil.params.Δ), + L_tol = 0.01*maximum(m.stencil.params.Δ)/(length(m.stencil.params.Δ)-1), C_tol = 0.01 ) h = m.history From ae39c6cb382b8fd7b067cd2fb503411f2fdf3cb1 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Wed, 10 Apr 2024 16:51:56 +1000 Subject: [PATCH 36/90] Rename stencil in scripts --- compile/warmup.jl | 4 +-- .../tutorials/minimum_thermal_compliance.md | 26 +++++++++---------- scripts/Benchmarks/benchmark.jl | 16 ++++++------ scripts/MPI/3d_elastic_compliance_ALM.jl | 4 +-- scripts/MPI/3d_hyperelastic_compliance_ALM.jl | 4 +-- .../3d_hyperelastic_compliance_neohook_ALM.jl | 4 +-- scripts/MPI/3d_inverse_homenisation_ALM.jl | 4 +-- scripts/MPI/3d_inverter_ALM.jl | 4 +-- scripts/MPI/3d_inverter_HPM.jl | 4 +-- .../3d_nonlinear_thermal_compliance_ALM.jl | 4 +-- scripts/MPI/3d_thermal_compliance_ALM.jl | 4 +-- scripts/MPI/elastic_compliance_ALM.jl | 4 +-- scripts/MPI/inverse_homenisation_ALM.jl | 4 +-- scripts/MPI/thermal_compliance_ALM.jl | 4 +-- scripts/MPI/thermal_compliance_ALM_PETSc.jl | 4 +-- scripts/Serial/elastic_compliance_ALM.jl | 4 +-- scripts/Serial/elastic_compliance_HPM.jl | 4 +-- scripts/Serial/elastic_compliance_LM.jl | 4 +-- scripts/Serial/hyperelastic_compliance_ALM.jl | 4 +-- .../hyperelastic_compliance_neohook_ALM.jl | 4 +-- scripts/Serial/inverse_homenisation_ALM.jl | 4 +-- scripts/Serial/inverter_ALM.jl | 4 +-- scripts/Serial/inverter_HPM.jl | 4 +-- .../nonlinear_thermal_compliance_ALM.jl | 4 +-- scripts/Serial/thermal_compliance_ALM.jl | 4 +-- .../thermal_compliance_ALM_higherorderlsf.jl | 4 +-- .../_dev/3d_hyperelastic_compliance_ALM.jl | 2 +- .../_dev/Paper_scripts/elast_comp_MPI_3D.jl | 4 +-- .../Paper_scripts/hyperelast_comp_MPI_3D.jl | 4 +-- .../_dev/Paper_scripts/inverse_hom_MPI_3D.jl | 4 +-- scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 4 +-- scripts/_dev/Paper_scripts/therm_comp_MPI.jl | 4 +-- .../_dev/Paper_scripts/therm_comp_MPI_3D.jl | 4 +-- .../_dev/Paper_scripts/therm_comp_serial.jl | 4 +-- .../MPI_benchmark_test_2D_themal.jl | 4 +-- .../MPI_benchmark_test_3D_themal.jl | 4 +-- .../benchmark_tests/serial_benchmark_test.jl | 4 +-- scripts/_dev/bug_issue_46/thermal_MPI.jl | 4 +-- scripts/_dev/bug_issue_46/thermal_serial.jl | 4 +-- scripts/_dev/full_piezo_script.jl | 4 +-- scripts/_dev/inv_hom_block_assem_testing.jl | 2 +- .../inv_hom_block_assem_testing_3D_MPI.jl | 4 +-- ...inv_hom_block_assem_testing_full_script.jl | 4 +-- scripts/_dev/mem_leak.jl | 4 +-- scripts/_dev/nonlinear_adjoint_MWE.jl | 2 +- ...nimum_thermal_compliance_implementation.jl | 4 +-- ...um_thermal_compliance_implementation_3d.jl | 4 +-- ...rmal_compliance_implementation_3d_petsc.jl | 4 +-- ..._compliance_implementation_3d_petsc_mpi.jl | 4 +-- ...mal_compliance_implementation_nonlinear.jl | 4 +-- test/seq/ThermalComplianceALMTests.jl | 4 +-- 51 files changed, 116 insertions(+), 116 deletions(-) diff --git a/compile/warmup.jl b/compile/warmup.jl index 70adbc03..c2b6e5e3 100644 --- a/compile/warmup.jl +++ b/compile/warmup.jl @@ -70,7 +70,7 @@ function main(mesh_partition,distribute) dJ = (q,u,φ,dΩ,dΓ_N) -> ∫((ξ-D*∇(u)⋅∇(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,Δ./order,max_steps,tol) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,Δ./order,max_steps,tol) reinit!(stencil,φ,γ_reinit) ## Setup solver and FE operators @@ -84,7 +84,7 @@ function main(mesh_partition,distribute) ## Optimiser _conv_cond = t->LevelSetTopOpt.conv_cond(t;coef=1/50); - optimiser = AugmentedLagrangian(φ,pcfs,stencil,vel_ext,interp,el_size,γ,γ_reinit,conv_criterion=_conv_cond); + optimiser = AugmentedLagrangian(φ,pcfs,ls_evo,vel_ext,interp,el_size,γ,γ_reinit,conv_criterion=_conv_cond); for history in optimiser it,Ji,_,_ = last(history) print_history(it,["J"=>Ji];ranks=ranks) diff --git a/docs/src/tutorials/minimum_thermal_compliance.md b/docs/src/tutorials/minimum_thermal_compliance.md index 0839f6e7..3d52db3c 100644 --- a/docs/src/tutorials/minimum_thermal_compliance.md +++ b/docs/src/tutorials/minimum_thermal_compliance.md @@ -346,7 +346,7 @@ Both of these equations can be solved numerically on a Cartesian mesh using a fi ```julia # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) +ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) ``` In the above we first build an object [`FirstOrderStencil`](@ref) that represents a finite difference stencil for a single step of the Hamilton-Jacobi evolution equation and reinitialisation equation. We use `length(el_size)` to indicate the dimension of the problem. We then create an [`HamiltonJacobiEvolution`](@ref) which enables finite differencing on order `O` finite elements in serial or parallel. The [`HamiltonJacobiEvolution`](@ref) object provides two important methods [`evolve!`](@ref) and [`reinit!`](@ref) that correspond to solving the Hamilton-Jacobi evolution equation and reinitialisation equation, respectively. @@ -357,7 +357,7 @@ We may now create the optimiser object. This structure holds all information reg ```julia # Optimiser -optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) +optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) ``` As optimisers inheriting from [`LevelSetTopOpt.Optimiser`](@ref) implement Julia's iterator functionality, we can solve the optimisation problem to convergence by iterating over the optimiser: @@ -461,9 +461,9 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) +ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser -optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) +optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve for (it,uh,φh) in optimiser data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] @@ -604,9 +604,9 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) +ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser -optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) +optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve for (it,uh,φh) in optimiser data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] @@ -754,9 +754,9 @@ function main() ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve for (it,uh,φh) in optimiser data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] @@ -827,7 +827,7 @@ We then adjust lines 28-31 as follows: The function `i_am_main` returns true only on the first processor. This function is useful for ensuring certain operations only happen once instead of several times across each executable. In addition, we now create a partitioned Cartesian model using `CartesianDiscreteModel(ranks,mesh_partition,dom,el_size)`. Finally, we adjust line 82 to ensure that verbosity only happens on the first processors: ```julia -optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; +optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) ``` @@ -918,9 +918,9 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) # Solve for (it,uh,φh) in optimiser @@ -1070,9 +1070,9 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) +ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser -optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) +optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve for (it,uh,φh) in optimiser data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/Benchmarks/benchmark.jl b/scripts/Benchmarks/benchmark.jl index 759bf6e0..862262d7 100644 --- a/scripts/Benchmarks/benchmark.jl +++ b/scripts/Benchmarks/benchmark.jl @@ -102,9 +102,9 @@ function nl_elast(mesh_partition,ranks,el_size,order,verbose) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose) + return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose) end function therm(mesh_partition,ranks,el_size,order,verbose) @@ -180,9 +180,9 @@ function therm(mesh_partition,ranks,el_size,order,verbose) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose) + return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose) end function elast(mesh_partition,ranks,el_size,order,verbose) @@ -256,9 +256,9 @@ function elast(mesh_partition,ranks,el_size,order,verbose) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose) + return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose) end function inverter_HPM(mesh_partition,ranks,el_size,order,verbose) @@ -329,7 +329,7 @@ function inverter_HPM(mesh_partition,ranks,el_size,order,verbose) UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out ## Finite difference solver - stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} @@ -355,7 +355,7 @@ function inverter_HPM(mesh_partition,ranks,el_size,order,verbose) ) ## Optimiser - return HilbertianProjection(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=verbose) + return HilbertianProjection(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=verbose) end with_mpi() do distribute diff --git a/scripts/MPI/3d_elastic_compliance_ALM.jl b/scripts/MPI/3d_elastic_compliance_ALM.jl index d44fdff3..558d05d8 100644 --- a/scripts/MPI/3d_elastic_compliance_ALM.jl +++ b/scripts/MPI/3d_elastic_compliance_ALM.jl @@ -81,7 +81,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} @@ -107,7 +107,7 @@ function main(mesh_partition,distribute,el_size) ) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl index c103beab..6cd67d04 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl @@ -83,7 +83,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} @@ -110,7 +110,7 @@ function main(mesh_partition,distribute,el_size) ) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl index 1a9fe02e..8ad44dc4 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl @@ -97,7 +97,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} @@ -124,7 +124,7 @@ function main(mesh_partition,distribute,el_size) ) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/MPI/3d_inverse_homenisation_ALM.jl b/scripts/MPI/3d_inverse_homenisation_ALM.jl index 2fed57d8..1746a942 100644 --- a/scripts/MPI/3d_inverse_homenisation_ALM.jl +++ b/scripts/MPI/3d_inverse_homenisation_ALM.jl @@ -85,7 +85,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} @@ -111,7 +111,7 @@ function main(mesh_partition,distribute,el_size) ) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))] diff --git a/scripts/MPI/3d_inverter_ALM.jl b/scripts/MPI/3d_inverter_ALM.jl index 5d270952..4fa6ee26 100644 --- a/scripts/MPI/3d_inverter_ALM.jl +++ b/scripts/MPI/3d_inverter_ALM.jl @@ -99,7 +99,7 @@ function main(mesh_partition,distribute,el_size) UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} @@ -125,7 +125,7 @@ function main(mesh_partition,distribute,el_size) ) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol,:UΓ_out]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/MPI/3d_inverter_HPM.jl b/scripts/MPI/3d_inverter_HPM.jl index f1684cf0..3aacbfe1 100644 --- a/scripts/MPI/3d_inverter_HPM.jl +++ b/scripts/MPI/3d_inverter_HPM.jl @@ -99,7 +99,7 @@ function main(mesh_partition,distribute,el_size) UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} @@ -126,7 +126,7 @@ function main(mesh_partition,distribute,el_size) ## Optimiser ls_enabled=false # Setting to true will use a line search instead of oscillation detection - optimiser = HilbertianProjection(pcfs,stencil,vel_ext,φh;γ,γ_reinit,ls_enabled,α_min=0.7, + optimiser = HilbertianProjection(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,ls_enabled,α_min=0.7, ls_γ_max=0.05,verbose=i_am_main(ranks),constraint_names=[:Vol,:UΓ_out]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl index 126309d5..e3bbfde2 100644 --- a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl @@ -85,7 +85,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} @@ -113,7 +113,7 @@ function main(mesh_partition,distribute,el_size) ) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/MPI/3d_thermal_compliance_ALM.jl b/scripts/MPI/3d_thermal_compliance_ALM.jl index e0cea609..2c63d3e0 100644 --- a/scripts/MPI/3d_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_thermal_compliance_ALM.jl @@ -81,7 +81,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} @@ -107,7 +107,7 @@ function main(mesh_partition,distribute,el_size) ) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/MPI/elastic_compliance_ALM.jl b/scripts/MPI/elastic_compliance_ALM.jl index 6fa7a17c..76a48e2b 100644 --- a/scripts/MPI/elastic_compliance_ALM.jl +++ b/scripts/MPI/elastic_compliance_ALM.jl @@ -74,7 +74,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} @@ -98,7 +98,7 @@ function main(mesh_partition,distribute,el_size) ls=PETScLinearSolver()) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/MPI/inverse_homenisation_ALM.jl b/scripts/MPI/inverse_homenisation_ALM.jl index ec4d8886..55fe3af0 100644 --- a/scripts/MPI/inverse_homenisation_ALM.jl +++ b/scripts/MPI/inverse_homenisation_ALM.jl @@ -73,7 +73,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} @@ -99,7 +99,7 @@ function main(mesh_partition,distribute,el_size) ) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))] diff --git a/scripts/MPI/thermal_compliance_ALM.jl b/scripts/MPI/thermal_compliance_ALM.jl index bce212f1..db881e3e 100644 --- a/scripts/MPI/thermal_compliance_ALM.jl +++ b/scripts/MPI/thermal_compliance_ALM.jl @@ -72,7 +72,7 @@ function main(mesh_partition,distribute) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) @@ -84,7 +84,7 @@ function main(mesh_partition,distribute) vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/MPI/thermal_compliance_ALM_PETSc.jl b/scripts/MPI/thermal_compliance_ALM_PETSc.jl index cfe2acd6..366f13ef 100644 --- a/scripts/MPI/thermal_compliance_ALM_PETSc.jl +++ b/scripts/MPI/thermal_compliance_ALM_PETSc.jl @@ -72,7 +72,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} @@ -98,7 +98,7 @@ function main(mesh_partition,distribute,el_size) ) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks),constraint_names=[:Vol]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/Serial/elastic_compliance_ALM.jl b/scripts/Serial/elastic_compliance_ALM.jl index 7cd20e1a..6b8e4d17 100644 --- a/scripts/Serial/elastic_compliance_ALM.jl +++ b/scripts/Serial/elastic_compliance_ALM.jl @@ -71,7 +71,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) @@ -83,7 +83,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/Serial/elastic_compliance_HPM.jl b/scripts/Serial/elastic_compliance_HPM.jl index 50964928..d13be2c1 100644 --- a/scripts/Serial/elastic_compliance_HPM.jl +++ b/scripts/Serial/elastic_compliance_HPM.jl @@ -72,7 +72,7 @@ function main() dVol = (q,u,φ,dΩ,dΓ_N) -> ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) @@ -84,7 +84,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - optimiser = HilbertianProjection(pcfs,stencil,vel_ext,φh; + optimiser = HilbertianProjection(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/Serial/elastic_compliance_LM.jl b/scripts/Serial/elastic_compliance_LM.jl index 0517ef1b..3accdfac 100644 --- a/scripts/Serial/elastic_compliance_LM.jl +++ b/scripts/Serial/elastic_compliance_LM.jl @@ -68,7 +68,7 @@ function main() dJ = (q,u,φ,dΩ,dΓ_N) -> ∫((- ξ + C ⊙ ε(u) ⊙ ε(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) @@ -80,7 +80,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true) + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) diff --git a/scripts/Serial/hyperelastic_compliance_ALM.jl b/scripts/Serial/hyperelastic_compliance_ALM.jl index c455de7b..63b9e1bf 100644 --- a/scripts/Serial/hyperelastic_compliance_ALM.jl +++ b/scripts/Serial/hyperelastic_compliance_ALM.jl @@ -71,7 +71,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = NonlinearFEStateMap(res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) @@ -83,7 +83,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl b/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl index 03ea9f55..72738c4e 100644 --- a/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl @@ -85,7 +85,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = NonlinearFEStateMap(res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) @@ -97,7 +97,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/Serial/inverse_homenisation_ALM.jl b/scripts/Serial/inverse_homenisation_ALM.jl index c079c08c..0ffdd411 100644 --- a/scripts/Serial/inverse_homenisation_ALM.jl +++ b/scripts/Serial/inverse_homenisation_ALM.jl @@ -71,7 +71,7 @@ function main() dVol(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = RepeatingAffineFEStateMap(3,a,l,U,V,V_φ,U_reg,φh,dΩ) @@ -83,7 +83,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))] diff --git a/scripts/Serial/inverter_ALM.jl b/scripts/Serial/inverter_ALM.jl index 2774a9ea..132a32e3 100644 --- a/scripts/Serial/inverter_ALM.jl +++ b/scripts/Serial/inverter_ALM.jl @@ -86,7 +86,7 @@ function main() UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out) @@ -98,7 +98,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol,:UΓ_out]) for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/Serial/inverter_HPM.jl b/scripts/Serial/inverter_HPM.jl index f2587eec..39ed22a0 100644 --- a/scripts/Serial/inverter_HPM.jl +++ b/scripts/Serial/inverter_HPM.jl @@ -87,7 +87,7 @@ function main() UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out) @@ -100,7 +100,7 @@ function main() ## Optimiser ls_enabled=false # Setting to true will use a line search instead of oscillation detection - optimiser = HilbertianProjection(pcfs,stencil,vel_ext,φh; + optimiser = HilbertianProjection(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,α_min=0.4,ls_enabled,verbose=true,constraint_names=[:Vol,:UΓ_out]) for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/Serial/nonlinear_thermal_compliance_ALM.jl b/scripts/Serial/nonlinear_thermal_compliance_ALM.jl index 51597244..621060a2 100644 --- a/scripts/Serial/nonlinear_thermal_compliance_ALM.jl +++ b/scripts/Serial/nonlinear_thermal_compliance_ALM.jl @@ -74,7 +74,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = NonlinearFEStateMap(res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) @@ -86,7 +86,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it, uh, φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/Serial/thermal_compliance_ALM.jl b/scripts/Serial/thermal_compliance_ALM.jl index 6ddf66cc..9cd0883e 100644 --- a/scripts/Serial/thermal_compliance_ALM.jl +++ b/scripts/Serial/thermal_compliance_ALM.jl @@ -72,7 +72,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) @@ -84,7 +84,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl b/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl index 0b076760..1cbc6344 100644 --- a/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl +++ b/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl @@ -78,7 +78,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) @@ -90,7 +90,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/_dev/3d_hyperelastic_compliance_ALM.jl b/scripts/_dev/3d_hyperelastic_compliance_ALM.jl index de79e6fc..ddc16243 100644 --- a/scripts/_dev/3d_hyperelastic_compliance_ALM.jl +++ b/scripts/_dev/3d_hyperelastic_compliance_ALM.jl @@ -153,7 +153,7 @@ function main_alt(mesh_partition,distribute,el_size,gz) res(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*((T ∘ ∇(u)) ⊙ ∇(v)))dΩ - ∫(g⋅v)dΓ_N ## Finite difference solver and level set function - # stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + # ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) # reinit!(stencil,φh,γ_reinit) ## Setup solver and FE operators diff --git a/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl index c903951a..d177d1da 100644 --- a/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl @@ -78,9 +78,9 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks)) # Solve for (it,uh,φh) in optimiser diff --git a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl index 6f463318..bef8a90d 100644 --- a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl @@ -92,9 +92,9 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks)) # Solve for (it,uh,φh) in optimiser diff --git a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl index 657b35c4..af7c2735 100644 --- a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl @@ -82,9 +82,9 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks)) # Solve for (it,uh,φh) in optimiser diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl index 75163cb0..d2e25582 100644 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -88,9 +88,9 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks)) # Solve for (it,uh,φh) in optimiser diff --git a/scripts/_dev/Paper_scripts/therm_comp_MPI.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI.jl index 8320ff76..902742bf 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_MPI.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_MPI.jl @@ -78,9 +78,9 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=i_am_main(ranks)) + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=i_am_main(ranks)) # Solve for (it,uh,φh) in optimiser data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl index 3cb4f8ba..5104e0d6 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl @@ -80,9 +80,9 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, verbose=i_am_main(ranks)) # Solve for (it,uh,φh) in optimiser diff --git a/scripts/_dev/Paper_scripts/therm_comp_serial.jl b/scripts/_dev/Paper_scripts/therm_comp_serial.jl index 9e7e2342..0b53164f 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_serial.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_serial.jl @@ -63,9 +63,9 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit, + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, verbose=true) # Solve for (it,uh,φh) in optimiser diff --git a/scripts/_dev/benchmark_tests/MPI_benchmark_test_2D_themal.jl b/scripts/_dev/benchmark_tests/MPI_benchmark_test_2D_themal.jl index 2d09b546..9a0c3e3f 100644 --- a/scripts/_dev/benchmark_tests/MPI_benchmark_test_2D_themal.jl +++ b/scripts/_dev/benchmark_tests/MPI_benchmark_test_2D_themal.jl @@ -62,7 +62,7 @@ function main(mesh_partition,el_size,ranks) dJ(q,u,φ,dΩ,dΓ_N) = ∫((-ξ+D*∇(u)⋅∇(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) reinit!(stencil,φh,γ_reinit) ## Setup solver and FE operators @@ -75,7 +75,7 @@ function main(mesh_partition,el_size,ranks) vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit) + return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit) end with_debug() do distribute diff --git a/scripts/_dev/benchmark_tests/MPI_benchmark_test_3D_themal.jl b/scripts/_dev/benchmark_tests/MPI_benchmark_test_3D_themal.jl index 5842ead6..b04bbac8 100644 --- a/scripts/_dev/benchmark_tests/MPI_benchmark_test_3D_themal.jl +++ b/scripts/_dev/benchmark_tests/MPI_benchmark_test_3D_themal.jl @@ -68,7 +68,7 @@ function main(mesh_partition,distribute,el_size) dJ(q,u,φ,dΩ,dΓ_N) = ∫((ξ-D*∇(u)⋅∇(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) reinit!(stencil,φh,γ_reinit) ## Setup solver and FE operators @@ -96,7 +96,7 @@ function main(mesh_partition,distribute,el_size) ## Optimiser make_dir(path;ranks=ranks) - return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit) + return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit) end with_mpi() do distribute diff --git a/scripts/_dev/benchmark_tests/serial_benchmark_test.jl b/scripts/_dev/benchmark_tests/serial_benchmark_test.jl index 0f8a784a..17eb71cf 100644 --- a/scripts/_dev/benchmark_tests/serial_benchmark_test.jl +++ b/scripts/_dev/benchmark_tests/serial_benchmark_test.jl @@ -56,7 +56,7 @@ function main() dJ(q,u,φ,dΩ,dΓ_N) = ∫((ξ-D*∇(u)⋅∇(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) reinit!(stencil,φh,γ_reinit) ## Setup solver and FE operators @@ -69,7 +69,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - return AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit) + return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit) end function main_benchmark() diff --git a/scripts/_dev/bug_issue_46/thermal_MPI.jl b/scripts/_dev/bug_issue_46/thermal_MPI.jl index 176e7b05..f318893d 100644 --- a/scripts/_dev/bug_issue_46/thermal_MPI.jl +++ b/scripts/_dev/bug_issue_46/thermal_MPI.jl @@ -68,9 +68,9 @@ function main(mesh_partition,distribute,use_l::Bool) vel_ext = VelocityExtension(a_hilb, U_reg, V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) # Solve for (it,uh,φh) in optimiser diff --git a/scripts/_dev/bug_issue_46/thermal_serial.jl b/scripts/_dev/bug_issue_46/thermal_serial.jl index b94a4d09..2d0e2017 100644 --- a/scripts/_dev/bug_issue_46/thermal_serial.jl +++ b/scripts/_dev/bug_issue_46/thermal_serial.jl @@ -67,9 +67,9 @@ function main(use_l::Bool) vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve for (it,uh,φh) in optimiser diff --git a/scripts/_dev/full_piezo_script.jl b/scripts/_dev/full_piezo_script.jl index 49dc507a..7ed4c1ab 100644 --- a/scripts/_dev/full_piezo_script.jl +++ b/scripts/_dev/full_piezo_script.jl @@ -92,7 +92,7 @@ function main(mesh_partition,distribute,el_size) dVol(q,u,φ,dΩ) = ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) reinit!(stencil,φh,γ_reinit) ## Setup solver and FE operators @@ -126,7 +126,7 @@ function main(mesh_partition,distribute,el_size) # ## Optimiser # make_dir(path;ranks=ranks) - # optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=i_am_main(ranks)) + # optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=i_am_main(ranks)) # for (it, uh, φh) in optimiser # write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) # write_history(path*"/history.txt",optimiser.history;ranks=ranks) diff --git a/scripts/_dev/inv_hom_block_assem_testing.jl b/scripts/_dev/inv_hom_block_assem_testing.jl index d8623a05..14d2b24a 100644 --- a/scripts/_dev/inv_hom_block_assem_testing.jl +++ b/scripts/_dev/inv_hom_block_assem_testing.jl @@ -74,7 +74,7 @@ Vol = (u,φ,dΩ) -> ∫(((ρ ∘ φ) - 0.5)/vol_D)dΩ; dVol = (q,u,φ,dΩ) -> ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function -stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol); +ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol); reinit!(stencil,φ,γ_reinit) ## Initialise op diff --git a/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl b/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl index d0317914..3c7e57a6 100644 --- a/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl +++ b/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl @@ -86,7 +86,7 @@ function main(mesh_partition,distribute,el_size,diag_assem::Bool) dVol = (q,u,φ,dΩ) -> ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,el_size./order,max_steps,tol) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,el_size./order,max_steps,tol) reinit!(stencil,φ,γ_reinit) ## Setup solver and FE operators @@ -130,7 +130,7 @@ function main(mesh_partition,distribute,el_size,diag_assem::Bool) ## Optimiser make_dir(path;ranks=ranks) - optimiser = AugmentedLagrangian(φ,pcfs,stencil,vel_ext,interp,el_size,γ,γ_reinit); + optimiser = AugmentedLagrangian(φ,pcfs,ls_evo,vel_ext,interp,el_size,γ,γ_reinit); for history in optimiser it,Ji,Ci,Li = last(history) λi = optimiser.λ; Λi = optimiser.Λ diff --git a/scripts/_dev/inv_hom_block_assem_testing_full_script.jl b/scripts/_dev/inv_hom_block_assem_testing_full_script.jl index 13da1a00..46d9baf3 100644 --- a/scripts/_dev/inv_hom_block_assem_testing_full_script.jl +++ b/scripts/_dev/inv_hom_block_assem_testing_full_script.jl @@ -77,7 +77,7 @@ function main(diag_block) dVol = (q,u,φ,dΩ) -> ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol) reinit!(stencil,φ,γ_reinit) ## Setup solver and FE operators @@ -109,7 +109,7 @@ function main(diag_block) ## Optimiser make_dir(path) - optimiser = AugmentedLagrangian(φ,pcfs,stencil,vel_ext,interp,el_size,γ,γ_reinit); + optimiser = AugmentedLagrangian(φ,pcfs,ls_evo,vel_ext,interp,el_size,γ,γ_reinit); for history in optimiser it,Ji,Ci,Li = last(history) λi = optimiser.λ; Λi = optimiser.Λ diff --git a/scripts/_dev/mem_leak.jl b/scripts/_dev/mem_leak.jl index 2865affb..278ec667 100644 --- a/scripts/_dev/mem_leak.jl +++ b/scripts/_dev/mem_leak.jl @@ -62,9 +62,9 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) +ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser -optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) +optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve for i = 1:10 LevelSetTopOpt.rrule(state_map,φh) diff --git a/scripts/_dev/nonlinear_adjoint_MWE.jl b/scripts/_dev/nonlinear_adjoint_MWE.jl index 082e78e0..df5fe18a 100644 --- a/scripts/_dev/nonlinear_adjoint_MWE.jl +++ b/scripts/_dev/nonlinear_adjoint_MWE.jl @@ -70,7 +70,7 @@ function main() J = (u,φ,dΩ,dΓ_N) -> ∫((I ∘ φ)*(D ∘ u)*∇(u)⋅∇(u) + ξ*(ρ ∘ φ))dΩ ## Finite difference solver and level set function - stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol) reinit!(stencil,φ,γ_reinit) ## Setup solver and FE operators diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation.jl index c9f05eca..91dbabaa 100644 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation.jl +++ b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation.jl @@ -61,9 +61,9 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) +ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser -optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) +optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve for (it,uh,φh) in optimiser data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d.jl index f6db4233..8218dabf 100644 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d.jl +++ b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d.jl @@ -63,9 +63,9 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) +ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser -optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) +optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve for (it,uh,φh) in optimiser data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc.jl index b41760df..10c1dacf 100644 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc.jl +++ b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc.jl @@ -77,9 +77,9 @@ function main() ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve for (it,uh,φh) in optimiser data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc_mpi.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc_mpi.jl index 7ea63770..1b88fd91 100644 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc_mpi.jl +++ b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc_mpi.jl @@ -78,9 +78,9 @@ function main(mesh_partition,distribute) ) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) - stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) # Solve for (it,uh,φh) in optimiser diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_nonlinear.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_nonlinear.jl index 69c03024..3642fb95 100644 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_nonlinear.jl +++ b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_nonlinear.jl @@ -59,9 +59,9 @@ a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) # Finite difference scheme scheme = FirstOrderStencil(length(el_size),Float64) -stencil = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) +ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) # Optimiser -optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) +optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Solve for (it,uh,φh) in optimiser data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] diff --git a/test/seq/ThermalComplianceALMTests.jl b/test/seq/ThermalComplianceALMTests.jl index 1d227f11..a5891838 100644 --- a/test/seq/ThermalComplianceALMTests.jl +++ b/test/seq/ThermalComplianceALMTests.jl @@ -71,7 +71,7 @@ function main() dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) @@ -83,7 +83,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh; + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) # Do a few iterations From 7603a8934548635565f36748b90e7f0a9d064564 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Wed, 10 Apr 2024 17:08:32 +1000 Subject: [PATCH 37/90] Undo Stencil naming --- docs/src/reference/levelsetevolution.md | 16 +++++----- .../HamiltonJacobiEvolution.jl | 14 ++++---- src/LevelSetEvolution/LevelSetEvolution.jl | 2 +- .../{SpatialStencil.jl => Stencil.jl} | 32 +++++++++---------- 4 files changed, 32 insertions(+), 32 deletions(-) rename src/LevelSetEvolution/{SpatialStencil.jl => Stencil.jl} (89%) diff --git a/docs/src/reference/levelsetevolution.md b/docs/src/reference/levelsetevolution.md index 3fd8ebf4..3f41a926 100644 --- a/docs/src/reference/levelsetevolution.md +++ b/docs/src/reference/levelsetevolution.md @@ -1,12 +1,12 @@ # LevelSetEvolution In LevelSetTopOpt, the level set is evolved and reinitialised using a `LevelSetEvolution` method. The most standard of these is the Hamilton-Jacobi evolution equation solved using a first order upwind finite difference scheme. A forward Euler in time method is provided below via `HamiltonJacobiEvolution <: LevelSetEvolution` along with an upwind finite difference stencil for the spatial discretisation via `FirstOrderStencil`. -This can be extended in several ways. For example, higher order spatial stencils can be implemented by extending the `SpatialStencil` interface below. In addition, more advanced ODE solvers could be implemented (e.g., Runge–Kutta methods) or entirely different level set evolution methods by extending the `LevelSetEvolution` interface below. +This can be extended in several ways. For example, higher order spatial stencils can be implemented by extending the `Stencil` interface below. In addition, more advanced ODE solvers could be implemented (e.g., Runge–Kutta methods) or entirely different level set evolution methods by extending the `LevelSetEvolution` interface below. ## `HamiltonJacobiEvolution` ```@docs LevelSetTopOpt.HamiltonJacobiEvolution -LevelSetTopOpt.HamiltonJacobiEvolution(stencil::LevelSetTopOpt.SpatialStencil,model,space,tol=1.e-3,max_steps=100,max_steps_reinit=2000) +LevelSetTopOpt.HamiltonJacobiEvolution(stencil::LevelSetTopOpt.Stencil,model,space,tol=1.e-3,max_steps=100,max_steps_reinit=2000) LevelSetTopOpt.evolve! LevelSetTopOpt.reinit! LevelSetTopOpt.get_dof_Δ(m::HamiltonJacobiEvolution) @@ -18,18 +18,18 @@ LevelSetTopOpt.get_dof_Δ(m::HamiltonJacobiEvolution) LevelSetTopOpt.FirstOrderStencil ``` -## Custom `SpatialStencil` +## Custom `Stencil` ```@docs -LevelSetTopOpt.SpatialStencil -LevelSetTopOpt.evolve!(::LevelSetTopOpt.SpatialStencil,φ,vel,Δt,Δx,isperiodic,caches) -LevelSetTopOpt.reinit!(::LevelSetTopOpt.SpatialStencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) -LevelSetTopOpt.allocate_caches(::LevelSetTopOpt.SpatialStencil,φ,vel) +LevelSetTopOpt.Stencil +LevelSetTopOpt.evolve!(::LevelSetTopOpt.Stencil,φ,vel,Δt,Δx,isperiodic,caches) +LevelSetTopOpt.reinit!(::LevelSetTopOpt.Stencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) +LevelSetTopOpt.allocate_caches(::LevelSetTopOpt.Stencil,φ,vel) LevelSetTopOpt.check_order ``` ## Custom `LevelSetEvolution` -To implement a custom level set evolution method, we can extend the methods below. For example, one could consider Reaction-Diffusion-based evolution of the level set function. This can be solved with a finite element method and so we can implement a new type that inherits from `LevelSetEvolution` independently of the `SpatialStencil` types. +To implement a custom level set evolution method, we can extend the methods below. For example, one could consider Reaction-Diffusion-based evolution of the level set function. This can be solved with a finite element method and so we can implement a new type that inherits from `LevelSetEvolution` independently of the `Stencil` types. ```@docs LevelSetTopOpt.LevelSetEvolution diff --git a/src/LevelSetEvolution/HamiltonJacobiEvolution.jl b/src/LevelSetEvolution/HamiltonJacobiEvolution.jl index f8052495..06dba88b 100644 --- a/src/LevelSetEvolution/HamiltonJacobiEvolution.jl +++ b/src/LevelSetEvolution/HamiltonJacobiEvolution.jl @@ -9,16 +9,16 @@ Based on the scheme by Osher and Fedkiw ([link](https://doi.org/10.1007/b98879)) # Parameters -- `stencil::SpatialStencil`: Spatial finite difference stencil for a single step HJ +- `stencil::Stencil`: Spatial finite difference stencil for a single step HJ equation and reinitialisation equation. - `model`: A `CartesianDiscreteModel`. - `space`: FE space for level-set function - `perm`: A permutation vector - `params`: Tuple of additional params -- `cache`: SpatialStencil cache +- `cache`: Stencil cache """ struct HamiltonJacobiEvolution{O} <: LevelSetEvolution - stencil :: SpatialStencil + stencil :: Stencil model space perm @@ -27,14 +27,14 @@ struct HamiltonJacobiEvolution{O} <: LevelSetEvolution end """ - HamiltonJacobiEvolution(stencil::SpatialStencil,model,space,tol,max_steps,max_steps_reinit) + HamiltonJacobiEvolution(stencil::Stencil,model,space,tol,max_steps,max_steps_reinit) Create an instance of `HamiltonJacobiEvolution` given a stencil, model, FE space, and additional optional arguments. This automatically creates the DoF permutation to handle high-order finite elements. """ function HamiltonJacobiEvolution( - stencil::SpatialStencil, + stencil::Stencil, model, space, tol=1.e-3, @@ -302,7 +302,7 @@ function PartitionedArrays.permute_indices(indices::LocalIndices,perm) return LocalIndices(n_glob,id,l2g,l2o) end -function allocate_caches(s::SpatialStencil,φ::Vector,vel::Vector,perm,order,ndofs) +function allocate_caches(s::Stencil,φ::Vector,vel::Vector,perm,order,ndofs) stencil_caches = allocate_caches(s,reshape(φ,ndofs),reshape(vel,ndofs)) φ_tmp = similar(φ) vel_tmp = similar(vel) @@ -310,7 +310,7 @@ function allocate_caches(s::SpatialStencil,φ::Vector,vel::Vector,perm,order,ndo return φ_tmp, vel_tmp, perm_caches, stencil_caches end -function allocate_caches(s::SpatialStencil,φ::PVector,vel::PVector,perm,order,local_ndofs) +function allocate_caches(s::Stencil,φ::PVector,vel::PVector,perm,order,local_ndofs) local_stencil_caches = map(local_views(φ),local_views(vel),local_views(local_ndofs)) do φ,vel,ndofs allocate_caches(s,reshape(φ,ndofs),reshape(vel,ndofs)) end diff --git a/src/LevelSetEvolution/LevelSetEvolution.jl b/src/LevelSetEvolution/LevelSetEvolution.jl index d6a743f4..6f9c4f32 100644 --- a/src/LevelSetEvolution/LevelSetEvolution.jl +++ b/src/LevelSetEvolution/LevelSetEvolution.jl @@ -35,5 +35,5 @@ function get_dof_Δ(::LevelSetEvolution) @abstractmethod end -include("SpatialStencil.jl") +include("Stencil.jl") include("HamiltonJacobiEvolution.jl") \ No newline at end of file diff --git a/src/LevelSetEvolution/SpatialStencil.jl b/src/LevelSetEvolution/Stencil.jl similarity index 89% rename from src/LevelSetEvolution/SpatialStencil.jl rename to src/LevelSetEvolution/Stencil.jl index f306442f..4b15e82e 100644 --- a/src/LevelSetEvolution/SpatialStencil.jl +++ b/src/LevelSetEvolution/Stencil.jl @@ -1,58 +1,58 @@ """ - abstract type SpatialStencil + abstract type Stencil -Spatial finite difference stencil for a single step of the Hamilton-Jacobi +Finite difference stencil for a single step of the Hamilton-Jacobi evolution equation and reinitialisation equation. Your own spatial stencil can be implemented by extending the methods below. """ -abstract type SpatialStencil end +abstract type Stencil end """ - allocate_caches(::SpatialStencil,φ,vel) + allocate_caches(::Stencil,φ,vel) -Allocate caches for a given `SpatialStencil`. +Allocate caches for a given `Stencil`. """ -function allocate_caches(::SpatialStencil,φ,vel) +function allocate_caches(::Stencil,φ,vel) nothing # By default, no caches are required. end """ - check_order(::SpatialStencil,order) + check_order(::Stencil,order) Throw error if insufficient reference element order to implement stencil in parallel. """ -function check_order(::SpatialStencil,order) +function check_order(::Stencil,order) @abstractmethod end """ - reinit!(::SpatialStencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) -> φ + reinit!(::Stencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) -> φ -Single finite difference step of the reinitialisation equation for a given `SpatialStencil`. +Single finite difference step of the reinitialisation equation for a given `Stencil`. """ -function reinit!(::SpatialStencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) +function reinit!(::Stencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) @abstractmethod end """ - evolve!(::SpatialStencil,φ,vel,Δt,Δx,isperiodic,caches) -> φ + evolve!(::Stencil,φ,vel,Δt,Δx,isperiodic,caches) -> φ Single finite difference step of the Hamilton-Jacobi evoluation equation for a given -`SpatialStencil`. +`Stencil`. """ -function evolve!(::SpatialStencil,φ,vel,Δt,Δx,isperiodic,caches) +function evolve!(::Stencil,φ,vel,Δt,Δx,isperiodic,caches) @abstractmethod end """ - struct FirstOrderStencil{D,T} <: SpatialStencil end + struct FirstOrderStencil{D,T} <: Stencil end A first order upwind difference scheme based on Osher and Fedkiw ([link](https://doi.org/10.1007/b98879)). """ -struct FirstOrderStencil{D,T} <: SpatialStencil +struct FirstOrderStencil{D,T} <: Stencil function FirstOrderStencil(D::Integer,::Type{T}) where T<:Real new{D,T}() end From 32f70e63a01b475935828fe4b5fb6e1db58aafa0 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 11 Apr 2024 08:55:16 +1000 Subject: [PATCH 38/90] Improvements to docs --- docs/src/getting-started.md | 5 ++++- docs/src/reference/io.md | 1 + docs/src/reference/optimisers.md | 4 ++++ 3 files changed, 9 insertions(+), 1 deletion(-) diff --git a/docs/src/getting-started.md b/docs/src/getting-started.md index 5b9eed32..485fb54f 100644 --- a/docs/src/getting-started.md +++ b/docs/src/getting-started.md @@ -32,8 +32,11 @@ In order to get familiar with the library we recommend following the numerical e > Zachary J. Wegert, Jordi M. Fuertes, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. +In addition, there are several driver scripts available in `/scripts/..` + More general tutorials for familiarising ones self with Gridap are available via the [Gridap Tutorials](https://gridap.github.io/Tutorials/dev/). ## Known issues - PETSc's GAMG preconditioner breaks for split Dirichlet DoFs (e.g., x constrained while y free for a single node). There is no simple fix for this. We recommend instead using MUMPS or another preconditioner for this case. -- Currently, our implementation of automatic differentiation does not support multiplication and division of optimisation functionals. We plan to add this in a future release of `LevelSetTopOpt.jl`. \ No newline at end of file +- Currently, our implementation of automatic differentiation does not support multiplication and division of optimisation functionals. We plan to add this in a future release of `LevelSetTopOpt.jl` -- Issue [#38](https://github.com/zjwegert/LSTO_Distributed/issues/38). +- Analytic gradient breaks in parallel for integrals of certain measures -- Issue [#46](https://github.com/zjwegert/LSTO_Distributed/issues/46) \ No newline at end of file diff --git a/docs/src/reference/io.md b/docs/src/reference/io.md index 5adc2248..e4c4ff89 100644 --- a/docs/src/reference/io.md +++ b/docs/src/reference/io.md @@ -1,4 +1,5 @@ # IO +In LevelSetTopOpt, the usual IO from [Gridap](https://github.com/gridap/Gridap.jl/) is available. In addition, we also implement the below IO for convenience. ## Optimiser history ```@docs diff --git a/docs/src/reference/optimisers.md b/docs/src/reference/optimisers.md index f886ccf2..647dea10 100644 --- a/docs/src/reference/optimisers.md +++ b/docs/src/reference/optimisers.md @@ -1,5 +1,9 @@ # Optimisers +In LevelSetTopOpt we implement optimisation algorithms as [iterators](https://docs.julialang.org/en/v1/manual/interfaces/) that inherit from an abstract type `Optimiser`. A concrete `Optimiser` implementation, say `OptEg`, then implements `iterate(m::OptEg) ↦ (var,state)` and `iterate(m::OptEg,state) ↦ (var,state)`, where `var` and `state` are the available items in the outer loop and internal state of the iterator, respectively. As a result we can iterate over the object `m=OptEg(...)` using `for var in m`. The benefit of this implementation is that the internals of the optimisation method can be hidden in the source code while the explicit `for` loop is still visible to the user. The body of the loop can then be used for auxiliary operations such as writing the optimiser history and other files. + +The below describes the implemented optimisers along with the `OptimiserHistory` type. Custom optimisers can be implemented by creating types that inherit from `Optimiser` and extending the interfaces in [Custom optimiser](@ref). + ## Lagrangian & Augmented Lagrangian method ```@autodocs Modules = [LevelSetTopOpt] From dd2ca0e58dca545eb2158bcf4a10a5c2da412571 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 11 Apr 2024 09:02:27 +1000 Subject: [PATCH 39/90] Adjust for consistency --- scripts/_dev/Paper_scripts/therm_comp_serial.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/_dev/Paper_scripts/therm_comp_serial.jl b/scripts/_dev/Paper_scripts/therm_comp_serial.jl index 78cd651c..b80a31c4 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_serial.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_serial.jl @@ -3,7 +3,7 @@ using LevelSetTopOpt, Gridap function main() # FE parameters order = 1 # Finite element order - xmax = ymax = 1.0 # Domain size + xmax,ymax = (1.0,1.0) # Domain size dom = (0,xmax,0,ymax) # Bounding domain el_size = (200,200) # Mesh partition size prop_Γ_N = 0.2 # Γ_N size parameter From 5e84e209125846baee32e79cfcf8fc72485fb716 Mon Sep 17 00:00:00 2001 From: Z J Wegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 11 Apr 2024 09:10:59 +1000 Subject: [PATCH 40/90] Create LICENSE --- LICENSE | 21 +++++++++++++++++++++ 1 file changed, 21 insertions(+) create mode 100644 LICENSE diff --git a/LICENSE b/LICENSE new file mode 100644 index 00000000..9772d89f --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2024 [Zachary Wegert](mailto:zach.wegert@hdr.qut.edu.au), [Jordi Fuertes](mailto:jordi.manyer@monash.edu), [Connor Mallon](mailto:connor.mallon@monash.edu), [Santiago Badia](mailto:santiago.badia@monash.edu) and [Vivien Challis](mailto:vivien.challis@qut.edu.au) + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. From 8c79b884ff0e846f307f7819dbc4e1ae84b5f081 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Thu, 11 Apr 2024 09:12:06 +1000 Subject: [PATCH 41/90] Missing .md --- LICENSE => LICENSE.md | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename LICENSE => LICENSE.md (100%) diff --git a/LICENSE b/LICENSE.md similarity index 100% rename from LICENSE rename to LICENSE.md From 7e4a0e87d93e2401839abeb5832c48a48f92023d Mon Sep 17 00:00:00 2001 From: JordiManyer Date: Thu, 11 Apr 2024 17:33:08 +1000 Subject: [PATCH 42/90] Bugfix: Distributed RepeatingAffineFEStateMaps --- Project.toml | 1 + scripts/MPI/inverse_homenisation_ALM.jl | 6 +++--- src/ChainRules.jl | 3 ++- src/GridapExtensions.jl | 17 +++++++++++++++-- src/LevelSetTopOpt.jl | 1 + 5 files changed, 22 insertions(+), 6 deletions(-) diff --git a/Project.toml b/Project.toml index 5bb5edb6..8e0627a6 100755 --- a/Project.toml +++ b/Project.toml @@ -13,6 +13,7 @@ DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab" FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b" Gridap = "56d4f2e9-7ea1-5844-9cf6-b9c51ca7ce8e" GridapDistributed = "f9701e48-63b3-45aa-9a63-9bc6c271f355" +GridapP4est = "c2c8e14b-f5fd-423d-9666-1dd9ad120af9" GridapPETSc = "bcdc36c2-0c3e-11ea-095a-c9dadae499f1" GridapSolvers = "6d3209ee-5e3c-4db7-a716-942eb12ed534" JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819" diff --git a/scripts/MPI/inverse_homenisation_ALM.jl b/scripts/MPI/inverse_homenisation_ALM.jl index 7a068021..b5f52841 100644 --- a/scripts/MPI/inverse_homenisation_ALM.jl +++ b/scripts/MPI/inverse_homenisation_ALM.jl @@ -21,14 +21,14 @@ function main(mesh_partition,distribute,el_size) γ = 0.05 γ_reinit = 0.5 max_steps = floor(Int,order*minimum(el_size)/10) - tol = 1/(5order^2)/minimum(el_size) + tol = 1/(5*order^2)/minimum(el_size) C = isotropic_elast_tensor(2,1.,0.3) η_coeff = 2 - α_coeff = 4max_steps*γ + α_coeff = 4*max_steps*γ vf = 0.5 path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM_MPI/" iter_mod = 10 - i_am_main(ranks) && mkdir(path) + #i_am_main(ranks) && mkdir(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true)); diff --git a/src/ChainRules.jl b/src/ChainRules.jl index f201a9c5..5ecc930d 100644 --- a/src/ChainRules.jl +++ b/src/ChainRules.jl @@ -714,7 +714,8 @@ struct RepeatingAffineFEStateMap{A,B,C,D,E,F,G} <: AbstractFEStateMap U, V = repeat_spaces(nblocks,U0,V0) spaces = (U,V,V_φ,U_reg) assem_U = SparseMatrixAssembler( - get_matrix_type(assem_U0),get_vector_type(assem_U0),U,V,FESpaces.get_assembly_strategy(assem_U0) + get_local_matrix_type(assem_U0), get_local_vector_type(assem_U0), + U, V, get_assembly_strategy(assem_U0) ) ## Pullback cache diff --git a/src/GridapExtensions.jl b/src/GridapExtensions.jl index f209d0f7..51b5d1e8 100644 --- a/src/GridapExtensions.jl +++ b/src/GridapExtensions.jl @@ -59,7 +59,7 @@ function assemble_adjoint_matrix!(f::Function,A::AbstractMatrix,a::Assembler,U:: end # Assembly addons - +""" function Gridap.FESpaces.allocate_matrix(a::Function,assem::Assembler,U::FESpace,V::FESpace) v = get_fe_basis(V) u = get_trial_fe_basis(U) @@ -77,6 +77,18 @@ function Gridap.FESpaces.assemble_matrix_and_vector!( u = get_trial_fe_basis(U) assemble_matrix_and_vector!(A,b,assem,collect_cell_matrix_and_vector(U,V,a(u,v),l(v),uhd)) end +""" + +get_local_matrix_type(a::Assembler) = get_matrix_type(a) +get_local_vector_type(a::Assembler) = get_vector_type(a) + +function get_local_matrix_type(a::GridapDistributed.DistributedSparseMatrixAssembler) + return getany(map(get_matrix_type,a.assems)) +end + +function get_local_vector_type(a::GridapDistributed.DistributedSparseMatrixAssembler) + return getany(map(get_vector_type,a.assems)) +end # PETScNonlinearSolver override @@ -88,8 +100,9 @@ function Gridap.Algebra.solve!(x::T,nls::PETScNonlinearSolver,op::Gridap.Algebra end # Stuff from ODE refactor - +""" function (+)(a::Gridap.CellData.DomainContribution,b::GridapDistributed.DistributedDomainContribution) @assert iszero(Gridap.CellData.num_domains(a)) return b end +""" \ No newline at end of file diff --git a/src/LevelSetTopOpt.jl b/src/LevelSetTopOpt.jl index 7b6ebc4d..51292647 100644 --- a/src/LevelSetTopOpt.jl +++ b/src/LevelSetTopOpt.jl @@ -15,6 +15,7 @@ using Gridap.Helpers, Gridap.Algebra, Gridap.TensorValues using Gridap.Geometry, Gridap.CellData, Gridap.Fields using Gridap.ReferenceFEs, Gridap.FESpaces, Gridap.MultiField using Gridap.Geometry: get_faces +using Gridap.FESpaces: get_assembly_strategy using Gridap: writevtk using GridapDistributed From 681bea89a81bc2704319729872856a21b85a18d8 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Fri, 12 Apr 2024 10:15:33 +1000 Subject: [PATCH 43/90] Typo in inverter script for paper --- scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl index b9f3269c..8f965df8 100644 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -61,7 +61,7 @@ function main(mesh_partition,distribute) Tv = Vector{PetscScalar} solver = ElasticitySolver(V) state_map = AffineFEStateMap( - a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; + a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), @@ -73,8 +73,8 @@ function main(mesh_partition,distribute) vol_Γ_out = sum(∫(1)dΓ_out) vol_D = sum(∫(1)dΩ) J(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅e₁)/vol_Γ_in)dΓ_in - C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + C1(u,φ,dΩ,dΓ_in,dΓ_out) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_in,dΓ_out) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ C2(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out pcfs = PDEConstrainedFunctionals(J,[C1,C2],state_map, analytic_dJ=dJ,analytic_dC=[dC1,nothing]) From 11ebdc23607f0725f0439b5a9ca8b543eabaaed3 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Fri, 12 Apr 2024 10:31:52 +1000 Subject: [PATCH 44/90] Missing NewtonSolver import --- scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl | 2 ++ 1 file changed, 2 insertions(+) diff --git a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl index 5b4730c5..fe74df74 100644 --- a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl @@ -1,6 +1,8 @@ using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, SparseMatricesCSR +using GridapSolvers: NewtonSolver + function main(mesh_partition,distribute) ranks = distribute(LinearIndices((prod(mesh_partition),))) # FE parameters From 537301909b24306a9f0eda5cfbb483f610f89709 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Fri, 12 Apr 2024 10:53:54 +1000 Subject: [PATCH 45/90] Missing --- scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 1 + 1 file changed, 1 insertion(+) diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl index 8f965df8..a04b319f 100644 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -22,6 +22,7 @@ function main(mesh_partition,distribute) # Problem parameters C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor g = VectorValue(0,0,-1) # Applied load on Γ_N + ks = 0.01 # Artificial spring stiffness vf = 0.4 # Volume fraction constraint sphere(x,(xc,yc,zc)) = -sqrt((x[1]-xc)^2+(x[2]-yc)^2+(x[3]-zc)^2) + 0.2 lsf_func(x) = max(initial_lsf(4,0.2)(x), # Initial level set function From c5838c9e80e8f9bc8b7e56a3808b344d26841f44 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Mon, 15 Apr 2024 14:56:16 +1000 Subject: [PATCH 46/90] Name corrections + remove TODO + 2d pz dev script --- LICENSE.md | 2 +- README.md | 2 +- docs/src/getting-started.md | 2 +- docs/src/index.md | 2 +- scripts/_dev/full_piezo_script_2d.jl | 246 +++++++++++++++++++++++++++ src/ChainRules.jl | 2 +- 6 files changed, 251 insertions(+), 5 deletions(-) create mode 100644 scripts/_dev/full_piezo_script_2d.jl diff --git a/LICENSE.md b/LICENSE.md index 9772d89f..1dbccfec 100644 --- a/LICENSE.md +++ b/LICENSE.md @@ -1,6 +1,6 @@ MIT License -Copyright (c) 2024 [Zachary Wegert](mailto:zach.wegert@hdr.qut.edu.au), [Jordi Fuertes](mailto:jordi.manyer@monash.edu), [Connor Mallon](mailto:connor.mallon@monash.edu), [Santiago Badia](mailto:santiago.badia@monash.edu) and [Vivien Challis](mailto:vivien.challis@qut.edu.au) +Copyright (c) 2024 [Zachary Wegert](mailto:zach.wegert@hdr.qut.edu.au), [Jordi Manyer](mailto:jordi.manyer@monash.edu), [Connor Mallon](mailto:connor.mallon@monash.edu), [Santiago Badia](mailto:santiago.badia@monash.edu) and [Vivien Challis](mailto:vivien.challis@qut.edu.au) Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal diff --git a/README.md b/README.md index 1ce80170..8fa50d55 100755 --- a/README.md +++ b/README.md @@ -4,7 +4,7 @@ LevelSetTopOpt is computational toolbox for level set-based topology optimisation implemented in Julia and the [Gridap](https://github.com/gridap/Gridap.jl) package ecosystem. See the documentation and following publication for further details: -> Zachary J. Wegert, Jordi M. Fuertes, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. +> Zachary J. Wegert, Jordi Manyer, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. ## Documentation diff --git a/docs/src/getting-started.md b/docs/src/getting-started.md index 485fb54f..80775cda 100644 --- a/docs/src/getting-started.md +++ b/docs/src/getting-started.md @@ -30,7 +30,7 @@ For more advanced installations, such as use of a custom MPI/PETSc installation ## Usage and tutorials In order to get familiar with the library we recommend following the numerical examples described in: -> Zachary J. Wegert, Jordi M. Fuertes, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. +> Zachary J. Wegert, Jordi Manyer, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. In addition, there are several driver scripts available in `/scripts/..` diff --git a/docs/src/index.md b/docs/src/index.md index 2a9769a0..e3b8ed44 100644 --- a/docs/src/index.md +++ b/docs/src/index.md @@ -4,7 +4,7 @@ Welcome to the documentation for `LevelSetTopOpt.jl`! ## Introduction `LevelSetTopOpt.jl` is computational toolbox for level set-based topology optimisation implemented in Julia and the Gridap package ecosystem. The core design principle of `LevelSetTopOpt.jl` is to provide an extendable framework for solving optimisation problems in serial or parallel with a high-level programming interface and automatic differentiation. See the following publication for further details: -> Zachary J. Wegert, Jordi M. Fuertes, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. +> Zachary J. Wegert, Jordi Manyer, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. ## How to use this documentation diff --git a/scripts/_dev/full_piezo_script_2d.jl b/scripts/_dev/full_piezo_script_2d.jl new file mode 100644 index 00000000..f56e65fa --- /dev/null +++ b/scripts/_dev/full_piezo_script_2d.jl @@ -0,0 +1,246 @@ +using LevelSetTopOpt, Gridap + +using Gridap, Gridap.TensorValues, Gridap.Geometry, Gridap.FESpaces, Gridap.Helpers, Gridap.Algebra +using GridapDistributed +using GridapPETSc +using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code +using PartitionedArrays +using SparseMatricesCSR +using ChainRulesCore + +using GridapSolvers +using Gridap.MultiField + +## Piezo helpers +function PZT5A(D::Int) + ε_0 = 8.854e-12; + if D == 3 + C_Voigt = [12.0400e10 7.52000e10 7.51000e10 0.0 0.0 0.0 + 7.52000e10 12.0400e10 7.51000e10 0.0 0.0 0.0 + 7.51000e10 7.51000e10 11.0900e10 0.0 0.0 0.0 + 0.0 0.0 0.0 2.1000e10 0.0 0.0 + 0.0 0.0 0.0 0.0 2.1000e10 0.0 + 0.0 0.0 0.0 0.0 0.0 2.30e10] + e_Voigt = [0.0 0.0 0.0 0.0 12.30000 0.0 + 0.0 0.0 0.0 12.30000 0.0 0.0 + -5.40000 -5.40000 15.80000 0.0 0.0 0.0] + K_Voigt = [540*ε_0 0 0 + 0 540*ε_0 0 + 0 0 830*ε_0] + elseif D == 2 + C_Voigt = [12.0400e10 7.51000e10 0.0 + 7.51000e10 11.0900e10 0.0 + 0.0 0.0 2.1000e10] + e_Voigt = [0.0 0.0 12.30000 + -5.40000 15.80000 0.0] + K_Voigt = [540*ε_0 0 + 0 830*ε_0] + else + @notimplemented + end + C = voigt2tensor4(C_Voigt) + e = voigt2tensor3(e_Voigt) + κ = voigt2tensor2(K_Voigt) + C,e,κ +end + +""" + Given a material constant given in Voigt notation, + return a SymFourthOrderTensorValue using ordering from Gridap +""" +function voigt2tensor4(A::Array{M,2}) where M + if isequal(size(A),(3,3)) + return SymFourthOrderTensorValue(A[1,1], A[3,1], A[2,1], + A[1,3], A[3,3], A[2,3], + A[1,2], A[3,2], A[2,2]) + elseif isequal(size(A),(6,6)) + return SymFourthOrderTensorValue(A[1,1], A[6,1], A[5,1], A[2,1], A[4,1], A[3,1], + A[1,6], A[6,6], A[5,6], A[2,6], A[4,6], A[3,6], + A[1,5], A[6,5], A[5,5], A[2,5], A[4,5], A[3,5], + A[1,2], A[6,2], A[5,2], A[2,2], A[4,2], A[3,2], + A[1,4], A[6,4], A[5,4], A[2,4], A[4,4], A[3,4], + A[1,3], A[6,3], A[5,3], A[2,3], A[4,3], A[3,3]) + else + @notimplemented + end +end + +""" + Given a material constant given in Voigt notation, + return a ThirdOrderTensorValue using ordering from Gridap +""" +function voigt2tensor3(A::Array{M,2}) where M + if isequal(size(A),(2,3)) + return ThirdOrderTensorValue(A[1,1], A[2,1], A[1,3], A[2,3], A[1,3], A[2,3], A[1,2], A[2,2]) + elseif isequal(size(A),(3,6)) + return ThirdOrderTensorValue( + A[1,1], A[2,1], A[3,1], A[1,6], A[2,6], A[3,6], A[1,5], A[2,5], A[3,5], + A[1,6], A[2,6], A[3,6], A[1,2], A[2,2], A[3,2], A[1,4], A[2,4], A[3,4], + A[1,5], A[2,5], A[3,5], A[1,4], A[2,4], A[3,4], A[1,3], A[2,3], A[3,3]) + else + @notimplemented + end +end + +""" + Given a material constant given in Voigt notation, + return a SymTensorValue using ordering from Gridap +""" +function voigt2tensor2(A::Array{M,2}) where M + return TensorValue(A) +end + +## Parameters +el_size = (100,100) +order = 1 +xmax,ymax=(1.0,1.0) +dom = (0,xmax,0,ymax) +γ = 0.1 +γ_reinit = 0.5 +max_steps = floor(Int,order*minimum(el_size)/10) +tol = 1/(5order^2)/minimum(el_size) +η_coeff = 2 +α_coeff = 4*max_steps*γ +vf = 0.5 +path = dirname(dirname(@__DIR__))*"/results/2d_PZ_inverse_homenisation_ALM" + +## FE Setup +model = CartesianDiscreteModel(dom,el_size,isperiodic=(true,true)) +el_Δ = get_el_Δ(model) +f_Γ_D(x) = iszero(x) +update_labels!(1,model,f_Γ_D,"origin") + +## Triangulations and measures +Ω = Triangulation(model) +dΩ = Measure(Ω,2*order) +vol_D = sum(∫(1)dΩ) + +## Spaces +reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) +reffe_scalar = ReferenceFE(lagrangian,Float64,order) +V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["origin"]) +U = TrialFESpace(V,VectorValue(0.0,0.0)) +Q = TestFESpace(model,reffe_scalar;conformity=:H1,dirichlet_tags=["origin"]) +P = TrialFESpace(Q,0) +# mfs = BlockMultiFieldStyle() +UP = MultiFieldFESpace([U,P])#;style=mfs) +VQ = MultiFieldFESpace([V,Q])#;style=mfs) + +V_φ = TestFESpace(model,reffe_scalar) +V_reg = TestFESpace(model,reffe_scalar) +U_reg = TrialFESpace(V_reg) + +## Create FE functions +φh = interpolate(initial_lsf(4,0.2),V_φ) + +## Interpolation and weak form +interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ))#,ϵ=10^-9) +I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + +## Material tensors +C, e, κ = PZT5A(2); +k0 = norm(C.data,Inf); +α0 = norm(e.data,Inf); +β0 = norm(κ.data,Inf); +γ = β0*k0/α0^2; + +## Weak forms +εᴹ = (SymTensorValue(1.0,0.0,0.0), + SymTensorValue(0.0,0.0,1.0), + SymTensorValue(0.0,1/2,0)) +Eⁱ = (VectorValue(1.0,0.0,), + VectorValue(0.0,1.0)) + +a((u,ϕ),(v,q),φ,dΩ) = ∫((I ∘ φ) * (1/k0*((C ⊙ ε(u)) ⊙ ε(v)) - + 1/α0*((-∇(ϕ) ⋅ e) ⊙ ε(v)) + + -1/α0*((e ⋅² ε(u)) ⋅ -∇(q)) + + -γ/β0*((κ ⋅ -∇(ϕ)) ⋅ -∇(q))) )dΩ; + +l_ε = [((v,q),φ,dΩ) -> ∫(((I ∘ φ) * (-C ⊙ εᴹ[i] ⊙ ε(v) + k0/α0*(e ⋅² εᴹ[i]) ⋅ -∇(q))))dΩ for i = 1:3]; +l_E = [((v,q),φ,dΩ) -> ∫((I ∘ φ) * ((Eⁱ[i] ⋅ e ⊙ ε(v) + k0/α0*(κ ⋅ Eⁱ[i]) ⋅ -∇(q))))dΩ for i = 1:2]; +l = [l_ε; l_E] + +state_map = RepeatingAffineFEStateMap(5,a,l,UP,VQ,V_φ,U_reg,φh,dΩ) + +x = state_map(φh) +U = LevelSetTopOpt.get_trial_space(state_map) +xh = FEFunction(U,x) +# u1,ϕ1,u2,ϕ2,u3,ϕ3,u4,ϕ4,u5,ϕ5 = xh + + +function Cᴴ(r,s,uϕ,φ,dΩ) # (normalised by 1/k0) + u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] + ∫(1/k0 * (I ∘ φ) * (((C ⊙ (1/k0*ε(u_s) + εᴹ[s])) ⊙ εᴹ[r]) + ((1/α0*∇(ϕ_s) ⋅ e) ⊙ εᴹ[r])))dΩ; +end + +function eᴴ(i,s,uϕ,φ,dΩ) # (normalised by 1/α0) + u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] + ∫(1/α0 * (I ∘ φ) * (((e ⋅² (1/k0*ε(u_s) + εᴹ[s])) ⋅ Eⁱ[i]) + ((κ ⋅ (-1/α0*∇(ϕ_s))) ⋅ Eⁱ[i])))dΩ; +end + +function κᴴ(i,j,uϕ,φ,dΩ) # (normalised by 1/β0) + u_j = uϕ[6+2j-1]; ϕ_j = uϕ[6+2j] + ∫(1/β0 * (I ∘ φ) * (((e ⋅² (1/k0*ε(u_j)) ⋅ Eⁱ[i]) + ((κ ⋅ (-1/α0*∇(ϕ_j) + Eⁱ[j])) ⋅ Eⁱ[i]))))dΩ; +end + +function dᴴ(uϕ,φ,dΩ) + _Cᴴ(r,s) = sum(Cᴴ(r,s,uϕ,φ,dΩ)) + _eᴴ(i,s) = sum(eᴴ(i,s,uϕ,φ,dΩ)) + (_Cᴴ(2,2)*_eᴴ(2,1) + _Cᴴ(1,1)*_eᴴ(2,2) - _Cᴴ(2,1)*(_eᴴ(2,1) + _eᴴ(2,2)))/ + (_Cᴴ(1,1)*_Cᴴ(2,2) - _Cᴴ(2,1)^2) +end + +# map(rs->sum(Cᴴ(rs[1],rs[2],xh,φh,dΩ)), CartesianIndices((1:3, 1:3))) +# map(is->sum(eᴴ(is[1],is[2],xh,φh,dΩ)), CartesianIndices((1:2, 1:3))) +# map(ij->sum(κᴴ(ij[1],ij[2],xh,φh,dΩ)), CartesianIndices((1:2, 1:2))) +dᴴ(xh,φh,dΩ)#*α0/k0 + +C_mat = map(rs->sum(Cᴴ(rs[1],rs[2],xh,φh,dΩ)), CartesianIndices((1:3, 1:3))) +e_mat = map(is->sum(eᴴ(is[1],is[2],xh,φh,dΩ)), CartesianIndices((1:2, 1:3))) +d_mat = e_mat*inv(C_mat); +dh = d_mat[2,1] + d_mat[2,2] + +nothing +# ## Optimisation functionals +# J((u, p),φ,dΩ) = ∫(0)dΩ +# dJ(q,(u, p),φ,dΩ) = ∫(0q)dΩ +# Vol((u, p),φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; +# dVol(q,(u, p),φ,dΩ) = ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + +# ## Finite difference solver and level set function +# stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + +# ## Setup solver and FE operators +# state_map = RepeatingAffineFEStateMap(5,a,l,UP,VQ,V_φ,U_reg,φh,dΩ) +# pcfs = PDEConstrainedFunctionals(J,[Vol],state_map;analytic_dJ=dJ,analytic_dC=[dVol]) + +# evaluate!(pcfs,φh) + +# ## Hilbertian extension-regularisation problems +# α = α_coeff*maximum(el_Δ) +# a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; +# vel_ext = VelocityExtension( +# a_hilb,U_reg,V_reg, +# assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), +# ls = PETScLinearSolver() +# ) + +# ## Optimiser +# make_dir(path;ranks=ranks) +# optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=i_am_main(ranks)) +# for (it, uh, φh) in optimiser +# write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) +# write_history(path*"/history.txt",optimiser.history;ranks=ranks) +# end +# it = optimiser.history.niter; uh = get_state(optimiser.problem) +# write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) + + +function dh(stuff) + C(M,N) = @notimplemented + e(i,M) = @notimplemented + dh = (C23^2*e31 - C22*C33*e31 + C13^2*e32 + C11*C23*e32 - C11*C33*e32 + + C12*C33*(e31 + e32) + C12^2*e33 + C11*(-C22 + C23)*e33 - C12*C23*(e31 + e33) + + C13*(-(C23*(e31 + e32)) + C22*(e31 + e33) - C12*(e32 + e33)))/( + C13^2*C22 - 2*C12*C13*C23 + C12^2*C33 + C11*(C23^2 - C22*C33)) +end diff --git a/src/ChainRules.jl b/src/ChainRules.jl index 5ecc930d..4112b5ae 100644 --- a/src/ChainRules.jl +++ b/src/ChainRules.jl @@ -521,7 +521,7 @@ end function update_adjoint_caches!(φ_to_u::AffineFEStateMap,uh,φh) adjoint_ns, adjoint_K, _, assem_adjoint = φ_to_u.adj_caches U, V, _, _ = φ_to_u.spaces - assemble_matrix!((u,v) -> φ_to_u.biform(v,u,φh),adjoint_K,assem_adjoint,V,U) # TODO: @Jordi, should this be `assemble_adjoint_matrix!`? + assemble_matrix!((u,v) -> φ_to_u.biform(v,u,φh),adjoint_K,assem_adjoint,V,U) numerical_setup!(adjoint_ns,adjoint_K) return φ_to_u.adj_caches end From b7f69b10527a3f4c62ac21dc8bef3bf1a5c07bd0 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Fri, 19 Apr 2024 10:49:17 +1000 Subject: [PATCH 47/90] Remove unnecessary packages from Project.toml --- Project.toml | 4 ---- scripts/MPI/elastic_compliance_ALM.jl | 3 +-- scripts/MPI/inverse_homenisation_ALM.jl | 3 +-- src/LevelSetTopOpt.jl | 6 +++--- src/Optimisers/AugmentedLagrangian.jl | 4 ++-- src/Optimisers/HilbertianProjection.jl | 6 +++--- src/Utilities.jl | 12 ++++++++++++ 7 files changed, 22 insertions(+), 16 deletions(-) diff --git a/Project.toml b/Project.toml index 8e0627a6..8f014570 100755 --- a/Project.toml +++ b/Project.toml @@ -7,23 +7,19 @@ version = "0.1.0" BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf" BlockArrays = "8e7c35d0-a365-5155-bbbb-fb81a777f24e" ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4" -ChaosTools = "608a59af-f2a3-5ad4-90b4-758bdf3122a7" CircularArrays = "7a955b69-7140-5f4e-a0ed-f168c5e2e749" DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab" FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b" Gridap = "56d4f2e9-7ea1-5844-9cf6-b9c51ca7ce8e" GridapDistributed = "f9701e48-63b3-45aa-9a63-9bc6c271f355" -GridapP4est = "c2c8e14b-f5fd-423d-9666-1dd9ad120af9" GridapPETSc = "bcdc36c2-0c3e-11ea-095a-c9dadae499f1" GridapSolvers = "6d3209ee-5e3c-4db7-a716-942eb12ed534" JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819" -LineSearches = "d3d80556-e9d4-5f37-9878-2ab0fcc64255" LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e" MPI = "da04e1cc-30fd-572f-bb4f-1f8673147195" MPIPreferences = "3da0fdf6-3ccc-4f1b-acd9-58baa6c99267" PartitionedArrays = "5a9dfac6-5c52-46f7-8278-5e2210713be9" Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7" -SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf" SparseMatricesCSR = "a0a7dd2c-ebf4-11e9-1f05-cf50bc540ca1" Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40" diff --git a/scripts/MPI/elastic_compliance_ALM.jl b/scripts/MPI/elastic_compliance_ALM.jl index 76a48e2b..48bacf32 100644 --- a/scripts/MPI/elastic_compliance_ALM.jl +++ b/scripts/MPI/elastic_compliance_ALM.jl @@ -113,8 +113,7 @@ with_mpi() do distribute mesh_partition = (2,2) el_size = (200,100) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" + -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(hilb_solver_options)) do main(mesh_partition,distribute,el_size) diff --git a/scripts/MPI/inverse_homenisation_ALM.jl b/scripts/MPI/inverse_homenisation_ALM.jl index e2ec347b..6cbe688b 100644 --- a/scripts/MPI/inverse_homenisation_ALM.jl +++ b/scripts/MPI/inverse_homenisation_ALM.jl @@ -114,8 +114,7 @@ with_mpi() do distribute mesh_partition = (2,2) el_size = (200,200) hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" + -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(hilb_solver_options)) do main(mesh_partition,distribute,el_size) diff --git a/src/LevelSetTopOpt.jl b/src/LevelSetTopOpt.jl index 9df3865b..52d28514 100644 --- a/src/LevelSetTopOpt.jl +++ b/src/LevelSetTopOpt.jl @@ -4,11 +4,11 @@ using GridapPETSc, GridapPETSc.PETSC using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code using MPI -using BlockArrays, SparseArrays, CircularArrays -using LinearAlgebra, SparseMatricesCSR +using BlockArrays +using CircularArrays +using LinearAlgebra using ChainRulesCore using DelimitedFiles, Printf -using ChaosTools: estimate_period using Gridap using Gridap.Helpers, Gridap.Algebra, Gridap.TensorValues diff --git a/src/Optimisers/AugmentedLagrangian.jl b/src/Optimisers/AugmentedLagrangian.jl index 6c2d48b5..843d7a3a 100644 --- a/src/Optimisers/AugmentedLagrangian.jl +++ b/src/Optimisers/AugmentedLagrangian.jl @@ -99,7 +99,7 @@ end get_history(m::AugmentedLagrangian) = m.history function default_has_oscillations(m::AugmentedLagrangian,os_it;itlength=25, - itstart=2itlength,algo=:zerocrossing) + itstart=2itlength) h = m.history it = get_last_iteration(h) if it < itstart || it < os_it + itlength + 1 @@ -107,7 +107,7 @@ function default_has_oscillations(m::AugmentedLagrangian,os_it;itlength=25, end L = h[:L] - return ~isnan(estimate_period(L[it-itlength+1:it+1],algo)) + return ~isnan(_zerocrossing_period(L[it-itlength+1:it+1])) end function default_al_init_params(J,C) diff --git a/src/Optimisers/HilbertianProjection.jl b/src/Optimisers/HilbertianProjection.jl index b4f18628..875466fe 100644 --- a/src/Optimisers/HilbertianProjection.jl +++ b/src/Optimisers/HilbertianProjection.jl @@ -274,7 +274,7 @@ function default_hp_converged( end function default_has_oscillations(m::HilbertianProjection,os_it; - itlength=50,itstart=2itlength,algo=:zerocrossing) + itlength=50,itstart=2itlength) h = m.history it = get_last_iteration(h) if it < itstart || it < os_it + itlength + 1 @@ -282,9 +282,9 @@ function default_has_oscillations(m::HilbertianProjection,os_it; end J = h[:J] - J_osc = ~isnan(estimate_period(J[it-itlength+1:it+1],algo)); + J_osc = ~isnan(_zerocrossing_period(J[it-itlength+1:it+1])); C = h[:C,it-itlength+1:it+1] - C_osc = all(x->~isnan(estimate_period(x,algo)),C); + C_osc = all(x->~isnan(_zerocrossing_period(x)),C); return J_osc && C_osc end diff --git a/src/Utilities.jl b/src/Utilities.jl index 25f6ab57..d3bed832 100644 --- a/src/Utilities.jl +++ b/src/Utilities.jl @@ -219,4 +219,16 @@ function isotropic_elast_tensor(D::Int,E::Number,v::Number) else @notimplemented end +end + +# function zerocrossing_period +# +# Find the period of oscillations based on a zero crossing algorithm. +# +# This is based on the zero crossing method from ChaosTools.jl +# See (https://github.com/JuliaDynamics/ChaosTools.jl) +function _zerocrossing_period(v;t=0:length(v)-1,line=sum(v)/length(v)) + inds = findall(@. ≥(line, $@view(v[2:end])) & <(line, $@view(v[1:end-1]))) + difft = diff(t[inds]) + sum(difft)/length(difft) end \ No newline at end of file From 6e02104e44d08c6dbb07136d8151e2035846a7a5 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Fri, 19 Apr 2024 20:40:35 +1000 Subject: [PATCH 48/90] fix benchmark single iter --- scripts/Benchmarks/benchmark.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/Benchmarks/benchmark.jl b/scripts/Benchmarks/benchmark.jl index 862262d7..1e630f8e 100644 --- a/scripts/Benchmarks/benchmark.jl +++ b/scripts/Benchmarks/benchmark.jl @@ -3,7 +3,7 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, using LevelSetTopOpt: get_deriv_space, get_aux_space,benchmark_optimizer, benchmark_forward_problem,benchmark_advection,benchmark_reinitialisation, - benchmark_velocity_extension,benchmark_hilbertian_projection_map + benchmark_velocity_extension,benchmark_hilbertian_projection_map,benchmark_single_iteration using GridapSolvers: NewtonSolver From 5d53eebe7fa27b6ff76afc5861f7f6b75716c6a9 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sat, 20 Apr 2024 06:25:04 +1000 Subject: [PATCH 49/90] bug fix --- scripts/Benchmarks/benchmark.jl | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/scripts/Benchmarks/benchmark.jl b/scripts/Benchmarks/benchmark.jl index 1e630f8e..02446951 100644 --- a/scripts/Benchmarks/benchmark.jl +++ b/scripts/Benchmarks/benchmark.jl @@ -409,12 +409,12 @@ with_mpi() do distribute end ## Benchmark reinitialisation if occursin("breinit",BMARK_TYPE) - breinit = benchmark_reinitialisation(optim.stencil, get_free_dof_values(optim.φ0), 0.1, ranks; nreps=NREPS) + breinit = benchmark_reinitialisation(optim.ls_evolver, get_free_dof_values(optim.φ0), 0.1, ranks; nreps=NREPS) else breinit = i_am_main(ranks) && zeros(NREPS) end ## Benchmark forward problem - reinit!(optim.stencil,optim.φ0,optim.params.γ_reinit) + reinit!(optim.ls_evolver,optim.φ0,optim.params.γ_reinit) if occursin("bfwd",BMARK_TYPE) bfwd = benchmark_forward_problem(optim.problem.state_map, optim.φ0, ranks; nreps=NREPS) else @@ -425,7 +425,7 @@ with_mpi() do distribute vh = interpolate(FEFunction(get_deriv_space(optim.problem.state_map),optim.problem.dJ), get_aux_space(optim.problem.state_map)) v = get_free_dof_values(vh) - badv = benchmark_advection(optim.stencil, get_free_dof_values(optim.φ0), v, 0.1, ranks; nreps=NREPS) + badv = benchmark_advection(optim.ls_evolver, get_free_dof_values(optim.φ0), v, 0.1, ranks; nreps=NREPS) else badv = i_am_main(ranks) && zeros(NREPS) end From fadee3a7d8c4251bec4dc33cd79dc2292b499506 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sun, 21 Apr 2024 17:46:45 +1000 Subject: [PATCH 50/90] Bug fix for for nonlinear problems in MPI with Gridap update --- src/ChainRules.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/src/ChainRules.jl b/src/ChainRules.jl index 4112b5ae..4d54eb9c 100644 --- a/src/ChainRules.jl +++ b/src/ChainRules.jl @@ -65,7 +65,7 @@ Gridap.gradient(F::IntegrandWithMeasure,uh) = Gridap.gradient(F,[uh],1) Given an an `IntegrandWithMeasure` `F` and a vector of `FEFunctions` or `CellField` `uh` (excluding measures) evaluate the Jacobian `F.F` with respect to `uh[K]`. """ -function Gridap.jacobian(F::IntegrandWithMeasure,uh::Vector{<:Union{FEFunction,CellField}},K::Int) +function Gridap.jacobian(F::IntegrandWithMeasure,uh::Vector{<:FEFunction},K::Int) @check 0 < K <= length(uh) _f(uk) = F.F(uh[1:K-1]...,uk,uh[K+1:end]...,F.dΩ...) return Gridap.jacobian(_f,uh[K]) From 0a7d20f45c80a0f136c7f045eee8d36eaa04018b Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sun, 21 Apr 2024 17:53:45 +1000 Subject: [PATCH 51/90] Added script for 2d nonlinear prob with MPI --- .../MPI/nonlinear_thermal_compliance_ALM.jl | 103 ++++++++++++++++++ 1 file changed, 103 insertions(+) create mode 100644 scripts/MPI/nonlinear_thermal_compliance_ALM.jl diff --git a/scripts/MPI/nonlinear_thermal_compliance_ALM.jl b/scripts/MPI/nonlinear_thermal_compliance_ALM.jl new file mode 100644 index 00000000..a4a835e5 --- /dev/null +++ b/scripts/MPI/nonlinear_thermal_compliance_ALM.jl @@ -0,0 +1,103 @@ +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, + PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + +""" + (MPI) Minimum thermal compliance with augmented Lagrangian method in 2D with nonlinear diffusivity. + + Optimisation problem: + Min J(Ω) = ∫ κ(u)*∇(u)⋅∇(u) dΩ + Ω + s.t., Vol(Ω) = vf, + ⎡u∈V=H¹(Ω;u(Γ_D)=0), + ⎣∫ κ(u)*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. + + In this example κ(u) = κ0*(exp(ξ*u)) +""" +function main(mesh_partition,distribute,el_size) + ranks = distribute(LinearIndices((prod(mesh_partition),))) + ## Parameters + order = 1 + xmax=ymax=1.0 + prop_Γ_N = 0.2 + prop_Γ_D = 0.2 + dom = (0,xmax,0,ymax) + γ = 0.1 + γ_reinit = 0.5 + max_steps = floor(Int,order*minimum(el_size)/10) + tol = 1/(5order^2)/minimum(el_size) + η_coeff = 2 + α_coeff = 4max_steps*γ + vf = 0.4 + path = dirname(dirname(@__DIR__))*"/results/nonlinear_thermal_compliance_ALM_MPI/" + iter_mod = 10 + mkdir(path) + + ## FE Setup + model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); + el_Δ = get_el_Δ(model) + f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || + x[2] >= ymax-ymax*prop_Γ_D - eps())); + f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= + ymax/2+ymax*prop_Γ_N/2 + eps()); + update_labels!(1,model,f_Γ_D,"Gamma_D") + update_labels!(2,model,f_Γ_N,"Gamma_N") + + ## Triangulations and measures + Ω = Triangulation(model) + Γ_N = BoundaryTriangulation(model,tags="Gamma_N") + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + vol_D = sum(∫(1)dΩ) + + ## Spaces + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,0.0) + V_φ = TestFESpace(model,reffe_scalar) + V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) + U_reg = TrialFESpace(V_reg,0) + + ## Create FE functions + φh = interpolate(initial_lsf(4,0.2),V_φ) + + ## Interpolation and weak form + interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + + κ0 = 1 + ξ = -1 + κ(u) = κ0*(exp(ξ*u)) + res(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(κ ∘ u)*∇(u)⋅∇(v))dΩ - ∫(v)dΓ_N + + ## Optimisation functionals + J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(κ ∘ u)*∇(u)⋅∇(u))dΩ + Vol(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; + dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + + ## Finite difference solver and level set function + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + + ## Setup solver and FE operators + state_map = NonlinearFEStateMap(res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) + pcfs = PDEConstrainedFunctionals(J,[Vol],state_map,analytic_dC=[dVol]) + + ## Hilbertian extension-regularisation problems + α = α_coeff*maximum(el_Δ) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ + vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) + + ## Optimiser + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; + γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) + for (it, uh, φh) in optimiser + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] + iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) + write_history(path*"/history.txt",optimiser.history;ranks=ranks) + end + it = get_history(optimiser).niter; uh = get_state(pcfs) + writevtk(Ω,path*"out$it",cellfields=["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) +end + +with_mpi() do distribute + main((2,2),distribute,(200,200)) +end \ No newline at end of file From c07eeb9194446ee2e32ccfda1b1eab9943ea91e7 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sun, 21 Apr 2024 19:57:30 +1000 Subject: [PATCH 52/90] fix single iter benchmark --- src/Benchmarks.jl | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/src/Benchmarks.jl b/src/Benchmarks.jl index 0c052a44..0a9c1428 100644 --- a/src/Benchmarks.jl +++ b/src/Benchmarks.jl @@ -86,8 +86,10 @@ Given an optimiser `m`, benchmark a single iteration after 0th iteration. """ function benchmark_single_iteration(m::Optimiser, ranks; nreps = 10) _, state = iterate(m) + _, L, J, C, dL, dJ, dC, uh, φh, vel, λ, Λ, γ, os_it = state; function f(m) - iterate(m, state) + _state = (;it=1,L,J,C,dL,dJ,dC,uh,φh,vel,λ,Λ,γ,os_it) + iterate(m, _state) end φ0 = copy(get_free_dof_values(m.φ0)) From ed2fc735bbfcff4749b61b27750004864730404e Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sun, 21 Apr 2024 21:34:46 +1000 Subject: [PATCH 53/90] Ensure benchmark fairness by filling dofs with zero at reset --- scripts/_dev/benchmark_tests/serial_benchmark_test.jl | 10 +++++++--- src/Benchmarks.jl | 9 ++++++--- 2 files changed, 13 insertions(+), 6 deletions(-) diff --git a/scripts/_dev/benchmark_tests/serial_benchmark_test.jl b/scripts/_dev/benchmark_tests/serial_benchmark_test.jl index 17eb71cf..6ad4eec8 100644 --- a/scripts/_dev/benchmark_tests/serial_benchmark_test.jl +++ b/scripts/_dev/benchmark_tests/serial_benchmark_test.jl @@ -57,7 +57,6 @@ function main() ## Finite difference solver and level set function ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) - reinit!(stencil,φh,γ_reinit) ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) @@ -69,7 +68,7 @@ function main() vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit) + return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true) end function main_benchmark() @@ -94,4 +93,9 @@ bopt bfwd badv brinit -bvelext \ No newline at end of file +bvelext + +opt = main() + ## Benchmark optimiser +bopt0 = LevelSetTopOpt.benchmark_optimizer(opt,0, nothing; nreps = 10) +bopt = LevelSetTopOpt.benchmark_single_iteration(opt, nothing; nreps = 10) \ No newline at end of file diff --git a/src/Benchmarks.jl b/src/Benchmarks.jl index 0a9c1428..5796eb95 100644 --- a/src/Benchmarks.jl +++ b/src/Benchmarks.jl @@ -73,6 +73,8 @@ function benchmark_optimizer(m::Optimiser, niter, ranks; nreps = 10) φ0 = copy(get_free_dof_values(m.φ0)) function opt_reset!(m::Optimiser) + u = get_free_dof_values(get_state(m.problem)); + fill!(u,zero(eltype(u))) copy!(get_free_dof_values(m.φ0), φ0) reset!(get_history(m)) end @@ -86,16 +88,17 @@ Given an optimiser `m`, benchmark a single iteration after 0th iteration. """ function benchmark_single_iteration(m::Optimiser, ranks; nreps = 10) _, state = iterate(m) - _, L, J, C, dL, dJ, dC, uh, φh, vel, λ, Λ, γ, os_it = state; function f(m) - _state = (;it=1,L,J,C,dL,dJ,dC,uh,φh,vel,λ,Λ,γ,os_it) - iterate(m, _state) + iterate(m, state) end φ0 = copy(get_free_dof_values(m.φ0)) function opt_reset!(m::Optimiser) + u = get_free_dof_values(get_state(m.problem)); + fill!(u,zero(eltype(u))) copy!(get_free_dof_values(m.φ0), φ0) reset!(get_history(m)) + iterate(m) end return benchmark(f, (m,), ranks; nreps, reset! = opt_reset!) end From 73add204e1ce102c3bfdae9c13dead58d7ea469f Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sun, 21 Apr 2024 21:40:33 +1000 Subject: [PATCH 54/90] Type consistency --- src/Optimisers/AugmentedLagrangian.jl | 2 +- src/Optimisers/HilbertianProjection.jl | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/src/Optimisers/AugmentedLagrangian.jl b/src/Optimisers/AugmentedLagrangian.jl index 843d7a3a..bf33e91d 100644 --- a/src/Optimisers/AugmentedLagrangian.jl +++ b/src/Optimisers/AugmentedLagrangian.jl @@ -224,7 +224,7 @@ function Base.iterate(m::AugmentedLagrangian,state) ## Update history and build state push!(history,(L,J,C...,γ,λ...,Λ...)) - state = (it+1,L,J,C,dL,dJ,dC,uh,φh,vel,λ,Λ,γ,os_it) + state = (;it=it+1,L,J,C,dL,dJ,dC,uh,φh,vel,λ,Λ,γ,os_it) vars = params.debug ? (it,uh,φh,state) : (it,uh,φh) return vars, state end diff --git a/src/Optimisers/HilbertianProjection.jl b/src/Optimisers/HilbertianProjection.jl index 875466fe..73b41ef2 100644 --- a/src/Optimisers/HilbertianProjection.jl +++ b/src/Optimisers/HilbertianProjection.jl @@ -384,7 +384,7 @@ function Base.iterate(m::HilbertianProjection,state) ## Update history and build state push!(history,(J,C...,γ)) - state = (it+1, J, C, θ, dJ, dC, uh, φh, vel, φ_tmp, γ, os_it) + state = (;it=it+1, J, C, θ, dJ, dC, uh, φh, vel, φ_tmp, γ, os_it) vars = params.debug ? (it,uh,φh,state) : (it,uh,φh) return vars, state end From 79effb8566093302c0b2d2f6580444e591fa1ee4 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Mon, 22 Apr 2024 06:33:30 +1000 Subject: [PATCH 55/90] adjust bmarks --- scripts/Benchmarks/benchmark.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/Benchmarks/benchmark.jl b/scripts/Benchmarks/benchmark.jl index 02446951..cd4126b4 100644 --- a/scripts/Benchmarks/benchmark.jl +++ b/scripts/Benchmarks/benchmark.jl @@ -414,13 +414,13 @@ with_mpi() do distribute breinit = i_am_main(ranks) && zeros(NREPS) end ## Benchmark forward problem - reinit!(optim.ls_evolver,optim.φ0,optim.params.γ_reinit) if occursin("bfwd",BMARK_TYPE) bfwd = benchmark_forward_problem(optim.problem.state_map, optim.φ0, ranks; nreps=NREPS) else bfwd = i_am_main(ranks) && zeros(NREPS) end ## Benchmark advection + reinit!(optim.ls_evolver,optim.φ0,optim.params.γ_reinit) if occursin("badv",BMARK_TYPE) vh = interpolate(FEFunction(get_deriv_space(optim.problem.state_map),optim.problem.dJ), get_aux_space(optim.problem.state_map)) From b948a7923252f2a62b9e3ce671ed8016d2a50b55 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Mon, 22 Apr 2024 08:38:18 +1000 Subject: [PATCH 56/90] fix job scripts --- scripts/Benchmarks/jobtemplate.sh | 2 +- scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs | 2 +- scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs | 2 +- scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs | 2 +- scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs | 2 +- scripts/MPI/jobs/3d_inverter_ALM.pbs | 2 +- scripts/MPI/jobs/3d_inverter_HPM.pbs | 2 +- scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs | 2 +- scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs | 2 +- scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs | 3 +-- scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs | 3 +-- scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs | 3 +-- scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs | 3 +-- scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs | 3 +-- 14 files changed, 14 insertions(+), 19 deletions(-) diff --git a/scripts/Benchmarks/jobtemplate.sh b/scripts/Benchmarks/jobtemplate.sh index 7adbe538..4c5962e4 100644 --- a/scripts/Benchmarks/jobtemplate.sh +++ b/scripts/Benchmarks/jobtemplate.sh @@ -11,7 +11,7 @@ PROJECT_DIR=$HOME/{{:dir_name}}/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n {{:ncpus}} julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/Benchmarks/benchmark.jl \ {{:name}} \ {{{:write_dir}}} \ diff --git a/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs b/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs index 81d10175..665cdea4 100644 --- a/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs @@ -11,7 +11,7 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/MPI/3d_elastic_compliance_ALM.jl \ 160 \ 80 \ diff --git a/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs b/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs index 9a9d94c6..9e2ae8b9 100644 --- a/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs @@ -11,7 +11,7 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/MPI/3d_hyperelastic_compliance_ALM.jl \ 160 \ 80 \ diff --git a/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs b/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs index 5b7ef3f7..a6825fe2 100644 --- a/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs +++ b/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs @@ -11,7 +11,7 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl \ 160 \ 80 \ diff --git a/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs b/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs index bf1e09f4..d16b2016 100644 --- a/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs +++ b/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs @@ -11,7 +11,7 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/MPI/3d_inverse_homenisation_ALM.jl \ 100 \ 100 \ diff --git a/scripts/MPI/jobs/3d_inverter_ALM.pbs b/scripts/MPI/jobs/3d_inverter_ALM.pbs index 5e80b93d..35713c7e 100644 --- a/scripts/MPI/jobs/3d_inverter_ALM.pbs +++ b/scripts/MPI/jobs/3d_inverter_ALM.pbs @@ -12,7 +12,7 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/MPI/3d_inverter_ALM.jl \ 100 \ 100 \ diff --git a/scripts/MPI/jobs/3d_inverter_HPM.pbs b/scripts/MPI/jobs/3d_inverter_HPM.pbs index c95b0423..78737ee8 100644 --- a/scripts/MPI/jobs/3d_inverter_HPM.pbs +++ b/scripts/MPI/jobs/3d_inverter_HPM.pbs @@ -12,7 +12,7 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/MPI/3d_inverter_HPM.jl \ 100 \ 100 \ diff --git a/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs b/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs index 3b8774a6..b8921872 100644 --- a/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs @@ -12,7 +12,7 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl \ 100 \ 100 \ diff --git a/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs b/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs index 5451c039..de99436c 100644 --- a/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs @@ -12,7 +12,7 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/MPI/3d_thermal_compliance_ALM.jl \ 150 \ 150 \ diff --git a/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs index f0e6a8e1..421c9cf6 100644 --- a/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs @@ -12,6 +12,5 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs index 2e765a8a..2a00f636 100644 --- a/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs @@ -12,6 +12,5 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs index 6b5f5c2c..e59a519b 100644 --- a/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs @@ -12,6 +12,5 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs index 29179f69..26d806c3 100644 --- a/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs @@ -12,6 +12,5 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs index 795dc33d..36e63880 100644 --- a/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs @@ -12,6 +12,5 @@ PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" -mpirun --hostfile $PBS_NODEFILE \ - julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ +mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ $PROJECT_DIR/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl \ No newline at end of file From 56455421c277c319f49e4ae4dc03bd4614422d50 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Mon, 22 Apr 2024 09:00:54 +1000 Subject: [PATCH 57/90] Another fix for lyra runs --- scripts/Benchmarks/jobtemplate.sh | 2 +- scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs | 2 +- scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs | 2 +- scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs | 2 +- scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs | 2 +- scripts/MPI/jobs/3d_inverter_ALM.pbs | 2 +- scripts/MPI/jobs/3d_inverter_HPM.pbs | 2 +- scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs | 2 +- scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs | 2 +- scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs | 2 +- scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs | 2 +- scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs | 2 +- scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs | 2 +- scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs | 2 +- 14 files changed, 14 insertions(+), 14 deletions(-) diff --git a/scripts/Benchmarks/jobtemplate.sh b/scripts/Benchmarks/jobtemplate.sh index 4c5962e4..09e204c3 100644 --- a/scripts/Benchmarks/jobtemplate.sh +++ b/scripts/Benchmarks/jobtemplate.sh @@ -6,7 +6,7 @@ #PBS -l walltime={{:wallhr}}:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/{{:dir_name}}/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs b/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs index 665cdea4..20e7f3c6 100644 --- a/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs @@ -6,7 +6,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs b/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs index 9e2ae8b9..b0f29779 100644 --- a/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs @@ -6,7 +6,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs b/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs index a6825fe2..7fd9279a 100644 --- a/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs +++ b/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs @@ -6,7 +6,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs b/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs index d16b2016..ffa8d005 100644 --- a/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs +++ b/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs @@ -6,7 +6,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/MPI/jobs/3d_inverter_ALM.pbs b/scripts/MPI/jobs/3d_inverter_ALM.pbs index 35713c7e..54b6311b 100644 --- a/scripts/MPI/jobs/3d_inverter_ALM.pbs +++ b/scripts/MPI/jobs/3d_inverter_ALM.pbs @@ -7,7 +7,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/MPI/jobs/3d_inverter_HPM.pbs b/scripts/MPI/jobs/3d_inverter_HPM.pbs index 78737ee8..c0390d54 100644 --- a/scripts/MPI/jobs/3d_inverter_HPM.pbs +++ b/scripts/MPI/jobs/3d_inverter_HPM.pbs @@ -7,7 +7,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs b/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs index b8921872..de3e8b48 100644 --- a/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs @@ -7,7 +7,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs b/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs index de99436c..f456d8a7 100644 --- a/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs @@ -7,7 +7,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs index 421c9cf6..94a34cfa 100644 --- a/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs @@ -7,7 +7,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs index 2a00f636..5a8b0387 100644 --- a/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs @@ -7,7 +7,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs index e59a519b..9da69050 100644 --- a/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs @@ -7,7 +7,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs index 26d806c3..6cfc5060 100644 --- a/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs @@ -7,7 +7,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" diff --git a/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs index 36e63880..d24b04a1 100644 --- a/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs @@ -7,7 +7,7 @@ #PBS -l walltime=23:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-ompi.sh +source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" From 97a31470b1aaebe838c5b2f7ba15b7b3b6bbf08f Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Mon, 22 Apr 2024 10:34:49 +1000 Subject: [PATCH 58/90] another fix --- scripts/Benchmarks/generate_benchmark_scripts.jl | 2 +- src/Benchmarks.jl | 14 ++++++++++---- 2 files changed, 11 insertions(+), 5 deletions(-) diff --git a/scripts/Benchmarks/generate_benchmark_scripts.jl b/scripts/Benchmarks/generate_benchmark_scripts.jl index 4214f36e..4ad06b06 100644 --- a/scripts/Benchmarks/generate_benchmark_scripts.jl +++ b/scripts/Benchmarks/generate_benchmark_scripts.jl @@ -65,7 +65,7 @@ dir_name= "LevelSetTopOpt"; write_dir = "\$HOME/$dir_name/results/benchmarks/" N = 1:10; # Number of partitions in x-axis -strong_dof=(150+1)^3*3; # Number of dofs for strong scaling +strong_dof=(100+1)^3*3; # Number of dofs for strong scaling # Phys type and number of dofs per node, and what to benchmark phys_types = [ diff --git a/src/Benchmarks.jl b/src/Benchmarks.jl index 5796eb95..342dcfed 100644 --- a/src/Benchmarks.jl +++ b/src/Benchmarks.jl @@ -86,19 +86,25 @@ end Given an optimiser `m`, benchmark a single iteration after 0th iteration. """ -function benchmark_single_iteration(m::Optimiser, ranks; nreps = 10) - _, state = iterate(m) +function benchmark_single_iteration(m::Optimiser,ranks; nreps = 10) + _,state = iterate(m) function f(m) - iterate(m, state) + iterate(m,state) end φ0 = copy(get_free_dof_values(m.φ0)) + λ0 = copy(state.λ); Λ0 = copy(state.Λ) + dL0 = copy(state.dL) function opt_reset!(m::Optimiser) u = get_free_dof_values(get_state(m.problem)); fill!(u,zero(eltype(u))) copy!(get_free_dof_values(m.φ0), φ0) + copy!(get_free_dof_values(state.φh), φ0) + copy!(state.λ,λ0) + copy!(state.Λ,Λ0) + copy!(state.dL,dL0) reset!(get_history(m)) - iterate(m) + get_history(m).niter = state.it - 1 # <- due to compilation end return benchmark(f, (m,), ranks; nreps, reset! = opt_reset!) end From fd8e2b7c80e5574c157aa18cfe2145d389ead33a Mon Sep 17 00:00:00 2001 From: JordiManyer Date: Mon, 22 Apr 2024 14:42:06 +1000 Subject: [PATCH 59/90] Cleanup GridapExtensions --- src/GridapExtensions.jl | 36 ------------------------------------ 1 file changed, 36 deletions(-) diff --git a/src/GridapExtensions.jl b/src/GridapExtensions.jl index 51b5d1e8..6b6b9991 100644 --- a/src/GridapExtensions.jl +++ b/src/GridapExtensions.jl @@ -59,25 +59,6 @@ function assemble_adjoint_matrix!(f::Function,A::AbstractMatrix,a::Assembler,U:: end # Assembly addons -""" -function Gridap.FESpaces.allocate_matrix(a::Function,assem::Assembler,U::FESpace,V::FESpace) - v = get_fe_basis(V) - u = get_trial_fe_basis(U) - allocate_matrix(assem,collect_cell_matrix(U,V,a(u,v))) -end - -function Gridap.FESpaces.allocate_vector(l::Function,assem::Assembler,V::FESpace) - v = get_fe_basis(V) - allocate_vector(assem,collect_cell_vector(V,l(v))) -end - -function Gridap.FESpaces.assemble_matrix_and_vector!( - a::Function,l::Function,A::AbstractMatrix,b::AbstractVector,assem::Assembler,U::FESpace,V::FESpace,uhd) - v = get_fe_basis(V) - u = get_trial_fe_basis(U) - assemble_matrix_and_vector!(A,b,assem,collect_cell_matrix_and_vector(U,V,a(u,v),l(v),uhd)) -end -""" get_local_matrix_type(a::Assembler) = get_matrix_type(a) get_local_vector_type(a::Assembler) = get_vector_type(a) @@ -89,20 +70,3 @@ end function get_local_vector_type(a::GridapDistributed.DistributedSparseMatrixAssembler) return getany(map(get_vector_type,a.assems)) end - -# PETScNonlinearSolver override - -function Gridap.Algebra.solve!(x::T,nls::PETScNonlinearSolver,op::Gridap.Algebra.NonlinearOperator, - cache::GridapPETSc.PETScNonlinearSolverCache{<:T}) where T <: AbstractVector - @check_error_code GridapPETSc.PETSC.SNESSolve(cache.snes[],C_NULL,cache.x_petsc.vec[]) - copy!(x,cache.x_petsc) - cache -end - -# Stuff from ODE refactor -""" -function (+)(a::Gridap.CellData.DomainContribution,b::GridapDistributed.DistributedDomainContribution) - @assert iszero(Gridap.CellData.num_domains(a)) - return b -end -""" \ No newline at end of file From 3dfec9b6004dc99e49169fb82bd34ed3b17442ac Mon Sep 17 00:00:00 2001 From: JordiManyer Date: Mon, 22 Apr 2024 15:03:20 +1000 Subject: [PATCH 60/90] RepeatedFEStateMaps support for BlockMultiFieldStyle --- src/ChainRules.jl | 63 +++++++++++++++++++++++++++++++++++++++++------ 1 file changed, 56 insertions(+), 7 deletions(-) diff --git a/src/ChainRules.jl b/src/ChainRules.jl index 4d54eb9c..7d6d52ca 100644 --- a/src/ChainRules.jl +++ b/src/ChainRules.jl @@ -747,23 +747,68 @@ struct RepeatingAffineFEStateMap{A,B,C,D,E,F,G} <: AbstractFEStateMap end end +const MultiFieldSpaceTypes = Union{<:MultiField.MultiFieldFESpace,<:GridapDistributed.DistributedMultiFieldFESpace} + function repeat_spaces(nblocks::Integer,U0::FESpace,V0::FESpace) U = MultiFieldFESpace([U0 for i in 1:nblocks];style=BlockMultiFieldStyle()) V = MultiFieldFESpace([V0 for i in 1:nblocks];style=BlockMultiFieldStyle()) return U,V end -function repeat_spaces( - nblocks::Integer,U0::T,V0::T -) where T <: Union{MultiField.MultiFieldFESpace,GridapDistributed.DistributedMultiFieldFESpace} +function repeat_spaces(nblocks::Integer,U0::MultiFieldSpaceTypes,V0::MultiFieldSpaceTypes) nfields = num_fields(U0) @assert nfields == num_fields(V0) - mfs = BlockMultiFieldStyle(nblocks,Tuple(fill(nfields,nblocks))) + @assert MultiFieldStyle(U0) === MultiFieldStyle(V0) + + mfs = repeat_mfs(nblocks,nfields,MultiFieldStyle(U0)) U = MultiFieldFESpace(repeat([U0...],nblocks);style=mfs) V = MultiFieldFESpace(repeat([V0...],nblocks);style=mfs) return U,V end +function repeat_mfs(nblocks::Integer,nfields::Integer,::ConsecutiveMultiFieldStyle) + return BlockMultiFieldStyle(nblocks,Tuple(fill(nfields,nblocks))) +end + +function repeat_mfs(nblocks::Integer,nfields::Integer,::BlockMultiFieldStyle{NB,SB,P}) where {NB,SB,P} + @assert length(P) == nfields + P_new = [P...] + for iB in 2:nblocks + P_new = vcat(P_new,(P .+ (iB-1)*nfields)...) + end + return BlockMultiFieldStyle(NB*nblocks, Tuple(repeat([SB...],nblocks)), Tuple(P_new)) +end + +repeated_blocks(V0::FESpace,x::AbstractBlockVector) = blocks(x) +repeated_blocks(V0::FESpace,xh) = xh + +repeated_blocks(V0::MultiFieldSpaceTypes,x) = repeated_blocks(MultiFieldStyle(V0),V0,x) +repeated_blocks(::ConsecutiveMultiFieldStyle,V0,x::AbstractBlockVector) = blocks(x) +repeated_blocks(::ConsecutiveMultiFieldStyle,V0,xh) = xh + +function repeated_blocks(::BlockMultiFieldStyle{NB},V0::MultiFieldSpaceTypes,x::AbstractBlockVector) where NB + xb = blocks(x) + @assert length(xb) % NB == 0 + + nblocks = length(xb) ÷ NB + rep_blocks = map(1:nblocks) do iB + mortar(xb[(iB-1)*NB+1:iB*NB]) + end + return rep_blocks +end + +function repeated_blocks(::BlockMultiFieldStyle,V0::MultiFieldSpaceTypes,xh) + xb = blocks(x) + nfields = num_fields(V0) + @assert length(xb) % nfields == 0 + + nblocks = length(xb) ÷ nfields + rep_blocks = map(1:nblocks) do iB + FEFunction(V0,xh[(iB-1)*nfields+1:iB*nfields]) + end + return rep_blocks +end + get_state(m::RepeatingAffineFEStateMap) = FEFunction(get_trial_space(m),m.fwd_caches[4]) get_measure(m::RepeatingAffineFEStateMap) = m.biform.dΩ get_spaces(m::RepeatingAffineFEStateMap) = m.spaces @@ -783,7 +828,7 @@ function forward_solve!(φ_to_u::RepeatingAffineFEStateMap,φh) rmul!(b0,-1) v = get_fe_basis(V0) - map(blocks(x),liforms) do xi, li + map(repeated_blocks(U0,x),liforms) do xi, li copy!(b,b0) vecdata = collect_cell_vector(V0,li(v,φh)) assemble_vector_add!(b,assem_U0,vecdata) @@ -794,9 +839,12 @@ end function dRdφ(φ_to_u::RepeatingAffineFEStateMap,uh,vh,φh) biform, liforms = φ_to_u.biform, φ_to_u.liform + U0, V0 = φ_to_u.spaces_0 + uh_blocks = repeated_blocks(U0,uh) + vh_blocks = repeated_blocks(V0,vh) res = DomainContribution() - for (liform,uhi,vhi) in zip(liforms,uh,vh) + for (liform,uhi,vhi) in zip(liforms,uh_blocks,vh_blocks) res = res + ∇(biform,[uhi,vhi,φh],3) - ∇(liform,[vhi,φh],2) end return res @@ -812,7 +860,8 @@ end function adjoint_solve!(φ_to_u::RepeatingAffineFEStateMap,du::AbstractBlockVector) adjoint_ns, _, adjoint_x, _ = φ_to_u.adj_caches - map(blocks(adjoint_x),blocks(du)) do xi, dui + U0, V0 = φ_to_u.spaces_0 + map(repeated_blocks(U0,adjoint_x),repeated_blocks(U0,du)) do xi, dui solve!(xi,adjoint_ns,dui) end return adjoint_x From a345da0accec3e876daa1e3e4791055b7c42c824 Mon Sep 17 00:00:00 2001 From: JordiManyer Date: Mon, 22 Apr 2024 15:13:40 +1000 Subject: [PATCH 61/90] Bugfix --- src/ChainRules.jl | 10 +++------- 1 file changed, 3 insertions(+), 7 deletions(-) diff --git a/src/ChainRules.jl b/src/ChainRules.jl index 7d6d52ca..8f57722c 100644 --- a/src/ChainRules.jl +++ b/src/ChainRules.jl @@ -798,13 +798,9 @@ function repeated_blocks(::BlockMultiFieldStyle{NB},V0::MultiFieldSpaceTypes,x:: end function repeated_blocks(::BlockMultiFieldStyle,V0::MultiFieldSpaceTypes,xh) - xb = blocks(x) - nfields = num_fields(V0) - @assert length(xb) % nfields == 0 - - nblocks = length(xb) ÷ nfields - rep_blocks = map(1:nblocks) do iB - FEFunction(V0,xh[(iB-1)*nfields+1:iB*nfields]) + x_blocks = repeated_blocks(MultiFieldStyle(V0),V0,get_free_values(xh)) + rep_blocks = map(x_blocks) do xb + FEFunction(V0,xb) end return rep_blocks end From e0399141c4f42213d32d925e0ed54f06ae7cc991 Mon Sep 17 00:00:00 2001 From: JordiManyer Date: Mon, 22 Apr 2024 22:46:32 +1000 Subject: [PATCH 62/90] More bugfixes --- scripts/_dev/piezo_repeating.jl | 354 ++++++++++++++++++++++++++++++++ src/ChainRules.jl | 19 +- src/GridapExtensions.jl | 15 +- 3 files changed, 382 insertions(+), 6 deletions(-) create mode 100644 scripts/_dev/piezo_repeating.jl diff --git a/scripts/_dev/piezo_repeating.jl b/scripts/_dev/piezo_repeating.jl new file mode 100644 index 00000000..4c069651 --- /dev/null +++ b/scripts/_dev/piezo_repeating.jl @@ -0,0 +1,354 @@ +using Gridap, GridapDistributed, GridapPETSc, GridapSolvers, + PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR +using Gridap.TensorValues, Gridap.Helpers, Gridap.MultiField +using GridapSolvers.BlockSolvers + +function PZT5A(D::Int) + ε_0 = 8.854e-12; + if D == 3 + C_Voigt = [12.0400e10 7.52000e10 7.51000e10 0.0 0.0 0.0 + 7.52000e10 12.0400e10 7.51000e10 0.0 0.0 0.0 + 7.51000e10 7.51000e10 11.0900e10 0.0 0.0 0.0 + 0.0 0.0 0.0 2.1000e10 0.0 0.0 + 0.0 0.0 0.0 0.0 2.1000e10 0.0 + 0.0 0.0 0.0 0.0 0.0 2.30e10] + e_Voigt = [0.0 0.0 0.0 0.0 12.30000 0.0 + 0.0 0.0 0.0 12.30000 0.0 0.0 + -5.40000 -5.40000 15.80000 0.0 0.0 0.0] + K_Voigt = [540*ε_0 0 0 + 0 540*ε_0 0 + 0 0 830*ε_0] + elseif D == 2 + C_Voigt = [12.0400e10 7.51000e10 0.0 + 7.51000e10 11.0900e10 0.0 + 0.0 0.0 2.1000e10] + e_Voigt = [0.0 0.0 12.30000 + -5.40000 15.80000 0.0] + K_Voigt = [540*ε_0 0 + 0 830*ε_0] + else + @notimplemented + end + C = voigt2tensor4(C_Voigt) + e = voigt2tensor3(e_Voigt) + κ = voigt2tensor2(K_Voigt) + C,e,κ +end + +""" + Given a material constant given in Voigt notation, + return a SymFourthOrderTensorValue using ordering from Gridap +""" +function voigt2tensor4(A::Array{M,2}) where M + if isequal(size(A),(3,3)) + return SymFourthOrderTensorValue(A[1,1], A[3,1], A[2,1], + A[1,3], A[3,3], A[2,3], + A[1,2], A[3,2], A[2,2]) + elseif isequal(size(A),(6,6)) + return SymFourthOrderTensorValue(A[1,1], A[6,1], A[5,1], A[2,1], A[4,1], A[3,1], + A[1,6], A[6,6], A[5,6], A[2,6], A[4,6], A[3,6], + A[1,5], A[6,5], A[5,5], A[2,5], A[4,5], A[3,5], + A[1,2], A[6,2], A[5,2], A[2,2], A[4,2], A[3,2], + A[1,4], A[6,4], A[5,4], A[2,4], A[4,4], A[3,4], + A[1,3], A[6,3], A[5,3], A[2,3], A[4,3], A[3,3]) + else + @notimplemented + end +end + +""" + Given a material constant given in Voigt notation, + return a ThirdOrderTensorValue using ordering from Gridap +""" +function voigt2tensor3(A::Array{M,2}) where M + if isequal(size(A),(2,3)) + return ThirdOrderTensorValue(A[1,1], A[2,1], A[1,3], A[2,3], A[1,3], A[2,3], A[1,2], A[2,2]) + elseif isequal(size(A),(3,6)) + return ThirdOrderTensorValue( + A[1,1], A[2,1], A[3,1], A[1,6], A[2,6], A[3,6], A[1,5], A[2,5], A[3,5], + A[1,6], A[2,6], A[3,6], A[1,2], A[2,2], A[3,2], A[1,4], A[2,4], A[3,4], + A[1,5], A[2,5], A[3,5], A[1,4], A[2,4], A[3,4], A[1,3], A[2,3], A[3,3]) + else + @notimplemented + end +end + +""" + Given a material constant given in Voigt notation, + return a SymTensorValue using ordering from Gridap +""" +function voigt2tensor2(A::Array{M,2}) where M + return TensorValue(A) +end + +## Parameters +#function main(mesh_partition,distribute) + #ranks = distribute(LinearIndices((prod(mesh_partition),))) + +mesh_partition = (1,1) +ranks = with_mpi() do distribute + distribute(LinearIndices((prod(mesh_partition),))) +end + +el_size = (100,100) +order = 1 +xmax,ymax=(1.0,1.0) +dom = (0,xmax,0,ymax) +γ = 0.1 +γ_reinit = 0.5 +max_steps = floor(Int,order*minimum(el_size)/10) +tol = 1/(5order^2)/minimum(el_size) +η_coeff = 2 +α_coeff = 4*max_steps*γ +vf = 0.5 +path = dirname(@__DIR__)*"/results/2d_PZ_inverse_homenisation_MPI_Nx$(mesh_partition[1])Ny$(mesh_partition[2])/" +#i_am_main(ranks) && mkpath(path) + +## FE Setup +model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true)) +el_Δ = get_el_Δ(model) +f_Γ_D(x) = iszero(x) +update_labels!(1,model,f_Γ_D,"origin") + +## Triangulations and measures +Ω = Triangulation(model) +dΩ = Measure(Ω,2*order) +vol_D = sum(∫(1)dΩ) + +## Spaces +reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) +reffe_scalar = ReferenceFE(lagrangian,Float64,order) +V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["origin"]) +U = TrialFESpace(V,VectorValue(0.0,0.0)) +Q = TestFESpace(model,reffe_scalar;conformity=:H1,dirichlet_tags=["origin"]) +P = TrialFESpace(Q,0) +mfs = BlockMultiFieldStyle() +UP = MultiFieldFESpace([U,P];style=mfs) +VQ = MultiFieldFESpace([V,Q];style=mfs) + +V_φ = TestFESpace(model,reffe_scalar) +V_reg = TestFESpace(model,reffe_scalar) +U_reg = TrialFESpace(V_reg) + +## Create FE functions +lsf_fn = initial_lsf(2,0.2) +φh = interpolate(lsf_fn,V_φ) + +## Interpolation and weak form +interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ),ϵ=10^-9) +I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + +## Material tensors +C, e, κ = PZT5A(2); +k0 = norm(C.data,Inf); +α0 = norm(e.data,Inf); +β0 = norm(κ.data,Inf); +γ0 = β0*k0/α0^2; + +## Weak forms +εᴹ = (SymTensorValue(1.0,0.0,0.0), + SymTensorValue(0.0,0.0,1.0), + SymTensorValue(0.0,1/2,0)) +Eⁱ = (VectorValue(1.0,0.0,), + VectorValue(0.0,1.0)) + +a((u,ϕ),(v,q),φ,dΩ) = ∫((I ∘ φ) * (1/k0*((C ⊙ ε(u)) ⊙ ε(v)) - + 1/α0*((-∇(ϕ) ⋅ e) ⊙ ε(v)) + + -1/α0*((e ⋅² ε(u)) ⋅ -∇(q)) + + -γ0/β0*((κ ⋅ -∇(ϕ)) ⋅ -∇(q))) )dΩ; + +l_ε = [((v,q),φ,dΩ) -> ∫(((I ∘ φ) * (-C ⊙ εᴹ[i] ⊙ ε(v) + k0/α0*(e ⋅² εᴹ[i]) ⋅ -∇(q))))dΩ for i = 1:3]; +l_E = [((v,q),φ,dΩ) -> ∫((I ∘ φ) * ((Eⁱ[i] ⋅ e ⊙ ε(v) + k0/α0*(κ ⋅ Eⁱ[i]) ⋅ -∇(q))))dΩ for i = 1:2]; +l = [l_ε; l_E] + +## Optimisation functionals +# Note, uϕ unpacks as -> uϕ = u1,ϕ1,u2,ϕ2,u3,ϕ3,u4,ϕ4,u5,ϕ5 +# where entries 1,2,3 correspond to εᴹ[1],εᴹ[2],εᴹ[3] and +# 4,5 correspond to Eⁱ[1],Eⁱ[2]. + +function Cᴴ(r,s,uϕ,φ,dΩ) # (normalised by 1/k0) + u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] + ∫(1/k0 * (I ∘ φ) * (((C ⊙ (1/k0*ε(u_s) + εᴹ[s])) ⊙ εᴹ[r]) - ((-1/α0*∇(ϕ_s) ⋅ e) ⊙ εᴹ[r])))dΩ; +end + +function DCᴴ(r,s,q,uϕ,φ,dΩ) # (normalised by 1/k0) + u_r = uϕ[2r-1]; ϕ_r = uϕ[2r] + u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] + ∫(- 1/k0 * q * ( + (C ⊙ (1/k0*ε(u_s) + εᴹ[s])) ⊙ (1/k0*ε(u_r) + εᴹ[r]) - + (-1/α0*∇(ϕ_s) ⋅ e) ⊙ (1/k0*ε(u_r) + εᴹ[r]) - + (e ⋅² (1/k0*ε(u_s) + εᴹ[s])) ⋅ (-1/α0*∇(ϕ_r)) - + (κ ⋅ (-1/α0*∇(ϕ_s))) ⋅ (-1/α0*∇(ϕ_r)) + ) * (DH ∘ φ) * (norm ∘ ∇(φ)) + )dΩ; +end + +function eᴴ(i,s,uϕ,φ,dΩ) # (normalised by 1/α0) + u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] + ∫(1/α0 * (I ∘ φ) * (((e ⋅² (1/k0*ε(u_s) + εᴹ[s])) ⋅ Eⁱ[i]) + ((κ ⋅ (-1/α0*∇(ϕ_s))) ⋅ Eⁱ[i])))dΩ; +end + +function Deᴴ(i,s,q,uϕ,φ,dΩ) # (normalised by 1/α0) + u_i = uϕ[6+2i-1]; ϕ_i = uϕ[6+2i] + u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] + ∫(- 1/α0 * q * ( + - (C ⊙ (1/k0*ε(u_s) + εᴹ[s])) ⊙ (1/k0*ε(u_i)) + + (-1/α0*∇(ϕ_s) ⋅ e) ⊙ (1/k0*ε(u_i)) + + (e ⋅² (1/k0*ε(u_s) + εᴹ[s])) ⋅ (-1/α0*∇(ϕ_i) + Eⁱ[i]) + + (κ ⋅ (-1/α0*∇(ϕ_s))) ⋅ (-1/α0*∇(ϕ_i) + Eⁱ[i]) + ) * (DH ∘ φ) * (norm ∘ ∇(φ)) + )dΩ; +end + +function κᴴ(i,j,uϕ,φ,dΩ) # (normalised by 1/β0) + u_j = uϕ[6+2j-1]; ϕ_j = uϕ[6+2j] + ∫(1/β0 * (I ∘ φ) * (((e ⋅² (1/k0*ε(u_j)) ⋅ Eⁱ[i]) + ((κ ⋅ (-1/α0*∇(ϕ_j) + Eⁱ[j])) ⋅ Eⁱ[i]))))dΩ; +end + +function Dκᴴ(i,j,q,uϕ,φ,dΩ) # (normalised by 1/β0) + u_i = uϕ[6+2i-1]; ϕ_i = uϕ[6+2i] + u_j = uϕ[6+2j-1]; ϕ_j = uϕ[6+2j] + ∫(- 1/β0 * q * ( + - (C ⊙ (1/k0*ε(u_j))) ⊙ (1/k0*ε(u_i)) + + ((-1/α0*∇(ϕ_j) + Eⁱ[j]) ⋅ e) ⊙ (1/k0*ε(u_i)) + + (e ⋅² (1/k0*ε(u_j))) ⋅ (-1/α0*∇(ϕ_i) + Eⁱ[i]) + + (κ ⋅ (-1/α0*∇(ϕ_j) + Eⁱ[j])) ⋅ (-1/α0*∇(ϕ_i) + Eⁱ[i]) + ) * (DH ∘ φ) * (norm ∘ ∇(φ)) + )dΩ; +end + +# Equiv to +# C_mat = map(rs->sum(Cᴴ(rs[1],rs[2],xh,φh,dΩ)), CartesianIndices((1:3, 1:3))) +# e_mat = map(is->sum(eᴴ(is[1],is[2],xh,φh,dΩ)), CartesianIndices((1:2, 1:3))) +# d_mat = e_mat*inv(C_mat); +# dh = d_mat[2,1] + d_mat[2,2] +function dᴴ(uϕ,φ,dΩ) + # We leave eᴴ_21 and eᴴ_22 as DomainContribution so that result is a DomainContribution. + # Note that this means AD applied to this functional would be incorrect. + Cᴴ_11 = sum(Cᴴ(1,1,uϕ,φ,dΩ)); + Cᴴ_22 = sum(Cᴴ(2,2,uϕ,φ,dΩ)); + Cᴴ_21 = sum(Cᴴ(2,1,uϕ,φ,dΩ)); + eᴴ_21 = eᴴ(2,1,uϕ,φ,dΩ); + eᴴ_22 = eᴴ(2,2,uϕ,φ,dΩ); + (Cᴴ_22*eᴴ_21 + Cᴴ_11*eᴴ_22 - Cᴴ_21*(eᴴ_21 + eᴴ_22))*(1/(Cᴴ_11*Cᴴ_22 - Cᴴ_21^2)) +end + +function Ddᴴ(q,uϕ,φ,dΩ) + Cᴴ_11 = sum(Cᴴ(1,1,uϕ,φ,dΩ)); DCᴴ_11 = DCᴴ(1,1,q,uϕ,φ,dΩ) + Cᴴ_22 = sum(Cᴴ(2,2,uϕ,φ,dΩ)); DCᴴ_22 = DCᴴ(2,2,q,uϕ,φ,dΩ) + Cᴴ_21 = sum(Cᴴ(2,1,uϕ,φ,dΩ)); DCᴴ_21 = DCᴴ(2,1,q,uϕ,φ,dΩ) + eᴴ_21 = sum(eᴴ(2,1,uϕ,φ,dΩ)); Deᴴ_21 = DCᴴ(2,1,q,uϕ,φ,dΩ) + eᴴ_22 = sum(eᴴ(2,2,uϕ,φ,dΩ)); Deᴴ_22 = DCᴴ(2,2,q,uϕ,φ,dΩ) + (-1*Cᴴ_11^2*eᴴ_22*(DCᴴ_22)+Cᴴ_22^2*(-eᴴ_21*(DCᴴ_11)+Cᴴ_11*(Deᴴ_21))+ + Cᴴ_21^3*((Deᴴ_21)+(Deᴴ_22))+Cᴴ_11*Cᴴ_22*(-1*((eᴴ_21+eᴴ_22)*(DCᴴ_21))+ + Cᴴ_11*(Deᴴ_22))-Cᴴ_21^2*(eᴴ_22*((DCᴴ_11)+(DCᴴ_21))+eᴴ_21*((DCᴴ_21)+(DCᴴ_22))+ + Cᴴ_22*(Deᴴ_21)+Cᴴ_11*(Deᴴ_22))+Cᴴ_21*(Cᴴ_11*(2*eᴴ_22*(DCᴴ_21)+(eᴴ_21+eᴴ_22)*(DCᴴ_22))+ + Cᴴ_22*((eᴴ_21+eᴴ_22)*(DCᴴ_11)+2*eᴴ_21*(DCᴴ_21)-Cᴴ_11*((Deᴴ_21)+(Deᴴ_22)))))*(1/(Cᴴ_21^2-Cᴴ_11*Cᴴ_22)^2) +end + +Bᴴ(uϕ,φ,dΩ) = 1/4*(Cᴴ(1,1,uϕ,φ,dΩ)+Cᴴ(2,2,uϕ,φ,dΩ)+2*Cᴴ(1,2,uϕ,φ,dΩ)) +DBᴴ(q,uϕ,φ,dΩ) = 1/4*(DCᴴ(1,1,q,uϕ,φ,dΩ)+DCᴴ(2,2,q,uϕ,φ,dΩ)+2*DCᴴ(1,2,q,uϕ,φ,dΩ)) + + +J(uϕ,φ,dΩ) = -1*dᴴ(uϕ,φ,dΩ) +DJ(q,uϕ,φ,dΩ) = -1*Ddᴴ(q,uϕ,φ,dΩ) +C1(uϕ,φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; +DC1(q,uϕ,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ +C2(uϕ,φ,dΩ) = Cᴴ(2,2,uϕ,φ,dΩ) - ∫(0.05/vol_D)dΩ +DC2(q,uϕ,φ,dΩ) = DCᴴ(2,2,q,uϕ,φ,dΩ) + +# ## Finite difference solver and level set function +stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + +# ## Setup solver and FE operators +Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} +Tv = Vector{PetscScalar} +solver_u = LUSolver() #ElasticitySolver(V) #GridapSolvers.LinearSolvers.ElasticitySolver(V) +solver_ϕ = LUSolver() #PETScLinearSolver() + +# P = GridapSolvers.BlockDiagonalSolver([solver_u,solver_ϕ]) +# solver = GridapSolvers.LinearSolvers.GMRESSolver(100;Pr=P,rtol=1.e-8,verbose=i_am_main(ranks)) +solver = BlockTriangularSolver([solver_u,solver_ϕ]) + +state_map = RepeatingAffineFEStateMap(5,a,l,UP,VQ,V_φ,U_reg,φh,dΩ; + assem_U = SparseMatrixAssembler(Tm,Tv,UP,VQ), + assem_adjoint = SparseMatrixAssembler(Tm,Tv,VQ,UP), + assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), + ls = solver,adjoint_ls = solver +) +pcfs = PDEConstrainedFunctionals(J,[C1,C2],state_map;analytic_dJ=DJ,analytic_dC=[DC1,DC2]) + +# ## Hilbertian extension-regularisation problems +α = α_coeff*maximum(el_Δ) +a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; +vel_ext = VelocityExtension( + a_hilb,U_reg,V_reg; + assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), + ls = PETScLinearSolver() +) + +# ## Optimiser +has_oscillations(m,os_it) = LevelSetTopOpt.default_has_oscillations(m,os_it;itlength=25) +optimiser = HilbertianProjection(pcfs,stencil,vel_ext,φh;γ,γ_reinit,has_oscillations, + verbose=i_am_main(ranks),ls_enabled=true) +for (it, uh, φh) in optimiser + u1,ϕ1,u2,ϕ2,u3,ϕ3,u4,ϕ4,u5,ϕ5 = uh + data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)), + "u1"=>1/k0*u1,"ϕ1"=>1/α0*ϕ1,"u2"=>1/k0*u2,"ϕ2"=>1/α0*ϕ2,"u3"=>1/k0*u3,"ϕ3"=>1/α0*ϕ3, + "u4"=>1/k0*u4,"ϕ4"=>1/α0*ϕ4,"u5"=>1/k0*u5,"ϕ5"=>1/α0*ϕ5] + writevtk(Ω,path*"out$it",cellfields=data) + write_history(path*"/history.txt",optimiser.history) +end +#end + +#with_debug() do distribute +# mesh_partition = (2,2) +# solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true +# -ksp_converged_reason -ksp_rtol 1.0e-12" +# GridapPETSc.with(args=split(solver_options)) do +# main(mesh_partition,distribute) +# end +#end + +# mesh_partition = (2,2) +# ranks = with_debug() do distribute +# distribute(LinearIndices((prod(mesh_partition),))) +# end + +# el_size = (200,200) +# order = 1 +# xmax,ymax=(1.0,1.0) +# dom = (0,xmax,0,ymax) +# γ = 0.1 +# γ_reinit = 0.5 +# max_steps = floor(Int,order*minimum(el_size)/10) +# tol = 1/(5order^2)/minimum(el_size) +# η_coeff = 2 +# α_coeff = 4*max_steps*γ +# vf = 0.5 + +# ## FE Setup +# model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true)) +# el_Δ = get_el_Δ(model) +# f_Γ_D(x) = iszero(x) +# update_labels!(1,model,f_Γ_D,"origin") + +# ## Triangulations and measures +# Ω = Triangulation(model) +# dΩ = Measure(Ω,2*order) +# vol_D = sum(∫(1)dΩ) + +# ## Spaces +# reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) +# reffe_scalar = ReferenceFE(lagrangian,Float64,order) +# V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["origin"]) +# U = TrialFESpace(V,VectorValue(0.0,0.0)) +# Q = TestFESpace(model,reffe_scalar;conformity=:H1,dirichlet_tags=["origin"]) +# P = TrialFESpace(Q,0) +# mfs = BlockMultiFieldStyle() +# UP = MultiFieldFESpace([U,P];style=mfs) +# VQ = MultiFieldFESpace([V,Q];style=mfs) + +# Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} +# Tv = Vector{PetscScalar} +# assem = SparseMatrixAssembler(Tm,Tv,UP,VQ) diff --git a/src/ChainRules.jl b/src/ChainRules.jl index 8f57722c..398f74db 100644 --- a/src/ChainRules.jl +++ b/src/ChainRules.jl @@ -695,7 +695,7 @@ struct RepeatingAffineFEStateMap{A,B,C,D,E,F,G} <: AbstractFEStateMap - The resulting `FEFunction` will be a `MultiFieldFEFunction` (or GridapDistributed equivalent) where each field corresponds to an entry in the vector of linear forms """ - function RepeatingAffineFEStateMap( + function RepeatingAffineFEStateMap( nblocks::Int,a::Function,l::Vector{<:Function}, U0,V0,V_φ,U_reg,φh,dΩ...; assem_U = SparseMatrixAssembler(U0,V0), @@ -715,7 +715,7 @@ struct RepeatingAffineFEStateMap{A,B,C,D,E,F,G} <: AbstractFEStateMap spaces = (U,V,V_φ,U_reg) assem_U = SparseMatrixAssembler( get_local_matrix_type(assem_U0), get_local_vector_type(assem_U0), - U, V, get_assembly_strategy(assem_U0) + U, V, get_local_assembly_strategy(assem_U0) ) ## Pullback cache @@ -731,13 +731,13 @@ struct RepeatingAffineFEStateMap{A,B,C,D,E,F,G} <: AbstractFEStateMap K = assemble_matrix((u,v) -> biform(u,v,φh),assem_U0,U0,V0) b = allocate_in_range(K); fill!(b,zero(eltype(b))) b0 = allocate_in_range(K); fill!(b0,zero(eltype(b0))) - x = mortar(map(i -> allocate_in_domain(K), 1:nblocks)); fill!(x,zero(eltype(x))) + x = repeated_allocate_in_domain(nblocks,K); fill!(x,zero(eltype(x))) ns = numerical_setup(symbolic_setup(ls,K),K) fwd_caches = (ns,K,b,x,uhd,assem_U0,b0,assem_U) ## Adjoint cache adjoint_K = assemble_matrix((u,v)->biform(v,u,φh),assem_adjoint,V0,U0) - adjoint_x = mortar(map(i -> allocate_in_domain(adjoint_K), 1:nblocks)); fill!(adjoint_x,zero(eltype(adjoint_x))) + adjoint_x = repeated_allocate_in_domain(nblocks,adjoint_K); fill!(adjoint_x,zero(eltype(adjoint_x))) adjoint_ns = numerical_setup(symbolic_setup(adjoint_ls,adjoint_K),adjoint_K) adj_caches = (adjoint_ns,adjoint_K,adjoint_x,assem_adjoint) @@ -782,6 +782,7 @@ end repeated_blocks(V0::FESpace,x::AbstractBlockVector) = blocks(x) repeated_blocks(V0::FESpace,xh) = xh +repeated_blocks(V0::MultiFieldSpaceTypes,x::AbstractBlockVector) = repeated_blocks(MultiFieldStyle(V0),V0,x) repeated_blocks(V0::MultiFieldSpaceTypes,x) = repeated_blocks(MultiFieldStyle(V0),V0,x) repeated_blocks(::ConsecutiveMultiFieldStyle,V0,x::AbstractBlockVector) = blocks(x) repeated_blocks(::ConsecutiveMultiFieldStyle,V0,xh) = xh @@ -798,13 +799,21 @@ function repeated_blocks(::BlockMultiFieldStyle{NB},V0::MultiFieldSpaceTypes,x:: end function repeated_blocks(::BlockMultiFieldStyle,V0::MultiFieldSpaceTypes,xh) - x_blocks = repeated_blocks(MultiFieldStyle(V0),V0,get_free_values(xh)) + x_blocks = repeated_blocks(MultiFieldStyle(V0),V0,get_free_dof_values(xh)) rep_blocks = map(x_blocks) do xb FEFunction(V0,xb) end return rep_blocks end +function repeated_allocate_in_domain(nblocks::Integer,M::AbstractMatrix) + mortar(map(i -> allocate_in_domain(M), 1:nblocks)) +end + +function repeated_allocate_in_domain(nblocks::Integer,M::AbstractBlockMatrix) + mortar(vcat(map(i -> blocks(allocate_in_domain(M)), 1:nblocks)...)) +end + get_state(m::RepeatingAffineFEStateMap) = FEFunction(get_trial_space(m),m.fwd_caches[4]) get_measure(m::RepeatingAffineFEStateMap) = m.biform.dΩ get_spaces(m::RepeatingAffineFEStateMap) = m.spaces diff --git a/src/GridapExtensions.jl b/src/GridapExtensions.jl index 6b6b9991..3e8b6e4b 100644 --- a/src/GridapExtensions.jl +++ b/src/GridapExtensions.jl @@ -62,11 +62,24 @@ end get_local_matrix_type(a::Assembler) = get_matrix_type(a) get_local_vector_type(a::Assembler) = get_vector_type(a) +get_local_assembly_strategy(a::Assembler) = get_assembly_strategy(a) function get_local_matrix_type(a::GridapDistributed.DistributedSparseMatrixAssembler) return getany(map(get_matrix_type,a.assems)) end - function get_local_vector_type(a::GridapDistributed.DistributedSparseMatrixAssembler) return getany(map(get_vector_type,a.assems)) end +function get_local_assembly_strategy(a::GridapDistributed.DistributedSparseMatrixAssembler) + return get_assembly_strategy(a) +end + +function get_local_matrix_type(a::MultiField.BlockSparseMatrixAssembler) + return get_local_matrix_type(first(a.block_assemblers)) +end +function get_local_vector_type(a::MultiField.BlockSparseMatrixAssembler) + return get_local_vector_type(first(a.block_assemblers)) +end +function get_local_assembly_strategy(a::MultiField.BlockSparseMatrixAssembler) + return get_local_assembly_strategy(first(a.block_assemblers)) +end From 249b60b3c856177db1a8b07e4b870826c8c9fc9a Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Tue, 23 Apr 2024 16:44:58 +1000 Subject: [PATCH 63/90] More fixes for Lyra jobs --- scripts/Benchmarks/jobtemplate.sh | 4 ++++ scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs | 4 ++++ scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs | 4 ++++ scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs | 4 ++++ scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs | 4 ++++ scripts/MPI/jobs/3d_inverter_ALM.pbs | 4 ++++ scripts/MPI/jobs/3d_inverter_HPM.pbs | 4 ++++ scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs | 4 ++++ scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs | 4 ++++ scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs | 4 ++++ scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs | 4 ++++ scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs | 4 ++++ scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs | 4 ++++ scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs | 4 ++++ 14 files changed, 56 insertions(+) diff --git a/scripts/Benchmarks/jobtemplate.sh b/scripts/Benchmarks/jobtemplate.sh index 09e204c3..049acb79 100644 --- a/scripts/Benchmarks/jobtemplate.sh +++ b/scripts/Benchmarks/jobtemplate.sh @@ -5,6 +5,10 @@ #PBS -l select={{:ncpus}}:ncpus=1:mpiprocs=1:ompthreads=1:mem={{:mem}}GB:cputype={{:cputype}} #PBS -l walltime={{:wallhr}}:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/{{:dir_name}}/ diff --git a/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs b/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs index 20e7f3c6..9ab66596 100644 --- a/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs @@ -5,6 +5,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ diff --git a/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs b/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs index b0f29779..58b91b3a 100644 --- a/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs @@ -5,6 +5,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ diff --git a/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs b/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs index 7fd9279a..67935f3b 100644 --- a/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs +++ b/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs @@ -5,6 +5,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ diff --git a/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs b/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs index ffa8d005..5a1e636d 100644 --- a/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs +++ b/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs @@ -5,6 +5,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ diff --git a/scripts/MPI/jobs/3d_inverter_ALM.pbs b/scripts/MPI/jobs/3d_inverter_ALM.pbs index 54b6311b..1eb0f7f2 100644 --- a/scripts/MPI/jobs/3d_inverter_ALM.pbs +++ b/scripts/MPI/jobs/3d_inverter_ALM.pbs @@ -6,6 +6,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ diff --git a/scripts/MPI/jobs/3d_inverter_HPM.pbs b/scripts/MPI/jobs/3d_inverter_HPM.pbs index c0390d54..66365043 100644 --- a/scripts/MPI/jobs/3d_inverter_HPM.pbs +++ b/scripts/MPI/jobs/3d_inverter_HPM.pbs @@ -6,6 +6,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ diff --git a/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs b/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs index de3e8b48..985235f3 100644 --- a/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs @@ -6,6 +6,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ diff --git a/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs b/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs index f456d8a7..5d69d821 100644 --- a/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs +++ b/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs @@ -6,6 +6,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ diff --git a/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs index 94a34cfa..b257f199 100644 --- a/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs @@ -6,6 +6,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ diff --git a/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs index 5a8b0387..c2fd001a 100644 --- a/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs @@ -6,6 +6,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ diff --git a/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs index 9da69050..e56cd3d1 100644 --- a/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs @@ -6,6 +6,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ diff --git a/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs index 6cfc5060..a2c4e55c 100644 --- a/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs @@ -6,6 +6,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ diff --git a/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs index d24b04a1..775f4a00 100644 --- a/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs @@ -6,6 +6,10 @@ #PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 #PBS -l walltime=23:00:00 #PBS -j oe +#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh +#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh +#PBS -v I_MPI_HYDRA_IFACE=ib0 +#PBS -v OMP_NUM_THREADS=1 source $HOME/hpc-environments-main/lyra/load-intel.sh PROJECT_DIR=$HOME/LevelSetTopOpt/ From 5c1ba52cc8f8946595bd145d5762ee7c590fc6ef Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Fri, 26 Apr 2024 06:27:02 +1000 Subject: [PATCH 64/90] script fix --- scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl index ff76c4a0..d1b3c677 100644 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -77,8 +77,7 @@ function main(mesh_partition,distribute) C1(u,φ,dΩ,dΓ_in,dΓ_out) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ dC1(q,u,φ,dΩ,dΓ_in,dΓ_out) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ C2(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out - pcfs = PDEConstrainedFunctionals(J,[C1,C2],state_map, - analytic_dJ=dJ,analytic_dC=[dC1,nothing]) + pcfs = PDEConstrainedFunctionals(J,[C1,C2],state_map,analytic_dC=[dC1,nothing]) # Velocity extension α = 4max_steps*γ*maximum(get_el_Δ(model)) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ From ad05548ba08b7730eb750b83cad8aecd3d0a9243 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Fri, 26 Apr 2024 16:34:40 +1000 Subject: [PATCH 65/90] added bmarks for gadi --- .../generate_benchmark_scripts_gadi.jl | 95 +++++++++++++++++++ scripts/Benchmarks/jobtemplate_gadi.sh | 26 +++++ 2 files changed, 121 insertions(+) create mode 100644 scripts/Benchmarks/generate_benchmark_scripts_gadi.jl create mode 100644 scripts/Benchmarks/jobtemplate_gadi.sh diff --git a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl new file mode 100644 index 00000000..8f2eb50f --- /dev/null +++ b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl @@ -0,0 +1,95 @@ +using Pkg +Pkg.activate() +using Mustache + +function generate( + template, + name, + type, + bmark_type, + cputype, + wallhr, + n_mesh_partition, + n_el_size, + fe_order, + verbose, + dir_name, + write_dir, + nreps + ) + + ncpus = n_mesh_partition^3 + wallhr = occursin("STRONG",name) && n_mesh_partition <= 3 ? 100 : wallhr + mem = occursin("STRONG",name) && n_mesh_partition == 1 ? 256 : + occursin("STRONG",name) && n_mesh_partition == 2 ? 32 : gb_per_cpu; + + settings = (;name,type,bmark_type,cputype,wallhr,ncpus,mem, + n_mesh_partition,n_el_size,fe_order,verbose,dir_name,write_dir,nreps) + Mustache.render(template, settings) +end + +function generate_jobs(template,phys_type,ndof_per_node,bmark_types) + npart = (N).^3; + weak_el_x = @. floor(Int,(dofs_per_proc*npart/ndof_per_node)^(1/3)-1); + dof_sanity_check = @.(floor(Int,ndof_per_node*(weak_el_x+1)^3/npart)), + maximum(abs,@. ndof_per_node*(weak_el_x+1)^3/npart/dofs_per_proc - 1) + + sname(phys_type,ndof_per_node,n,elx) = "STRONG_$(phys_type)_dof$(ndof_per_node)_N$(n)_elx$(elx)" + wname(phys_type,ndof_per_node,n,elx) = "WEAK_$(phys_type)_dof$(ndof_per_node)_N$(n)_elx$(elx)" + + strong_el_x = ceil(Int,(strong_dof/ndof_per_node)^(1/3)); + + strong_jobs = map(n->(sname(phys_type,ndof_per_node,n,strong_el_x), + generate(template,sname(phys_type,ndof_per_node,n,strong_el_x),phys_type,bmark_types, + cputype,wallhr,n,strong_el_x,fe_order,verbose,dir_name,write_dir,nreps)),N) + weak_jobs = map((n,elx)->(wname(phys_type,ndof_per_node,n,elx), + generate(template,wname(phys_type,ndof_per_node,n,elx),phys_type,bmark_types, + cputype,wallhr,n,elx,fe_order,verbose,dir_name,write_dir,nreps)),N,weak_el_x) + + strong_jobs,weak_jobs,dof_sanity_check +end + +dir_name= "LevelSetTopOpt"; +job_output_path = "\$SCRATCH/$dir_name/scripts/Benchmarks/jobs-gadi/"; +mkpath(job_output_path); + +# SETUP PARAMETERS +cputype=""; # Not needed here +gb_per_cpu = 8 # GB +wallhr = 3 ; # Hours (Note may want to manually change some afterwards) + +nreps = 10; # Number of benchmark repetitions +dofs_per_proc = 32000; +fe_order= 1; +verbose= 1; +write_dir = "\$SCRATCH/$dir_name/results/benchmarks/" + +N = 1:10; # Number of partitions in x-axis +strong_dof=(100+1)^3*3; # Number of dofs for strong scaling + +# Phys type and number of dofs per node, and what to benchmark +phys_types = [ + ("THERM",1,"bopt0,bopt1,bfwd,badv,breinit,bvelext"), + ("ELAST",3,"bopt0,bopt1,bfwd,badv,breinit,bvelext"), + ("NLELAST",3,"bopt0,bopt1,bfwd"), + # ("INVERTER_HPM",3,"bhpm"), +]; + +# Template +template = read("\$SCRATCH/$dir_name/scripts/Benchmarks/jobtemplate_gadi.sh",String) + +## Generate Jobs +jobs_by_phys = map(x->(x[1],generate_jobs(template,x[1],x[2],x[3])),phys_types); + +for jobs in jobs_by_phys + strong_jobs,weak_jobs,dof_sanity_check = jobs[2] + + println("$(jobs[1]): Weak dofs = $(dof_sanity_check[1])\n Error = $(dof_sanity_check[2])\n") + for job in vcat(strong_jobs,weak_jobs) + name = job[1] + content = job[2] + open(job_output_path*"$name.pbs","w") do f + write(f,content) + end + end +end \ No newline at end of file diff --git a/scripts/Benchmarks/jobtemplate_gadi.sh b/scripts/Benchmarks/jobtemplate_gadi.sh new file mode 100644 index 00000000..63dfe4d8 --- /dev/null +++ b/scripts/Benchmarks/jobtemplate_gadi.sh @@ -0,0 +1,26 @@ +#!/bin/bash + +#PBS -P np01 +#PBS -q normal +#PBS -N "{{:name}}" +#PBS -l ncpus={{:ncpus}} +#PBS -l mem={{:mem}}GB +#PBS -l walltime={{:wallhr}}:00:00 +#PBS -j oe + +source $HOME/hpc-environments/gadi/load-intel.sh +PROJECT_DIR=$SCRATCH/{{:dir_name}}/ + +julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" + +mpirun -n {{:ncpus}} julia --project=$PROJECT_DIR --check-bounds no -O3 \ + $PROJECT_DIR/scripts/Benchmarks/benchmark.jl \ + {{:name}} \ + {{{:write_dir}}} \ + {{:type}} \ + {{:bmark_type}} \ + {{:n_mesh_partition}} \ + {{:n_el_size}} \ + {{:fe_order}} \ + {{:verbose}} \ + {{:nreps}} \ No newline at end of file From 9601445d3668c0a54ba276d6eb5099d9970a8955 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Fri, 26 Apr 2024 17:07:38 +1000 Subject: [PATCH 66/90] fix --- scripts/Benchmarks/generate_benchmark_scripts_gadi.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl index 8f2eb50f..d1988f80 100644 --- a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl +++ b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl @@ -50,7 +50,7 @@ function generate_jobs(template,phys_type,ndof_per_node,bmark_types) end dir_name= "LevelSetTopOpt"; -job_output_path = "\$SCRATCH/$dir_name/scripts/Benchmarks/jobs-gadi/"; +job_output_path = "./$dir_name/scripts/Benchmarks/jobs-gadi/"; mkpath(job_output_path); # SETUP PARAMETERS @@ -76,7 +76,7 @@ phys_types = [ ]; # Template -template = read("\$SCRATCH/$dir_name/scripts/Benchmarks/jobtemplate_gadi.sh",String) +template = read("./$dir_name/scripts/Benchmarks/jobtemplate_gadi.sh",String) ## Generate Jobs jobs_by_phys = map(x->(x[1],generate_jobs(template,x[1],x[2],x[3])),phys_types); From df1718fbf8d142a6e2425b1c8327f3637522651a Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Fri, 26 Apr 2024 17:08:48 +1000 Subject: [PATCH 67/90] another fix --- scripts/Benchmarks/generate_benchmark_scripts_gadi.jl | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl index d1988f80..bf288c4b 100644 --- a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl +++ b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl @@ -50,7 +50,7 @@ function generate_jobs(template,phys_type,ndof_per_node,bmark_types) end dir_name= "LevelSetTopOpt"; -job_output_path = "./$dir_name/scripts/Benchmarks/jobs-gadi/"; +job_output_path = "$(ENV["SCRATCH"])/$dir_name/scripts/Benchmarks/jobs-gadi/"; mkpath(job_output_path); # SETUP PARAMETERS @@ -76,7 +76,7 @@ phys_types = [ ]; # Template -template = read("./$dir_name/scripts/Benchmarks/jobtemplate_gadi.sh",String) +template = read("$(ENV["SCRATCH"])/$dir_name/scripts/Benchmarks/jobtemplate_gadi.sh",String) ## Generate Jobs jobs_by_phys = map(x->(x[1],generate_jobs(template,x[1],x[2],x[3])),phys_types); From 16b8293a74b614a3eda1be6dc9b8f017440cefec Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Fri, 26 Apr 2024 21:58:24 +1000 Subject: [PATCH 68/90] Fixed bmarks for gadi --- scripts/Benchmarks/benchmark_gadi.jl | 460 ++++++++++++++++++ .../generate_benchmark_scripts_gadi.jl | 50 +- scripts/Benchmarks/jobtemplate_gadi.sh | 6 +- 3 files changed, 499 insertions(+), 17 deletions(-) create mode 100644 scripts/Benchmarks/benchmark_gadi.jl diff --git a/scripts/Benchmarks/benchmark_gadi.jl b/scripts/Benchmarks/benchmark_gadi.jl new file mode 100644 index 00000000..c3dc701c --- /dev/null +++ b/scripts/Benchmarks/benchmark_gadi.jl @@ -0,0 +1,460 @@ +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, + PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + +using LevelSetTopOpt: get_deriv_space, get_aux_space,benchmark_optimizer, + benchmark_forward_problem,benchmark_advection,benchmark_reinitialisation, + benchmark_velocity_extension,benchmark_hilbertian_projection_map,benchmark_single_iteration + +using GridapSolvers: NewtonSolver + +global NAME = ARGS[1] +global WRITE_DIR = ARGS[2] +global PROB_TYPE = ARGS[3] +global BMARK_TYPE = ARGS[4] +global Nx = parse(Int,ARGS[5]) +global Ny = parse(Int,ARGS[6]) +global Nz = parse(Int,ARGS[7]) +global N_EL = parse(Int,ARGS[8]) +global ORDER = parse(Int,ARGS[9]) +global VERBOSE = parse(Int,ARGS[10]) +global NREPS = parse(Int,ARGS[11]) + +function nl_elast(mesh_partition,ranks,el_size,order,verbose) + # FE parameters + xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size + dom = (0,xmax,0,ymax,0,zmax) # Bounding domain + prop_Γ_N = 0.2 # Γ_N size parameter + f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function + (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& + (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0) # Γ_D indicator function + # FD parameters + γ = 0.1 # HJ eqn time step coeff + γ_reinit = 0.5 # Reinit. eqn time step coeff + max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection + tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance + # Problem parameters + E = 1000 # Young's modulus + ν = 0.3 # Poisson's ratio + μ, λ = E/(2*(1 + ν)), E*ν/((1 + ν)*(1 - 2*ν)) # Lame constants + g = VectorValue(0,0,-1) # Applied load on Γ_N + vf = 0.4 # Volume fraction constraint + lsf_func = initial_lsf(4,0.2) # Initial level set function + # Model + model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); + update_labels!(1,model,f_Γ_D,"Gamma_D") + update_labels!(2,model,f_Γ_N,"Gamma_N") + # Triangulation and measures + Ω = Triangulation(model) + Γ_N = BoundaryTriangulation(model,tags="Gamma_N") + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + # Spaces + reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) + V_φ = TestFESpace(model,reffe_scalar) + V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) + U_reg = TrialFESpace(V_reg,0) + # Level set and interpolator + φh = interpolate(lsf_func,V_φ) + interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + # Weak formulation + ## Piola-Kirchhoff tensor + function S(∇u) + Cinv = inv(C(F(∇u))) + μ*(one(∇u)-Cinv) + λ*log(J(F(∇u)))*Cinv + end + ## Derivative of Green strain + dE(∇du,∇u) = 0.5*( ∇du⋅F(∇u) + (∇du⋅F(∇u))' ) + ## Right Cauchy-Green deformation tensor + C(F) = (F')⋅F + ## Deformation gradient tensor + F(∇u) = one(∇u) + ∇u' + ## Volume change + J(F) = sqrt(det(C(F))) + ## Residual + res(u,v,φ,dΩ,dΓ_N) = ∫( (I ∘ φ)*((dE ∘ (∇(v),∇(u))) ⊙ (S ∘ ∇(u))) )*dΩ - ∫(g⋅v)dΓ_N + Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} + Tv = Vector{PetscScalar} + lin_solver = ElasticitySolver(V) + nl_solver = NewtonSolver(lin_solver;maxiter=50,rtol=10^-8,verbose) + state_map = NonlinearFEStateMap( + res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; + assem_U = SparseMatrixAssembler(Tm,Tv,U,V), + assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), + assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), + nls = nl_solver, adjoint_ls = lin_solver + ) + # Objective and constraints + J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*((dE ∘ (∇(u),∇(u))) ⊙ (S ∘ ∇(u))))dΩ + vol_D = sum(∫(1)dΩ) + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C1],state_map,analytic_dC=[dC1]) + # Velocity extension + α = 4max_steps*γ*maximum(get_el_Δ(model)) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ + vel_ext = VelocityExtension( + a_hilb, U_reg, V_reg; + assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), + ls = PETScLinearSolver() + ) + # Finite difference scheme + scheme = FirstOrderStencil(length(el_size),Float64) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + # Optimiser + return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose) +end + +function therm(mesh_partition,ranks,el_size,order,verbose) + # FE parameters + xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size + dom = (0,xmax,0,ymax,0,zmax) # Bounding domain + prop_Γ_N = 0.2 # Γ_N size parameter + prop_Γ_D = 0.2 # Γ_D size parameter + f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function + (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& + (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function + (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps()) && + (x[3] <= zmax*prop_Γ_D + eps() || x[3] >= zmax-zmax*prop_Γ_D - eps()) + # FD parameters + γ = 0.1 # HJ eqn time step coeff + γ_reinit = 0.5 # Reinit. eqn time step coeff + max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection + tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance + # Problem parameters + κ = 1 # Diffusivity + g = 1 # Heat flow in + vf = 0.4 # Volume fraction constraint + lsf_func = initial_lsf(4,0.2) # Initial level set function + # Model + model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); + update_labels!(1,model,f_Γ_D,"Gamma_D") + update_labels!(2,model,f_Γ_N,"Gamma_N") + # Triangulation and measures + Ω = Triangulation(model) + Γ_N = BoundaryTriangulation(model,tags="Gamma_N") + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + # Spaces + reffe = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,0.0) + V_φ = TestFESpace(model,reffe) + V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) + U_reg = TrialFESpace(V_reg,0) + # Level set and interpolator + φh = interpolate(lsf_func,V_φ) + interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + # Weak formulation + a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ + l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N + Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} + Tv = Vector{PetscScalar} + solver = PETScLinearSolver() + state_map = AffineFEStateMap( + a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; + assem_U = SparseMatrixAssembler(Tm,Tv,U,V), + assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), + assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), + ls = solver,adjoint_ls = solver + ) + # Objective and constraints + J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ + dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + vol_D = sum(∫(1)dΩ) + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C1],state_map, + analytic_dJ=dJ,analytic_dC=[dC1]) + # Velocity extension + α = 4max_steps*γ*maximum(get_el_Δ(model)) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ + vel_ext = VelocityExtension( + a_hilb, U_reg, V_reg; + assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), + ls = solver + ) + # Finite difference scheme + scheme = FirstOrderStencil(length(el_size),Float64) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + # Optimiser + return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose) +end + +function elast(mesh_partition,ranks,el_size,order,verbose) + # FE parameters + xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size + dom = (0,xmax,0,ymax,0,zmax) # Bounding domain + prop_Γ_N = 0.2 # Γ_N size parameter + f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function + (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& + (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0) # Γ_D indicator function + # FD parameters + γ = 0.1 # HJ eqn time step coeff + γ_reinit = 0.5 # Reinit. eqn time step coeff + max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection + tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance + # Problem parameters + C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor + g = VectorValue(0,0,-1) # Applied load on Γ_N + vf = 0.4 # Volume fraction constraint + lsf_func = initial_lsf(4,0.2) # Initial level set function + # Model + model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); + update_labels!(1,model,f_Γ_D,"Gamma_D") + update_labels!(2,model,f_Γ_N,"Gamma_N") + # Triangulation and measures + Ω = Triangulation(model) + Γ_N = BoundaryTriangulation(model,tags="Gamma_N") + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + # Spaces + reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) + V_φ = TestFESpace(model,reffe_scalar) + V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) + U_reg = TrialFESpace(V_reg,0) + # Level set and interpolator + φh = interpolate(lsf_func,V_φ) + interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + # Weak formulation + a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ + l(v,φ,dΩ,dΓ_N) = ∫(v⋅g)dΓ_N + Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} + Tv = Vector{PetscScalar} + solver = ElasticitySolver(V) + state_map = AffineFEStateMap( + a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; + assem_U = SparseMatrixAssembler(Tm,Tv,U,V), + assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), + assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), + ls = solver,adjoint_ls = solver + ) + # Objective and constraints + J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(u)))dΩ + dJ(q,u,φ,dΩ,dΓ_N) = ∫((C ⊙ ε(u) ⊙ ε(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + vol_D = sum(∫(1)dΩ) + C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + pcfs = PDEConstrainedFunctionals(J,[C1],state_map, + analytic_dJ=dJ,analytic_dC=[dC1]) + # Velocity extension + α = 4max_steps*γ*maximum(get_el_Δ(model)) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ + vel_ext = VelocityExtension( + a_hilb, U_reg, V_reg; + assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), + ls = PETScLinearSolver() + ) + # Finite difference scheme + scheme = FirstOrderStencil(length(el_size),Float64) + ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) + # Optimiser + return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose) +end + +function inverter_HPM(mesh_partition,ranks,el_size,order,verbose) + ## Parameters + dom = (0,1,0,1,0,1) + γ = 0.05 + γ_reinit = 0.5 + max_steps = floor(Int,minimum(el_size)/3) + tol = 1/(2order^2)/minimum(el_size) + C = isotropic_elast_tensor(3,1.0,0.3) + η_coeff = 2 + α_coeff = 4 + vf=0.4 + δₓ=0.5 + ks = 0.01 + g = VectorValue(1,0,0) + + ## FE Setup + model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); + el_Δ = get_el_Δ(model) + f_Γ_in(x) = (x[1] ≈ 0.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && + (0.4 - eps() <= x[3] <= 0.6 + eps()) + f_Γ_out(x) = (x[1] ≈ 1.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && + (0.4 - eps() <= x[3] <= 0.6 + eps()) + f_Γ_out_ext(x) = ~f_Γ_out(x) && (0.9 <= x[1] <= 1.0) && (0.3 - eps() <= x[2] <= 0.7 + eps()) && + (0.3 - eps() <= x[3] <= 0.7 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0) && (x[2] <= 0.1 || x[2] >= 0.9) && (x[3] <= 0.1 || x[3] >= 0.9) + update_labels!(1,model,f_Γ_in,"Gamma_in") + update_labels!(2,model,f_Γ_out,"Gamma_out") + update_labels!(3,model,f_Γ_out_ext,"Gamma_out_ext") + update_labels!(4,model,f_Γ_D,"Gamma_D") + + ## Triangulations and measures + Ω = Triangulation(model) + Γ_in = BoundaryTriangulation(model,tags="Gamma_in") + Γ_out = BoundaryTriangulation(model,tags="Gamma_out") + dΩ = Measure(Ω,2*order) + dΓ_in = Measure(Γ_in,2*order) + dΓ_out = Measure(Γ_out,2*order) + vol_D = sum(∫(1)dΩ) + vol_Γ_in = sum(∫(1)dΓ_in) + vol_Γ_out = sum(∫(1)dΓ_out) + + ## Spaces + reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) + V_φ = TestFESpace(model,reffe_scalar) + V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_in","Gamma_out","Gamma_out_ext"]) + U_reg = TrialFESpace(V_reg,[0,0,0]) + + ## Create FE functions + φh = interpolate(initial_lsf(4,0.1),V_φ); + + ## Interpolation and weak form + interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + + a(u,v,φ,dΩ,dΓ_in,dΓ_out) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ + ∫(ks*(u⋅v))dΓ_out + l(v,φ,dΩ,dΓ_in,dΓ_out) = ∫(v⋅g)dΓ_in + + ## Optimisation functionals + e₁ = VectorValue(1,0,0) + J(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅e₁)/vol_Γ_in)dΓ_in + Vol(u,φ,dΩ,dΓ_in,dΓ_out) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; + dVol(q,u,φ,dΩ,dΓ_in,dΓ_out) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out + + ## Finite difference solver + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + + ## Setup solver and FE operators + Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} + Tv = Vector{PetscScalar} + solver = ElasticitySolver(V) + + state_map = AffineFEStateMap( + a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out; + assem_U = SparseMatrixAssembler(Tm,Tv,U,V), + assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), + assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), + ls = solver, adjoint_ls = solver + ) + pcfs = PDEConstrainedFunctionals(J,[Vol,UΓ_out],state_map,analytic_dC=[dVol,nothing]) + + ## Hilbertian extension-regularisation problems + α = α_coeff*maximum(el_Δ) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; + vel_ext = VelocityExtension( + a_hilb,U_reg,V_reg; + assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), + ls = PETScLinearSolver() + ) + + ## Optimiser + return HilbertianProjection(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=verbose) +end + +with_mpi() do distribute + # Setup + mesh_partition = (Nx,Ny,Nz) + ranks = distribute(LinearIndices((prod(mesh_partition),))) + el_size = (N_EL,N_EL,N_EL) + verbose = Bool(VERBOSE) ? i_am_main(ranks) : false; + if PROB_TYPE == "NLELAST" + options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + -ksp_converged_reason -ksp_rtol 1.0e-12" + opt = nl_elast + elseif PROB_TYPE == "THERM" + options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + -ksp_converged_reason -ksp_rtol 1.0e-12" + opt = therm + elseif PROB_TYPE == "ELAST" + options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + -ksp_converged_reason -ksp_rtol 1.0e-12" + opt = elast + elseif PROB_TYPE == "INVERTER_HPM" + options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + -ksp_converged_reason -ksp_rtol 1.0e-12" + opt = inverter_HPM + else + error("Problem not defined") + end + + # Output + i_am_main(ranks) && ~isdir(WRITE_DIR) && mkpath(WRITE_DIR) + # Run + t_start = PTimer(ranks); + GridapPETSc.with(args=split(options)) do + tic!(t_start;barrier=true) + optim = opt(mesh_partition,ranks,el_size,ORDER,verbose) + toc!(t_start,"startup") + startup_time = map_main(t_start.data) do data + map(x -> x.max,values(data)) + end |> PartitionedArrays.getany + bstart = i_am_main(ranks) && [startup_time; zeros(NREPS-1)] + ## Benchmark optimiser + if occursin("bopt0",BMARK_TYPE) + bopt0 = benchmark_optimizer(optim, 0, ranks; nreps=NREPS) + else + bopt0 = i_am_main(ranks) && zeros(NREPS) + end + if occursin("bopt1",BMARK_TYPE) + bopt1 = benchmark_single_iteration(optim, ranks; nreps = NREPS) + else + bopt1 = i_am_main(ranks) && zeros(NREPS) + end + ## Benchmark reinitialisation + if occursin("breinit",BMARK_TYPE) + breinit = benchmark_reinitialisation(optim.ls_evolver, get_free_dof_values(optim.φ0), 0.1, ranks; nreps=NREPS) + else + breinit = i_am_main(ranks) && zeros(NREPS) + end + ## Benchmark forward problem + if occursin("bfwd",BMARK_TYPE) + bfwd = benchmark_forward_problem(optim.problem.state_map, optim.φ0, ranks; nreps=NREPS) + else + bfwd = i_am_main(ranks) && zeros(NREPS) + end + ## Benchmark advection + reinit!(optim.ls_evolver,optim.φ0,optim.params.γ_reinit) + if occursin("badv",BMARK_TYPE) + vh = interpolate(FEFunction(get_deriv_space(optim.problem.state_map),optim.problem.dJ), + get_aux_space(optim.problem.state_map)) + v = get_free_dof_values(vh) + badv = benchmark_advection(optim.ls_evolver, get_free_dof_values(optim.φ0), v, 0.1, ranks; nreps=NREPS) + else + badv = i_am_main(ranks) && zeros(NREPS) + end + ## Benchmark velocity extension + if occursin("bvelext",BMARK_TYPE) + bvelext = benchmark_velocity_extension(optim.vel_ext, optim.problem.dJ, ranks; nreps=NREPS) + else + bvelext = i_am_main(ranks) && zeros(NREPS) + end + ## HPM + if occursin("bhpm",BMARK_TYPE) + @assert typeof(optim) <: HilbertianProjection + J, C, dJ, dC = Gridap.evaluate!(optim.problem,optim.φ0) + optim.projector,dJ,C,dC,optim.vel_ext.K + bhpm = benchmark_hilbertian_projection_map(optim.projector,dJ,C,dC,optim.vel_ext.K,ranks) + else + bhpm = i_am_main(ranks) && zeros(NREPS) + end + ## Write results + if i_am_main(ranks) + open(WRITE_DIR*NAME*".txt","w") do f + bcontent = "startup,bopt(0),bopt(1),bfwd,badv,breinit,bvelext,bhpm\n" + for i = 1:NREPS + bcontent *= "$(bstart[i]),$(bopt0[i]),$(bopt1[i]),$(bfwd[i]),$(badv[i]),$(breinit[i]),$(bvelext[i]),$(bhpm[i])\n" + end + write(f,bcontent) + end + end + end +end \ No newline at end of file diff --git a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl index bf288c4b..453ff8c0 100644 --- a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl +++ b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl @@ -2,6 +2,21 @@ using Pkg Pkg.activate() using Mustache +# These are generated by solving +# Minimise X + Y + Z s.t. X*Y*Z=i*48 for X,Y,Z∈ℤ⁺ (See bottom) +mesh_partitions = [(4, 4, 3),(4, 4, 6),(4, 6, 6),(4, 6, 8),(5, 6, 8),(6, 6, 8),(7, 6, 8),(6, 8, 8),(6, 9, 8),(10, 6, 8), + (11, 6, 8),(9, 8, 8),(13, 6, 8),(12, 7, 8),(10, 9, 8),(12, 8, 8),(6, 8, 17),(12, 9, 8),(6, 8, 19), + (10, 12, 8),(14, 9, 8),(11, 12, 8),(6, 8, 23),(12, 12, 8),(10, 10, 12),(13, 12, 8),(12, 12, 9),(12, 14, 8), + (6, 8, 29),(10, 12, 12),(6, 8, 31),(8, 12, 16),(11, 12, 12),(8, 12, 17),(10, 12, 14),(12, 12, 12),(6, 8, 37), + (8, 12, 19),(13, 12, 12),(10, 12, 16),(6, 8, 41),(12, 12, 14),(6, 8, 43),(11, 12, 16),(12, 12, 15),(8, 12, 23), + (6, 8, 47),(12, 12, 16),(12, 14, 14),(10, 15, 16),(12, 12, 17),(12, 13, 16),(6, 8, 53),(12, 12, 18),(11, 15, 16), + (12, 14, 16),(12, 12, 19),(8, 12, 29),(6, 8, 59),(12, 15, 16),(6, 8, 61),(8, 12, 31),(12, 14, 18),(12, 16, 16), + (13, 15, 16),(11, 16, 18),(6, 8, 67),(12, 16, 17),(12, 12, 23),(14, 15, 16),(6, 8, 71),(12, 16, 18),(6, 8, 73), + (8, 12, 37),(15, 15, 16),(12, 16, 19),(11, 16, 21),(13, 16, 18),(6, 8, 79),(15, 16, 16),(12, 18, 18),(8, 12, 41), + (6, 8, 83),(14, 16, 18),(15, 16, 17),(8, 12, 43),(12, 12, 29),(12, 16, 22),(6, 8, 89),(15, 16, 18)] + +@assert Int.(prod.(mesh_partitions)/48) == collect(1:length(mesh_partitions)) + function generate( template, name, @@ -9,7 +24,7 @@ function generate( bmark_type, cputype, wallhr, - n_mesh_partition, + mesh_partition, n_el_size, fe_order, verbose, @@ -18,33 +33,34 @@ function generate( nreps ) - ncpus = n_mesh_partition^3 - wallhr = occursin("STRONG",name) && n_mesh_partition <= 3 ? 100 : wallhr - mem = occursin("STRONG",name) && n_mesh_partition == 1 ? 256 : - occursin("STRONG",name) && n_mesh_partition == 2 ? 32 : gb_per_cpu; + ncpus = prod(mesh_partition) + wallhr = occursin("STRONG",name) && ncpus <= 8 ? 100 : wallhr + mem = occursin("STRONG",name) && ncpus == 1 ? 100 : + occursin("STRONG",name) && ncpus == 8 ? 32 : Int(gb_per_node*ncpus/cps_per_node); + Nx_partition, Ny_partition, Nz_partition = mesh_partition settings = (;name,type,bmark_type,cputype,wallhr,ncpus,mem, - n_mesh_partition,n_el_size,fe_order,verbose,dir_name,write_dir,nreps) + Nx_partition,Ny_partition,Nz_partition,n_el_size,fe_order,verbose,dir_name,write_dir,nreps) Mustache.render(template, settings) end function generate_jobs(template,phys_type,ndof_per_node,bmark_types) - npart = (N).^3; + npart = prod.(parts) weak_el_x = @. floor(Int,(dofs_per_proc*npart/ndof_per_node)^(1/3)-1); dof_sanity_check = @.(floor(Int,ndof_per_node*(weak_el_x+1)^3/npart)), maximum(abs,@. ndof_per_node*(weak_el_x+1)^3/npart/dofs_per_proc - 1) - sname(phys_type,ndof_per_node,n,elx) = "STRONG_$(phys_type)_dof$(ndof_per_node)_N$(n)_elx$(elx)" - wname(phys_type,ndof_per_node,n,elx) = "WEAK_$(phys_type)_dof$(ndof_per_node)_N$(n)_elx$(elx)" + sname(phys_type,ndof_per_node,n,elx) = "STRONG_$(phys_type)_dof$(ndof_per_node)_N$(prod(n))_elx$(elx)" + wname(phys_type,ndof_per_node,n,elx) = "WEAK_$(phys_type)_dof$(ndof_per_node)_N$(prod(n))_elx$(elx)" strong_el_x = ceil(Int,(strong_dof/ndof_per_node)^(1/3)); strong_jobs = map(n->(sname(phys_type,ndof_per_node,n,strong_el_x), generate(template,sname(phys_type,ndof_per_node,n,strong_el_x),phys_type,bmark_types, - cputype,wallhr,n,strong_el_x,fe_order,verbose,dir_name,write_dir,nreps)),N) + cputype,wallhr,n,strong_el_x,fe_order,verbose,dir_name,write_dir,nreps)),parts) weak_jobs = map((n,elx)->(wname(phys_type,ndof_per_node,n,elx), generate(template,wname(phys_type,ndof_per_node,n,elx),phys_type,bmark_types, - cputype,wallhr,n,elx,fe_order,verbose,dir_name,write_dir,nreps)),N,weak_el_x) + cputype,wallhr,n,elx,fe_order,verbose,dir_name,write_dir,nreps)),parts,weak_el_x) strong_jobs,weak_jobs,dof_sanity_check end @@ -55,7 +71,8 @@ mkpath(job_output_path); # SETUP PARAMETERS cputype=""; # Not needed here -gb_per_cpu = 8 # GB +gb_per_node = 192 # GB +cps_per_node = 48 wallhr = 3 ; # Hours (Note may want to manually change some afterwards) nreps = 10; # Number of benchmark repetitions @@ -64,7 +81,7 @@ fe_order= 1; verbose= 1; write_dir = "\$SCRATCH/$dir_name/results/benchmarks/" -N = 1:10; # Number of partitions in x-axis +parts = [(1,1,1);(2,2,2);(3,3,3);mesh_partitions[1:3:22]] # Mesh partitions strong_dof=(100+1)^3*3; # Number of dofs for strong scaling # Phys type and number of dofs per node, and what to benchmark @@ -92,4 +109,9 @@ for jobs in jobs_by_phys write(f,content) end end -end \ No newline at end of file +end + +# Mathematica code: +# F[N_]:=Minimize[{X+Y+Z,X*Y*Z==N*48, X>0, Y>0, Z>0,X\[Element] Integers,Y\[Element] Integers,Z\[Element] Integers},{X,Y,Z}] +# For[i=1,i<=50,i++,X[i]=F[i]]; +# For[i=1,i<=90,i++,Print[{X[i][[2]][[1]][[2]],X[i][[2]][[2]][[2]],X[i][[2]][[3]][[2]]}]] \ No newline at end of file diff --git a/scripts/Benchmarks/jobtemplate_gadi.sh b/scripts/Benchmarks/jobtemplate_gadi.sh index 63dfe4d8..63ef1507 100644 --- a/scripts/Benchmarks/jobtemplate_gadi.sh +++ b/scripts/Benchmarks/jobtemplate_gadi.sh @@ -11,15 +11,15 @@ source $HOME/hpc-environments/gadi/load-intel.sh PROJECT_DIR=$SCRATCH/{{:dir_name}}/ -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - mpirun -n {{:ncpus}} julia --project=$PROJECT_DIR --check-bounds no -O3 \ $PROJECT_DIR/scripts/Benchmarks/benchmark.jl \ {{:name}} \ {{{:write_dir}}} \ {{:type}} \ {{:bmark_type}} \ - {{:n_mesh_partition}} \ + {{:Nx_partition}} \ + {{:Ny_partition}} \ + {{:Nz_partition}} \ {{:n_el_size}} \ {{:fe_order}} \ {{:verbose}} \ From 4de04fc1f6ba8b55771d5ecbe8625448b0609f4a Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Fri, 26 Apr 2024 22:21:21 +1000 Subject: [PATCH 69/90] Missing gadi --- scripts/Benchmarks/jobtemplate_gadi.sh | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/Benchmarks/jobtemplate_gadi.sh b/scripts/Benchmarks/jobtemplate_gadi.sh index 63ef1507..5d41e56a 100644 --- a/scripts/Benchmarks/jobtemplate_gadi.sh +++ b/scripts/Benchmarks/jobtemplate_gadi.sh @@ -12,7 +12,7 @@ source $HOME/hpc-environments/gadi/load-intel.sh PROJECT_DIR=$SCRATCH/{{:dir_name}}/ mpirun -n {{:ncpus}} julia --project=$PROJECT_DIR --check-bounds no -O3 \ - $PROJECT_DIR/scripts/Benchmarks/benchmark.jl \ + $PROJECT_DIR/scripts/Benchmarks/benchmark_gadi.jl \ {{:name}} \ {{{:write_dir}}} \ {{:type}} \ From c02c65692d5030cfdf6f798fc4fbd77e92f77456 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Fri, 26 Apr 2024 23:15:13 +1000 Subject: [PATCH 70/90] adjust script for gadi --- scripts/Benchmarks/generate_benchmark_scripts_gadi.jl | 5 ++++- scripts/Benchmarks/jobtemplate_gadi.sh | 2 +- 2 files changed, 5 insertions(+), 2 deletions(-) diff --git a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl index 453ff8c0..a313cb83 100644 --- a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl +++ b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl @@ -81,7 +81,10 @@ fe_order= 1; verbose= 1; write_dir = "\$SCRATCH/$dir_name/results/benchmarks/" -parts = [(1,1,1);(2,2,2);(3,3,3);mesh_partitions[1:3:22]] # Mesh partitions +# parts = [(1,1,1);(2,2,2);(3,3,3);mesh_partitions[1:3:22]] # Mesh partitions +# parts = [(1,1,1);mesh_partitions[1:2:20]] +# parts = [(1,1,1);mesh_partitions[[1,2,3,4,5]];mesh_partitions[8:4:20]] +parts = [(1,1,1);mesh_partitions[[1,2,3,5]];mesh_partitions[8:5:23]] strong_dof=(100+1)^3*3; # Number of dofs for strong scaling # Phys type and number of dofs per node, and what to benchmark diff --git a/scripts/Benchmarks/jobtemplate_gadi.sh b/scripts/Benchmarks/jobtemplate_gadi.sh index 5d41e56a..4bee92f9 100644 --- a/scripts/Benchmarks/jobtemplate_gadi.sh +++ b/scripts/Benchmarks/jobtemplate_gadi.sh @@ -11,7 +11,7 @@ source $HOME/hpc-environments/gadi/load-intel.sh PROJECT_DIR=$SCRATCH/{{:dir_name}}/ -mpirun -n {{:ncpus}} julia --project=$PROJECT_DIR --check-bounds no -O3 \ +mpiexec -n {{:ncpus}} julia --project=$PROJECT_DIR --check-bounds no -O3 \ $PROJECT_DIR/scripts/Benchmarks/benchmark_gadi.jl \ {{:name}} \ {{{:write_dir}}} \ From fce7613a53c3946b283629fc04e5b1ff208a3fff Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sat, 27 Apr 2024 08:32:55 +1000 Subject: [PATCH 71/90] adjust for first two runs --- scripts/Benchmarks/generate_benchmark_scripts_gadi.jl | 11 ++++------- 1 file changed, 4 insertions(+), 7 deletions(-) diff --git a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl index a313cb83..469e1220 100644 --- a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl +++ b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl @@ -34,9 +34,9 @@ function generate( ) ncpus = prod(mesh_partition) - wallhr = occursin("STRONG",name) && ncpus <= 8 ? 100 : wallhr - mem = occursin("STRONG",name) && ncpus == 1 ? 100 : - occursin("STRONG",name) && ncpus == 8 ? 32 : Int(gb_per_node*ncpus/cps_per_node); + wallhr = occursin("STRONG",name) && ncpus == 1 ? 100 : + occursin("STRONG",name) && ncpus == 8 ? 24 : wallhr + mem = occursin("STRONG",name) && ncpus == 1 ? 100 : Int(gb_per_node*ncpus/cps_per_node); Nx_partition, Ny_partition, Nz_partition = mesh_partition settings = (;name,type,bmark_type,cputype,wallhr,ncpus,mem, @@ -81,10 +81,7 @@ fe_order= 1; verbose= 1; write_dir = "\$SCRATCH/$dir_name/results/benchmarks/" -# parts = [(1,1,1);(2,2,2);(3,3,3);mesh_partitions[1:3:22]] # Mesh partitions -# parts = [(1,1,1);mesh_partitions[1:2:20]] -# parts = [(1,1,1);mesh_partitions[[1,2,3,4,5]];mesh_partitions[8:4:20]] -parts = [(1,1,1);mesh_partitions[[1,2,3,5]];mesh_partitions[8:5:23]] +parts = [(2,2,2);(3,3,3);mesh_partitions[[1,2,3,5]];mesh_partitions[8:5:23]] strong_dof=(100+1)^3*3; # Number of dofs for strong scaling # Phys type and number of dofs per node, and what to benchmark From ba203403df533fd84d9f7bb9b5c1b07e06b6c160 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sat, 27 Apr 2024 10:14:09 +1000 Subject: [PATCH 72/90] add full TO scripts for gadi --- .../Benchmarks/generate_benchmark_scripts_gadi.jl | 7 +++++-- scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl | 2 +- .../_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl | 2 +- scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl | 2 +- scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 2 +- .../Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs | 14 ++++++++++++++ .../jobs-gadi/hyperelast_comp_MPI_3D.pbs | 14 ++++++++++++++ .../Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs | 14 ++++++++++++++ .../Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs | 14 ++++++++++++++ .../Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs | 14 ++++++++++++++ scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl | 2 +- 11 files changed, 80 insertions(+), 7 deletions(-) create mode 100644 scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs create mode 100644 scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs create mode 100644 scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs create mode 100644 scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs create mode 100644 scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs diff --git a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl index 469e1220..f142b86b 100644 --- a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl +++ b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl @@ -35,8 +35,11 @@ function generate( ncpus = prod(mesh_partition) wallhr = occursin("STRONG",name) && ncpus == 1 ? 100 : - occursin("STRONG",name) && ncpus == 8 ? 24 : wallhr - mem = occursin("STRONG",name) && ncpus == 1 ? 100 : Int(gb_per_node*ncpus/cps_per_node); + occursin("STRONG",name) && ncpus == 8 ? 24 : + occursin("STRONG",name) && ncpus == 27 ? 10 : wallhr + mem = occursin("STRONG",name) && ncpus == 1 ? 100 : + occursin("STRONG",name) && ncpus == 8 ? 128 : + occursin("STRONG",name) && ncpus == 27 ? 192 : Int(gb_per_node*ncpus/cps_per_node); Nx_partition, Ny_partition, Nz_partition = mesh_partition settings = (;name,type,bmark_type,cputype,wallhr,ncpus,mem, diff --git a/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl index d177d1da..ec1cea4d 100644 --- a/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl @@ -95,7 +95,7 @@ function main(mesh_partition,distribute) end with_mpi() do distribute - mesh_partition = (5,5,5) + mesh_partition = (4,6,6) solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do diff --git a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl index 7e532243..45efaaaa 100644 --- a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl @@ -111,7 +111,7 @@ function main(mesh_partition,distribute) end with_mpi() do distribute - mesh_partition = (5,5,5) + mesh_partition = (4,6,6) solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do diff --git a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl index af7c2735..efb3f3f9 100644 --- a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl @@ -99,7 +99,7 @@ function main(mesh_partition,distribute) end with_mpi() do distribute - mesh_partition = (5,5,5) + mesh_partition = (4,6,6) solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl index d1b3c677..a9e382e4 100644 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -105,7 +105,7 @@ function main(mesh_partition,distribute) end with_mpi() do distribute - mesh_partition = (5,5,5) + mesh_partition = (4,6,6) solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs new file mode 100644 index 00000000..fda46ec2 --- /dev/null +++ b/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs @@ -0,0 +1,14 @@ +#!/bin/bash -l +#PBS -P np01 +#PBS -q normal +#PBS -N elast_comp_MPI_3D +#PBS -l ncpus=144 +#PBS -l mem=576GB +#PBS -l walltime=10:00:00 +#PBS -j oe + +source $HOME/hpc-environments-main/lyra/load-intel.sh +PROJECT_DIR=$HOME/LevelSetTopOpt/ + +mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ + $PROJECT_DIR/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs new file mode 100644 index 00000000..73943486 --- /dev/null +++ b/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs @@ -0,0 +1,14 @@ +#!/bin/bash -l +#PBS -P np01 +#PBS -q normal +#PBS -N hyperelast_comp_MPI_3D +#PBS -l ncpus=144 +#PBS -l mem=576GB +#PBS -l walltime=10:00:00 +#PBS -j oe + +source $HOME/hpc-environments-main/lyra/load-intel.sh +PROJECT_DIR=$HOME/LevelSetTopOpt/ + +mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ + $PROJECT_DIR/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs new file mode 100644 index 00000000..dd590bea --- /dev/null +++ b/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs @@ -0,0 +1,14 @@ +#!/bin/bash -l +#PBS -P np01 +#PBS -q normal +#PBS -N inverse_hom_MPI_3D +#PBS -l ncpus=144 +#PBS -l mem=576GB +#PBS -l walltime=24:00:00 +#PBS -j oe + +source $HOME/hpc-environments-main/lyra/load-intel.sh +PROJECT_DIR=$HOME/LevelSetTopOpt/ + +mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ + $PROJECT_DIR/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs new file mode 100644 index 00000000..1e04d719 --- /dev/null +++ b/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs @@ -0,0 +1,14 @@ +#!/bin/bash -l +#PBS -P np01 +#PBS -q normal +#PBS -N inverter_MPI_3D +#PBS -l ncpus=144 +#PBS -l mem=576GB +#PBS -l walltime=16:00:00 +#PBS -j oe + +source $HOME/hpc-environments-main/lyra/load-intel.sh +PROJECT_DIR=$HOME/LevelSetTopOpt/ + +mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ + $PROJECT_DIR/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs new file mode 100644 index 00000000..72a28429 --- /dev/null +++ b/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs @@ -0,0 +1,14 @@ +#!/bin/bash -l +#PBS -P np01 +#PBS -q normal +#PBS -N therm_comp_MPI_3D +#PBS -l ncpus=144 +#PBS -l mem=576GB +#PBS -l walltime=16:00:00 +#PBS -j oe + +source $HOME/hpc-environments-main/lyra/load-intel.sh +PROJECT_DIR=$HOME/LevelSetTopOpt/ + +mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ + $PROJECT_DIR/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl index 5104e0d6..a9014711 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl @@ -97,7 +97,7 @@ function main(mesh_partition,distribute) end with_mpi() do distribute - mesh_partition = (5,5,5) + mesh_partition = (4,6,6) solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do From d69663108996805fa3cd9142338f18e1f7488147 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sat, 27 Apr 2024 10:17:06 +1000 Subject: [PATCH 73/90] oops --- scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs | 4 ++-- .../_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs | 4 ++-- scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs | 4 ++-- scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs | 4 ++-- scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs | 6 +++--- 5 files changed, 11 insertions(+), 11 deletions(-) diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs index fda46ec2..0d2dbc39 100644 --- a/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs @@ -7,8 +7,8 @@ #PBS -l walltime=10:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ +source $HOME/hpc-environments/gadi/load-intel.sh +PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ $PROJECT_DIR/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs index 73943486..978321a3 100644 --- a/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs @@ -7,8 +7,8 @@ #PBS -l walltime=10:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ +source $HOME/hpc-environments/gadi/load-intel.sh +PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ $PROJECT_DIR/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs index dd590bea..1ee191c2 100644 --- a/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs @@ -7,8 +7,8 @@ #PBS -l walltime=24:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ +source $HOME/hpc-environments/gadi/load-intel.sh +PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ $PROJECT_DIR/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs index 1e04d719..5db3bed6 100644 --- a/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs @@ -7,8 +7,8 @@ #PBS -l walltime=16:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ +source $HOME/hpc-environments/gadi/load-intel.sh +PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ $PROJECT_DIR/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs index 72a28429..7597a0a8 100644 --- a/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs @@ -4,11 +4,11 @@ #PBS -N therm_comp_MPI_3D #PBS -l ncpus=144 #PBS -l mem=576GB -#PBS -l walltime=16:00:00 +#PBS -l walltime=3:00:00 #PBS -j oe -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ +source $HOME/hpc-environments/gadi/load-intel.sh +PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ $PROJECT_DIR/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl From f49b9ee18c925ea8ceb3abc778deba3a43027402 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sat, 27 Apr 2024 10:54:21 +1000 Subject: [PATCH 74/90] Fix writing to scratch --- scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl | 7 ++++--- scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl | 7 ++++--- scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl | 7 ++++--- scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 7 ++++--- scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs | 3 ++- .../Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs | 3 ++- .../_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs | 3 ++- scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs | 3 ++- scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs | 3 ++- scripts/_dev/Paper_scripts/therm_comp_MPI.jl | 7 ++++--- scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl | 7 ++++--- 11 files changed, 34 insertions(+), 23 deletions(-) diff --git a/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl index ec1cea4d..f3e23201 100644 --- a/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl @@ -1,7 +1,7 @@ using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, SparseMatricesCSR -function main(mesh_partition,distribute) +function main(mesh_partition,distribute,write_dir) ranks = distribute(LinearIndices((prod(mesh_partition),))) # FE parameters order = 1 # Finite element order @@ -24,7 +24,7 @@ function main(mesh_partition,distribute) vf = 0.4 # Volume fraction constraint lsf_func = initial_lsf(4,0.2) # Initial level set function iter_mod = 10 # VTK Output modulo - path = "./results/elast_comp_MPI_3D/" # Output path + path = "$write_dir/elast_comp_MPI_3D/" # Output path i_am_main(ranks) && mkpath(path) # Create path # Model model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -96,9 +96,10 @@ end with_mpi() do distribute mesh_partition = (4,6,6) + write_dir = ARGS[1] solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute) + main(mesh_partition,distribute,write_dir) end end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl index 45efaaaa..d164c73d 100644 --- a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl @@ -3,7 +3,7 @@ using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, using GridapSolvers: NewtonSolver -function main(mesh_partition,distribute) +function main(mesh_partition,distribute,write_dir) ranks = distribute(LinearIndices((prod(mesh_partition),))) # FE parameters order = 1 # Finite element order @@ -28,7 +28,7 @@ function main(mesh_partition,distribute) vf = 0.4 # Volume fraction constraint lsf_func = initial_lsf(4,0.2) # Initial level set function iter_mod = 10 # VTK Output modulo - path = "./results/hyperelast_comp_MPI_3D/" # Output path + path = "$write_dir/hyperelast_comp_MPI_3D/" # Output path i_am_main(ranks) && mkpath(path) # Create path # Model model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -112,9 +112,10 @@ end with_mpi() do distribute mesh_partition = (4,6,6) + write_dir = ARGS[1] solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute) + main(mesh_partition,distribute,write_dir) end end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl index efb3f3f9..0bab1470 100644 --- a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl @@ -1,7 +1,7 @@ using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, SparseMatricesCSR -function main(mesh_partition,distribute) +function main(mesh_partition,distribute,write_dir) ranks = distribute(LinearIndices((prod(mesh_partition),))) # FE parameters order = 1 # Finite element order @@ -21,7 +21,7 @@ function main(mesh_partition,distribute) lsf_func(x) = cos(2π*x[1]) + cos(2π*x[2]) + # Initial level set function cos(2π*x[3]) iter_mod = 10 # VTK Output modulo - path = "./results/inverse_hom_MPI_3D/" # Output path + path = "$write_dir/inverse_hom_MPI_3D/" # Output path i_am_main(ranks) && mkpath(path) # Create path # Model model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true,true)); @@ -100,9 +100,10 @@ end with_mpi() do distribute mesh_partition = (4,6,6) + write_dir = ARGS[1] solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute) + main(mesh_partition,distribute,write_dir) end end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl index a9e382e4..e22b4874 100644 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -1,7 +1,7 @@ using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, SparseMatricesCSR -function main(mesh_partition,distribute) +function main(mesh_partition,distribute,write_dir) ranks = distribute(LinearIndices((prod(mesh_partition),))) # FE parameters order = 1 # Finite element order @@ -29,7 +29,7 @@ function main(mesh_partition,distribute) sphere(x,(1,0,0)),sphere(x,(1,0,1)),sphere(x,(1,1,0)),sphere(x,(1,1,1))) lsf_func = initial_lsf(4,0.2) # Initial level set function iter_mod = 10 # VTK Output modulo - path = "./results/inverter_MPI_3D/" # Output path + path = "$write_dir/inverter_MPI_3D/" # Output path i_am_main(ranks) && mkpath(path) # Create path # Model model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -106,9 +106,10 @@ end with_mpi() do distribute mesh_partition = (4,6,6) + write_dir = ARGS[1] solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute) + main(mesh_partition,distribute,write_dir) end end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs index 0d2dbc39..9fb3b55b 100644 --- a/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs @@ -11,4 +11,5 @@ source $HOME/hpc-environments/gadi/load-intel.sh PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl + $PROJECT_DIR/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl \ + $PROJECT_DIR/results diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs index 978321a3..f9b7897f 100644 --- a/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs @@ -11,4 +11,5 @@ source $HOME/hpc-environments/gadi/load-intel.sh PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl + $PROJECT_DIR/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl \ + $PROJECT_DIR/results diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs index 1ee191c2..9cbe2ad9 100644 --- a/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs @@ -11,4 +11,5 @@ source $HOME/hpc-environments/gadi/load-intel.sh PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl + $PROJECT_DIR/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl \ + $PROJECT_DIR/results diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs index 5db3bed6..d16868d7 100644 --- a/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs @@ -11,4 +11,5 @@ source $HOME/hpc-environments/gadi/load-intel.sh PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl + $PROJECT_DIR/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl \ + $PROJECT_DIR/results diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs index 7597a0a8..d859dc27 100644 --- a/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs +++ b/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs @@ -11,4 +11,5 @@ source $HOME/hpc-environments/gadi/load-intel.sh PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl + $PROJECT_DIR/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl \ + $PROJECT_DIR/results diff --git a/scripts/_dev/Paper_scripts/therm_comp_MPI.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI.jl index 902742bf..a5476e50 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_MPI.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_MPI.jl @@ -1,7 +1,7 @@ using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, SparseMatricesCSR -function main(mesh_partition,distribute) +function main(mesh_partition,distribute,write_dir) ranks = distribute(LinearIndices((prod(mesh_partition),))) # FE parameters order = 1 # Finite element order @@ -25,7 +25,7 @@ function main(mesh_partition,distribute) vf = 0.4 # Volume fraction constraint lsf_func = initial_lsf(4,0.2) # Initial level set function iter_mod = 10 # VTK Output modulo - path = "./results/therm_comp_MPI/" # Output path + path = "$write_dir/results/therm_comp_MPI/" # Output path i_am_main(ranks) && mkpath(path) # Create path # Model model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -95,9 +95,10 @@ end with_mpi() do distribute mesh_partition = (2,2) + write_dir = ARGS[1] solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute) + main(mesh_partition,distribute,write_dir) end end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl index a9014711..be63b8db 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl @@ -1,7 +1,7 @@ using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, SparseMatricesCSR -function main(mesh_partition,distribute) +function main(mesh_partition,distribute,write_dir) ranks = distribute(LinearIndices((prod(mesh_partition),))) # FE parameters order = 1 # Finite element order @@ -27,7 +27,7 @@ function main(mesh_partition,distribute) vf = 0.4 # Volume fraction constraint lsf_func = initial_lsf(4,0.2) # Initial level set function iter_mod = 10 # VTK Output modulo - path = "./results/therm_comp_MPI_3D/" # Output path + path = "$write_dir/therm_comp_MPI_3D/" # Output path i_am_main(ranks) && mkpath(path) # Create path # Model model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -98,9 +98,10 @@ end with_mpi() do distribute mesh_partition = (4,6,6) + write_dir = ARGS[1] solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute) + main(mesh_partition,distribute,write_dir) end end \ No newline at end of file From e80369c39f78dabce1e4ba0fb30eddffd7450877 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sat, 27 Apr 2024 11:06:41 +1000 Subject: [PATCH 75/90] bug fixes --- scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl | 4 ++-- scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 1 + 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl index 0bab1470..1d7c2425 100644 --- a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl @@ -68,8 +68,8 @@ function main(mesh_partition,distribute,write_dir) dκ(q,u,φ,dΩ) = -1/9*(dCᴴ(1,1,q,u,φ,dΩ)+dCᴴ(2,2,q,u,φ,dΩ)+dCᴴ(3,3,q,u,φ,dΩ)+ 2*(dCᴴ(1,2,q,u,φ,dΩ)+dCᴴ(1,3,q,u,φ,dΩ)+dCᴴ(2,3,q,u,φ,dΩ))) vol_D = sum(∫(1)dΩ) - C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + C1(u,φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dC1(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ pcfs = PDEConstrainedFunctionals(κ,[C1],state_map, analytic_dJ=dκ,analytic_dC=[dC1]) # Velocity extension diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl index e22b4874..dd8117bd 100644 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -23,6 +23,7 @@ function main(mesh_partition,distribute,write_dir) C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor g = VectorValue(0,0,-1) # Applied load on Γ_N ks = 0.01 # Artificial spring stiffness + δₓ = 0.5 # Required displacement vf = 0.4 # Volume fraction constraint sphere(x,(xc,yc,zc)) = -sqrt((x[1]-xc)^2+(x[2]-yc)^2+(x[3]-zc)^2) + 0.2 lsf_func(x) = max(initial_lsf(4,0.2)(x), # Initial level set function From d6b06514885190390d37d44c152ac10b849a8715 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sat, 27 Apr 2024 16:14:58 +1000 Subject: [PATCH 76/90] loaded messed up --- scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl index dd8117bd..c52e206c 100644 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -21,7 +21,7 @@ function main(mesh_partition,distribute,write_dir) tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance # Problem parameters C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor - g = VectorValue(0,0,-1) # Applied load on Γ_N + g = VectorValue(1,0,0) # Applied load on Γ_N ks = 0.01 # Artificial spring stiffness δₓ = 0.5 # Required displacement vf = 0.4 # Volume fraction constraint From b3b3781a5b56caad82ea56e36fb9be9c8ba67ef0 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sat, 27 Apr 2024 22:23:46 +1000 Subject: [PATCH 77/90] Inverter now includes Gamma_out_ext --- scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 11 ++++++++--- 1 file changed, 8 insertions(+), 3 deletions(-) diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl index c52e206c..ab2e1faa 100644 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -12,6 +12,9 @@ function main(mesh_partition,distribute,write_dir) (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) f_Γ_out(x) = (x[1] ≈ 1.0) && # Γ_out indicator function (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) + f_Γ_out_ext(x) = ~f_Γ_out(x) && # Γ_out_ext indicator function + (0.95 <= x[1] <= 1.0) && (0.35 - eps() <= x[2] <= 0.65 + eps()) && + (0.35 - eps() <= x[3] <= 0.65 + eps()) f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function (x[2] <= 0.1 || x[2] >= 0.9) && (x[3] <= 0.1 || x[3] >= 0.9) # FD parameters @@ -21,9 +24,9 @@ function main(mesh_partition,distribute,write_dir) tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance # Problem parameters C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor - g = VectorValue(1,0,0) # Applied load on Γ_N + g = VectorValue(1,0,0) # Applied load on Γ_N ks = 0.01 # Artificial spring stiffness - δₓ = 0.5 # Required displacement + δₓ = 0.25 # Required displacement vf = 0.4 # Volume fraction constraint sphere(x,(xc,yc,zc)) = -sqrt((x[1]-xc)^2+(x[2]-yc)^2+(x[3]-zc)^2) + 0.2 lsf_func(x) = max(initial_lsf(4,0.2)(x), # Initial level set function @@ -36,6 +39,7 @@ function main(mesh_partition,distribute,write_dir) model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); update_labels!(1,model,f_Γ_in,"Gamma_in") update_labels!(2,model,f_Γ_out,"Gamma_out") + update_labels!(3,model,f_Γ_out_ext,"Gamma_out_ext") update_labels!(4,model,f_Γ_D,"Gamma_D") # Triangulation and measures Ω = Triangulation(model) @@ -50,7 +54,8 @@ function main(mesh_partition,distribute,write_dir) V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_in","Gamma_out"]) + V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=[ + "Gamma_in","Gamma_out","Gamma_out_ext"]) U_reg = TrialFESpace(V_reg,0) # Level set and interpolator φh = interpolate(lsf_func,V_φ); From 103465bc436fb499b3406ce5142598901edaf9e9 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Sun, 28 Apr 2024 15:28:02 +1000 Subject: [PATCH 78/90] inverter results done --- scripts/_dev/Paper_scripts/inverter_MPI_3D.jl | 5 ++--- 1 file changed, 2 insertions(+), 3 deletions(-) diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl index ab2e1faa..5ecde638 100644 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl @@ -13,7 +13,7 @@ function main(mesh_partition,distribute,write_dir) f_Γ_out(x) = (x[1] ≈ 1.0) && # Γ_out indicator function (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) f_Γ_out_ext(x) = ~f_Γ_out(x) && # Γ_out_ext indicator function - (0.95 <= x[1] <= 1.0) && (0.35 - eps() <= x[2] <= 0.65 + eps()) && + (0.9 <= x[1] <= 1.0) && (0.35 - eps() <= x[2] <= 0.65 + eps()) && (0.35 - eps() <= x[3] <= 0.65 + eps()) f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function (x[2] <= 0.1 || x[2] >= 0.9) && (x[3] <= 0.1 || x[3] >= 0.9) @@ -26,12 +26,11 @@ function main(mesh_partition,distribute,write_dir) C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor g = VectorValue(1,0,0) # Applied load on Γ_N ks = 0.01 # Artificial spring stiffness - δₓ = 0.25 # Required displacement + δₓ = 0.4 # Required displacement vf = 0.4 # Volume fraction constraint sphere(x,(xc,yc,zc)) = -sqrt((x[1]-xc)^2+(x[2]-yc)^2+(x[3]-zc)^2) + 0.2 lsf_func(x) = max(initial_lsf(4,0.2)(x), # Initial level set function sphere(x,(1,0,0)),sphere(x,(1,0,1)),sphere(x,(1,1,0)),sphere(x,(1,1,1))) - lsf_func = initial_lsf(4,0.2) # Initial level set function iter_mod = 10 # VTK Output modulo path = "$write_dir/inverter_MPI_3D/" # Output path i_am_main(ranks) && mkpath(path) # Create path From 710e1260220b36bc85d32a83775cb7774572ad19 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Mon, 29 Apr 2024 14:45:56 +1000 Subject: [PATCH 79/90] minor script change for paper --- scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl | 1 - 1 file changed, 1 deletion(-) diff --git a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl index 1d7c2425..83175010 100644 --- a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl +++ b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl @@ -16,7 +16,6 @@ function main(mesh_partition,distribute,write_dir) tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance # Problem parameters C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor - g = VectorValue(0,0,-1) # Applied load on Γ_N vf = 0.4 # Volume fraction constraint lsf_func(x) = cos(2π*x[1]) + cos(2π*x[2]) + # Initial level set function cos(2π*x[3]) From 637c22852d4504b6f16ddcb71b03adb7248a23f6 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Mon, 29 Apr 2024 16:15:23 +1000 Subject: [PATCH 80/90] minor update to serial script for paper --- scripts/_dev/Paper_scripts/therm_comp_serial.jl | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/scripts/_dev/Paper_scripts/therm_comp_serial.jl b/scripts/_dev/Paper_scripts/therm_comp_serial.jl index efd90e5f..69fc7d73 100644 --- a/scripts/_dev/Paper_scripts/therm_comp_serial.jl +++ b/scripts/_dev/Paper_scripts/therm_comp_serial.jl @@ -1,6 +1,6 @@ using LevelSetTopOpt, Gridap -function main() +function main(write_dir) # FE parameters order = 1 # Finite element order xmax,ymax = (1.0,1.0) # Domain size @@ -23,7 +23,7 @@ function main() vf = 0.4 # Volume fraction constraint lsf_func = initial_lsf(4,0.2) # Initial level set function iter_mod = 10 # VTK Output modulo - path = "./results/therm_comp_serial/" # Output path + path = "$write_dir/therm_comp_serial/" # Output path mkpath(path) # Create path # Model model = CartesianDiscreteModel(dom,el_size); @@ -79,4 +79,4 @@ function main() "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end -main() \ No newline at end of file +main("results/") \ No newline at end of file From 357e02280a18f7c63ee14cbba5cf28f5c3c377b6 Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Tue, 30 Apr 2024 08:12:09 +1000 Subject: [PATCH 81/90] Added some serial tests + bug fix in ChainRules --- scripts/MPI/3d_thermal_compliance_ALM.jl | 2 +- src/ChainRules.jl | 6 +- src/LevelSetTopOpt.jl | 4 +- test/seq/InverseHomogenisationALMTests.jl | 103 ++++++++++++++++ test/seq/InverterHPMTests.jl | 114 ++++++++++++++++++ .../seq/NonlinearThermalComplianceALMTests.jl | 101 ++++++++++++++++ test/seq/ThermalComplianceALMTests.jl | 112 +++++++++++++++-- test/seq/runtests.jl | 3 + 8 files changed, 433 insertions(+), 12 deletions(-) create mode 100644 test/seq/InverseHomogenisationALMTests.jl create mode 100644 test/seq/InverterHPMTests.jl create mode 100644 test/seq/NonlinearThermalComplianceALMTests.jl diff --git a/scripts/MPI/3d_thermal_compliance_ALM.jl b/scripts/MPI/3d_thermal_compliance_ALM.jl index 2c63d3e0..ce4849db 100644 --- a/scripts/MPI/3d_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_thermal_compliance_ALM.jl @@ -29,7 +29,7 @@ function main(mesh_partition,distribute,el_size) dom = (0,xmax,0,ymax,0,zmax) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,order*minimum(el_size)/step) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(coef*order^2)/minimum(el_size) κ = 1 η_coeff = 2 diff --git a/src/ChainRules.jl b/src/ChainRules.jl index 398f74db..1a2a5f49 100644 --- a/src/ChainRules.jl +++ b/src/ChainRules.jl @@ -65,13 +65,15 @@ Gridap.gradient(F::IntegrandWithMeasure,uh) = Gridap.gradient(F,[uh],1) Given an an `IntegrandWithMeasure` `F` and a vector of `FEFunctions` or `CellField` `uh` (excluding measures) evaluate the Jacobian `F.F` with respect to `uh[K]`. """ -function Gridap.jacobian(F::IntegrandWithMeasure,uh::Vector{<:FEFunction},K::Int) +function Gridap.jacobian(F::IntegrandWithMeasure,uh::Vector{<:Union{FEFunction,CellField}},K::Int) @check 0 < K <= length(uh) _f(uk) = F.F(uh[1:K-1]...,uk,uh[K+1:end]...,F.dΩ...) return Gridap.jacobian(_f,uh[K]) end -function Gridap.jacobian(F::IntegrandWithMeasure,uh::Vector,K::Int) +DistributedFields = Union{DistributedCellField,DistributedMultiFieldCellField} + +function Gridap.jacobian(F::IntegrandWithMeasure,uh::Vector{<:DistributedFields},K::Int) @check 0 < K <= length(uh) local_fields = map(local_views,uh) |> to_parray_of_arrays local_measures = map(local_views,F.dΩ) |> to_parray_of_arrays diff --git a/src/LevelSetTopOpt.jl b/src/LevelSetTopOpt.jl index 52d28514..43f948f7 100644 --- a/src/LevelSetTopOpt.jl +++ b/src/LevelSetTopOpt.jl @@ -21,8 +21,8 @@ using Gridap: writevtk using GridapDistributed using GridapDistributed: DistributedDiscreteModel, DistributedTriangulation, DistributedFESpace, DistributedDomainContribution, to_parray_of_arrays, - allocate_in_domain, DistributedCellField, DistributedMultiFieldFEBasis, - BlockPMatrix, BlockPVector, change_ghost + allocate_in_domain, DistributedCellField, DistributedMultiFieldCellField, + DistributedMultiFieldFEBasis, BlockPMatrix, BlockPVector, change_ghost using PartitionedArrays using PartitionedArrays: getany, tuple_of_arrays, matching_ghost_indices diff --git a/test/seq/InverseHomogenisationALMTests.jl b/test/seq/InverseHomogenisationALMTests.jl new file mode 100644 index 00000000..82929b7d --- /dev/null +++ b/test/seq/InverseHomogenisationALMTests.jl @@ -0,0 +1,103 @@ +module InverseHomogenisationALMTests +using Test + +using Gridap, LevelSetTopOpt + +""" + (Serial) Maximum bulk modulus inverse homogenisation with augmented Lagrangian method in 2D. + + Optimisation problem: + Min J(Ω) = -κ(Ω) + Ω + s.t., Vol(Ω) = vf, + ⎡For unique εᴹᵢ, find uᵢ∈V=H¹ₚₑᵣ(Ω)ᵈ, + ⎣∫ ∑ᵢ C ⊙ ε(uᵢ) ⊙ ε(vᵢ) dΩ = ∫ -∑ᵢ C ⊙ ε⁰ᵢ ⊙ ε(vᵢ) dΩ, ∀v∈V. +""" +function main(;AD) + ## Parameters + order = 1 + xmax,ymax=(1.0,1.0) + dom = (0,xmax,0,ymax) + el_size = (20,20) + γ = 0.05 + γ_reinit = 0.5 + max_steps = floor(Int,order*minimum(el_size)/10) + tol = 1/(5order^2)/minimum(el_size) + C = isotropic_elast_tensor(2,1.,0.3) + η_coeff = 2 + α_coeff = 4max_steps*γ + vf = 0.5 + + ## FE Setup + model = CartesianDiscreteModel(dom,el_size,isperiodic=(true,true)) + el_Δ = get_el_Δ(model) + f_Γ_D(x) = iszero(x) + update_labels!(1,model,f_Γ_D,"origin") + + ## Triangulations and measures + Ω = Triangulation(model) + dΩ = Measure(Ω,2*order) + vol_D = sum(∫(1)dΩ) + + ## Spaces + reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["origin"]) + U = TrialFESpace(V,VectorValue(0.0,0.0)) + V_reg = V_φ = TestFESpace(model,reffe_scalar) + U_reg = TrialFESpace(V_reg) + + ## Create FE functions + lsf_fn = x->max(initial_lsf(2,0.4)(x),initial_lsf(2,0.4;b=VectorValue(0,0.5))(x)) + φh = interpolate(lsf_fn,V_φ) + + ## Interpolation and weak form + interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + + εᴹ = (TensorValue(1.,0.,0.,0.), # ϵᵢⱼ⁽¹¹⁾≡ϵᵢⱼ⁽¹⁾ + TensorValue(0.,0.,0.,1.), # ϵᵢⱼ⁽²²⁾≡ϵᵢⱼ⁽²⁾ + TensorValue(0.,1/2,1/2,0.)) # ϵᵢⱼ⁽¹²⁾≡ϵᵢⱼ⁽³⁾ + + a(u,v,φ,dΩ) = ∫((I ∘ φ) * C ⊙ ε(u) ⊙ ε(v) )dΩ + l = [(v,φ,dΩ) -> ∫(-(I ∘ φ)* C ⊙ εᴹ[i] ⊙ ε(v))dΩ for i in 1:3] + + ## Optimisation functionals + Cᴴ(r,s,u,φ,dΩ) = ∫((I ∘ φ)*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ εᴹ[s]))dΩ + dCᴴ(r,s,q,u,φ,dΩ) = ∫(-q*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ (ε(u[s])+εᴹ[s]))*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + κ(u,φ,dΩ) = -1/4*(Cᴴ(1,1,u,φ,dΩ)+Cᴴ(2,2,u,φ,dΩ)+2*Cᴴ(1,2,u,φ,dΩ)) + dκ(q,u,φ,dΩ) = -1/4*(dCᴴ(1,1,q,u,φ,dΩ)+dCᴴ(2,2,q,u,φ,dΩ)+2*dCᴴ(1,2,q,u,φ,dΩ)) + Vol(u,φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dVol(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + + ## Finite difference solver and level set function + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + + ## Setup solver and FE operators + state_map = RepeatingAffineFEStateMap(3,a,l,U,V,V_φ,U_reg,φh,dΩ) + pcfs = if AD + PDEConstrainedFunctionals(κ,[Vol],state_map;analytic_dJ=dκ,analytic_dC=[dVol]) + else + PDEConstrainedFunctionals(κ,[Vol],state_map) + end + + ## Hilbertian extension-regularisation problems + α = α_coeff*maximum(el_Δ) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ + vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) + + ## Optimiser + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; + γ,γ_reinit,verbose=true,constraint_names=[:Vol]) + + # Do a few iterations + vars, state = iterate(optimiser) + vars, state = iterate(optimiser,state) + true +end + +# Test that these run successfully +@test main(;AD=true) +@test main(;AD=false) + +end # module \ No newline at end of file diff --git a/test/seq/InverterHPMTests.jl b/test/seq/InverterHPMTests.jl new file mode 100644 index 00000000..ce94a389 --- /dev/null +++ b/test/seq/InverterHPMTests.jl @@ -0,0 +1,114 @@ +module InverterHPMTests +using Test + +using Gridap, LevelSetTopOpt + +""" + (Serial) Inverter mechanism with Hilbertian projection method in 2D. + + Optimisation problem: + Min J(Ω) = ηᵢₙ*∫ u⋅e₁ dΓᵢₙ/Vol(Γᵢₙ) + Ω + s.t., Vol(Ω) = vf, + C(Ω) = 0, + ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, + ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ + ∫ kₛv⋅u dΓₒᵤₜ = ∫ v⋅g dΓᵢₙ , ∀v∈V. + + where C(Ω) = ∫ -u⋅e₁-δₓ dΓₒᵤₜ/Vol(Γₒᵤₜ). We assume symmetry in the problem to aid + convergence. +""" +function main() + ## Parameters + order = 1 + dom = (0,1,0,0.5) + el_size = (20,20) + γ = 0.1 + γ_reinit = 0.5 + max_steps = floor(Int,order*minimum(el_size)/10) + tol = 1/(5order^2)/minimum(el_size) + C = isotropic_elast_tensor(2,1.0,0.3) + η_coeff = 2 + α_coeff = 4max_steps*γ + vf = 0.4 + δₓ = 0.2 + ks = 0.1 + g = VectorValue(0.5,0) + + ## FE Setup + model = CartesianDiscreteModel(dom,el_size) + el_Δ = get_el_Δ(model) + f_Γ_in(x) = (x[1] ≈ 0.0) && (x[2] <= 0.03 + eps()) + f_Γ_out(x) = (x[1] ≈ 1.0) && (x[2] <= 0.07 + eps()) + f_Γ_D(x) = (x[1] ≈ 0.0) && (x[2] >= 0.4) + f_Γ_D2(x) = (x[2] ≈ 0.0) + update_labels!(1,model,f_Γ_in,"Gamma_in") + update_labels!(2,model,f_Γ_out,"Gamma_out") + update_labels!(3,model,f_Γ_D,"Gamma_D") + update_labels!(4,model,f_Γ_D2,"SymLine") + + ## Triangulations and measures + Ω = Triangulation(model) + Γ_in = BoundaryTriangulation(model,tags="Gamma_in") + Γ_out = BoundaryTriangulation(model,tags="Gamma_out") + dΩ = Measure(Ω,2order) + dΓ_in = Measure(Γ_in,2order) + dΓ_out = Measure(Γ_out,2order) + vol_D = sum(∫(1)dΩ) + vol_Γ_in = sum(∫(1)dΓ_in) + vol_Γ_out = sum(∫(1)dΓ_out) + + ## Spaces + reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D","SymLine"], + dirichlet_masks=[(true,true),(false,true)]) + U = TrialFESpace(V,[VectorValue(0.0,0.0),VectorValue(0.0,0.0)]) + V_φ = TestFESpace(model,reffe_scalar) + V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_in","Gamma_out"]) + U_reg = TrialFESpace(V_reg,[0,0]) + + ## Create FE functions + lsf_fn(x) = min(max(initial_lsf(6,0.2)(x),-sqrt((x[1]-1)^2+(x[2]-0.5)^2)+0.2), + sqrt((x[1])^2+(x[2]-0.5)^2)-0.1) + φh = interpolate(lsf_fn,V_φ) + + ## Interpolation and weak form + interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + + a(u,v,φ,dΩ,dΓ_in,dΓ_out) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ + ∫(ks*(u⋅v))dΓ_out + l(v,φ,dΩ,dΓ_in,dΓ_out) = ∫(v⋅g)dΓ_in + + ## Optimisation functionals + e₁ = VectorValue(1,0) + J(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅e₁)/vol_Γ_in)dΓ_in + Vol(u,φ,dΩ,dΓ_in,dΓ_out) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ + dVol(q,u,φ,dΩ,dΓ_in,dΓ_out) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out + + ## Finite difference solver and level set function + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + + ## Setup solver and FE operators + state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out) + pcfs = PDEConstrainedFunctionals(J,[Vol,UΓ_out],state_map,analytic_dC=[dVol,nothing]) + + ## Hilbertian extension-regularisation problems + α = α_coeff*maximum(el_Δ) + a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; + vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) + + ## Optimiser + optimiser = HilbertianProjection(pcfs,ls_evo,vel_ext,φh; + γ,γ_reinit,verbose=true,debug=true,constraint_names=[:Vol,:UΓ_out]) + + # Do a few iterations + vars, state = iterate(optimiser) + vars, state = iterate(optimiser,state) + true +end + +# Test that these run successfully +@test main() + +end # module \ No newline at end of file diff --git a/test/seq/NonlinearThermalComplianceALMTests.jl b/test/seq/NonlinearThermalComplianceALMTests.jl new file mode 100644 index 00000000..c624d997 --- /dev/null +++ b/test/seq/NonlinearThermalComplianceALMTests.jl @@ -0,0 +1,101 @@ +module NonlinearThermalComplianceALMTests +using Test + +using Gridap, LevelSetTopOpt + +""" + (Serial) Minimum thermal compliance with augmented Lagrangian method in 2D with nonlinear diffusivity. + + Optimisation problem: + Min J(Ω) = ∫ κ(u)*∇(u)⋅∇(u) dΩ + Ω + s.t., Vol(Ω) = vf, + ⎡u∈V=H¹(Ω;u(Γ_D)=0), + ⎣∫ κ(u)*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. + + In this example κ(u) = κ0*(exp(ξ*u)) +""" +function main() + ## Parameters + order = 1 + xmax=ymax=1.0 + prop_Γ_N = 0.2 + prop_Γ_D = 0.2 + dom = (0,xmax,0,ymax) + el_size = (20,20) + γ = 0.1 + γ_reinit = 0.5 + max_steps = floor(Int,order*minimum(el_size)/10) + tol = 1/(5order^2)/minimum(el_size) + η_coeff = 2 + α_coeff = 4max_steps*γ + vf = 0.4 + + ## FE Setup + model = CartesianDiscreteModel(dom,el_size); + el_Δ = get_el_Δ(model) + f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || + x[2] >= ymax-ymax*prop_Γ_D - eps())); + f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= + ymax/2+ymax*prop_Γ_N/2 + eps()); + update_labels!(1,model,f_Γ_D,"Gamma_D") + update_labels!(2,model,f_Γ_N,"Gamma_N") + + ## Triangulations and measures + Ω = Triangulation(model) + Γ_N = BoundaryTriangulation(model,tags="Gamma_N") + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + vol_D = sum(∫(1)dΩ) + + ## Spaces + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,0.0) + V_φ = TestFESpace(model,reffe_scalar) + V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) + U_reg = TrialFESpace(V_reg,0) + + ## Create FE functions + φh = interpolate(initial_lsf(4,0.2),V_φ) + + ## Interpolation and weak form + interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + + κ0 = 1 + ξ = -1 + κ(u) = κ0*(exp(ξ*u)) + res(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(κ ∘ u)*∇(u)⋅∇(v))dΩ - ∫(v)dΓ_N + + ## Optimisation functionals + J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(κ ∘ u)*∇(u)⋅∇(u))dΩ + Vol(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; + dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + + ## Finite difference solver and level set function + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + + ## Setup solver and FE operators + state_map = NonlinearFEStateMap(res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) + pcfs = PDEConstrainedFunctionals(J,[Vol],state_map,analytic_dC=[dVol]) + + ## Hilbertian extension-regularisation problems + α = α_coeff*maximum(el_Δ) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ + vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) + + ## Optimiser + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; + γ,γ_reinit,verbose=true,constraint_names=[:Vol]) + + # Do a few iterations + vars, state = iterate(optimiser) + vars, state = iterate(optimiser,state) + true +end + +# Test that these run successfully +@test main() + +end # module \ No newline at end of file diff --git a/test/seq/ThermalComplianceALMTests.jl b/test/seq/ThermalComplianceALMTests.jl index a5891838..c96225f8 100644 --- a/test/seq/ThermalComplianceALMTests.jl +++ b/test/seq/ThermalComplianceALMTests.jl @@ -1,4 +1,5 @@ module ThermalComplianceALMTests +using Test using Gridap, LevelSetTopOpt @@ -12,22 +13,21 @@ using Gridap, LevelSetTopOpt ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. """ -function main() - ## Parameters| - order = 1 - xmax=ymax=1.0 +function main(;order,AD) + ## Parameters + xmax = ymax = 1.0 prop_Γ_N = 0.2 prop_Γ_D = 0.2 dom = (0,xmax,0,ymax) el_size = (20,20) γ = 0.1 γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) + max_steps = floor(Int,order*minimum(el_size)/10) tol = 1/(5*order^2)/minimum(el_size) κ = 1 vf = 0.4 η_coeff = 2 - α_coeff = 4 + α_coeff = 4max_steps*γ ## FE Setup model = CartesianDiscreteModel(dom,el_size); @@ -73,6 +73,99 @@ function main() ## Finite difference solver and level set function ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + ## Setup solver and FE operators + state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) + pcfs = if AD + PDEConstrainedFunctionals(J,[Vol],state_map,analytic_dJ=dJ,analytic_dC=[dVol]) + else + PDEConstrainedFunctionals(J,[Vol],state_map) + end + + ## Hilbertian extension-regularisation problems + α = α_coeff*maximum(el_Δ) + a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; + vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) + + ## Optimiser + optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; + γ,γ_reinit,verbose=true,constraint_names=[:Vol]) + + # Do a few iterations + vars, state = iterate(optimiser) + vars, state = iterate(optimiser,state) + true +end + +""" + (Serial) Minimum thermal compliance with augmented Lagrangian method in 3D. + + Optimisation problem: + Min J(Ω) = ∫ κ*∇(u)⋅∇(u) dΩ + Ω + s.t., Vol(Ω) = vf, + ⎡u∈V=H¹(Ω;u(Γ_D)=0), + ⎣∫ κ*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. +""" +function main_3d(;order) + ## Parameters + xmax = ymax = zmax = 1.0 + prop_Γ_N = 0.2 + prop_Γ_D = 0.2 + dom = (0,xmax,0,ymax,0,zmax) + el_size = (20,20,20) + γ = 0.1 + γ_reinit = 0.5 + max_steps = floor(Int,order*minimum(el_size)/10) + tol = 1/(5*order^2)/minimum(el_size) + κ = 1 + vf = 0.4 + η_coeff = 2 + α_coeff = 4max_steps*γ + + ## FE Setup + model = CartesianDiscreteModel(dom,el_size); + el_Δ = get_el_Δ(model) + f_Γ_D(x) = (x[1] ≈ 0.0) && (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps()) && + (x[3] <= zmax*prop_Γ_D + eps() || x[3] >= zmax-zmax*prop_Γ_D - eps()) + f_Γ_N(x) = (x[1] ≈ xmax) && (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) && + (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) + update_labels!(1,model,f_Γ_D,"Gamma_D") + update_labels!(2,model,f_Γ_N,"Gamma_N") + + ## Triangulations and measures + Ω = Triangulation(model) + Γ_N = BoundaryTriangulation(model,tags="Gamma_N") + dΩ = Measure(Ω,2*order) + dΓ_N = Measure(Γ_N,2*order) + vol_D = sum(∫(1)dΩ) + + ## Spaces + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_D"]) + U = TrialFESpace(V,0.0) + V_φ = TestFESpace(model,reffe_scalar) + V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) + U_reg = TrialFESpace(V_reg,0) + + ## Create FE functions + φh = interpolate(initial_lsf(4,0.2),V_φ) + + ## Interpolation and weak form + interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + + a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ + l(v,φ,dΩ,dΓ_N) = ∫(v)dΓ_N + + ## Optimisation functionals + J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ + dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; + Vol(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; + dVol(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + + ## Finite difference solver and level set function + ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) + ## Setup solver and FE operators state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) pcfs = PDEConstrainedFunctionals(J,[Vol],state_map,analytic_dJ=dJ,analytic_dC=[dVol]) @@ -89,8 +182,13 @@ function main() # Do a few iterations vars, state = iterate(optimiser) vars, state = iterate(optimiser,state) + true end -main() +# Test that these run successfully +@test main(;order=1,AD=true) +@test main(;order=2,AD=true) +@test main(;order=1,AD=false) +@test main_3d(;order=1) end # module \ No newline at end of file diff --git a/test/seq/runtests.jl b/test/seq/runtests.jl index 92ccacfa..20fd54e7 100644 --- a/test/seq/runtests.jl +++ b/test/seq/runtests.jl @@ -3,5 +3,8 @@ module LSTOSequentialTests using Test @time @testset "Thermal Compliance - ALM" begin include("ThermalComplianceALMTests.jl") end +@time @testset "Nonlinear Thermal Compliance - ALM" begin include("NonLinearThermalComplianceALMTests.jl") end +@time @testset "Inverse Homogenisation - ALM" begin include("InverseHomogenisationALMTests.jl") end +@time @testset "Inverter - HPM" begin include("InverterHPMTests.jl") end end # module \ No newline at end of file From e93e121eb23e773fb019bf4c3b08d4ec788024db Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Tue, 30 Apr 2024 08:33:00 +1000 Subject: [PATCH 82/90] Add PZMultiFieldRepeatingState Tests --- test/seq/PZMultiFieldRepeatingStateTests.jl | 191 ++++++++++++++++++++ test/seq/runtests.jl | 1 + 2 files changed, 192 insertions(+) create mode 100644 test/seq/PZMultiFieldRepeatingStateTests.jl diff --git a/test/seq/PZMultiFieldRepeatingStateTests.jl b/test/seq/PZMultiFieldRepeatingStateTests.jl new file mode 100644 index 00000000..827f9c91 --- /dev/null +++ b/test/seq/PZMultiFieldRepeatingStateTests.jl @@ -0,0 +1,191 @@ +module PZMultiFieldRepeatingStateTests +using Test + +using Gridap, GridapDistributed, GridapPETSc, GridapSolvers, + PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + +using Gridap.TensorValues, Gridap.Helpers + +## Parameters +function main(;AD) + el_size = (20,20) + order = 1 + xmax,ymax=(1.0,1.0) + dom = (0,xmax,0,ymax) + γ = 0.1 + γ_reinit = 0.5 + max_steps = floor(Int,order*minimum(el_size)/10) + tol = 1/(5order^2)/minimum(el_size) + η_coeff = 2 + α_coeff = 4*max_steps*γ + vf = 0.5 + + ## FE Setup + model = CartesianDiscreteModel(dom,el_size,isperiodic=(true,true)) + el_Δ = get_el_Δ(model) + f_Γ_D(x) = iszero(x) + update_labels!(1,model,f_Γ_D,"origin") + + ## Triangulations and measures + Ω = Triangulation(model) + dΩ = Measure(Ω,2*order) + vol_D = sum(∫(1)dΩ) + + ## Spaces + reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) + reffe_scalar = ReferenceFE(lagrangian,Float64,order) + V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["origin"]) + U = TrialFESpace(V,VectorValue(0.0,0.0)) + Q = TestFESpace(model,reffe_scalar;conformity=:H1,dirichlet_tags=["origin"]) + P = TrialFESpace(Q,0) + UP = MultiFieldFESpace([U,P]) + VQ = MultiFieldFESpace([V,Q]) + + V_φ = TestFESpace(model,reffe_scalar) + V_reg = TestFESpace(model,reffe_scalar) + U_reg = TrialFESpace(V_reg) + + ## Create FE functions + φh = interpolate(initial_lsf(2,0.2),V_φ) + + ## Interpolation and weak form + interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ),ϵ=10^-9) + I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ + + ## Material tensors + C, e, κ = PZT5A_2D(); + k0 = norm(C.data,Inf); + α0 = norm(e.data,Inf); + β0 = norm(κ.data,Inf); + γ0 = β0*k0/α0^2; + + ## Weak forms + εᴹ = (SymTensorValue(1.0,0.0,0.0), + SymTensorValue(0.0,0.0,1.0), + SymTensorValue(0.0,1/2,0)) + Eⁱ = (VectorValue(1.0,0.0,), + VectorValue(0.0,1.0)) + + a((u,ϕ),(v,q),φ,dΩ) = ∫((I ∘ φ) * (1/k0*((C ⊙ ε(u)) ⊙ ε(v)) - + 1/α0*((-∇(ϕ) ⋅ e) ⊙ ε(v)) + + -1/α0*((e ⋅² ε(u)) ⋅ -∇(q)) + + -γ0/β0*((κ ⋅ -∇(ϕ)) ⋅ -∇(q))) )dΩ; + + l_ε = [((v,q),φ,dΩ) -> ∫(((I ∘ φ) * (-C ⊙ εᴹ[i] ⊙ ε(v) + k0/α0*(e ⋅² εᴹ[i]) ⋅ -∇(q))))dΩ for i = 1:3]; + l_E = [((v,q),φ,dΩ) -> ∫((I ∘ φ) * ((Eⁱ[i] ⋅ e ⊙ ε(v) + k0/α0*(κ ⋅ Eⁱ[i]) ⋅ -∇(q))))dΩ for i = 1:2]; + l = [l_ε; l_E] + + function Cᴴ(r,s,uϕ,φ,dΩ) + u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] + ∫(1/k0 * (I ∘ φ) * (((C ⊙ (1/k0*ε(u_s) + εᴹ[s])) ⊙ εᴹ[r]) - ((-1/α0*∇(ϕ_s) ⋅ e) ⊙ εᴹ[r])))dΩ; + end + + function DCᴴ(r,s,q,uϕ,φ,dΩ) + u_r = uϕ[2r-1]; ϕ_r = uϕ[2r] + u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] + ∫(- 1/k0 * q * ( + (C ⊙ (1/k0*ε(u_s) + εᴹ[s])) ⊙ (1/k0*ε(u_r) + εᴹ[r]) - + (-1/α0*∇(ϕ_s) ⋅ e) ⊙ (1/k0*ε(u_r) + εᴹ[r]) - + (e ⋅² (1/k0*ε(u_s) + εᴹ[s])) ⋅ (-1/α0*∇(ϕ_r)) - + (κ ⋅ (-1/α0*∇(ϕ_s))) ⋅ (-1/α0*∇(ϕ_r)) + ) * (DH ∘ φ) * (norm ∘ ∇(φ)) + )dΩ; + end + + Bᴴ(uϕ,φ,dΩ) = 1/4*(Cᴴ(1,1,uϕ,φ,dΩ)+Cᴴ(2,2,uϕ,φ,dΩ)+2*Cᴴ(1,2,uϕ,φ,dΩ)) + DBᴴ(q,uϕ,φ,dΩ) = 1/4*(DCᴴ(1,1,q,uϕ,φ,dΩ)+DCᴴ(2,2,q,uϕ,φ,dΩ)+2*DCᴴ(1,2,q,uϕ,φ,dΩ)) + + J(uϕ,φ,dΩ) = -1*Bᴴ(uϕ,φ,dΩ) + DJ(q,uϕ,φ,dΩ) = -1*DBᴴ(q,uϕ,φ,dΩ) + C1(uϕ,φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; + DC1(q,uϕ,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ + + ## Finite difference solver and level set function + stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) + + ## Setup solver and FE operators + state_map = RepeatingAffineFEStateMap(5,a,l,UP,VQ,V_φ,U_reg,φh,dΩ) + pcfs = if AD + PDEConstrainedFunctionals(J,[C1],state_map;analytic_dJ=DJ,analytic_dC=[DC1]) + else + PDEConstrainedFunctionals(J,[C1],state_map) + end + + ## Hilbertian extension-regularisation problems + α = α_coeff*maximum(el_Δ) + a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; + vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) + + # ## Optimiser + optimiser = HilbertianProjection(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=true) + vars, state = iterate(optimiser) + vars, state = iterate(optimiser,state) + true +end + +function PZT5A_2D() + ε_0 = 8.854e-12; + C_Voigt = [12.0400e10 7.51000e10 0.0 + 7.51000e10 11.0900e10 0.0 + 0.0 0.0 2.1000e10] + e_Voigt = [0.0 0.0 12.30000 + -5.40000 15.80000 0.0] + K_Voigt = [540*ε_0 0 + 0 830*ε_0] + C = voigt2tensor4(C_Voigt) + e = voigt2tensor3(e_Voigt) + κ = voigt2tensor2(K_Voigt) + C,e,κ +end + +""" + Given a material constant given in Voigt notation, + return a SymFourthOrderTensorValue using ordering from Gridap +""" +function voigt2tensor4(A::Array{M,2}) where M + if isequal(size(A),(3,3)) + return SymFourthOrderTensorValue(A[1,1], A[3,1], A[2,1], + A[1,3], A[3,3], A[2,3], + A[1,2], A[3,2], A[2,2]) + elseif isequal(size(A),(6,6)) + return SymFourthOrderTensorValue(A[1,1], A[6,1], A[5,1], A[2,1], A[4,1], A[3,1], + A[1,6], A[6,6], A[5,6], A[2,6], A[4,6], A[3,6], + A[1,5], A[6,5], A[5,5], A[2,5], A[4,5], A[3,5], + A[1,2], A[6,2], A[5,2], A[2,2], A[4,2], A[3,2], + A[1,4], A[6,4], A[5,4], A[2,4], A[4,4], A[3,4], + A[1,3], A[6,3], A[5,3], A[2,3], A[4,3], A[3,3]) + else + @notimplemented + end +end + +""" + Given a material constant given in Voigt notation, + return a ThirdOrderTensorValue using ordering from Gridap +""" +function voigt2tensor3(A::Array{M,2}) where M + if isequal(size(A),(2,3)) + return ThirdOrderTensorValue(A[1,1], A[2,1], A[1,3], A[2,3], A[1,3], A[2,3], A[1,2], A[2,2]) + elseif isequal(size(A),(3,6)) + return ThirdOrderTensorValue( + A[1,1], A[2,1], A[3,1], A[1,6], A[2,6], A[3,6], A[1,5], A[2,5], A[3,5], + A[1,6], A[2,6], A[3,6], A[1,2], A[2,2], A[3,2], A[1,4], A[2,4], A[3,4], + A[1,5], A[2,5], A[3,5], A[1,4], A[2,4], A[3,4], A[1,3], A[2,3], A[3,3]) + else + @notimplemented + end +end + +""" + Given a material constant given in Voigt notation, + return a SymTensorValue using ordering from Gridap +""" +function voigt2tensor2(A::Array{M,2}) where M + return TensorValue(A) +end + +# Test that these run successfully +@test main(;AD=true) +@test main(;AD=false) + +end # module \ No newline at end of file diff --git a/test/seq/runtests.jl b/test/seq/runtests.jl index 20fd54e7..6338d22d 100644 --- a/test/seq/runtests.jl +++ b/test/seq/runtests.jl @@ -6,5 +6,6 @@ using Test @time @testset "Nonlinear Thermal Compliance - ALM" begin include("NonLinearThermalComplianceALMTests.jl") end @time @testset "Inverse Homogenisation - ALM" begin include("InverseHomogenisationALMTests.jl") end @time @testset "Inverter - HPM" begin include("InverterHPMTests.jl") end +@time @testset "PZMultiFieldRepeatingState - ALM" begin include("PZMultiFieldRepeatingStateTests.jl") end end # module \ No newline at end of file From 38ad633a06dd128d65c60b4625a7062d84bf915d Mon Sep 17 00:00:00 2001 From: JordiManyer Date: Wed, 1 May 2024 10:28:42 +1000 Subject: [PATCH 83/90] Bugfix: repeated_blocks --- src/ChainRules.jl | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/src/ChainRules.jl b/src/ChainRules.jl index 1a2a5f49..501c4f7b 100644 --- a/src/ChainRules.jl +++ b/src/ChainRules.jl @@ -785,9 +785,7 @@ repeated_blocks(V0::FESpace,x::AbstractBlockVector) = blocks(x) repeated_blocks(V0::FESpace,xh) = xh repeated_blocks(V0::MultiFieldSpaceTypes,x::AbstractBlockVector) = repeated_blocks(MultiFieldStyle(V0),V0,x) -repeated_blocks(V0::MultiFieldSpaceTypes,x) = repeated_blocks(MultiFieldStyle(V0),V0,x) repeated_blocks(::ConsecutiveMultiFieldStyle,V0,x::AbstractBlockVector) = blocks(x) -repeated_blocks(::ConsecutiveMultiFieldStyle,V0,xh) = xh function repeated_blocks(::BlockMultiFieldStyle{NB},V0::MultiFieldSpaceTypes,x::AbstractBlockVector) where NB xb = blocks(x) @@ -800,7 +798,7 @@ function repeated_blocks(::BlockMultiFieldStyle{NB},V0::MultiFieldSpaceTypes,x:: return rep_blocks end -function repeated_blocks(::BlockMultiFieldStyle,V0::MultiFieldSpaceTypes,xh) +function repeated_blocks(V0::MultiFieldSpaceTypes,xh) x_blocks = repeated_blocks(MultiFieldStyle(V0),V0,get_free_dof_values(xh)) rep_blocks = map(x_blocks) do xb FEFunction(V0,xb) From 6e1bcc1b2a86b70019cc3aa3f60e12cc437ccc35 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Tue, 7 May 2024 11:11:51 +1000 Subject: [PATCH 84/90] clean up repo --- .../Deprecated_root_files/ChainRules.jl | 594 ------------------ Deprecated/Deprecated_root_files/LevelSet.jl | 205 ------ Deprecated/Deprecated_root_files/MainMPI.jl | 59 -- .../Deprecated_root_files/OptimiseALM.jl | 68 -- .../Deprecated_root_files/OptimiseHPM.jl | 89 --- .../Deprecated_root_files/ProjectionMethod.jl | 144 ----- Deprecated/Deprecated_root_files/Setup.jl | 444 ------------- Deprecated/Deprecated_root_files/Utilities.jl | 136 ---- 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mode 100644 index 0d428fb6..00000000 --- a/Deprecated/Deprecated_root_files/ChainRules.jl +++ /dev/null @@ -1,594 +0,0 @@ -# ========================================================== -# ========================================================== -# HELPER FUNCTIONS -# ========================================================== -# ========================================================== - -function Adjoint(ϕ,u,du,op,res,Q)#,solver) - A = Gridap.jacobian(op,u) # = dr/du - Aᵀ = adjoint(A) - V = op.test - λₕ = FEFunction(V,Aᵀ\du)#,solver) - ϕh = FEFunction(Q,ϕ) - dϕ() = Gridap.FESpaces.gradient(ϕh -> res(u,λₕ,ϕh),ϕh) - dϕ = -assemble_vector(dϕ(),Q) -end - -function AdjointAffine(ϕ,u,du,op,a,Q)#,solver) - A = Gridap.jacobian(op,u) # = dr/du - Aᵀ = adjoint(A) - V = op.test - λₕ = FEFunction(V,Aᵀ\du)#,solver) - ϕh = FEFunction(Q,ϕ) - dϕ() = Gridap.FESpaces.gradient(ϕh -> res(u,λₕ,ϕh,Q),ϕh) - dϕ = -assemble_vector(dϕ(),Q) -end - -# ================ -# ================ -# CHAIN RULES MAIN -# ================ -# ================ - -# ============================================================ -# u -> J : Struct representing the scalar objective evaluation -# ============================================================ - -struct LossFunction{P,U} - loss::Function - param_sp::P - state_sp::U - # assem::Assembler -end - -function (u_to_j::LossFunction)(u,ϕ) - loss=u_to_j.loss - U=u_to_j.state_sp - Q=u_to_j.param_sp - uₕ=FEFunction(U,u) - ϕₕ=FEFunction(Q,ϕ) - sum(loss(uₕ,ϕₕ)) -end - -function ChainRulesCore.rrule(u_to_j::LossFunction,u,ϕ) - loss=u_to_j.loss - U=u_to_j.state_sp - Q=u_to_j.param_sp - uₕ=FEFunction(U,u) - ϕₕ=FEFunction(Q,ϕ) - jp=sum(loss(uₕ,ϕₕ)) - function u_to_j_pullback(dj) - djdu = ∇(uₕ->loss(uₕ,ϕₕ))(uₕ) - djdu_vec = assemble_vector(djdu,U) - djdϕ = ∇(ϕₕ->loss(uₕ,ϕₕ))(ϕₕ) - djdϕ_vec = assemble_vector(djdϕ,Q) - ( NoTangent(), dj*djdu_vec, dj*djdϕ_vec ) - end - jp, u_to_j_pullback -end -# ================================================================================================================================== -# ϕ -> u : Struct that represents the FE solution of a parameterised Affine PDE. It is a map from the parameter space P to a FESpace -# ================================================================================================================================== - -struct _AffineFEStateMap{P,U <: FESpace, V <: FESpace} - a::Function - ℓ::Function - res::Function - param_sp::P # params (CellData) - trial::U - test::V - # assem::Assembler -end - -function (ϕ_to_u::_AffineFEStateMap)(ϕ) - a=ϕ_to_u.a - l=ϕ_to_u.ℓ - res=ϕ_to_u.res - Q=ϕ_to_u.param_sp - U=ϕ_to_u.trial - V=ϕ_to_u.test - op = AffineFEOperator(a(ϕ),l(ϕ),U,V) - get_free_dof_values(Gridap.solve(op)) -end - -function ChainRulesCore.rrule(ϕ_to_u::_AffineFEStateMap,ϕ) - a=ϕ_to_u.a - l=ϕ_to_u.ℓ - res=ϕ_to_u.res - Q=ϕ_to_u.param_sp - U=ϕ_to_u.trial - V=ϕ_to_u.test - op = AffineFEOperator(a(ϕ),l(ϕ),U,V) - uₕ = Gridap.solve(op) - function ϕ_to_u_pullback(du) - dϕ = Adjoint(ϕ,uₕ,du,op,res,Q) - ( NoTangent(),dϕ) - end - get_free_dof_values(uₕ), ϕ_to_u_pullback -end - -# ========================================================= -# ϕn1 -> ϕb4 : Adding the volume constraint enforcing bias -# ========================================================= - -struct VolumeConstraintMap{P} - ϕ_b_to_ϕc::Function - b::Function - ϕ_b_to_Vol::Function - param_sp::P - Vₘₐₓ::Float64 - problem#::ProblemType -end - -function (ϕₛ₃_to_ϕ::VolumeConstraintMap)(ϕₛ₃) - ϕ_b_to_ϕc=ϕₛ₃_to_ϕ.ϕ_b_to_ϕc - b = ϕₛ₃_to_ϕ.b - Vbg = ϕₛ₃_to_ϕ.param_sp - Vₘₐₓ = ϕₛ₃_to_ϕ.Vₘₐₓ - problem = ϕₛ₃_to_ϕ.problem - - bp = b(ϕₛ₃,Vbg,Vₘₐₓ,problem) - ϕp = ϕ_b_to_ϕc(ϕₛ₃,bp,problem) -end - -function ChainRulesCore.rrule(ϕₛ₃_to_ϕ::VolumeConstraintMap,ϕₛ₃) - ϕ_b_to_ϕc=ϕₛ₃_to_ϕ.ϕ_b_to_ϕc - b = ϕₛ₃_to_ϕ.b - ϕ_b_to_Vol = ϕₛ₃_to_ϕ.ϕ_b_to_Vol - Vbg = ϕₛ₃_to_ϕ.param_sp - Vₘₐₓ = ϕₛ₃_to_ϕ.Vₘₐₓ - problem = ϕₛ₃_to_ϕ.problem - - bp = b(ϕₛ₃,Vbg,Vₘₐₓ,problem) - ϕp = ϕ_b_to_ϕc(ϕₛ₃,bp,problem) - - ab_r = AD.ReverseDiffBackend() - pb_ϕₛ₃ = AD.pullback_function(ab_r, ϕₛ₃ -> ϕ_b_to_ϕc(ϕₛ₃,bp,problem) , ϕₛ₃) - pb_b = AD.pullback_function(ab_r, bp -> ϕ_b_to_ϕc(ϕₛ₃,bp,problem) , bp) - - function ϕᵤ_to_ϕ_pullback(dϕ) - dVoldϕₛ₃ = ReverseDiff.gradient( ϕ -> ϕ_b_to_Vol(ϕ,bp,Vbg,problem), reshape(ϕₛ₃,(length(ϕₛ₃),1))) # N X 1 - dVoldb = ForwardDiff.derivative( b -> ϕ_b_to_Vol(ϕₛ₃,b,Vbg,problem), bp) # N X 1 - dϕdb_dϕ = pb_b(dϕ)[1][1] #sum(dϕ) # 1 X 1 = ( 1 X N ) * ( N X 1 ) - dϕₛ₃₍ₘ₎ = pb_ϕₛ₃(dϕ)[1] - dVoldϕₛ₃*(dVoldb)^-1 * dϕdb_dϕ # N X Q X Q X 1 + (N X 1) X (1 X 1) X [(1 X 1)] where the last 1X1 is from the above loop - dϕₛ₃ = collect1d(dϕₛ₃₍ₘ₎) - (NoTangent(), dϕₛ₃) - end - ϕp,ϕᵤ_to_ϕ_pullback -end - -#= - -function (ϕₛ₃_to_ϕ::VolumeConstraintMap)(ϕₛ₃,method::MethodType{:constrained}) - ϕₛ₃ -end - -function ChainRulesCore.rrule(ϕₛ₃_to_ϕ::VolumeConstraintMap,ϕₛ₃,method::MethodType{:constrained}) - function ϕᵤ_to_ϕ_pullback(dϕ) - (NoTangent(), dϕ, NoTangent()) - end - ϕₛ₃,ϕᵤ_to_ϕ_pullback -end - -function (ϕₛ₃_to_ϕ::VolumeConstraintMap)(ϕₛ₃,method::MethodType{:unconstrained}) - ϕₛ₃_to_ϕ(ϕₛ₃) -end - -function ChainRulesCore.rrule(ϕₛ₃_to_ϕ::VolumeConstraintMap,ϕₛ₃,method::MethodType{:unconstrained}) - ϕₛ₃,ϕᵤ_to_ϕ_pullback =rrule(ϕₛ₃_to_ϕ,ϕₛ₃) - function ϕᵤ_to_ϕ_pullback_with_extra_NoTangent(dϕ) - (ϕᵤ_to_ϕ_pullback(dϕ)...,NoTangent()) - end - ϕₛ₃, ϕᵤ_to_ϕ_pullback_with_extra_NoTangent -end - -=# - -# ============================================================================================================================================================================================= -# ϕᵧ₂ -> ϕₛ₃ : Applying the signed distance reinitialisation. This is another FEStateMap which, as apposed to the Affine version, solves the nonlinear residual using a specified initial point -# ============================================================================================================================================================================================= - -struct InitialisableFEStateMap{P,U <: FESpace, V <: FESpace} - res::Function - jac::Function - get_geo_params::Function - param_sp::P # params (CellData) - trial::U - test::V - # assem::Assembler -end - -function (ϕᵧ₂_to_ϕₛ₃::InitialisableFEStateMap)(ϕ) - res=ϕᵧ₂_to_ϕₛ₃.res - jac=ϕᵧ₂_to_ϕₛ₃.jac - #get_geo_params_=ϕᵧ₂_to_ϕₛ₃.get_geo_params - Q=ϕᵧ₂_to_ϕₛ₃.param_sp - U=ϕᵧ₂_to_ϕₛ₃.trial - V=ϕᵧ₂_to_ϕₛ₃.test - #fϕ,_=get_geo_params(ϕ,Q) - op = FEOperator(res(ϕ),jac(ϕ),U,V) - ls = LUSolver() - nls = NLSolver( - show_trace=true, method=:newton, linesearch=BackTracking(), ftol=1e-12, iterations= 50 ) - solver = FESolver(nls) - ϕh = FEFunction(V,copy(ϕ)) - ϕₛ₃,_ = Gridap.solve!(ϕh,nls,op) - ϕₛ₃.free_values -end - -function ChainRulesCore.rrule(ϕᵧ₂_to_ϕₛ₃::InitialisableFEStateMap,ϕ) - res=ϕᵧ₂_to_ϕₛ₃.res - jac=ϕᵧ₂_to_ϕₛ₃.jac - #get_geo_params_=ϕᵧ₂_to_ϕₛ₃.get_geo_params - Q=ϕᵧ₂_to_ϕₛ₃.param_sp - U=ϕᵧ₂_to_ϕₛ₃.trial - V=ϕᵧ₂_to_ϕₛ₃.test - #fϕ,_=get_geo_params(ϕ,Q) - op = FEOperator(res(ϕ),jac(ϕ),U,V) - ls = LUSolver() - nls = NLSolver( - show_trace=true, method=:newton, linesearch=BackTracking(), ftol=1e-12, iterations= 50 ) - solver = FESolver(nls) - ϕh = FEFunction(V,copy(ϕ)) - ϕₛ₃,_ = Gridap.solve!(ϕh,nls,op) - function ϕᵧ₂_to_ϕₛ₃_pullback(dϕₛ₃) - dϕᵧ₂ = Adjoint(ϕ,ϕₛ₃,dϕₛ₃,op,res,Q) - (NoTangent(),dϕᵧ₂) - end - ϕₛ₃.free_values, ϕᵧ₂_to_ϕₛ₃_pullback -end - -#= - -function (ϕᵧ₂_to_ϕₛ₃::InitialisableFEStateMap)(ϕᵧ₂,method::MethodType{:unconstrained},problem::ProblemType{:heat_simp}) - ϕᵧ₂ -end - -function ChainRulesCore.rrule(ϕᵧ₂_to_ϕₛ₃::InitialisableFEStateMap,ϕᵧ₂,method::MethodType{:unconstrained},problem::ProblemType{:heat_simp}) - function ϕᵧ₂_to_ϕₛ₃_pullback(dϕₛ₃) - ( NoTangent(),dϕₛ₃, NoTangent(), NoTangent()) - end - ϕᵧ₂, ϕᵧ₂_to_ϕₛ₃_pullback -end - -function (ϕᵧ₂_to_ϕₛ₃::InitialisableFEStateMap)(ϕᵧ₂,method::MethodType{:constrained},problem::ProblemType{:heat_simp}) - ϕᵧ₂ -end - -function ChainRulesCore.rrule(ϕᵧ₂_to_ϕₛ₃::InitialisableFEStateMap,ϕᵧ₂,method::MethodType{:constrained},problem::ProblemType{:heat_simp}) - function ϕᵧ₂_to_ϕₛ₃_pullback(dϕₛ₃) - ( NoTangent(),dϕₛ₃, NoTangent(), NoTangent()) - end - ϕᵧ₂, ϕᵧ₂_to_ϕₛ₃_pullback -end - -function (ϕᵧ₂_to_ϕₛ₃::InitialisableFEStateMap)(ϕᵧ₂,method::MethodType{:constrained},problem) - ϕᵧ₂ -end - -function ChainRulesCore.rrule(ϕᵧ₂_to_ϕₛ₃::InitialisableFEStateMap,ϕᵧ₂,method::MethodType{:constrained},problem) - function ϕᵧ₂_to_ϕₛ₃_pullback(dϕₛ₃) - ( NoTangent(),dϕₛ₃, NoTangent(), NoTangent()) - end - ϕᵧ₂, ϕᵧ₂_to_ϕₛ₃_pullback -end - -function (ϕᵧ₂_to_ϕₛ₃::InitialisableFEStateMap)(ϕᵧ₂,method::MethodType{:unconstrained},problem) - ϕᵧ₂_to_ϕₛ₃(ϕᵧ₂) -end - -function ChainRulesCore.rrule(ϕᵧ₂_to_ϕₛ₃::InitialisableFEStateMap,ϕᵧ₂,method::MethodType{:unconstrained},problem) - ϕₛ₃,ϕᵧ₂_to_ϕₛ₃_pullback = rrule(ϕᵧ₂_to_ϕₛ₃,ϕᵧ₂) - function ϕᵧ₂_to_ϕₛ₃_pullback_with_extra_NoTangent(dϕₛ₃) - (ϕᵧ₂_to_ϕₛ₃_pullback(dϕₛ₃)...,NoTangent(), NoTangent()) - end - ϕₛ₃, ϕᵧ₂_to_ϕₛ₃_pullback_with_extra_NoTangent -end - -=# - - -# ============================================================================================================================================================================================= -# An extra Affine InitialisableAffineFEStateMap -# ============================================================================================================================================================================================= - -struct InitialisableAffineFEStateMap{P,U <: FESpace, V <: FESpace} - a::Function - l::Function - res::Function - param_sp::P # params (CellData) - trial::U - test::V - # assem::Assembler -end - -function (ϕᵧ₂_to_ϕₛ₃::InitialisableAffineFEStateMap)(ϕ) - a = ϕᵧ₂_to_ϕₛ₃.a - l = ϕᵧ₂_to_ϕₛ₃.l - res=ϕᵧ₂_to_ϕₛ₃.res - Q=ϕᵧ₂_to_ϕₛ₃.param_sp - U=ϕᵧ₂_to_ϕₛ₃.trial - V=ϕᵧ₂_to_ϕₛ₃.test - op = AffineFEOperator(a(ϕ),l(ϕ),U,V) - ls = LUSolver() - solver = FESolver(nls) - ϕh = FEFunction(V,copy(ϕ)) - ϕₛ₃,_ = Gridap.solve!(ϕh,ls,op) - ϕₛ₃.free_values -end - -function ChainRulesCore.rrule(ϕᵧ₂_to_ϕₛ₃::InitialisableAffineFEStateMap,ϕ) - res=ϕᵧ₂_to_ϕₛ₃.res - jac=ϕᵧ₂_to_ϕₛ₃.jac - #get_geo_params_=ϕᵧ₂_to_ϕₛ₃.get_geo_params - Q=ϕᵧ₂_to_ϕₛ₃.param_sp - U=ϕᵧ₂_to_ϕₛ₃.trial - V=ϕᵧ₂_to_ϕₛ₃.test - #fϕ,_=get_geo_params(ϕ,Q) - op = AffineFEOperator(a(ϕ),l(ϕ),U,V) - ls = LUSolver() - solver = FESolver(nls) - ϕh = FEFunction(V,copy(ϕ)) - ϕₛ₃,_ = Gridap.solve!(ϕh,ls,op) - function ϕᵧ₂_to_ϕₛ₃_pullback(dϕₛ₃) - dϕᵧ₂ = Adjoint(ϕ,ϕₛ₃,dϕₛ₃,op,res,Q) - (NoTangent(),dϕᵧ₂) - end - ϕₛ₃.free_values, ϕᵧ₂_to_ϕₛ₃_pullback -end - - -# ============================================================================================================================================================================================= -# An extra Affine InitialisableFEStateMap that can utilise autodiff but has to use a hack for the part of res not dep on u for the moment -# ============================================================================================================================================================================================= - -struct InitialisableAutoFEStateMap{P,U <: FESpace, V <: FESpace} - res::Function - res_ϕ::Function - param_sp::P # params (CellData) - trial::U - test::V - u0::Array{Float64} - # assem::Assembler -end - -function (ϕᵧ₂_to_ϕₛ₃::InitialisableAutoFEStateMap)(ϕ) - res=ϕᵧ₂_to_ϕₛ₃.res - res_ϕ=ϕᵧ₂_to_ϕₛ₃.res_ϕ - Q=ϕᵧ₂_to_ϕₛ₃.param_sp - U=ϕᵧ₂_to_ϕₛ₃.trial - V=ϕᵧ₂_to_ϕₛ₃.test - u0 = ϕᵧ₂_to_ϕₛ₃.u0 - op = FEOperator(res(ϕ),U,V) - #ls = LUSolver() - nls = NLSolver( - show_trace=true, method=:newton, linesearch=BackTracking(), ftol=1e-9, iterations= 50 ) - solver = FESolver(nls) - ϕₛ₃0h = FEFunction(V,copy(u0)) - ϕₛ₃,_ = Gridap.solve!(ϕₛ₃0h,nls,op) - ϕₛ₃.free_values -end - -function ChainRulesCore.rrule(ϕᵧ₂_to_ϕₛ₃::InitialisableAutoFEStateMap,ϕ) - res=ϕᵧ₂_to_ϕₛ₃.res - res_ϕ=ϕᵧ₂_to_ϕₛ₃.res_ϕ - Q=ϕᵧ₂_to_ϕₛ₃.param_sp - U=ϕᵧ₂_to_ϕₛ₃.trial - V=ϕᵧ₂_to_ϕₛ₃.test - u0 = ϕᵧ₂_to_ϕₛ₃.u0 - op = FEOperator(res(ϕ),U,V) - #ls = LUSolver() - nls = NLSolver( - show_trace=true, method=:newton, linesearch=BackTracking(), ftol=1e-9, iterations= 50 ) - solver = FESolver(nls) - ϕh = FEFunction(V,copy(u0)) - ϕₛ₃,_ = Gridap.solve!(ϕh,nls,op) - function ϕᵧ₂_to_ϕₛ₃_pullback(dϕₛ₃) - dϕᵧ₂ = Adjoint(ϕ,ϕₛ₃,dϕₛ₃,op,res_ϕ,Q) - (NoTangent(),dϕᵧ₂) - end - ϕₛ₃.free_values, ϕᵧ₂_to_ϕₛ₃_pullback -end - -# ========================================================= -# ϕₙ₁ -> ϕᵧ₂ : Smoothing the level set with a linear filter -# ========================================================= - -struct LinearFilter - bgmodel::CartesianDiscreteModel - filter_weights::Matrix{Float64} - pullback_jacobian::Function # This is a constant matrix : we keep it as a pullback to avoid assembling -end - -function (ϕₙ₁_to_ϕᵧ₂::LinearFilter)(ϕₙ₁) - bgmodel=ϕₙ₁_to_ϕᵧ₂.bgmodel - filter_weights = ϕₙ₁_to_ϕᵧ₂.filter_weights - ϕᵧ₂ = apply_filter(filter_weights,bgmodel,ϕₙ₁) -end - -function ChainRulesCore.rrule(ϕₙ₁_to_ϕᵧ₂::LinearFilter,ϕₙ₁) - bgmodel=ϕₙ₁_to_ϕᵧ₂.bgmodel - filter_weights = ϕₙ₁_to_ϕᵧ₂.filter_weights - pb_f = ϕₙ₁_to_ϕᵧ₂.pullback_jacobian - ϕᵧ₂ = apply_filter(filter_weights,bgmodel,ϕₙ₁) - function ϕₙ₁_to_ϕᵧ₂_pullback(dϕᵧ₂) - dϕₙ₁M = pb_f(dϕᵧ₂)[1] - cd = Gridap.Geometry.get_cartesian_descriptor(bgmodel) - cells = cd.partition - dϕₙ₁ = collect(reshape(dϕₙ₁M,(cells[1]+1)*(cells[2]+1))) - (NoTangent(),dϕₙ₁) - end - ϕᵧ₂,ϕₙ₁_to_ϕᵧ₂_pullback -end - -function apply_filter(filter_weights,bgmodel,ϕₙ₁) - cd = Gridap.Geometry.get_cartesian_descriptor(bgmodel) - cells = cd.partition - ϕₙ₁M=reshape(ϕₙ₁,(cells[1]+1,cells[2]+1)) - w = centered(filter_weights) - ϕᵧ₂M = imfilter(ϕₙ₁M,w,"replicate") - ϕᵧ₂ = reshape(ϕᵧ₂M,(cells[1]+1)*(cells[2]+1)) -end - -# =============================================================================================================================================================================================== -# p -> ϕn1 : A map from the initial parameterisation to level set values. The initial parameterisation may be a neural network or simply pixel based (in which case this map is the identity). -# =============================================================================================================================================================================================== - -# We also include here a tape for mapping p to L where L is the sub-objective for matching a level set to a desired level set. This is used to train a neural network to provide a specified initial guess (defined by a set of level set values). -struct NeuralObjective - N0::Vector{Float64} -end - -function (ϕₙ₁_to_L::NeuralObjective)(ϕₙ₁) - N0 = ϕₙ₁_to_L.N0 - sum( (N0.-ϕₙ₁).^2 ) / length(N0) -end - -function ChainRulesCore.rrule(ϕₙ₁_to_L::NeuralObjective,ϕₙ₁) - function ϕₙ₁_to_L_pullback(dL) - dϕₙ₁ = ForwardDiff.gradient(ϕₙ₁_to_L,ϕₙ₁) * dL - ( NoTangent(), dϕₙ₁) - end - ϕₙ₁_to_L(ϕₙ₁), ϕₙ₁_to_L_pullback -end - -struct NeuralGeometry - N::Function - pP::Vector{Float64} -end - -function (p_to_ϕₙ₁::NeuralGeometry)(p) - N = p_to_ϕₙ₁.N - pP = p_to_ϕₙ₁.pP - Nh = N(p) # nucleation_promotion(N(p),pP) # - Np = collect(Iterators.flatten(Nh)) -end - -function ChainRulesCore.rrule(p_to_ϕₙ₁::NeuralGeometry,p) - N = p_to_ϕₙ₁.N - pP = p_to_ϕₙ₁.pP - Nh, dNdp_vjp = Zygote.pullback(N,p) # Zygote.pullback(p->nucleation_promotion(N(p),pP),p) # - Np = collect(Iterators.flatten(Nh)) - function p_to_ϕₙ₁_pullback(ds) - dp = dNdp_vjp(Float32.(ds))[1] - ( NoTangent(),dp ) - end - Np, p_to_ϕₙ₁_pullback -end - -#= - -function (p_to_ϕₙ₁::NeuralGeometry)(p,prior::PriorType{:pixel}) - p -end - -function ChainRulesCore.rrule(p_to_ϕₙ₁::NeuralGeometry,p,prior::PriorType{:pixel}) - function p_to_ϕₙ₁_pullback(dϕₙ₁) - dp=dϕₙ₁ - ( NoTangent(),dp, NoTangent()) - end - p_to_ϕₙ₁(p,prior), p_to_ϕₙ₁_pullback -end - -function (p_to_ϕₙ₁::NeuralGeometry)(p,prior::PriorType{:neural}) - p_to_ϕₙ₁(p) -end - -function ChainRulesCore.rrule(p_to_ϕₙ₁::NeuralGeometry,p,prior::PriorType{:neural}) - ϕₙ₁, p_to_ϕₙ₁_pullback = rrule(p_to_ϕₙ₁,p) - function p_to_ϕₙ₁_pullbackrrule_with_extra_NoTangent(dϕₙ₁) - (p_to_ϕₙ₁_pullback(dϕₙ₁)..., NoTangent()) - end - ϕₙ₁, p_to_ϕₙ₁_pullbackrrule_with_extra_NoTangent -end - -function p_to_L(p,bg_params) #prior) - ϕₙ₁ = p_to_ϕₙ₁(p,bg_params) #prior) - L = ϕₙ₁_to_L(ϕₙ₁,bg_params) # unfiltered unconstrained nodal values (s) to filtered unconstrained values (ϕᵤ) - L -end - -p_to_L(prior) = p -> p_to_L(p,prior) - -=# - -# ========================================================== -# ========================================================== -# CHAIN RULES CONSTRAINTS ( FOR USE WITH MMA ) -# ========================================================== -# ========================================================== - -struct VolumeMap{V<:FESpace} - ϕc_to_Vol::Function - param_space::V - problem#::ProblemType -end - -function (ϕ_to_Vol::VolumeMap)(ϕ) - ϕc_to_Vol=ϕ_to_Vol.ϕc_to_Vol - Vbg=ϕ_to_Vol.param_space - problem = ϕ_to_Vol.problem - - ϕc_to_Vol(ϕ,Vbg,problem) -end - -function ChainRulesCore.rrule(ϕ_to_Vol::VolumeMap,ϕ) - ϕc_to_Vol=ϕ_to_Vol.ϕc_to_Vol - Vbg=ϕ_to_Vol.param_space - problem = ϕ_to_Vol.problem - - Vol0=ϕc_to_Vol(ϕ,Vbg,problem) - - function ϕ_to_Vol_pullback(dVol) - dVoldϕ = ReverseDiff.gradient(ϕ -> ϕc_to_Vol(ϕ,Vbg,problem),reshape(ϕ,(length(ϕ),1))) - dϕₘ = dVol*dVoldϕ - dϕ = collect1d(dϕₘ) - ( NoTangent(),dϕ ) - end - Vol0, ϕ_to_Vol_pullback -end - -struct UnstructuredVolumeMap{V<:FESpace} - unstructured_ϕc_to_Vol::Function - param_space::V -end - -function (ϕ_to_Vol::UnstructuredVolumeMap)(ϕ) - unstructured_ϕc_to_Vol=ϕ_to_Vol.unstructured_ϕc_to_Vol - Qf=ϕ_to_Vol.param_space - - ϕh = FEFunction(Qf,ϕ) - - sum(unstructured_ϕc_to_Vol(ϕh)) -end - -function ChainRulesCore.rrule(ϕ_to_Vol::UnstructuredVolumeMap,ϕ) - unstructured_ϕc_to_Vol=ϕ_to_Vol.unstructured_ϕc_to_Vol - Qf=ϕ_to_Vol.param_space - - ϕh = FEFunction(Qf,ϕ) - - Vol0=sum(unstructured_ϕc_to_Vol(ϕh)) - - function ϕ_to_Vol_pullback(dVol) - dVoldϕ() = Gridap.FESpaces.gradient(ϕh -> unstructured_ϕc_to_Vol(ϕh),ϕh) #ReverseDiff.gradient(ϕ -> ϕc_to_Vol(ϕ,Vbg,problem),reshape(ϕ,(length(ϕ),1))) - dVoldϕ = assemble_vector(dVoldϕ(),Qf) - dϕ = dVol*dVoldϕ - ( NoTangent(),dϕ ) - end - Vol0, ϕ_to_Vol_pullback -end - -## Helpers -function φ_to_φₕ(φ::AbstractArray,Q) - φ = FEFunction(Q,φ) -end -function φ_to_φₕ(φ::FEFunction,Q) - φ -end -function φ_to_φₕ(φ::CellField,Q) - φ -end -function φ_to_φₕ(φ::GridapDistributed.DistributedCellField,Q) - φ -end \ No newline at end of file diff --git a/Deprecated/Deprecated_root_files/LevelSet.jl b/Deprecated/Deprecated_root_files/LevelSet.jl deleted file mode 100755 index b8ac90da..00000000 --- a/Deprecated/Deprecated_root_files/LevelSet.jl +++ /dev/null @@ -1,205 +0,0 @@ -# Generate initial LSF -gen_lsf(ξ,a) = x::VectorValue -> -1/4*prod(cos.(get_array(ξ*pi*x))) - a/4 - -# struct LevelSetUpdate{N,M} -# model -# fe_space -# γ -# max_steps -# cache - -# function LevelSetUpdate{M,N}() where {M,N} -# new{M,N}() -# end - -# end - -# struct VelocityExtension -# U -# V -# assem -# dΩ -# K -# cache -# end - -# struct LevelSetCache{N,M} - -# φ_tmp - -# end - -## H-J and reinit -""" - Single step for first order upwind method for H-J equation (2D) -""" -function advect!(φ::T,V::T,Δ::NTuple{2,M},Δt::M,caches) where {M,T<:Array{M,2}} - D⁺ʸ,D⁺ˣ,D⁻ʸ,D⁻ˣ,∇⁺,∇⁻=caches - Δx,Δy = Δ - # Prepare shifted lsf - circshift!(D⁺ʸ,φ,(0,-1)); circshift!(D⁻ʸ,φ,(0,1)); - circshift!(D⁺ˣ,φ,(-1,0)); circshift!(D⁻ˣ,φ,(1,0)); - # Forward (+) & Backward (-) - D⁺ʸ .= @. (D⁺ʸ - φ)/Δy; - D⁺ˣ .= @. (D⁺ˣ - φ)/Δx; - D⁻ʸ .= @. (φ - D⁻ʸ)/Δy; - D⁻ˣ .= @. (φ - D⁻ˣ)/Δx; - # Check for boundaries with ghost nodes - D⁺ʸ[:,end] .= zero(M); - D⁺ˣ[end,:] .= zero(M); - D⁻ʸ[:,1] .= zero(M); - D⁻ˣ[1,:] .= zero(M); - # Operators - ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2); - ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2); - # Update - φ .= @. φ - Δt*(max(V,0)*∇⁺ + min(V,0)*∇⁻); - return nothing -end - -""" - Single step for first order upwind method for reinitialisation equation (2D) -""" -function reinit!(φ::T,φ_tmp::T,S::T,Δ::NTuple{2,M},Δt::M,caches) where {M,T<:Array{M,2}} - D⁺ʸ,D⁺ˣ,D⁻ʸ,D⁻ˣ,∇⁺,∇⁻=caches - Δx,Δy = Δ - # Prepare shifted lsf - circshift!(D⁺ʸ,φ,(0,-1)); circshift!(D⁻ʸ,φ,(0,1)); - circshift!(D⁺ˣ,φ,(-1,0)); circshift!(D⁻ˣ,φ,(1,0)); - # Forward (+) & Backward (-) - D⁺ʸ .= @. (D⁺ʸ - φ)/Δy; - D⁺ˣ .= @. (D⁺ˣ - φ)/Δx; - D⁻ʸ .= @. (φ - D⁻ʸ)/Δy; - D⁻ˣ .= @. (φ - D⁻ˣ)/Δx; - # Check for boundaries with ghost nodes - D⁺ʸ[:,end] .= zero(M); - D⁺ˣ[end,:] .= zero(M); - D⁻ʸ[:,1] .= zero(M); - D⁻ˣ[1,:] .= zero(M); - # Operators - ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2); - ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2); - # Update - φ_tmp .= @. φ - Δt*(max(S,0)*∇⁺ + min(S,0)*∇⁻ - S); - return nothing -end - -""" - Single step for first order upwind method for H-J equation (3D) -""" -function advect!(φ::T,V::T,Δ::NTuple{3,M},Δt::M,caches) where {M,T<:Array{M,3}} - D⁺ʸ,D⁺ˣ,D⁻ʸ,D⁻ˣ,∇⁺,∇⁻=caches - Δx,Δy,Δz = Δ - # Prepare shifted lsf - circshift!(D⁺ʸ,φ,(0,-1,0)); circshift!(D⁻ʸ,φ,(0,1,0)); - circshift!(D⁺ˣ,φ,(-1,0,0)); circshift!(D⁻ˣ,φ,(1,0,0)); - circshift!(D⁺ᶻ,φ,(0,0,-1)); circshift!(D⁻ᶻ,φ,(0,0,1)); - # Forward (+) & Backward (-) - D⁺ʸ .= (D⁺ʸ - φ)/Δy; - D⁺ˣ .= (D⁺ˣ - φ)/Δx; - D⁺ᶻ .= (D⁺ᶻ - φ)/Δz; - D⁻ʸ .= (φ - D⁻ʸ)/Δy; - D⁻ˣ .= (φ - D⁻ˣ)/Δx; - D⁻ᶻ .= (φ - D⁻ᶻ)/Δz; - # Check for boundaries with ghost nodes - D⁺ʸ[:,end,:] .= zero(M); - D⁺ˣ[end,:,:] .= zero(M); - D⁺ᶻ[:,:,end] .= zero(M); - D⁻ʸ[:,1,:] .= zero(M); - D⁻ˣ[1,:,:] .= zero(M); - D⁻ᶻ[:,:,1] .= zero(M); - # Operators - ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2 + max(D⁻ᶻ,0)^2 + min(D⁺ᶻ,0)^2); - ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2 + max(D⁺ᶻ,0)^2 + min(D⁻ᶻ,0)^2); - # Update - φ .= @. φ - Δt*(max(V,0)*∇⁺ + min(V,0)*∇⁻); - return nothing -end - -""" - Single step for first order upwind method for reinitialisation equation (3D) -""" -function reinit!(φ::T,φ_tmp::T,S::T,Δ::NTuple{3,M},Δt::M) where {M,T<:Array{M,3}} - D⁺ʸ,D⁺ˣ,D⁻ʸ,D⁻ˣ,∇⁺,∇⁻=caches - Δx,Δy,Δz = Δ - # Prepare shifted lsf - circshift!(D⁺ʸ,φ,(0,-1,0)); circshift!(D⁻ʸ,φ,(0,1,0)); - circshift!(D⁺ˣ,φ,(-1,0,0)); circshift!(D⁻ˣ,φ,(1,0,0)); - circshift!(D⁺ᶻ,φ,(0,0,-1)); circshift!(D⁻ᶻ,φ,(0,0,1)); - # Forward (+) & Backward (-) - D⁺ʸ .= (D⁺ʸ - φ)/Δy; - D⁺ˣ .= (D⁺ˣ - φ)/Δx; - D⁺ᶻ .= (D⁺ᶻ - φ)/Δz; - D⁻ʸ .= (φ - D⁻ʸ)/Δy; - D⁻ˣ .= (φ - D⁻ˣ)/Δx; - D⁻ᶻ .= (φ - D⁻ᶻ)/Δz; - # Check for boundaries with ghost nodes - D⁺ʸ[:,end,:] .= zero(M); - D⁺ˣ[end,:,:] .= zero(M); - D⁺ᶻ[:,:,end] .= zero(M); - D⁻ʸ[:,1,:] .= zero(M); - D⁻ˣ[1,:,:] .= zero(M); - D⁻ᶻ[:,:,1] .= zero(M); - # Operators - ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2 + max(D⁻ᶻ,0)^2 + min(D⁺ᶻ,0)^2); - ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2 + max(D⁺ᶻ,0)^2 + min(D⁻ᶻ,0)^2); - # Update - φ_tmp .= @. φ - Δt*(max(S,0)*∇⁺ + min(S,0)*∇⁻ - S); - return nothing -end - -function advect!(φ::T,V::T,model::D,Δ::NTuple{N,M},γ::M,max_steps::Int) where {N,M, - T<:PVector{Vector{M}},D<:DistributedDiscreteModel} - ## CFL Condition (requires γ≤1.0) - Δt = γ*min(Δ...)/(eps(M)^2+infnorm(V)) - # Find part size and location of boundaries with ghost nodes - part_size,g_loc = map(ghost_values(φ),local_views(model)) do φ_ghost,model - part_size = size(model.grid.node_coords) - g_loc = find_part_ghost_boundaries(φ_ghost,part_size) - part_size,g_loc - end |> tuple_of_arrays - for _ ∈ Base.OneTo(max_steps) - # Apply operations across partitions - map(local_views(φ),local_views(V),part_size,g_loc) do φ,V,part_size,g_loc - # Step of 1st order upwind H-J evolution equation - advect_step!(reshape(φ,part_size),reshape(V,part_size),g_loc,Δ,Δt) - end - # Update ghost nodes - consistent!(φ) |> fetch - end -end - -function reinit!(φ::T,model::D,Δ::NTuple{N,M},γ::M,max_steps::Int,tol::M,caches) where {N,M, - T<:PVector{Vector{M}},D<:DistributedDiscreteModel} - # Initalise φ_tmp - φ_tmp = zero(φ) # <- cache me - # Compute approx sign function S - ∏Δ = prod(Δ); - S = zero(φ) # <- cache me - map(local_views(S),local_views(φ)) do S,φ - S .= @. φ/sqrt(φ^2 + ∏Δ) - end - ## CFL Condition (requires γ≤0.5) - Δt = γ*min(Δ...) - part_size = map(local_views(model)) do model # <- in setup - get_cartesian_descriptor(model).partition .+ 1 - end - # Apply operations across partitions - for _ ∈ Base.OneTo(max_steps) - # Step of 1st order upwind reinitialisation equation - map(local_views(φ),local_views(φ_tmp),local_views(S),part_size) do φ,φ_tmp,S,part_size - reinit_step!(reshape(φ,part_size),reshape(φ_tmp,part_size),reshape(S,part_size),Δ,Δt,caches) - end - # Update ghost nodes - consistent!(φ_tmp) |> fetch - # Check convergence |φ-φ_tmp|<ε - if infnorm(φ-φ_tmp) fetch - end -end \ No newline at end of file diff --git a/Deprecated/Deprecated_root_files/MainMPI.jl b/Deprecated/Deprecated_root_files/MainMPI.jl deleted file mode 100755 index 650b3b68..00000000 --- a/Deprecated/Deprecated_root_files/MainMPI.jl +++ /dev/null @@ -1,59 +0,0 @@ -using SparseMatricesCSR -using SparseArrays -using Gridap, Gridap.TensorValues, Gridap.Geometry -using GridapDistributed -using GridapPETSc -using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code -using PartitionedArrays -using DelimitedFiles -using LinearAlgebra -using Printf - -import GridapDistributed.DistributedCellField -import GridapDistributed.DistributedFESpace -import GridapDistributed.DistributedDiscreteModel -import GridapDistributed.DistributedMeasure - -include("Utilities.jl"); -include("LevelSet.jl"); -include("Setup.jl"); -include("ProjectionMethod.jl"); -# Currently, to switch between augmented Lagrangian method and -# Hilbertian projection method for constrained optimisation -# replace "OptimiseALM.jl" with "OptimiseHPM.jl". This will -# change later. -include("OptimiseALM.jl"); - -const mesh_partition = length(ARGS) == 3 ? parse.(Int,(ARGS[2],ARGS[3])) : - length(ARGS) == 4 ? parse.(Int,(ARGS[2],ARGS[3],ARGS[4])) : - error("mesh_partition should be of length 2 or 3"); - -function main(mesh_partition,distribute) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - # Set PETSc options - options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - # Get setup function and check exists - setup = getfield(Main, Symbol(ARGS[1])) - @assert @isdefined(setup) && isa(setup,Function) "Setup not defined" - # Create results path - ptn_str = replace(string(mesh_partition),"("=>"",")"=>"",", "=>"x") - path = "$(pwd())/Results_p$(ptn_str)_$setup" - if i_am_main(ranks) - !isdir(path) ? mkdir(path) : rm(path,recursive=true); - !isdir(path) ? mkdir(path) : 0; - end - # Run and time - t = PTimer(ranks) - tic!(t) - GridapPETSc.with(args=split(options)) do - optimise(ranks,mesh_partition,setup,path) - end - toc!(t,"Run time") - t -end - -t = with_mpi() do distribute - main(mesh_partition,distribute) -end -display(t) diff --git a/Deprecated/Deprecated_root_files/OptimiseALM.jl b/Deprecated/Deprecated_root_files/OptimiseALM.jl deleted file mode 100755 index a1830a0d..00000000 --- a/Deprecated/Deprecated_root_files/OptimiseALM.jl +++ /dev/null @@ -1,68 +0,0 @@ -function optimise(ranks,mesh_partition,setup::Function,path::String) - ### Get parameters - prob,obj,lsf,vf,mat,g,fe_order,coord_max,el,η_coeff, - α_coeff,_,_,_,γ,steps,reinit_tol = setup() - vol_D = prod(coord_max); - Δ = coord_max./el # Element size - η = η_coeff*maximum(Δ); α = α_coeff*maximum(Δ) # Smoothing parameters - interp = SmoothErsatzMaterialInterpolation(η=η) # Material interpolation - λ = -0.01; Λ = 100; ζ = 0.9; # Augmented Lagrangian parameters - ### Setup FE data - model,Ω,V_φ,solve_data,hilb_data = prob(ranks,mesh_partition,fe_order,coord_max,el,α) - ### Setup level set - φh = interpolate(lsf,V_φ) - φ = get_free_dof_values(φh) - reinit!(φ,model,Δ,0.5,2000,reinit_tol) - ### Main loop - history = NaN*zeros(1000,3); - for it in 1:1000 - ## Calculate objective and constraints - J_new,v_J,uh = obj(φh,g,mat,solve_data,interp) - C_new,v_C = vol(φh,interp,solve_data.dΩ,solve_data.V_L2,vol_D) - L_new = J_new - λ*(C_new - vf) + 1/(2Λ)*(C_new - vf)^2 - ## Log - history[it,:] = [J_new,C_new,L_new] - if i_am_main(ranks) - println("it: ",it," | J: ",round(J_new;digits=5)," | ","Vol: ",round(C_new;digits=5)) - println("λ = ",λ," Λ = ",Λ) - writedlm("$path/history.csv",history[1:it,:]) - end - isone(it) || iszero(it % 30) ? write_vtk(Ω,"$path/struc_$it",φh,uh,interp.H) : 0 - # write_vtk(Ω,"$path/struc_$it",φh,uh,interp.H) - ## Check stopping criteria - if it > 10 && all(@.(abs(L_new-history[it-5:it-1,3])) .< 1/5/maximum(el)*L_new) && - abs(C_new-vf) < 0.0001 - write_vtk(Ω,"$path/struc_$it",φh,uh,interp.H) - break - end - ## Extend shape sensitivities - ext_v_J = hilbertian_ext(v_J,φh,hilb_data,interp) |> get_free_dof_values - ext_v_C = hilbertian_ext(v_C,φh,hilb_data,interp) |> get_free_dof_values - # Augmented Lagrangian method - λ -= 1/Λ*(C_new - vf); - iszero(it % 5) ? Λ *= ζ : 0; - v_Lh = FEFunction(hilb_data.U_reg,ext_v_J - λ*ext_v_C + 1/Λ*(C_new - vf)*ext_v_C) - v_Lh_full = interpolate(v_Lh,V_φ) - g_Ω = get_free_dof_values(v_Lh_full); - ## Advect & Reinitialise - advect!(φ,g_Ω,model,Δ,γ,steps) - reinit!(φ,model,Δ,0.5,2000,reinit_tol) - end -end - -# Hilbertian extension-regulariation -function hilbertian_ext(vh::DistributedCellField,φh::DistributedCellField,hilb_data::NT, - interp::T) where {T<:SmoothErsatzMaterialInterpolation,NT<:NamedTuple} - ## Unpack - dΩ=hilb_data.dΩ; K=hilb_data.K; DH = interp.DH - ## Linear Form - J′(v) = ∫(-vh*v*(DH ∘ φh)*(norm ∘ ∇(φh)))dΩ; - ## Assembly - b = assemble_vector(J′,hilb_data.assem,hilb_data.V_reg) - op = AffineFEOperator(hilb_data.U_reg,hilb_data.V_reg,K,b) - ## Solve - ls = PETScLinearSolver() - xh = solve(ls,op) - x = correct_ghost_layout(xh,K.col_partition) - return FEFunction(hilb_data.U_reg,x) -end \ No newline at end of file diff --git a/Deprecated/Deprecated_root_files/OptimiseHPM.jl b/Deprecated/Deprecated_root_files/OptimiseHPM.jl deleted file mode 100755 index 70f177d6..00000000 --- a/Deprecated/Deprecated_root_files/OptimiseHPM.jl +++ /dev/null @@ -1,89 +0,0 @@ -function optimise(ranks,mesh_partition,setup::Function,path::String) - ### Get parameters - prob,obj,lsf,vf,mat,g,fe_order,coord_max,el,η_coeff, - α_coeff,μ,γ_max,γ_min,γ,steps,reinit_tol = setup() - vol_D = prod(coord_max); - Δ = coord_max./el # Element size - η,α = [η_coeff*maximum(Δ),α_coeff*maximum(Δ)] # Smoothing parameters - interp = SmoothErsatzMaterialInterpolation(η=η) # Material interpolation - HPM = HilbertianProjectionMethod{Float64}() # Projection method - ### Setup FE data - model,Ω,V_φ,solve_data,hilb_data = prob(ranks,mesh_partition,fe_order,coord_max,el,α) - ### Setup level set - φh = interpolate(lsf,V_φ) - φ = get_free_dof_values(φh) - reinit!(φ,model,Δ,0.1,2000,reinit_tol) - φ0 = zero(φ); φ0 .= φ; - ### Main loop - J_new,_,uh = obj(φh,g,mat,solve_data,interp) - C_new,_ = vol(φh,interp,solve_data.dΩ,solve_data.V_L2,vol_D) - history = NaN*zeros(1000,2); - history[1,:] = [J_new,C_new] - i_am_main(ranks) ? println("it: ",0," | J: ", - round(J_new;digits=5)," | ","Vol: ",round(C_new;digits=5)) : 0 - write_vtk(Ω,"$path/struc_0",φh,uh,interp.H) - for it in 1:1000 - ## Create temp level set structure and other objects - φ0 .= φ; - consistent!(φ0) |> fetch - J,C = [copy(J_new),copy(C_new)]; - ## Calculate shape sensitivities and apply constraint method - _,v_J,uh = obj(φh,g,mat,solve_data,interp) - _,v_C = vol(φh,interp,solve_data.dΩ,solve_data.V_L2,vol_D) - ext_v_J = hilbertian_ext(v_J,φh,hilb_data,interp) - ext_v_C = hilbertian_ext(v_C,φh,hilb_data,interp) - θn_h = project(get_free_dof_values(ext_v_J),[C-vf],[get_free_dof_values(ext_v_C)], - hilb_data.K,hilb_data.U_reg,HPM) - θn_h_full = interpolate(θn_h,V_φ) - g_Ω = get_free_dof_values(θn_h_full); - ## Line search - for k ∈ 1:10 - ## Advect & Reinitialise - advect!(φ,g_Ω,model,Δ,γ,steps) - reinit!(φ,model,Δ,0.1,2000,reinit_tol) - ## Calcuate new objective and constraints - J_new,_,uh = obj(φh,g,mat,solve_data,interp) - C_new,_ = vol(φh,interp,solve_data.dΩ,solve_data.V_L2,vol_D) - ## Reduce line search parameter if constraints close to saturation - _μ = abs(C_new-vf) < 0.01 ? μ/10 : μ - if J_new < J + _μ*abs(J) || γ <= γ_min ## Accept - γ = min(1.1*γ,γ_max) - break - else ## Reject - γ = max(0.7*γ,γ_min) - φ .= φ0 - consistent!(φ) |> fetch - end - end - ## Log - history[it,:] = [J_new,C_new] - if i_am_main(ranks) - println("it: ",it," | J: ",round(J_new;digits=5)," | ","Vol: ",round(C_new;digits=5)) - writedlm("$path/history.csv",history[1:it,:]) - end - isone(it) || iszero(it % 30) ? write_vtk(Ω,"$path/struc_$it",φh,uh,interp.H) : 0 - ## Check stopping criteria - if it > 10 && all(@.(abs(J_new-history[it-5:it-1,1])) .< 1/5/maximum(el)*J_new) && - abs(C_new-vf) < 0.0001 - write_vtk(Ω,"$path/struc_$it",φh,uh,interp.H) - break - end - end -end - -# Hilbertian extension-regulariation -function hilbertian_ext(vh::DistributedCellField,φh::DistributedCellField,hilb_data::NT, - interp::T) where {T<:SmoothErsatzMaterialInterpolation,NT<:NamedTuple} - ## Unpack - dΩ=hilb_data.dΩ; K=hilb_data.K; DH = interp.DH - ## Linear Form - J′(v) = ∫(-vh*v*(DH ∘ φh)*(norm ∘ ∇(φh)))dΩ; - ## Assembly - b = assemble_vector(J′,hilb_data.assem,hilb_data.V_reg) - op = AffineFEOperator(hilb_data.U_reg,hilb_data.V_reg,K,b) - ## Solve - ls = PETScLinearSolver() - xh = solve(ls,op) - x = correct_ghost_layout(xh,K.col_partition) - return FEFunction(hilb_data.U_reg,x) -end \ No newline at end of file diff --git a/Deprecated/Deprecated_root_files/ProjectionMethod.jl b/Deprecated/Deprecated_root_files/ProjectionMethod.jl deleted file mode 100755 index 4283d972..00000000 --- a/Deprecated/Deprecated_root_files/ProjectionMethod.jl +++ /dev/null @@ -1,144 +0,0 @@ -Base.@kwdef struct HilbertianProjectionMethod{M<:AbstractFloat} - λ::M = M(0.5) - α_min::M = M(0.1) - α_max::M = M(1.0) -end - -ip(u::T1,K::T2,v::T3) where {T1<:AbstractArray,T2<:AbstractMatrix,T3<:AbstractArray} = dot(u,K*v) - -function project(V::VT,Cᵥ::Vector{M},C::P,B::T,VSpace::VS,m::HilbertianProjectionMethod{M}) where - {M<:AbstractFloat,VT<:PVector{Vector{M}},P<:Vector{<:PVector{Vector{M}}},T<:PSparseMatrix,VS<:DistributedFESpace} - # Get Data - λ = m.λ; α_min = m.α_min; α_max = m.α_max; - # Orthogonalisation - C_orthog,nullity,len_sq=gram_schmidt_orthog(C,B) - C_len = sqrt.(len_sq); - # Check norm and nullity - k = length(C_orthog) - orth_norm = zeros(k,k); - for i = Base.OneTo(k), j = Base.OneTo(k) - orth_norm[i,j] = ip(C_orthog[i],B,C_orthog[j]) - end - orth_norm[diagind(orth_norm)].=0; - # Project V - V,norm_PCperp_V = project_V(V,C_orthog,len_sq,B) - p_norm = ip.([V],[B],C_orthog) - # Calculate αᵢ - α = copy(Cᵥ); - compute_α!(α,C_orthog,C,len_sq,C_len,B) - ∑α² =λ^2*dot(α,α); - # Printing and check ∑α² and update λ if required - # i_am_main(ranks) - # print("\n ↱----------------------------------------------------------↰\n") - # printstyled(" Orthogonalisation method: gram_schmidt_orthog ",color=:yellow); - # @printf("\n --> Orthogonality inf-norm: %e\n",norm(orth_norm,Inf)) - # @printf(" --> Projection inf-norm: %e\n",(norm(p_norm,Inf))) - # println(" --> Basis nullity: ",nullity) - # end - if ∑α² ≈ zero(M) - # i_am_main(ranks) ? println(" --> Constraints satisfied: ∑α² ≈ 0.") : 0; - elseif ∑α² > α_max - λ *= sqrt(α_max/∑α²) - ∑α² = α_max - # i_am_main(ranks) ? @printf(" --> ∑α² > α_max, scaling λ: %e\n",λ) : 0; - elseif ∑α² < α_min - λ *= sqrt(α_min/∑α²) - ∑α² = α_min - # i_am_main(ranks) ? @printf(" --> ∑α² < α_max, scaling λ: %e\n",λ) : 0; - end - # i_am_main(ranks) ? print(" ↳----------------------------------------------------------↲\n") : 0; - α .*= λ - # Calculate direction - idx_non_zero = (Base.OneTo(k))[.~iszero.(C_len)] - θₙ = sqrt(1-∑α²)*V/norm_PCperp_V + sum(α[i] * C_orthog[i] / C_len[i] for i ∈ idx_non_zero) - consistent!(θₙ) |> fetch - return FEFunction(VSpace,θₙ) -end - -# Compute α ignoring λ for now -function compute_α!(α::Vector{M},C_orthog::P,C::P,len_sq::Vector{M},C_len::Vector{M},B::T) where { - M<:AbstractFloat,P<:Vector{<:PVector{Vector{M}}},T<:PSparseMatrix} - k = length(C_orthog); - for i ∈ Base.OneTo(k) - if iszero(len_sq[i]) - α[i] = zero(M) - else - for j = 1:i-1 - if ~iszero(len_sq[j]) - # αᵢ|̄vᵢ| = λCᵢ - ∑ⱼ₌₁ⁱ⁻¹[ αⱼ(̄vⱼ⋅vᵢ)/|̄vⱼ| ] - α[i] -= α[j]*ip(C_orthog[j],B,C[i])/C_len[j] - end - end - α[i] /= C_len[i] # |̄vᵢ| - end - end - return nothing -end - -# Form projection operator for C⟂ of V: P_C⟂_V = V - ∑[(̄vᵢ ⋅ m)/|̄vᵢ|² ̄vᵢ] where ̄vᵢ spans C and ̄vᵢ ⋅ ̄vⱼ = δᵢⱼ -# Return norm of projected V -function project_V(V::VT,C_orthog::P,len_sq::Vector{M},B::T) where {M<:AbstractFloat,VT<:PVector{Vector{M}}, - P<:Vector{<:PVector{Vector{M}}},T<:PSparseMatrix} - k = length(C_orthog); - for i ∈ Base.OneTo(k) - if ~iszero(len_sq[i]) - V -= ip(C_orthog[i],B,V)/len_sq[i]*C_orthog[i] # [(̄vᵢ ⋅ m)/|̄vᵢ|² ̄vᵢ] - end - end - # Check if projected V is zero vector - consistent!(V) |> fetch - if sqrt(ip(V,B,V)) ≈ 0 - return V,one(M) - else - return V,sqrt(ip(V,B,V)) - end -end - -function gram_schmidt_orthog(C::P,B::T) where {M<:AbstractFloat,P<:Vector{<:PVector{Vector{M}}},T<:PSparseMatrix} - k = length(C); - nullity = 0; - len_sq= zeros(M,k); - tmp = zeros(M,k); - C_orthog = zero.(C) - for i ∈ Base.OneTo(k) - C_orthog[i] .= C[i] - consistent!(C_orthog[i]) |> fetch - end - # Loop - len_sq[1] = ip(C_orthog[1],B,C_orthog[1]); # |̄v₁|² - for i = 2:k - len_sq[i] = ip(C_orthog[i],B,C_orthog[i]); # |̄vᵢ|² - for j = 1:i-1 - if iszero(len_sq[j]) - # V: The j_th vector in the sum is linearly dependent with previous vectors so ignore it - continue - end - tmp[j] = ip(C_orthog[j],B,C_orthog[i]); # vᵢ ⋅ ̄vⱼ - end - for j = 1:i-1 - if iszero(len_sq[j]) - # V: The j_th vector in the sum is linearly dependent with previous vectors so ignore it - continue - end - # ̄vᵢ = vᵢ - ∑ⱼ₌₁ⁱ⁻¹ [(vᵢ ⋅ ̄vⱼ)/|̄vⱼ|² ̄vⱼ] - C_orthog[i] = C_orthog[i] - tmp[j]*C_orthog[j]/len_sq[j] - end - - # Check for a linear dependency - if len_sq[i] < 10^-14 - nullity += 1 - len_sq[i] = zero(M) - C_orthog[i] = zero(C_orthog[i]) - elseif ip(C_orthog[i],B,C_orthog[i])/len_sq[i] < 10^-14 - nullity += 1 - len_sq[i] = zero(M) - C_orthog[i] = zero(C_orthog[i]) - else - len_sq[i] = ip(C_orthog[i],B,C_orthog[i]) - end - end - for i ∈ Base.OneTo(k) - consistent!(C_orthog[i]) |> fetch - end - C_orthog,nullity,len_sq -end \ No newline at end of file diff --git a/Deprecated/Deprecated_root_files/Setup.jl b/Deprecated/Deprecated_root_files/Setup.jl deleted file mode 100755 index 7f0d5217..00000000 --- a/Deprecated/Deprecated_root_files/Setup.jl +++ /dev/null @@ -1,444 +0,0 @@ -## User defined setups - -########################## -# Thermal Compliance # -########################## -## Objective and shape sensitivity -function li2019_mumps_setup(ksp) - pc = Ref{GridapPETSc.PETSC.PC}() - mumpsmat = Ref{GridapPETSc.PETSC.Mat}() - @check_error_code GridapPETSc.PETSC.KSPView(ksp[],C_NULL) - @check_error_code GridapPETSc.PETSC.KSPSetType(ksp[],GridapPETSc.PETSC.KSPPREONLY) - @check_error_code GridapPETSc.PETSC.KSPGetPC(ksp[],pc) - @check_error_code GridapPETSc.PETSC.PCSetType(pc[],GridapPETSc.PETSC.PCLU) - @check_error_code GridapPETSc.PETSC.PCFactorSetMatSolverType(pc[],GridapPETSc.PETSC.MATSOLVERMUMPS) - @check_error_code GridapPETSc.PETSC.PCFactorSetUpMatSolverType(pc[]) - @check_error_code GridapPETSc.PETSC.PCFactorGetMatrix(pc[],mumpsmat) - @check_error_code GridapPETSc.PETSC.MatMumpsSetIcntl(mumpsmat[], 4, 1) - @check_error_code GridapPETSc.PETSC.MatMumpsSetIcntl(mumpsmat[], 7, 0) - # @check_error_code GridapPETSc.PETSC.MatMumpsSetIcntl(mumpsmat[], 14, 1000) - @check_error_code GridapPETSc.PETSC.MatMumpsSetIcntl(mumpsmat[], 28, 2) - @check_error_code GridapPETSc.PETSC.MatMumpsSetIcntl(mumpsmat[], 29, 2) - @check_error_code GridapPETSc.PETSC.MatMumpsSetCntl(mumpsmat[], 3, 1.0e-6) -end - -function thermal_compliance(φh::DistributedCellField,g,D::M,solve_data::NT,interp::T) where { - M<:AbstractFloat,T<:SmoothErsatzMaterialInterpolation,NT<:NamedTuple} - I = interp.I; dΩ=solve_data.dΩ; dΓ_N=solve_data.dΓ_N; - ## Weak form - a(u,v) = ∫((I ∘ φh)*D*∇(u)⋅∇(v))dΩ - l(v) = ∫(v*g)dΓ_N - ## Assembly - op = AffineFEOperator(a,l,solve_data.U,solve_data.V,solve_data.assem) - K = op.op.matrix; - ## Solve - ls = PETScLinearSolver(li2019_mumps_setup) - uh = solve(ls,op) - u = correct_ghost_layout(uh,K.col_partition) - ## Compute J and v_J - J = dot(u,(K*u)) - v_J = interpolate(-D*∇(uh)⋅∇(uh),solve_data.V_L2) - return J,v_J,uh -end - -## Problem setups -function pipe_setup_2d() - ## FE setup name and objective - prob = pipe_2d - obj = thermal_compliance - vf = 0.5; # Required volume fraction - ## Material and loading - D = 1.0 # Thermal coefficient - g = 1.0; # Heat flow - ## FE Parameters - fe_order = 1; - coord_max=(1.0,1.0); - el=(800,800); # Elements in axial directions - ## LS Paramters - lsf = gen_lsf(4,0.2); # Initial LSF - η_coeff = 2 # Interpolation radius coefficent - α_coeff = 4 # Hilbertian smoothing coefficent - μ=0.005 # Line search parameter - γ,γ_min,γ_max = [0.05,0.001,0.1] # CFL Coefficent - steps = Int(floor(minimum(el)/10)) # Finite diff. steps - reinit_tol = min(4*prod(inv,el),10^-4) # Reinit tol. - - return prob,obj,lsf,vf,D,g,fe_order,coord_max,el, - η_coeff,α_coeff,μ,γ_max,γ_min,γ,steps,reinit_tol -end - -function pipe_setup_3d() - ## FE setup name - prob = pipe_3d - obj = thermal_compliance - vf = 0.5; # Required volume fraction - ## Material and loading - D = 1.0 # Thermal coefficient - g = 3.0 # Heat flow - ## FE Parameters - fe_order = 1; - coord_max=(1.0,1.0,1.0); - el=(100,100,100); # Elements in axial directions - ## LS Paramters - lsf = gen_lsf(4,0.2); # Initial LSF - η_coeff = 2 # Interpolation radius coefficent - α_coeff = 4 # Hilbertian smoothing coefficent - μ=0.005 # Line search parameter - γ,γ_min,γ_max = [0.1,0.001,0.1] # CFL Coefficent - steps = Int(floor(minimum(el)/3)); # Finite diff. steps - reinit_tol = min(1000*prod(inv,el),10^-3) # Reinit tol. - - return prob,obj,lsf,vf,D,g,fe_order,coord_max,el, - η_coeff,α_coeff,μ,γ_max,γ_min,γ,steps,reinit_tol -end - -function pipe_2d(ranks,mesh_partition,order::T,coord_max::NTuple{2,M}, - el_size::NTuple{2,T},α::M) where {T<:Integer,M<:AbstractFloat} - ## Model - dom = (0,coord_max[1],0,coord_max[2]); - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - ## Define Γ_N and Γ_D - xmax,ymax = coord_max - prop_Γ_N,prop_Γ_D = [0.4,0.2] - f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || - x[2] >= ymax-ymax*prop_Γ_D - eps())) ? true : false; - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/4 - eps() <= x[2] <= - ymax/2+ymax*prop_Γ_N/4 + eps()) ? true : false; - update_labels!(1,model,f_Γ_D,coord_max,"Gamma_D") - update_labels!(2,model,f_Γ_N,coord_max,"Gamma_N") - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - ## Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;conformity=:H1, - dirichlet_tags=["Gamma_D"],dirichlet_masks=[true]) - U = TrialFESpace(V,[0.0]) - ## Assembler - Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv=Vector{PetscScalar} - assem=SparseMatrixAssembler(Tm,Tv,U,V) - # Space for shape sensitivities - V_L2 = TestFESpace(model,reffe;conformity=:L2) - # Space in Hilb. ext.-reg. endowed with H-regularity - V_reg = TestFESpace(model,reffe;conformity=:H1, - dirichlet_tags=["Gamma_N"],dirichlet_masks=[true]) - U_reg = TrialFESpace(V_reg,[0.0]) - # FE space for LSF - V_φ = TestFESpace(model,reffe;conformity=:H1) - ## Build stiffness matrix for Hilbertian ext-reg - A(u,v) = α^2*∫(∇(u) ⊙ ∇(v))dΩ + ∫(u ⋅ v)dΩ; - Hilb_assem=SparseMatrixAssembler(Tm,Tv,U_reg,V_reg) - K = assemble_matrix(A,Hilb_assem,U_reg,V_reg) - ## Collect data - solve_data = (U=U,V=V,assem=assem,V_L2=V_L2,dΩ=dΩ,dΓ_N=dΓ_N) - hilb_data = (U_reg=U_reg,V_reg=V_reg,assem=Hilb_assem,dΩ=dΩ,K=K) - return model,Ω,V_φ,solve_data,hilb_data -end - -function pipe_3d(ranks,mesh_partition,order::T,coord_max::NTuple{3,M}, - el_size::NTuple{3,T},α::M) where {T<:Integer,M<:AbstractFloat} - ## Model - dom = (0,coord_max[1],0,coord_max[2],0,coord_max[3]); - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - ## Define Γ_N and Γ_D - xmax,ymax,zmax = coord_max - prop_Γ_N = 0.4 - prop_Γ_D = 0.2 - f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || - x[2] >= ymax-ymax*prop_Γ_D - eps()) && (x[3] <= zmax*prop_Γ_D + eps() || - x[3] >= zmax-zmax*prop_Γ_D - eps())) ? true : false; - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/4 - eps() <= x[2] <= - ymax/2+ymax*prop_Γ_N/4 + eps() && zmax/2-zmax*prop_Γ_N/4 - eps() <= x[3] - <= zmax/2+zmax*prop_Γ_N/4 + eps()) ? true : false; - update_labels!(1,model,f_Γ_D,coord_max,"Gamma_D") - update_labels!(2,model,f_Γ_N,coord_max,"Gamma_N") - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - ## Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;conformity=:H1, - dirichlet_tags=["Gamma_D"],dirichlet_masks=[true]) - U = TrialFESpace(V,[0.0]) - ## Assembler - Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv=Vector{PetscScalar} - assem=SparseMatrixAssembler(Tm,Tv,U,V) - # Space for shape sensitivities - V_L2 = TestFESpace(model,reffe;conformity=:L2) - # Space in Hilb. ext.-reg. endowed with H-regularity - V_reg = TestFESpace(model,reffe;conformity=:H1, - dirichlet_tags=["Gamma_N"],dirichlet_masks=[true]) - U_reg = TrialFESpace(V_reg,[0.0]) - # FE space for LSF - V_φ = TestFESpace(model,reffe;conformity=:H1) - ## Build stiffness matrix for Hilbertian ext-reg - A(u,v) = α^2*∫(∇(u) ⊙ ∇(v))dΩ + ∫(u ⋅ v)dΩ; - Hilb_assem=SparseMatrixAssembler(Tm,Tv,U_reg,V_reg) - K = assemble_matrix(A,Hilb_assem,U_reg,V_reg) - ## Collect data - solve_data = (U=U,V=V,assem=assem,V_L2=V_L2,dΩ=dΩ,dΓ_N=dΓ_N) - hilb_data = (U_reg=U_reg,V_reg=V_reg,assem=Hilb_assem,dΩ=dΩ,K=K) - return model,Ω,V_φ,solve_data,hilb_data -end - -function pipe2_setup_3d() - ## FE setup name - prob = pipe2_3d - obj = thermal_compliance - vf = 0.3; # Required volume fraction - ## Material and loading - D = 1.0 # Thermal coefficient - g = 5.0 # Heat flow - ## FE Parameters - fe_order = 1; - coord_max=(1.0,1.0,1.0); - el=(100,100,100); # Elements in axial directions - ## LS Paramters - lsf = gen_lsf(2,0.4); # Initial LSF - η_coeff = 2 # Interpolation radius coefficent - α_coeff = 4 # Hilbertian smoothing coefficent - μ=0.005 # Line search parameter - γ,γ_min,γ_max = [0.1,0.001,0.1] # CFL Coefficent - steps = Int(floor(minimum(el)/3)); # Finite diff. steps - reinit_tol = min(1000*prod(inv,el),10^-3) # Reinit tol. - - return prob,obj,lsf,vf,D,g,fe_order,coord_max,el, - η_coeff,α_coeff,μ,γ_max,γ_min,γ,steps,reinit_tol -end - -function pipe2_3d(ranks,mesh_partition,order::T,coord_max::NTuple{3,M}, - el_size::NTuple{3,T},α::M) where {T<:Integer,M<:AbstractFloat} - ## Model - @assert isone(coord_max[1]) && isone(coord_max[2]) && isone(coord_max[3]) - dom = (0,coord_max[1],0,coord_max[2],0,coord_max[3]); - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - ## Define Γ_N and Γ_D - f_Γ_D(x) = (max(abs(x[1]-0.2),abs(x[2]-0.5),abs(x[3]-0.5)) <= 0.05+eps() || - max(abs(x[1]-0.8),abs(x[2]-0.5),abs(x[3]-0.5)) <= 0.05+eps() || - max(abs(x[1]-0.5),abs(x[2]-0.2),abs(x[3]-0.5)) <= 0.05+eps() || - max(abs(x[1]-0.5),abs(x[2]-0.8),abs(x[3]-0.5)) <= 0.05+eps()) ? true : false; - f_Γ_N(x) = (max(abs(x[1]),abs(x[2]),abs(x[3])) <= 0.05+eps() && (iszero(x[1]) || iszero(x[2]) || iszero(x[3])))|| - (max(abs(x[1]-1),abs(x[2]),abs(x[3])) <= 0.05+eps() && (isone(x[1]) || iszero(x[2]) || iszero(x[3])))|| - (max(abs(x[1]),abs(x[2]-1),abs(x[3])) <= 0.05+eps() && (iszero(x[1]) || isone(x[2]) || iszero(x[3])))|| - (max(abs(x[1]-1),abs(x[2]-1),abs(x[3])) <= 0.05+eps() && (isone(x[1]) || isone(x[2]) || iszero(x[3])))|| - (max(abs(x[1]),abs(x[2]),abs(x[3]-1)) <= 0.05+eps() && (iszero(x[1]) || iszero(x[2]) || isone(x[3])))|| - (max(abs(x[1]-1),abs(x[2]),abs(x[3]-1)) <= 0.05+eps() && (isone(x[1]) || iszero(x[2]) || isone(x[3])))|| - (max(abs(x[1]),abs(x[2]-1),abs(x[3]-1)) <= 0.05+eps() && (iszero(x[1]) || isone(x[2]) || isone(x[3])))|| - (max(abs(x[1]-1),abs(x[2]-1),abs(x[3]-1)) <= 0.05+eps() && (isone(x[1]) || isone(x[2]) || isone(x[3]))) ? true : false; - update_labels!(1,model,f_Γ_D,coord_max,"Gamma_D") - update_labels!(2,model,f_Γ_N,coord_max,"Gamma_N") - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - ## Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;conformity=:H1, - dirichlet_tags=["Gamma_N","Gamma_D"],dirichlet_masks=[true,true]) - U = TrialFESpace(V,[0.0,0.0]) - ## Assembler - Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv=Vector{PetscScalar} - assem=SparseMatrixAssembler(Tm,Tv,U,V) - # Space for shape sensitivities - V_L2 = TestFESpace(model,reffe;conformity=:L2) - # Space in Hilb. ext.-reg. endowed with H-regularity - V_reg = TestFESpace(model,reffe;conformity=:H1, - dirichlet_tags=["Gamma_N","Gamma_D"],dirichlet_masks=[true,true]) - U_reg = TrialFESpace(V_reg,[0.0,0.0]) - # FE space for LSF - V_φ = TestFESpace(model,reffe;conformity=:H1) - ## Build stiffness matrix for Hilbertian ext-reg - A(u,v) = α^2*∫(∇(u) ⊙ ∇(v))dΩ + ∫(u ⋅ v)dΩ; - Hilb_assem=SparseMatrixAssembler(Tm,Tv,U_reg,V_reg) - K = assemble_matrix(A,Hilb_assem,U_reg,V_reg) - ## Collect data - solve_data = (U=U,V=V,assem=assem,V_L2=V_L2,dΩ=dΩ,dΓ_N=dΓ_N) - hilb_data = (U_reg=U_reg,V_reg=V_reg,assem=Hilb_assem,dΩ=dΩ,K=K) - return model,Ω,V_φ,solve_data,hilb_data -end - -########################## -# Elastic Compliance # -########################## -## Objective and shape sensitivity -function elastic_compliance(φh::DistributedCellField,g,C::S,solve_data::NT,interp::T) where { - S<:SymFourthOrderTensorValue,T<:SmoothErsatzMaterialInterpolation,NT<:NamedTuple} - I = interp.I; dΩ=solve_data.dΩ; dΓ_N=solve_data.dΓ_N; - ## Weak form - a(u,v) = ∫((I ∘ φh)*(C ⊙ ε(u) ⊙ ε(v)))dΩ - l(v) = ∫(v ⋅ g)dΓ_N - ## Solve finite element problem - op = AffineFEOperator(a,l,solve_data.U,solve_data.V,solve_data.assem) - K = op.op.matrix; - ## Solve - ls = PETScLinearSolver() - uh = solve(ls,op) - u = correct_ghost_layout(uh,K.col_partition) - ## Compute J and v_J - J = dot(u,(K*u)) - v_J = interpolate(-C ⊙ ε(uh) ⊙ ε(uh),solve_data.V_L2) - return J,v_J,uh -end - -function cantilever_setup_2d() - ## FE setup name - prob = cantilever_2d - obj = elastic_compliance - vf = 0.5; # Required volume fraction - ## Material and loading - C = isotropic_2d(1.0,0.3) # Stiffness tensor - g = VectorValue(0,-0.1); # Loading - ## FE Parameters - fe_order = 1; - coord_max=(2.0,1.0); - el=(800,400); # Elements in axial directions - ## LS Paramters - lsf = gen_lsf(4,0.2); # Initial LSF - η_coeff = 2 # Interpolation radius coefficent - α_coeff = 4 # Hilbertian smoothing coefficent - μ=0.005 # Line search parameter - γ,γ_min,γ_max = [0.1,0.001,0.1] # CFL Coefficent - steps = Int(floor(minimum(el)/10)) # Finite diff. steps - reinit_tol = min(4*prod(inv,el),10^-4) # Reinit tol. - - return prob,obj,lsf,vf,C,g,fe_order,coord_max,el, - η_coeff,α_coeff,μ,γ_max,γ_min,γ,steps,reinit_tol -end - -function cantilever_setup_3d() - ## FE setup name - prob = cantilever_3d - obj = elastic_compliance - vf = 0.5; # Required volume fraction - ## Material and loading - C = isotropic_3d(1.0,0.3) # Stiffness tensor - g = VectorValue(0,0,-0.1); # Loading - ## FE Parameters - fe_order = 1; - coord_max=(2.0,1.0,1.0); - el=(100,50,50); # Elements in axial directions - ## LS Paramters - lsf = gen_lsf(4,0.2); # Initial LSF - η_coeff = 2 # Interpolation radius coefficent - α_coeff = 4 # Hilbertian smoothing coefficent - μ=0.005 # Line search parameter - γ,γ_min,γ_max = [0.1,0.001,0.1] # CFL Coefficent - steps = Int(floor(minimum(el)/3)); # Finite diff. steps - reinit_tol = min(1000*prod(inv,el),10^-3) # Reinit tol. - - return prob,obj,lsf,vf,C,g,fe_order,coord_max,el, - η_coeff,α_coeff,μ,γ_max,γ_min,γ,steps,reinit_tol -end - -function cantilever_2d(ranks,mesh_partition,order::T,coord_max::NTuple{2,M}, - el_size::NTuple{2,T},α::M) where {T<:Integer,M<:AbstractFloat} - ## Model - dom = (0,coord_max[1],0,coord_max[2]); - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - ## Define Γ_N and Γ_D - xmax,ymax = coord_max - prop_Γ_N = 0.4 - f_Γ_D(x) = (x[1] ≈ 0.0) ? true : false; - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/4 - eps() <= x[2] <= - ymax/2+ymax*prop_Γ_N/4 + eps()) ? true : false; - update_labels!(1,model,f_Γ_D,coord_max,"Gamma_D") - update_labels!(2,model,f_Γ_N,coord_max,"Gamma_N") - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) - V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["Gamma_D"], - dirichlet_masks=[(true,true)],vector_type=Vector{PetscScalar}) - U = TrialFESpace(V,[VectorValue(0.0,0.0)]) - ## Assembler - Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv=Vector{PetscScalar} - assem=SparseMatrixAssembler(Tm,Tv,U,V) - # Space for shape sensitivities - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V_L2 = TestFESpace(model,reffe_scalar;conformity=:L2) - # Space in Hilb. ext.-reg. endowed with H-regularity - V_reg = TestFESpace(model,reffe_scalar;conformity=:H1, - dirichlet_tags=["Gamma_N"],dirichlet_masks=[true]) - U_reg = TrialFESpace(V_reg,[0.0]) - # FE space for LSF - V_φ = TestFESpace(model,reffe_scalar;conformity=:H1) - ## Build stiffness matrix for Hilbertian ext-reg - A(u,v) = α^2*∫(∇(u) ⊙ ∇(v))dΩ + ∫(u ⋅ v)dΩ; - Hilb_assem=SparseMatrixAssembler(Tm,Tv,U_reg,V_reg) - K = assemble_matrix(A,Hilb_assem,U_reg,V_reg) - ## Collect data - solve_data = (U=U,V=V,assem=assem,V_L2=V_L2,dΩ=dΩ,dΓ_N=dΓ_N) - hilb_data = (U_reg=U_reg,V_reg=V_reg,assem=Hilb_assem,dΩ=dΩ,K=K) - return model,Ω,V_φ,solve_data,hilb_data -end - -function cantilever_3d(ranks,mesh_partition,order::T,coord_max::NTuple{3,M}, - el_size::NTuple{3,T},α::M) where {T<:Integer,M<:AbstractFloat} - ## Model - dom = (0,coord_max[1],0,coord_max[2],0,coord_max[3]); - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - ## Define Γ_N and Γ_D - xmax,ymax,zmax = coord_max - prop_Γ_N = 0.4 - f_Γ_D(x) = (x[1] ≈ 0.0) ? true : false; - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/4 - eps() <= x[2] <= - ymax/2+ymax*prop_Γ_N/4 + eps() && zmax/2-zmax*prop_Γ_N/4 - eps() <= x[3] - <= zmax/2+zmax*prop_Γ_N/4 + eps()) ? true : false; - update_labels!(1,model,f_Γ_D,coord_max,"Gamma_D") - update_labels!(2,model,f_Γ_N,coord_max,"Gamma_N") - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) - V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["Gamma_D"], - dirichlet_masks=[(true,true,true)]) - U = TrialFESpace(V,[VectorValue(0.0,0.0,0.0)]) - ## Assembler - Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv=Vector{PetscScalar} - assem=SparseMatrixAssembler(Tm,Tv,U,V) - # Space for shape sensitivities - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V_L2 = TestFESpace(model,reffe_scalar;conformity=:L2) - # Space in Hilb. ext.-reg. endowed with H-regularity - V_reg = TestFESpace(model,reffe_scalar;conformity=:H1, - dirichlet_tags=["Gamma_N"],dirichlet_masks=[true]) - U_reg = TrialFESpace(V_reg,[0.0]) - # FE space for LSF - V_φ = TestFESpace(model,reffe_scalar;conformity=:H1) - ## Build stiffness matrix for Hilbertian ext-reg - A(u,v) = α^2*∫(∇(u) ⊙ ∇(v))dΩ + ∫(u ⋅ v)dΩ; - Hilb_assem=SparseMatrixAssembler(Tm,Tv,U_reg,V_reg) - K = assemble_matrix(A,Hilb_assem,U_reg,V_reg) - ## Collect data - solve_data = (U=U,V=V,assem=assem,V_L2=V_L2,dΩ=dΩ,dΓ_N=dΓ_N) - hilb_data = (U_reg=U_reg,V_reg=V_reg,assem=Hilb_assem,dΩ=dΩ,K=K) - return model,Ω,V_φ,solve_data,hilb_data -end - -########################## -# Volume # -########################## -function vol(φh::DistributedCellField,interp::T,dΩ::ME,V_L2::V,vol_D::M) where { - M<:AbstractFloat,T<:SmoothErsatzMaterialInterpolation, - V<:DistributedFESpace,ME<:DistributedMeasure} - ρ = interp.ρ; - vol = sum(∫(ρ ∘ φh)dΩ)/vol_D; - v_vol = interpolate(x->one(M)/vol_D,V_L2) - return vol,v_vol -end \ No newline at end of file diff --git a/Deprecated/Deprecated_root_files/Utilities.jl b/Deprecated/Deprecated_root_files/Utilities.jl deleted file mode 100755 index af5f0792..00000000 --- a/Deprecated/Deprecated_root_files/Utilities.jl +++ /dev/null @@ -1,136 +0,0 @@ -# Heaviside function -function H_η(t::M;η::M) where M<:AbstractFloat - if t<-η - return zero(M) - elseif abs(t)<=η - return M(1/2*(1+t/η+1/pi*sin(pi*t/η))) - elseif t>η - return one(M) - end -end - -function DH_η(t::M;η::M) where M<:AbstractFloat - if t<-η - return zero(M) - elseif abs(t)<=η - return M(1/2/η*(1+cos(pi*t/η))) - elseif t>η - return zero(M) - end -end - -# Material interpolation -Base.@kwdef struct SmoothErsatzMaterialInterpolation{M<:AbstractFloat} - η::M # Smoothing radius - ϵₘ::M = 10^-3 # Void material multiplier - H = x -> H_η(x,η=η) - DH = x -> DH_η(x,η=η) - I = φ -> (1 - H(φ)) + ϵₘ*H(φ) - ρ = φ -> 1 - H(φ) -end - -write_vtk(Ω,path,φh,uh,H) = writevtk(Ω,path,cellfields=["phi"=>φh, - "H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) - -# Update layout of ghost nodes to match columns of stiffness matrix -function correct_ghost_layout(xh::DistributedCellField,cols) - x_tmp = get_free_dof_values(xh) - x = pfill(0.0, cols) - map(local_views(own_values(x)),local_views(own_values(x_tmp))) do x,x_tmp - x .= x_tmp - end - consistent!(x) |> fetch - return x -end - -# Inf norm -function infnorm(a::PVector) - contibs = map(own_values(a)) do oid_to_value - norm(oid_to_value,Inf) - end - reduce(max,contibs;init=zero(eltype(contibs))) -end - -# Update label given function f_Γ. e should be the count of added tags. -function update_labels!(e::Int,model::D,f_Γ::F,::T,name::String) where { - M<:AbstractFloat,F<:Function,T<:NTuple{2,M},D<:DistributedDiscreteModel} - cell_to_entity = map(local_views(model)) do model - labels = get_face_labeling(model) - cell_to_entity = labels.d_to_dface_to_entity[end] - entity = maximum(cell_to_entity) + e - # Vertices - vtx_coords = model.grid_topology.vertex_coordinates - vtxs_Γ = findall(isone,f_Γ.(vtx_coords)) - vtx_edge_connectivity = Array(Geometry.get_faces(model.grid_topology,0,1)[vtxs_Γ]) - # Edges - edge_entries = [findall(x->any(x .∈ vtx_edge_connectivity[1:end.!=j]), - vtx_edge_connectivity[j]) for j = 1:length(vtx_edge_connectivity)] - edge_Γ = unique(reduce(vcat,getindex.(vtx_edge_connectivity,edge_entries),init=[])) - labels.d_to_dface_to_entity[1][vtxs_Γ] .= entity - labels.d_to_dface_to_entity[2][edge_Γ] .= entity - add_tag!(labels,name,[entity]) - cell_to_entity - end - cell_gids=get_cell_gids(model) - cache=GridapDistributed.fetch_vector_ghost_values_cache(cell_to_entity,partition(cell_gids)) - GridapDistributed.fetch_vector_ghost_values!(cell_to_entity,cache) -end - -function update_labels!(e::Int,model::D,f_Γ::F,::T,name::String) where { - M<:AbstractFloat,F<:Function,T<:NTuple{3,M},D<:DistributedDiscreteModel} - cell_to_entity = map(local_views(model)) do model - labels = get_face_labeling(model) - cell_to_entity = labels.d_to_dface_to_entity[end] - entity = maximum(cell_to_entity) + e - # Vertices - vtx_coords = model.grid_topology.vertex_coordinates - vtxs_Γ = findall(isone,f_Γ.(vtx_coords)) - vtx_edge_connectivity = Array(Geometry.get_faces(model.grid_topology,0,1)[vtxs_Γ]) - vtx_face_connectivity = Array(Geometry.get_faces(model.grid_topology,0,2)[vtxs_Γ]) - # Edges - edge_entries = [findall(x->any(x .∈ vtx_edge_connectivity[1:end.!=j]), - vtx_edge_connectivity[j]) for j = 1:length(vtx_edge_connectivity)] - edge_Γ = unique(reduce(vcat,getindex.(vtx_edge_connectivity,edge_entries),init=[])) - # Faces - face_entries = [findall(x->count(x .∈ vtx_face_connectivity[1:end.!=j])>2, - vtx_face_connectivity[j]) for j = 1:length(vtx_face_connectivity)] - face_Γ = unique(reduce(vcat,getindex.(vtx_face_connectivity,face_entries),init=[])) - labels.d_to_dface_to_entity[1][vtxs_Γ] .= entity - labels.d_to_dface_to_entity[2][edge_Γ] .= entity - labels.d_to_dface_to_entity[3][face_Γ] .= entity - add_tag!(labels,name,[entity]) - cell_to_entity - end - cell_gids=get_cell_gids(model) - cache=GridapDistributed.fetch_vector_ghost_values_cache(cell_to_entity,partition(cell_gids)) - GridapDistributed.fetch_vector_ghost_values!(cell_to_entity,cache) -end - -# Isotropic elasticity tensors -function isotropic_2d(E::M,ν::M) where M<:AbstractFloat - λ = E*ν/((1+ν)*(1-ν)); μ = E/(2*(1+ν)) - C = [λ+2μ λ 0 - λ λ+2μ 0 - 0 0 μ]; - SymFourthOrderTensorValue( - C[1,1], C[3,1], C[2,1], - C[1,3], C[3,3], C[2,3], - C[1,2], C[3,2], C[2,2]) -end - -function isotropic_3d(E::M,ν::M) where M<:AbstractFloat - λ = E*ν/((1+ν)*(1-2ν)); μ = E/(2*(1+ν)) - C =[λ+2μ λ λ 0 0 0 - λ λ+2μ λ 0 0 0 - λ λ λ+2μ 0 0 0 - 0 0 0 μ 0 0 - 0 0 0 0 μ 0 - 0 0 0 0 0 μ]; - return SymFourthOrderTensorValue( - C[1,1], C[6,1], C[5,1], C[2,1], C[4,1], C[3,1], - C[1,6], C[6,6], C[5,6], C[2,6], C[4,6], C[3,6], - C[1,5], C[6,5], C[5,5], C[2,5], C[4,5], C[3,5], - C[1,2], C[6,2], C[5,2], C[2,2], C[4,2], C[3,2], - C[1,4], C[6,4], C[5,4], C[2,4], C[4,4], C[3,4], - C[1,3], C[6,3], C[5,3], C[2,3], C[4,3], C[3,3]) -end \ No newline at end of file diff --git a/Deprecated/Deprecated_root_files/auto_diff_elastic_compliance_parallel.jl b/Deprecated/Deprecated_root_files/auto_diff_elastic_compliance_parallel.jl deleted file mode 100644 index 5816ae01..00000000 --- a/Deprecated/Deprecated_root_files/auto_diff_elastic_compliance_parallel.jl +++ /dev/null @@ -1,216 +0,0 @@ -using Gridap, Gridap.TensorValues, Gridap.Geometry, Gridap.FESpaces, Gridap.Helpers -using GridapDistributed -using GridapPETSc -using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code -using PartitionedArrays -using SparseMatricesCSR -using ChainRulesCore - -include("src/ChainRules.jl") -include("src/Utilities.jl") -include("src/MaterialInterpolation.jl") - -###################################################### -## FE Setup -function main(mesh_partition,distribute) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - order = 1; - el_size = (200,200); - dom = (0.,1.,0.,1.); - coord_max = dom[2],dom[4] - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - ## Define Γ_N and Γ_D - xmax,ymax = coord_max - prop_Γ_N = 0.4 - f_Γ_D(x) = (x[1] ≈ 0.0) ? true : false; - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/4 - eps() <= x[2] <= - ymax/2+ymax*prop_Γ_N/4 + eps()) ? true : false; - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) - V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["Gamma_D"], - dirichlet_masks=[(true,true)],vector_type=Vector{PetscScalar}) - U = TrialFESpace(V,[VectorValue(0.0,0.0)]) - # Space for shape sensitivities - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - # FE space for LSF - V_φ = TestFESpace(model,reffe_scalar;conformity=:H1) - # FE Space for shape derivatives - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0.0) - ###################################################### - eΔ = (xmax,ymax)./el_size; - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(eΔ)) - C = isotropic_2d(1.,0.3) - g = VectorValue(0.,-1.0) - φh = interpolate(x->-sqrt((x[1]-0.5)^2+(x[2]-0.5)^2)+0.25,V_φ) - - ## Weak form - I = interp.I; - DH = interp.DH - - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ - l(v,φh,dΩ,dΓ_N) = ∫(v ⋅ g)dΓ_N - res(u,v,φ,dΩ,dΓ_N) = a(u,v,φ,dΩ,dΓ_N) - l(v,φ,dΩ,dΓ_N) - - ## Functionals J and DJ - J = (u,φ,dΩ,dΓ_N) -> a(u,u,φ,dΩ,dΓ_N) - DJ = (q,u,φ,dΩ,dΓ_N) -> ∫((C ⊙ ε(u) ⊙ ε(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; - state_map = AffineFEStateMap(a,l,res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) - pcfs = PDEConstrainedFunctionals(J,Function[J],state_map,analytic_dC=[DJ]) - - φ = get_free_dof_values(φh) - j,c,dJ,dC = Gridap.evaluate!(pcfs,φ) - uh = get_state(pcfs) - - println("J = $j | C = $c") - - ## Shape derivative - # Autodiff - dF = dJ - # Analytic - dF_analytic = first(dC) - - abs_error = maximum(abs,dF-dF_analytic) - rel_error = (abs_error)/maximum(abs,dF_analytic) - - ## Hilb ext reg - α = 4*maximum(eΔ) - A(u,v) = α^2*∫(∇(u) ⊙ ∇(v))dΩ + ∫(u ⋅ v)dΩ; - Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv=Vector{PetscScalar} - Hilb_assem=SparseMatrixAssembler(Tm,Tv,U_reg,V_reg) - hilb_K = assemble_matrix(A,Hilb_assem,U_reg,V_reg) - ## Autodiff result - op = AffineFEOperator(U_reg,V_reg,hilb_K,-dF) - dF_Ω = get_free_dof_values(solve(op)) - ## Analytic result - op = AffineFEOperator(U_reg,V_reg,hilb_K,-dF_analytic) - dF_analytic_Ω = get_free_dof_values(solve(op)) - - hilb_abs_error = maximum(abs,dF_Ω-dF_analytic_Ω) - hilb_rel_error = (hilb_abs_error)/maximum(abs,dF_analytic_Ω) - # path = dirname(dirname(@__DIR__))*"/results/AutoDiffTesting_Parallel"; - # writevtk(Ω,path,cellfields=["phi"=>φh, - # "H(phi)"=>(interp.H ∘ φh), - # "|nabla(phi)|"=>(norm ∘ ∇(φh)), - # "uh"=>uh, - # "J′_analytic"=>FEFunction(U_reg,dF_analytic), - # "J′_autodiff"=>FEFunction(U_reg,dF), - # "v_J_Ω"=>FEFunction(U_reg,dF_analytic_Ω), - # "dJφh_Ω"=>FEFunction(U_reg,dF_Ω) - # ]) - abs_error,rel_error,hilb_abs_error,hilb_rel_error -end - -out = with_debug() do distribute - main((3,3),distribute) -end - -#################### -# Debug Testing # -#################### -using BenchmarkTools -include("ChainRules.jl"); -function test(;run_as_serial::Bool=true) - ranks = with_debug() do distribute - distribute(LinearIndices((1,))) - end - - model = if run_as_serial - CartesianDiscreteModel((0,1,0,1),(2,2)) - else - CartesianDiscreteModel(ranks,(1,1),(0,1,0,1),(2,2)) - end - - Ω = Triangulation(model) - dΩ = Measure(Ω,2) - V_φ = FESpace(model,ReferenceFE(lagrangian,Float64,1)) - V_reg = FESpace(model,ReferenceFE(lagrangian,Float64,1),dirichlet_tags=["tag_1"]) - U_reg = TrialFESpace(V_reg,1) - φh = interpolate(x->1,V_φ); - φ = get_free_dof_values(φh) - - # FE Problem - V = FESpace(model,ReferenceFE(lagrangian,Float64,1),dirichlet_tags=["boundary"]) - U = TrialFESpace(V,2) - a(u,v,φ,dΩ) = ∫( φ*∇(v)⋅∇(u) )*dΩ - l(v,φ,dΩ) = ∫(v)*dΩ - res(u,v,φ,dΩ) = a(u,v,φ,dΩ) - l(v,φ,dΩ) - - J = (u,φ,dΩ) -> ∫(1+(u⋅u)*(u⋅u)+sqrt ∘ φ)dΩ - state_map = AffineFEStateMap(a,l,res,U,V,V_φ,U_reg,φh,dΩ) - pcfs = PDEConstrainedFunctionals(J,state_map) - - - j,c,dJ,dC = Gridap.evaluate!(pcfs,φ) - - println("J = $j | C = $c") - - ### Connor's implementation: - if run_as_serial - function _a(u,v,φ) - __φh = φ_to_φₕ(φ,V_φ) - a(u,v,__φh,dΩ) - end - function _l(v,φ) - __φh = φ_to_φₕ(φ,V_φ) - l(v,__φh,dΩ) - end - _a(φ) = (u,v) -> _a(u,v,φ) - _l(φ) = v -> _l(v,φ) - _res(u,v,φ) = _a(u,v,φ) - _l(v,φ) - - _φ_to_u = _AffineFEStateMap(_a,_l,_res,V_φ,U,V) - _u_to_j = LossFunction((u,φ) -> J(u,φ,dΩ),V_φ,U) - - _u, _u_pullback = rrule(_φ_to_u,φ) - _j, _j_pullback = rrule(_u_to_j,_u,φ) - _, _du, _dφ₍ⱼ₎ = _j_pullback(1) # dj = 1 - _, _dφ₍ᵤ₎ = _u_pullback(_du) - dφ_connor = _dφ₍ᵤ₎ + _dφ₍ⱼ₎ - if ~(V_φ === U_reg) - dφ_connor = get_free_dof_values(interpolate(FEFunction(V_φ,dφ_connor),U_reg)) - end - - return dJ,dJ-dφ_connor - else - return dJ,nothing - end -end - -_out_serial,_diff = test(run_as_serial=true); - -_out,_ = test(run_as_serial=false); - -@show norm(_out_serial-_out.vector_partition.items[1],Inf) - -""" -assemble_matrix_and_vector!: - - Line 310 Assemblers.jl: assemble_matrix_and_vector!(f::Function,b::Function,M::AbstractMatrix,r::AbstractVector,a::Assembler,U::FESpace,V::FESpace) - - -> Calls Line 453 Assemblers.jl: data = collect_cell_matrix_and_vector(trial::FESpace,test::FESpace,biform::DomainContribution,liform::DomainContribution) - - -> Line 85 SparseMatrixAssembler.jl: assemble_matrix_and_vector!(A,b,a::SparseMatrixAssembler, data) -> assemble_matrix_and_vector_add!... - -AffineFEOperator: - - Line 23 AffineFEOperator.jl: AffineFEOperator(weakform::Function,trial::FESpace,test::FESpace,assem::Assembler) - - -> Line 464 Assemblers.jl: data = collect_cell_matrix_and_vector(trial::FESpace,test::FESpace,biform::DomainContribution,liform::DomainContribution,uhd::FEFunction) - - -> Line 244 Assemblers.jl: assemble_matrix_and_vector(a::Assembler,data) - - ->-> Line 73 SparseMatrixAssembler.jl: A,b = allocate_matrix_and_vector(a,data) - - ->-> Line 85 SparseMatrixAssembler.jl: assemble_matrix_and_vector!(A,b,a::SparseMatrixAssembler, data) -> assemble_matrix_and_vector_add!... - -Why does assemble_matrix_and_vector! at the top not take uhd??? -""" \ No newline at end of file diff --git a/Deprecated/Deprecated_root_files/inverse_homogenisation_parallel.jl b/Deprecated/Deprecated_root_files/inverse_homogenisation_parallel.jl deleted file mode 100644 index 7ffb6e68..00000000 --- a/Deprecated/Deprecated_root_files/inverse_homogenisation_parallel.jl +++ /dev/null @@ -1,234 +0,0 @@ -using Gridap, Gridap.TensorValues, Gridap.Geometry, Gridap.FESpaces, Gridap.Helpers -using GridapDistributed -using GridapPETSc -using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code -using PartitionedArrays -using SparseMatricesCSR -using ChainRulesCore - -include("src/ChainRules.jl") -include("src/Utilities.jl") -include("src/MaterialInterpolation.jl") - -###################################################### -## FE Setup -function main(mesh_partition,distribute) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - order = 1; - el_size = (100,100); - dom = (0.,1.,0.,1.); - coord_max = dom[2],dom[4] - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true)); - ## Define Γ_N and Γ_D - xmax,ymax = coord_max - f_Γ_D(x) = iszero(x) - update_labels!(1,model,f_Γ_D,"origin") - ## Triangulations and measures - Ω = Triangulation(model) - dΩ = Measure(Ω,2order) - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) - _V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["origin"]) - _U = TrialFESpace(_V,[VectorValue(0.0,0.0)]) - V = MultiFieldFESpace([_V,_V,_V]) - U = MultiFieldFESpace([_U,_U,_U]) - # Space for shape sensitivities - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - # FE space for LSF - V_φ = TestFESpace(model,reffe_scalar;conformity=:H1) - # FE Space for shape derivatives - V_reg = TestFESpace(model,reffe_scalar;conformity=:H1) - U_reg = TrialFESpace(V_reg) - ###################################################### - eΔ = (xmax,ymax)./el_size; - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(eΔ)) - C = isotropic_2d(1.,0.3) - φh = interpolate(x->-sqrt((x[1]-0.5)^2+(x[2]-0.5)^2)+0.25,V_φ) - - ## Weak form - I = interp.I; - DH = interp.DH - - εᴹ = (TensorValue(1.,0.,0.,0.), # ϵᵢⱼ⁽¹¹⁾≡ϵᵢⱼ⁽¹⁾ - TensorValue(0.,0.,0.,1.), # ϵᵢⱼ⁽²²⁾≡ϵᵢⱼ⁽²⁾ - TensorValue(0.,1/2,1/2,0.)) # ϵᵢⱼ⁽¹²⁾≡ϵᵢⱼ⁽³⁾ - - a((u1,u2,u3),(v1,v2,v3),φ,dΩ) = ∫((I ∘ φ)*(C ⊙ ε(u1) ⊙ ε(v1)) + - (I ∘ φ)*(C ⊙ ε(u2) ⊙ ε(v2)) + - (I ∘ φ)*(C ⊙ ε(u3) ⊙ ε(v3)))dΩ - l((v1,v2,v3),φ,dΩ) = ∫(-(I ∘ φ)*(C ⊙ εᴹ[1] ⊙ ε(v1)) - - (I ∘ φ)*(C ⊙ εᴹ[2] ⊙ ε(v2)) - - (I ∘ φ)*(C ⊙ εᴹ[3] ⊙ ε(v3)))dΩ; - - res(u,v,φ,dΩ) = a(u,v,φ,dΩ) - l(v,φ,dΩ) - - _C(ε_p,ε_q) = C ⊙ ε_p ⊙ ε_q; - _K((u1,u2,u3),εᴹ) = (_C(ε(u1)+εᴹ[1],εᴹ[1]) + _C(ε(u2)+εᴹ[2],εᴹ[2]) + 2*_C(ε(u1)+εᴹ[1],εᴹ[2]))/4 - _v_K((u1,u2,u3),εᴹ) = (_C(ε(u1)+εᴹ[1],ε(u1)+εᴹ[1]) + _C(ε(u2)+εᴹ[2],ε(u2)+εᴹ[2]) + 2*_C(ε(u1)+εᴹ[1],ε(u2)+εᴹ[2]))/4 - - K_mod = (u,φ,dΩ) -> ∫((I ∘ φ)*_K(u,εᴹ))dΩ; - DK_mod = (q,u,φ,dΩ) -> ∫(-_v_K(u,εᴹ)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; - - state_map = AffineFEStateMap(a,l,res,U,V,V_φ,U_reg,φh,dΩ) - pcfs = PDEConstrainedFunctionals(K_mod,[K_mod],state_map,analytic_dC=[DK_mod]) - - φ = get_free_dof_values(φh) - j,c,dJ,dC = Gridap.evaluate!(pcfs,φ) - uh = get_state(pcfs) - - dFh = interpolate(FEFunction(V_φ,dJ),U_reg) - dF = get_free_dof_values(dFh) - - dFh_analytic = interpolate(FEFunction(V_φ,first(dC)),U_reg) - dF_analytic = get_free_dof_values(dFh_analytic) - - pre_hilb_abs_error = maximum(abs,dF-dF_analytic) - pre_hilb_rel_error = maximum(abs,dF-dF_analytic)/maximum(abs,dF_analytic) - - abs_error = abs(dFh-dFh_analytic) - rel_error = (abs(dFh-dFh_analytic))/abs(dFh_analytic) - - ## Hilb ext reg - α = 4*maximum(eΔ) - A(u,v) = α^2*∫(∇(u) ⊙ ∇(v))dΩ + ∫(u ⋅ v)dΩ; - Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv=Vector{PetscScalar} - Hilb_assem=SparseMatrixAssembler(Tm,Tv,U_reg,V_reg) - hilb_K = assemble_matrix(A,Hilb_assem,U_reg,V_reg) - ## Autodiff result - op = AffineFEOperator(U_reg,V_reg,hilb_K,-get_free_dof_values(dFh)) - dFh_Ω = solve(op) - dF_Ω = get_free_dof_values(dFh_Ω) - ## Analytic result - op = AffineFEOperator(U_reg,V_reg,hilb_K,-get_free_dof_values(dFh_analytic)) - dFh_analytic_Ω = solve(op) - dF_analytic_Ω = get_free_dof_values(dFh_analytic_Ω) - - hilb_abs_error = abs(dFh_Ω-dFh_analytic_Ω) - hilb_rel_error = (abs(dFh_Ω-dFh_analytic_Ω))/abs(dFh_analytic_Ω) - - post_hilb_abs_error = maximum(abs,dF_Ω-dF_analytic_Ω) - post_hilb_rel_error = maximum(abs,dF_Ω-dF_analytic_Ω)/maximum(abs,dF_analytic_Ω) - - path = dirname(dirname(@__DIR__))*"/results/InvHomLE_AutoDiffTesting_Parallel"; - writevtk(Ω,path,cellfields=["phi"=>φh, - "H(phi)"=>(interp.H ∘ φh), - "|nabla(phi)|"=>(norm ∘ ∇(φh)), - "uh1"=>uh[1], - "uh2"=>uh[2], - "uh3"=>uh[3], - "J′_abs_error"=>abs_error, - "J′_rel_error"=>rel_error, - "J′_analytic"=>dFh_analytic, - "J′_autodiff"=>dFh, - "hilb_abs_error"=>hilb_abs_error, - "hilb_rel_error"=>hilb_rel_error, - "v_J_Ω"=>dFh_analytic_Ω, - "dJφh_Ω"=>dFh_Ω - ]) - - return pre_hilb_abs_error,pre_hilb_rel_error,post_hilb_abs_error,post_hilb_rel_error -end - -out = with_debug() do distribute - main((3,3),distribute) -end - -#################### -# Serial Testing # -#################### -# function update_labels!(e::Int,model::CartesianDiscreteModel,f_Γ::F,::T,name::String) where { -# M<:AbstractFloat,F<:Function,T<:NTuple{2,M}} -# labels = get_face_labeling(model) -# cell_to_entity = labels.d_to_dface_to_entity[end] -# entity = maximum(cell_to_entity) + e -# # Vertices -# vtx_coords = model.grid_topology.vertex_coordinates -# vtxs_Γ = findall(isone,f_Γ.(vtx_coords)) -# vtx_edge_connectivity = Array(Geometry.get_faces(model.grid_topology,0,1)[vtxs_Γ]) -# # Edges -# edge_entries = [findall(x->any(x .∈ vtx_edge_connectivity[1:end.!=j]), -# vtx_edge_connectivity[j]) for j = 1:length(vtx_edge_connectivity)] -# edge_Γ = unique(reduce(vcat,getindex.(vtx_edge_connectivity,edge_entries),init=[])) -# labels.d_to_dface_to_entity[1][vtxs_Γ] .= entity -# labels.d_to_dface_to_entity[2][edge_Γ] .= entity -# add_tag!(labels,name,[entity]) -# end - -# order = 1; -# el_size = (100,100); -# dom = (0.,1.,0.,1.); -# coord_max = dom[2],dom[4] -# model = CartesianDiscreteModel(dom,el_size,isperiodic=(true,true)); -# ## Define Γ_N and Γ_D -# xmax,ymax = coord_max -# # f_Γ_D(x) = iszero(x) ? true : false; -# # update_labels!(1,model,f_Γ_D,coord_max,"origin") -# ## Triangulations and measures -# Ω = Triangulation(model) -# dΩ = Measure(Ω,2order) -# ## Spaces -# reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) -# V = TestFESpace(model,reffe;conformity=:H1,constraint = :zeromean) -# U = TrialFESpace(V,[VectorValue(0.0,0.0)]) - -# all_V = MultiFieldFESpace([V,V,V]) -# all_U = MultiFieldFESpace([U,U,U]) - -# # Space for shape sensitivities -# reffe_scalar = ReferenceFE(lagrangian,Float64,order) -# # FE space for LSF -# V_φ = TestFESpace(model,reffe_scalar;conformity=:H1) -# # FE Space for shape derivatives -# V_reg = TestFESpace(model,reffe_scalar;conformity=:H1) -# U_reg = TrialFESpace(V_reg) -# ###################################################### -# eΔ = (xmax,ymax)./el_size; -# interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(eΔ)) -# C = isotropic_2d(1.,0.3) -# g = VectorValue(0.,-1.0) -# φh = interpolate(x->-sqrt((x[1]-0.5)^2+(x[2]-0.5)^2)+0.25,V_φ) -# uh = zero(all_U) - -# ## Weak form -# I = interp.I; -# DH = interp.DH - -# εᴹ = (TensorValue(1.,0.,0.,0.), # ϵᵢⱼ⁽¹¹⁾≡ϵᵢⱼ⁽¹⁾ -# TensorValue(0.,0.,0.,1.), # ϵᵢⱼ⁽²²⁾≡ϵᵢⱼ⁽²⁾ -# TensorValue(0.,1/2,1/2,0.)) # ϵᵢⱼ⁽¹²⁾≡ϵᵢⱼ⁽³⁾ - -# a((u1,u2,u3),(v1,v2,v3),φ,dΩ) = ∫((I ∘ φ)*(C ⊙ ε(u1) ⊙ ε(v1)) + -# (I ∘ φ)*(C ⊙ ε(u2) ⊙ ε(v2)) + -# (I ∘ φ)*(C ⊙ ε(u3) ⊙ ε(v3)))dΩ -# l((v1,v2,v3),φ,dΩ) = ∫(-(I ∘ φ)*(C ⊙ εᴹ[1] ⊙ ε(v1)) - -# (I ∘ φ)*(C ⊙ εᴹ[2] ⊙ ε(v2)) - -# (I ∘ φ)*(C ⊙ εᴹ[2] ⊙ ε(v3)))dΩ; - -# a(φ,dΩ) = (u,v) -> a(u,v,φ,dΩ) -# l(φ,dΩ) = (v) -> l(v,φ,dΩ) -# res(u,v,φ,dΩ) = a(u,v,φ,dΩ) - l(v,φ,dΩ) - -# _C(ε_p,ε_q) = C ⊙ ε_p ⊙ ε_q; -# _K((u1,u2,u3),εᴹ) = (_C(ε(u1)+εᴹ[1],εᴹ[1]) + _C(ε(u2)+εᴹ[2],εᴹ[2]) + 2*_C(ε(u1)+εᴹ[1],εᴹ[2]))/4 -# _v_K((u1,u2,u3),εᴹ) = (_C(ε(u1)+εᴹ[1],ε(u1)+εᴹ[1]) + _C(ε(u2)+εᴹ[2],ε(u2)+εᴹ[2]) + 2*_C(ε(u1)+εᴹ[1],ε(u2)+εᴹ[2]))/4 - -# K_mod = (u,φ,dΩ) -> ∫((I ∘ φ)*_K(u,εᴹ))dΩ; -# DK_mod = (q,u,φ,dΩ) -> ∫(-_v_K(u,εᴹ)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; - -# K_mod_func = Functional(K_mod,dΩ,uh,φh); -# K_mod_func_analytic = Functional(K_mod,dΩ,uh,φh;DF=DK_mod); -# K_mod_smap, C_smaps = AffineFEStateMap(K_mod_func,[K_mod_func_analytic],all_U,all_V,V_φ,a,l,res;ls = LUSolver()); - -# K_mod_smap(φh) -# K_mod_smap.F.F() -# C_smaps[1].F.F() - -# dFh = compute_shape_derivative!(φh,K_mod_smap) -# dF = get_free_dof_values(dFh) - -# dFh_analytic = compute_shape_derivative!(φh,C_smaps[1]) -# dF_analytic = get_free_dof_values(dFh_analytic) - -# norm(dF-dF_analytic,Inf) -# norm(dF-dF_analytic,Inf)/norm(dF_analytic,Inf) \ No newline at end of file diff --git a/Deprecated/Deprecated_root_files/test_iterate.jl b/Deprecated/Deprecated_root_files/test_iterate.jl deleted file mode 100644 index 60519f0e..00000000 --- a/Deprecated/Deprecated_root_files/test_iterate.jl +++ /dev/null @@ -1,37 +0,0 @@ -struct MyIterator{A,B,C} - cache :: Tuple{A,B,C} -end - -function conv_criterion(m::MyIterator,item,state) - it,J,C = item - _,φ,dL = state - return it>10 -end - -function Base.iterate(m::MyIterator) - _,_,_ = m.cache - J = 1; C = [1,1] - return (0,J,C),(0,[],[]) -end - -function Base.iterate(m::MyIterator,state) - (it,φ,dL) = state; - a,b,c = m.cache - - J_new = a + rand() - C_new = @. b + rand() - - new_item = (it+1,J_new,C_new) - new_state = (it+1,φ,dL) - - if conv_criterion(m,new_item,new_state) - return nothing - else - return new_item,new_state - end -end - -m = MyIterator((-1,-2,-3)) -for (it,J_new,C_new) in m - println("$it: $J_new | $C_new") -end \ No newline at end of file diff --git a/Deprecated/Deprecated_scripts/AD_AM_testing.jl b/Deprecated/Deprecated_scripts/AD_AM_testing.jl deleted file mode 100644 index c944b317..00000000 --- a/Deprecated/Deprecated_scripts/AD_AM_testing.jl +++ /dev/null @@ -1,139 +0,0 @@ -using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, LevelSetTopOpt - -""" - ... -""" -function main() - ## Parameters - order = 2; - xmax,ymax=(1.0,1.0) - prop_Γ_N = 0.4; - dom = (0,xmax,0,ymax); - el_size = (500,500); - γ = 0.1; - γ_reinit = 0.5; - max_steps = floor(Int,minimum(el_size)/10) - tol = 1/(order^2*10)*prod(inv,minimum(el_size)) - C = isotropic_2d(1.,0.3); - η_coeff = 2; - α_coeff = 4; - g = VectorValue(0,-1); - path = dirname(dirname(@__DIR__))*"/results/minimum_length_scale" - - ## FE Setup - model = CartesianDiscreteModel(dom,el_size); - Δ = get_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0) ? true : false; - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/4 - eps() <= x[2] <= - ymax/2+ymax*prop_Γ_N/4 + eps()) ? true : false; - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,VectorValue(0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - - ## Create FE functions - φh = interpolate(gen_lsf(4,0.2),V_φ); - φ = get_free_dof_values(φh) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(Δ),ϵₘ=0.0) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(v⋅g)dΓ_N - res(u,v,φ,dΩ,dΓ_N) = a(u,v,φ,dΩ,dΓ_N) - l(v,φ,dΩ,dΓ_N) - - ## Optimisation functionals - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,Δ./order,max_steps,tol) - reinit!(stencil,φ,γ_reinit) - - uh = interpolate(x->x[1],V_φ) - # f = φ->∫((DH ∘ φ)*(norm ∘ φ)*uh)dΩ; - f = φ->∫((I ∘ φ)*uh)dΩ; # <- this corresponds to J_1Ω - df = gradient(f,φh) - dfh = FEFunction(V_φ, assemble_vector(df,V_φ)) - - # df_analytic = q->∫(q*(∇(uh)⋅∇(φh)+laplacian(φh)*uh)*(DH ∘ φh)*(norm ∘ φh))dΩ - df_analytic = q->∫(uh*q*(DH ∘ φh))dΩ#*(norm ∘ ∇(φh)))dΩ # <- assume |∇φ| = 1 - df_analytic_h = FEFunction(V_φ, assemble_vector(df_analytic,V_φ)) - - make_dir(path) - writevtk(Ω,"$path/TestVariational",cellfields=["dfh_analytic"=>df_analytic_h,"dfh"=>dfh]) - - ## When it doesn't work: - """ - Take - J(Ω) = ∫ j(φ) dD - where D is the whole bounding domain and φ is a signed distance function. Then, - J'(Ω)(θ) = ... a very complicated expression. -""" - - return nothing - - - - P_minT = (u,φ,dΩ,dΓ_N) -> ∫(φ*φ*(_max ∘ φ)*(_max ∘ φ))dΩ # ∫(H ∘ φ)dΩ - - function dP_minT(q,uu,_φ,dΩ,dΓ_N) - jp = 2_φ*(_max ∘ _φ)*(_max ∘ _φ)-_φ*_φ*(_max ∘ _φ) #DH ∘ _φ - - ω(_φ,_Δφ) = 1/(1 + 100*abs(_φ)^3.5*abs(_Δφ)^3.5) - - bi_form(u,v) = ∫(u*v*(DH ∘ _φ)*(norm ∘ ∇(_φ)) + (ω ∘ (_φ,laplacian(_φ)))*(∇(_φ) ⋅ ∇(u))*(∇(_φ) ⋅ ∇(v)) )dΩ; - li_form(v) = ∫(-jp*v)dΩ - - op = AffineFEOperator(bi_form,li_form,V_φ,V_φ) - xh = solve(op) - ∫(xh*q*(DH ∘ _φ)*(norm ∘ ∇(_φ)))dΩ - end - - ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,Δ./order,max_steps,tol) - reinit!(stencil,φ,γ_reinit) - - ## Setup solver and FE operators - state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) - # pcfs = PDEConstrainedFunctionals(P_minT,state_map) - pcfs = PDEConstrainedFunctionals(P_minT,[P_minT],state_map,analytic_dC=[dP_minT]) - J_val,C_val,dJ,dC = Gridap.evaluate!(pcfs,φ) - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(Δ) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; - vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - - make_dir(path) - # optimiser = AugmentedLagrangian(φ,pcfs,stencil,vel_ext,interp,el_size,γ,γ_reinit); - # for history in optimiser - # it,Ji,_,_= last(history) - # print_history(it,["J"=>Ji]) - # write_history(history,path*"/history.csv") - # uhi = get_state(pcfs) - # write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))];iter_mod=1) - # end - # it,Ji,_,_ = last(optimiser.history) - # print_history(it,["J"=>Ji]) - # write_history(optimiser.history,path*"/history.csv") - # uhi = get_state(pcfs) - # write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))];iter_mod=1) - - @show J_val - - writevtk(Ω,"$path/TestVariational",cellfields=["φh"=>φh,"dJ"=>FEFunction(U_reg,dJ),"dJ_analytic"=>FEFunction(U_reg,dC[1])]) - maximum(abs,dJ-dC[1]),maximum(abs,dJ-dC[1])/maximum(abs,dC[1]) -end - -main() \ No newline at end of file diff --git a/Deprecated/Deprecated_scripts/advection.jl b/Deprecated/Deprecated_scripts/advection.jl deleted file mode 100644 index bed8fe88..00000000 --- a/Deprecated/Deprecated_scripts/advection.jl +++ /dev/null @@ -1,30 +0,0 @@ - -# This file shows how to modify the advection scheme - -using GridapTopOp - -struct MyStencil <: GridapTopOp.AdvectionStencil end - -function GridapTopOp.allocate_caches(::MyStencil,φ,vel) - # Do stuff here... -end - -function GridapTopOp.reinit!(::MyStencil,φ_new,φ_old,vel,Δt,Δx,caches) - # Do stuff here... -end - -function GridapTopOp.advect!(::MyStencil,φ,vel,Δt,Δx,caches) - # Do stuff here... -end - -function GridapTopOp.compute_Δt(s::MyStencil{D,T},φ,vel) where {D,T} - # Do stuff here... -end - -######################################## - -# Basically same code as the standard one, but using our new stencil -function main() - -end - diff --git a/Deprecated/Deprecated_scripts/inverter_AD_testing.jl b/Deprecated/Deprecated_scripts/inverter_AD_testing.jl deleted file mode 100644 index 79425c83..00000000 --- a/Deprecated/Deprecated_scripts/inverter_AD_testing.jl +++ /dev/null @@ -1,114 +0,0 @@ -using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, LevelSetTopOpt - -""" - (Serial) Inverter mechanism with augmented Lagrangian method in 2D. - - Ref: http://doi.org/10.1007/s00158-018-1950-2 - - Optimisation problem: - Min J(Ω) = ∫ ηᵢₙ * uₓ dΓᵢₙ + ∫ ηₒᵤₜ * uₓ dΓₒᵤₜ - Ω - s.t., Vol(Ω) = Vf, - ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, - ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ + ∫ kₛv⋅u dΓₒᵤₜ = ∫ v⋅g dΓᵢₙ , ∀v∈V. -""" -function main() - ## Parameters - order = 1; - dom = (0,1,0,1); - el_size = (200,200); - γ = 0.1; - γ_reinit = 0.5; - max_steps = floor(Int,minimum(el_size)/10) - tol = 1/(10order^2)*prod(inv,minimum(el_size)) - C = isotropic_2d(1.0,0.3); - η_coeff = 2; - α_coeff = 4; - path = dirname(dirname(@__DIR__))*"/results/testing_inverter_AD" - - η_in = 2; - η_out = 1; - ks = 0.01; - g = VectorValue(1,0); - - ## FE Setup - model = CartesianDiscreteModel(dom,el_size); - Δ = get_Δ(model) - f_Γ_in(x) = (x[1] ≈ 0.0) && 0.47 - eps() <= x[2] <= 0.53 + eps() ? true : false; - f_Γ_out(x) = (x[1] ≈ 1.0) && 0.43 - eps() <= x[2] <= 0.57 + eps() ? true : false; - f_Γ_D(x) = x[1] ≈ 0.0 && (x[2] <= 0.1 || x[2] >= 0.9) ? true : false; - update_labels!(1,model,f_Γ_in,"Gamma_in") - update_labels!(2,model,f_Γ_out,"Gamma_out") - update_labels!(3,model,f_Γ_D,"Gamma_D") - - ## Triangulations and measures - Ω = Triangulation(model) - Γ_in = BoundaryTriangulation(model,tags="Gamma_in") - Γ_out = BoundaryTriangulation(model,tags="Gamma_out") - dΩ = Measure(Ω,2order) - dΓ_in = Measure(Γ_in,2order) - dΓ_out = Measure(Γ_out,2order) - vol_D = sum(∫(1)dΩ) - - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,VectorValue(0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_in","Gamma_out"]) - U_reg = TrialFESpace(V_reg,[0,0]) - - ## Create FE functions - φh = interpolate(gen_lsf(4,0.2),V_φ); - φ = get_free_dof_values(φh) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(Δ),ϵₘ=10^-8) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - a(u,v,φ,dΩ,dΓ_in,dΓ_out) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ + ∫(ks*(u⋅v))dΓ_out - l(v,φ,dΩ,dΓ_in,dΓ_out) = ∫(v⋅g)dΓ_in - res(u,v,φ,dΩ,dΓ_in,dΓ_out) = a(u,v,φ,dΩ,dΓ_in,dΓ_out) - l(v,φ,dΩ,dΓ_in,dΓ_out) - - ## Optimisation functionals - J = (u,φ,dΩ,dΓ_in,dΓ_out) -> ∫(η_in*u⋅VectorValue(1,0))dΓ_in + - ∫(η_out*u⋅VectorValue(1,0))dΓ_out - - function dJ(q,u,φ,dΩ,dΓ_in,dΓ_out) - a_adjoint(λ,v) = ∫((I ∘ φ)*(C ⊙ ε(λ) ⊙ ε(v)))dΩ + ∫(ks*(λ⋅v))dΓ_out - l_adjoint(v) = ∫(-η_in*v⋅VectorValue(1,0))dΓ_in + ∫(-η_out*v⋅VectorValue(1,0))dΓ_out - - op = AffineFEOperator(a_adjoint,l_adjoint,U,V) - λh = solve(op) - - ∫(q*(C ⊙ ε(u) ⊙ ε(λh))*(DH ∘ φh))dΩ - end - - Vol = (u,φ,dΩ,dΓ_in,dΓ_out) -> ∫(((ρ ∘ φ) - 0.5)/vol_D)dΩ; - dVol = (q,u,φ,dΩ,dΓ_in,dΓ_out) -> ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - - ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,Δ./order,max_steps,tol) - reinit!(stencil,φ,γ_reinit) - - ## Setup solver and FE operators - state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out) - pcfs = PDEConstrainedFunctionals(J,[Vol,J],state_map,analytic_dC=[dVol,dJ]) - - J_val,C_val,dJ,dC = Gridap.evaluate!(pcfs,φ) - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(Δ) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; - vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - - ## Optimiser - make_dir(path) - - writevtk(Ω,"$path/TestVariational",cellfields=["φh"=>φh,"dJ"=>FEFunction(U_reg,dJ),"dJ_analytic"=>FEFunction(U_reg,dC[2])]) - - maximum(abs,dJ-dC[2]),maximum(abs,dJ-dC[2])/maximum(abs,dC[2]) -end - -main(); \ No newline at end of file diff --git a/Deprecated/Deprecated_scripts/main_inverter_(Based on Laurain).jl b/Deprecated/Deprecated_scripts/main_inverter_(Based on Laurain).jl deleted file mode 100644 index 11a8e574..00000000 --- a/Deprecated/Deprecated_scripts/main_inverter_(Based on Laurain).jl +++ /dev/null @@ -1,112 +0,0 @@ -using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, LevelSetTopOpt - -""" - (Serial) Inverter mechanism with augmented Lagrangian method in 2D. - - Ref: http://doi.org/10.1007/s00158-018-1950-2 - - Optimisation problem: - Min J(Ω) = ∫ ηᵢₙ * uₓ dΓᵢₙ + ∫ ηₒᵤₜ * uₓ dΓₒᵤₜ - Ω - s.t., Vol(Ω) = Vf, - ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, - ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ + ∫ kₛv⋅u dΓₒᵤₜ = ∫ v⋅g dΓᵢₙ , ∀v∈V. -""" -function main() - ## Parameters - order = 1; - dom = (0,1,0,1); - el_size = (200,200); - γ = 0.1; - γ_reinit = 0.5; - max_steps = floor(Int,minimum(el_size)/10) - tol = 1/(order^2*10)*prod(inv,minimum(el_size)) - C = isotropic_2d(1.0,0.3); - η_coeff = 2; - α_coeff = 4; - path = dirname(dirname(@__DIR__))*"/results/main_inverter_mechanism" - - η_in = 2; - η_out = 1; - ks = 0.01; - g = VectorValue(1,0); - - ## FE Setup - model = CartesianDiscreteModel(dom,el_size); - Δ = get_Δ(model) - f_Γ_in(x) = (x[1] ≈ 0.0) && 0.47 - eps() <= x[2] <= 0.53 + eps() ? true : false; - f_Γ_out(x) = (x[1] ≈ 1.0) && 0.43 - eps() <= x[2] <= 0.57 + eps() ? true : false; - f_Γ_D(x) = x[1] ≈ 0.0 && (x[2] <= 0.1 || x[2] >= 0.9) ? true : false; - update_labels!(1,model,f_Γ_in,"Gamma_in") - update_labels!(2,model,f_Γ_out,"Gamma_out") - update_labels!(3,model,f_Γ_D,"Gamma_D") - - ## Triangulations and measures - Ω = Triangulation(model) - Γ_in = BoundaryTriangulation(model,tags="Gamma_in") - Γ_out = BoundaryTriangulation(model,tags="Gamma_out") - dΩ = Measure(Ω,2order) - dΓ_in = Measure(Γ_in,2order) - dΓ_out = Measure(Γ_out,2order) - vol_D = sum(∫(1)dΩ) - - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,VectorValue(0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_in","Gamma_out"]) - U_reg = TrialFESpace(V_reg,[0,0]) - - ## Create FE functions - φh = interpolate(gen_lsf(4,0.2),V_φ); - φ = get_free_dof_values(φh) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - a(u,v,φ,dΩ,dΓ_in,dΓ_out) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ + ∫(ks*(u⋅v))dΓ_out - l(v,φ,dΩ,dΓ_in,dΓ_out) = ∫(v⋅g)dΓ_in - res(u,v,φ,dΩ,dΓ_in,dΓ_out) = a(u,v,φ,dΩ,dΓ_in,dΓ_out) - l(v,φ,dΩ,dΓ_in,dΓ_out) - - ## Optimisation functionals - J = (u,φ,dΩ,dΓ_in,dΓ_out) -> ∫(η_in*u⋅VectorValue(1,0))dΓ_in + - ∫(η_out*u⋅VectorValue(1,0))dΓ_out - Vol = (u,φ,dΩ,dΓ_in,dΓ_out) -> ∫(((ρ ∘ φ) - 0.5)/vol_D)dΩ; - dVol = (q,u,φ,dΩ,dΓ_in,dΓ_out) -> ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - - ## Finite difference solver and level set function - stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,Δ./order,max_steps,tol) - reinit!(stencil,φ,γ_reinit) - - ## Setup solver and FE operators - state_map = AffineFEStateMap(a,l,res,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out) - pcfs = PDEConstrainedFunctionals(J,[Vol],state_map,analytic_dC=[dVol]) - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(Δ) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; - vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - - ## Optimiser - make_dir(path) - optimiser = AugmentedLagrangian(φ,pcfs,stencil,vel_ext,interp,el_size,γ,γ_reinit); - for history in optimiser - it,Ji,Ci,Li = last(history) - λi = optimiser.λ; Λi = optimiser.Λ - print_history(it,["J"=>Ji,"C"=>Ci,"L"=>Li,"λ"=>λi,"Λ"=>Λi]) - write_history(history,path*"/history.csv") - # uhi = get_state(pcfs) - # write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uhi];iter_mod=1) - end - it,Ji,Ci,Li = last(optimiser.history) - λi = optimiser.λ; Λi = optimiser.Λ - print_history(it,["J"=>Ji,"C"=>Ci,"L"=>Li,"λ"=>λi,"Λ"=>Λi]) - write_history(optimiser.history,path*"/history.csv") - uhi = get_state(pcfs) - write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uhi];iter_mod=1) -end - -main(); \ No newline at end of file diff --git a/Deprecated/Images/Algorithm.png b/Deprecated/Images/Algorithm.png deleted file mode 100644 index aa6a2f64c9c9176c8804d419fc3bfe46a62a6487..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 1482410 zcmeFZXIPV2yEcrY=qL)KQbYutp$P~my)%phNSEG0q)83ZdmI!C2q-Ots#NKn(4!(H zKnT4TQ3J1 ze}8{rXAf6zJ6lf&VThMg>Zbfn8k*ZQ>VGO52BfV|`v(}~zA9})Zo9oNk^WupmuFiM zZz8id71l<~ElNU*{F*iZ;Q=25U}94hnFswiBSF2ySD 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z`%e@`_HOFVM&Wx#T>s&3UpAFHhlc;QTsO_f8!yacU@Ca3AKL%ut2il9UfI1wP1EkfP0QpYTk=xcdP@Vq9W!PD0%# z#uhArbHds`@~EP!0uJ8gb6;adG$6b-!GWr)d$HL)-fAHDV=I2h?%Y3>XeS-2<_QAHM+K0cXqVWTT-GM8-h%7x4GkXgs0f<{Gt)@rC*AVGTxl8f45)dMi=h>Zd7s zj^c74Q6v2y>uZ{$T}%3~(aRr8ICUl&5qJLbVKhmDwM}d;P5mic4ps(zMQkLI=%lfc zO?w8X&TNmbD%eOZ9+`#1L(#79>5z{4F$vEu-?e9$wOiS+m348W%?=30evPNC|!pCih~zeb@DAQ=0vO ztp14xcqU@01U}G0^}C z0sgV>!9|oR%;OQ-<$2~`B$Ro~&7+2+u>R1>+^djEgCN;rU2=+nrxnI1nr*gY?CCn)fWS9VTP>vuF1_6a+T=%k*^ogw|2n|NM*Xmj=phMk20$}0wPTgwR~M&q@HRw3^y7`asuCQ5PzI@S^@U3;(i&ll zyiLMZSdQGF)n0M0mpN?go{i@WDjOO(w-Ex4i- za847gyX1Y&@;>#Fub-d3cz_HLbMV|A z%hJvLEhh?Jmqi=U9t|N_2UFYD%8J;M@W46~>v$<|4&m2?*Ef2v3jS{}S6ZQPLOF6j^Jos+bLY8;)9_5LC$ zE86F`rjv|6gt7uRb&fQQr{hdX8s6@$>@?%Y#&K?`)MnjwygE<4mp-=ZqbmIcMZ4_7 zOZm20-M>)@x&B@=W0J9&hmFT06RZ=&(t9q;CAwO5+tS$(xy_qXZ7#YCyhq&I{+Bm; Pkqdc;!-IYZJaO?qK6GU` diff --git a/Deprecated/assembler_bug.jl b/Deprecated/assembler_bug.jl deleted file mode 100644 index b318e859..00000000 --- a/Deprecated/assembler_bug.jl +++ /dev/null @@ -1,43 +0,0 @@ -using Gridap, Gridap.FESpaces, Gridap.Helpers - -## Current version @ Line 310 of Assemblers.jl - -## Proposed version -function Gridap.FESpaces.assemble_matrix_and_vector!(a,l,K,b,assem_U,U,V,uhd) - du = get_trial_fe_basis(U) - dv = get_fe_basis(V); - data = collect_cell_matrix_and_vector(U,V,a(du,dv),l(dv),uhd) - assemble_matrix_and_vector!(K,b,assem_U,data) -end - -function main(with_standard::Bool) - model = CartesianDiscreteModel((0,1,0,1),(2,2)); - - Ω = Triangulation(model) - dΩ = Measure(Ω,2) - - # FE Problem - V = FESpace(model,ReferenceFE(lagrangian,Float64,1),dirichlet_tags=["boundary"]) - U = TrialFESpace(V,2) - a(u,v) = ∫( ∇(v)⋅∇(u) )*dΩ - l(v) = ∫(v)*dΩ - - assem_U = SparseMatrixAssembler(U,V); - op = AffineFEOperator(a,l,U,V,assem_U); - - K = get_matrix(op); - b = get_vector(op); - b_old = copy(b); - - if with_standard - assemble_matrix_and_vector!(a,l,K,b,U,V) - else - assemble_matrix_and_vector!(a,l,K,b,assem_U,U,V,zero(U)) - end - - norm(b - b_old,Inf) -end - -main(true) - -main(false) \ No newline at end of file diff --git a/Deprecated/auto_diff_elastic_compliance_serial.jl b/Deprecated/auto_diff_elastic_compliance_serial.jl deleted file mode 100644 index 53bf8681..00000000 --- a/Deprecated/auto_diff_elastic_compliance_serial.jl +++ /dev/null @@ -1,214 +0,0 @@ -using Gridap, Gridap.TensorValues, Gridap.Geometry, Gridap.FESpaces -using PartitionedArrays - -using ChainRulesCore -using Zygote -include("ChainRules.jl"); - -# Heaviside function -function H_η(t;η) - M = typeof(η*t) - if t<-η - return zero(M) - elseif abs(t)<=η - return M(1/2*(1+t/η+1/pi*sin(pi*t/η))) - elseif t>η - return one(M) - end -end - -function DH_η(t::M;η::M) where M<:AbstractFloat - if t<-η - return zero(M) - elseif abs(t)<=η - return M(1/2/η*(1+cos(pi*t/η))) - elseif t>η - return zero(M) - end -end - -# Material interpolation -Base.@kwdef struct SmoothErsatzMaterialInterpolation{M<:AbstractFloat} - η::M # Smoothing radius - ϵₘ::M = 10^-3 # Void material multiplier - H = x -> H_η(x,η=η) - DH = x -> DH_η(x,η=η) - I = φ -> (1 - H(φ)) + ϵₘ*H(φ) - ρ = φ -> 1 - H(φ) -end - -function isotropic_2d(E::M,ν::M) where M<:AbstractFloat - λ = E*ν/((1+ν)*(1-ν)); μ = E/(2*(1+ν)) - C = [λ+2μ λ 0 - λ λ+2μ 0 - 0 0 μ]; - SymFourthOrderTensorValue( - C[1,1], C[3,1], C[2,1], - C[1,3], C[3,3], C[2,3], - C[1,2], C[3,2], C[2,2]) -end - -###################################################### -# begin -## FE Setup -order = 1; -el_size = (200,200); -dom = (0.,1.,0.,1.); -model = CartesianDiscreteModel(dom,el_size); -## Define Γ_N and Γ_D -xmax,ymax = dom[2],dom[4] -labels = get_face_labeling(model) -entity = num_entities(labels) + 1 -prop_Γ_N = 0.4 -prop_Γ_D = 0.2 -f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) ? true : false; -f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/4 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/4 + eps()) ? true : false; -# Vertices -vtx_coords = model.grid_topology.vertex_coordinates -vtxs_Γ_D = findall(isone,f_Γ_D.(vtx_coords)) -vtx_edge_connectivity = Array(model.grid_topology.n_m_to_nface_to_mfaces[1,2][vtxs_Γ_D]); -# Edges -edge_entires = [findall(x->any(x .∈ vtx_edge_connectivity[1:end.!=j]),vtx_edge_connectivity[j]) for j = 1:length(vtx_edge_connectivity)] -edge_Γ_D = unique(reduce(vcat,getindex.(vtx_edge_connectivity,edge_entires),init=[])) -labels.d_to_dface_to_entity[1][vtxs_Γ_D] .= entity -labels.d_to_dface_to_entity[2][edge_Γ_D] .= entity -add_tag!(labels,"Gamma_D",[entity]) -# Γ_N -entity = num_entities(labels) + 1 -# Vertices -vtxs_Γ_N = findall(isone,f_Γ_N.(vtx_coords)) -vtx_edge_connectivity = Array(model.grid_topology.n_m_to_nface_to_mfaces[1,2][vtxs_Γ_N]); -# Edges -edge_entires = [findall(x->any(x .∈ vtx_edge_connectivity[(1:end.!=j)]),vtx_edge_connectivity[j]) for j = 1:length(vtx_edge_connectivity)] -edge_Γ_N = unique(reduce(vcat,getindex.(vtx_edge_connectivity,edge_entires),init=[])) -labels.d_to_dface_to_entity[1][vtxs_Γ_N] .= entity -labels.d_to_dface_to_entity[2][edge_Γ_N] .= entity -add_tag!(labels,"Gamma_N",[entity]) -## Triangulations and measures -Ω = Triangulation(model) -Γ_N = BoundaryTriangulation(model,tags="Gamma_N") -dΩ = Measure(Ω,2order) -dΓ_N = Measure(Γ_N,2order) -## Spaces -reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) -V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["Gamma_D"], - dirichlet_masks=[(true,true)],vector_type=Vector{Float64}) -U = TrialFESpace(V,[VectorValue(0.0,0.0)]) -# Space for shape sensitivities -reffe_scalar = ReferenceFE(lagrangian,Float64,order) -V_L2 = TestFESpace(model,reffe_scalar;conformity=:L2) -# FE space for LSF -V_φ = TestFESpace(model,reffe_scalar;conformity=:H1) -# FE Space for shape derivatives -V_reg = TestFESpace(model,reffe_scalar;conformity=:H1, - dirichlet_tags=["Gamma_N"],dirichlet_masks=[true]) -U_reg = TrialFESpace(V_reg,[0.0]) -###################################################### -eΔ = (xmax,ymax)./el_size; -interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(eΔ)) -C = isotropic_2d(1.,0.3) -g = VectorValue(0.,-1.0) -φh = interpolate(x->-sqrt((x[1]-0.5)^2+(x[2]-0.5)^2)+0.25,V_φ) - -## Weak form -I = interp.I; - -function ϕ_to_ϕₕ(ϕ::AbstractArray,Q) - ϕ = FEFunction(Q,ϕ) -end -function ϕ_to_ϕₕ(ϕ::FEFunction,Q) - ϕ -end -function ϕ_to_ϕₕ(ϕ::CellField,Q) - ϕ -end - -function a(u,v,φ) - φh = ϕ_to_ϕₕ(φ,V_φ) - ∫((I ∘ φh)*(C ⊙ ε(u) ⊙ ε(v)))dΩ -end -a(φ) = (u,v) -> a(u,v,φ) - -l(v,φh) = ∫(v ⋅ g)dΓ_N -l(φ) = v -> l(v,φ) - -res(u,v,φ,V_φ) = a(u,v,φ) - l(v,φ) - -φ = φh.free_values - -## Solve finite element problem -op = AffineFEOperator(a(φ),l(φ),U,V) -K = op.op.matrix; -## Solve -uh = solve(op) -## Compute J and v_J -_J(u,φ) = (a(u,u,φ)) # ∫(interp.ρ ∘ φ)dΩ -# _J(u,φ) = ∫(1+(u⋅u)*(u⋅u)+φ)dΩ # <- weird stuff works here - - -φ_to_u = AffineFEStateMap(a,l,res,V_φ,U,V) -u_to_j = LossFunction(_J,V_φ,U) - -u, u_pullback = rrule(φ_to_u,φ) -j, j_pullback = rrule(u_to_j,u,φ) -_, du, dϕ₍ⱼ₎ = j_pullback(1) # dj = 1 -_, dϕ₍ᵤ₎ = u_pullback(du) - dϕ = dϕ₍ᵤ₎ + dϕ₍ⱼ₎ - -function φ_to_j(φ) - u = φ_to_u(φ) - j = u_to_j(u,φ) -end - -j,dφ = Zygote.withgradient(φ_to_j,φ) - -sum(_J(uh,φh)) -j - -## Shape derivative -# Autodiff -dϕh = interpolate_everywhere(FEFunction(V_φ,dϕ),U_reg) - -# Analytic -J′(v,v_h) = ∫(-v_h*v*(interp.DH ∘ φh)*(norm ∘ ∇(φh)))dΩ; -v_J = -(C ⊙ ε(uh) ⊙ ε(uh)) -b = assemble_vector(v->J′(v,v_J),V_reg) -analytic_J′ = FEFunction(V_reg,b) - -abs_error = abs(dϕh-analytic_J′) -rel_error = (abs(dϕh-analytic_J′))/abs(analytic_J′) - -############################# -## Hilb ext reg -α = 4*maximum(eΔ) -A(u,v) = α^2*∫(∇(u) ⊙ ∇(v))dΩ + ∫(u ⋅ v)dΩ; -hilb_K = assemble_matrix(A,U_reg,V_reg) - -## Autodiff result -# -dϕh is AD version of J′ that we plug in usually! -op = AffineFEOperator(U_reg,V_reg,hilb_K,dϕh.free_values) -dϕh_Ω = solve(op) - -## Analytic result -b = assemble_vector(v->J′(v,v_J),V_reg) -op = AffineFEOperator(U_reg,V_reg,hilb_K,b) -v_J_Ω = solve(op) - -hilb_abs_error = abs(dϕh_Ω-v_J_Ω) -hilb_rel_error = (abs(dϕh_Ω-v_J_Ω))/abs(v_J_Ω) - -path = dirname(dirname(@__DIR__))*"/results/AutoDiffTesting"; -writevtk(Ω,path,cellfields=["phi"=>φh, - "H(phi)"=>(interp.H ∘ φh), - "|nabla(phi)|"=>(norm ∘ ∇(φh)), - "uh"=>uh, - "J′_abs_error"=>abs_error, - "J′_rel_error"=>rel_error, - "J′_analytic"=>analytic_J′, - "J′_autodiff"=>dϕh, - "hilb_abs_error"=>hilb_abs_error, - "hilb_rel_error"=>hilb_rel_error, - "v_J_Ω"=>v_J_Ω, - "dJϕh_Ω"=>dϕh_Ω -]) -# end \ No newline at end of file diff --git a/Deprecated/dg_upwinding_tests.jl b/Deprecated/dg_upwinding_tests.jl deleted file mode 100644 index 006584fe..00000000 --- a/Deprecated/dg_upwinding_tests.jl +++ /dev/null @@ -1,63 +0,0 @@ - -using Gridap -using Gridap.Geometry, Gridap.FESpaces, Gridap.ReferenceFEs -using GridapDistributed, PartitionedArrays - -nprocs = (2,1) -ranks = with_debug() do distribute - distribute(LinearIndices((prod(nprocs),))) -end - -D = 2 -nc = (10,1) -domain = (0,1,0,1) -model = CartesianDiscreteModel(ranks,nprocs,domain,nc;isperiodic=(true,false)) - -order = 2 -poly = QUAD -reffe = LagrangianRefFE(Float64,poly,order) -V = FESpace(model,reffe) - -cell_masks = map(local_views(model)) do model - coords = get_node_coordinates(model) - cell_ids = get_cell_node_ids(model) - JaggedArray(map(ids -> lazy_map(Reindex(coords),ids),cell_ids)) -end -gids = get_cell_gids(model) -p_coords = PVector(cell_coords,partition(gids)) -consistent!(p_coords) |> fetch - - -function mark_nodes(f,model) - local_masks = map(local_views(model)) do model - topo = get_grid_topology(model) - coords = get_vertex_coordinates(topo) - mask = map(f,coords) - return mask - end - gids = get_face_gids(model,0) - mask = PVector(local_masks,partition(gids)) - assemble!(|,mask) |> fetch - consistent!(mask) |> fetch - return mask -end - -fΓ(x::T) where T = (x ≈ zero(T)) -mask = mark_nodes(fΓ,model) - - -gids = get_face_gids(model,0) -local_masks = map(local_views(model),partition(gids)) do model, gids - topo = get_grid_topology(model) - coords = get_vertex_coordinates(topo) - mask = map(fΓ,coords) - println(mask) - println(local_to_owner(gids)) - return nothing -end - - - -_model = CartesianDiscreteModel(domain,nc) -coords1 = get_node_coordinates(_model) -coords2 = get_vertex_coordinates(get_grid_topology(_model)) diff --git a/Deprecated/elastic_compliance_for_jordi.jl b/Deprecated/elastic_compliance_for_jordi.jl deleted file mode 100644 index ad149f7f..00000000 --- a/Deprecated/elastic_compliance_for_jordi.jl +++ /dev/null @@ -1,128 +0,0 @@ -using Gridap, Gridap.TensorValues, Gridap.Geometry -using GridapDistributed -using GridapPETSc -using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code -using PartitionedArrays -using SparseMatricesCSR - -import GridapDistributed.DistributedCellField -import GridapDistributed.DistributedFESpace -import GridapDistributed.DistributedDiscreteModel -import GridapDistributed.DistributedMeasure - -include("Utilities.jl"); # <- For some useful functions - -# Make script for Jordi that can take msh size and processors for modifying PETSc (3D) + lsf fn. - -function main(mesh_partition,distribute) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - el_size = (100,50,50) - coord_max = (2.,1.,1.) - order = 1; - Δ = coord_max./el_size; - path = (@__DIR__)*"/Results/LinearElastic3DSolverTesting"; - t = PTimer(ranks) - GridapPETSc.with(args=split(options)) do - model,Ω,V_φ,solve_data = fe_setup(ranks,mesh_partition,order,coord_max,el_size) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(Δ)) - C = _isotropic_3d(1.,0.3) - g = VectorValue(0.,0.,-1.0) - φh = interpolate(x->-sqrt((x[1]-0.5)^2+(x[2]-0.5)^2+(x[3]-0.5)^2)+0.25,V_φ) - J,v_J,uh = elastic_compliance(φh,g,C,solve_data,interp,t) - display("Objective = $J") - writevtk(Ω,path,cellfields=["phi"=>φh,"H(phi)"=>(interp.H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) - end - t -end - -function elastic_compliance(φh::DistributedCellField,g,C::S,solve_data::NT,interp::T,t) where { - S<:SymFourthOrderTensorValue,T<:SmoothErsatzMaterialInterpolation,NT<:NamedTuple} - I = interp.I; dΩ=solve_data.dΩ; dΓ_N=solve_data.dΓ_N; - ## Weak form - a(u,v,φh) = ∫((I ∘ φh)*(C ⊙ ε(u) ⊙ ε(v)))dΩ - l(v) = ∫(v ⋅ g)dΓ_N - ## Solve finite element problem - tic!(t) - op = AffineFEOperator(a,l,solve_data.U,solve_data.V,solve_data.assem) - toc!(t,"Assembly time") - K = op.op.matrix; - ## Solve - ls = PETScLinearSolver() - tic!(t) - uh = solve(ls,op) - toc!(t,"Solve time") - u = correct_ghost_layout(uh,K.col_partition) - ## Compute J and v_J - # J = dot(u,(K*u)) - _J(φh) = sum(a(uh,uh,φh)) - J = _J(φh) - - # dJ/dφ_h # <- AD? - - tic!(t) - v_J = interpolate(-C ⊙ ε(uh) ⊙ ε(uh),solve_data.V_L2) - toc!(t,"Interpolate shape sensitivity") - return J,v_J,uh -end - -function fe_setup(ranks,mesh_partition,order::T,coord_max::NTuple{3,M}, - el_size::NTuple{3,T}) where {T<:Integer,M<:AbstractFloat} - ## Model - dom = (0,coord_max[1],0,coord_max[2],0,coord_max[3]); - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - ## Define Γ_N and Γ_D - xmax,ymax,zmax = coord_max - prop_Γ_N = 0.4 - f_Γ_D(x) = (x[1] ≈ 0.0) ? true : false; - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/4 - eps() <= x[2] <= - ymax/2+ymax*prop_Γ_N/4 + eps() && zmax/2-zmax*prop_Γ_N/4 - eps() <= x[3] - <= zmax/2+zmax*prop_Γ_N/4 + eps()) ? true : false; - update_labels!(1,model,f_Γ_D,coord_max,"Gamma_D") - update_labels!(2,model,f_Γ_N,coord_max,"Gamma_N") - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["Gamma_D"], - dirichlet_masks=[(true,true,true)]) - U = TrialFESpace(V,[VectorValue(0.0,0.0,0.0)]) - ## Assembler - Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv=Vector{PetscScalar} - assem=SparseMatrixAssembler(Tm,Tv,U,V) - # Space for shape sensitivities - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V_L2 = TestFESpace(model,reffe_scalar;conformity=:L2) - # FE space for LSF - V_φ = TestFESpace(model,reffe_scalar;conformity=:H1) - ## Collect data - solve_data = (U=U,V=V,assem=assem,V_L2=V_L2,dΩ=dΩ,dΓ_N=dΓ_N) - return model,Ω,V_φ,solve_data -end - -function _isotropic_3d(E::M,nu::M) where M<:AbstractFloat - λ = E*nu/((1+nu)*(1-2nu)); μ = E/(2*(1+nu)) - C =[λ+2μ λ λ 0 0 0 - λ λ+2μ λ 0 0 0 - λ λ λ+2μ 0 0 0 - 0 0 0 μ 0 0 - 0 0 0 0 μ 0 - 0 0 0 0 0 μ]; - return SymFourthOrderTensorValue( - C[1,1], C[6,1], C[5,1], C[2,1], C[4,1], C[3,1], - C[1,6], C[6,6], C[5,6], C[2,6], C[4,6], C[3,6], - C[1,5], C[6,5], C[5,5], C[2,5], C[4,5], C[3,5], - C[1,2], C[6,2], C[5,2], C[2,2], C[4,2], C[3,2], - C[1,4], C[6,4], C[5,4], C[2,4], C[4,4], C[3,4], - C[1,3], C[6,3], C[5,3], C[2,3], C[4,3], C[3,3]) -end - -t = with_debug() do distribute - main((3,3,3),distribute) -end; -display(t) diff --git a/Deprecated/get_dof_coords.jl b/Deprecated/get_dof_coords.jl deleted file mode 100644 index 99b909bb..00000000 --- a/Deprecated/get_dof_coords.jl +++ /dev/null @@ -1,72 +0,0 @@ - -using Gridap, GridapDistributed, PartitionedArrays, GridapPETSc -using Gridap.Geometry, Gridap.FESpaces, Gridap.ReferenceFEs, Gridap.CellData, Gridap.Arrays -using FillArrays - -function get_dof_coordinates(space::GridapDistributed.DistributedSingleFieldFESpace) - coords = map(local_views(space),partition(space.gids)) do space, dof_ids - local_to_own_dofs = local_to_own(dof_ids) - return get_dof_coordinates(space;perm=local_to_own_dofs) - end - - ngdofs = length(space.gids) - indices = map(local_views(space.gids)) do dof_indices - owner = part_id(dof_indices) - own_indices = OwnIndices(ngdofs,owner,own_to_global(dof_indices)) - ghost_indices = GhostIndices(ngdofs,Int64[],Int32[]) # We only consider owned dofs - OwnAndGhostIndices(own_indices,ghost_indices) - end - return PVector(coords,indices) -end - -function get_dof_coordinates(space::FESpace;perm=Base.OneTo(num_free_dofs(space))) - trian = get_triangulation(space) - cell_dofs = get_fe_dof_basis(space) - cell_ids = get_cell_dof_ids(space) - - cell_ref_nodes = lazy_map(get_nodes,CellData.get_data(cell_dofs)) - cell_dof_to_node = lazy_map(get_dof_to_node,CellData.get_data(cell_dofs)) - cell_dof_to_comp = lazy_map(get_dof_to_comp,CellData.get_data(cell_dofs)) - - cmaps = get_cell_map(trian) - cell_phys_nodes = lazy_map(evaluate,cmaps,cell_ref_nodes) - - node_coords = Vector{Float64}(undef,maximum(perm)) - cache_nodes = array_cache(cell_phys_nodes) - cache_ids = array_cache(cell_ids) - cache_dof_to_node = array_cache(cell_dof_to_node) - cache_dof_to_comp = array_cache(cell_dof_to_comp) - for cell in 1:num_cells(trian) - ids = getindex!(cache_ids,cell_ids,cell) - nodes = getindex!(cache_nodes,cell_phys_nodes,cell) - dof_to_comp = getindex!(cache_dof_to_comp,cell_dof_to_comp,cell) - dof_to_node = getindex!(cache_dof_to_node,cell_dof_to_node,cell) - for (dof,c,n) in zip(ids,dof_to_comp,dof_to_node) - if (dof > 0) && (perm[dof] > 0) - node_coords[perm[dof]] = nodes[n][c] - end - end - end - return node_coords -end - -function ReferenceFEs.get_dof_to_node(a::LagrangianDofBasis) - return a.dof_to_node -end -function ReferenceFEs.get_dof_to_comp(a::LagrangianDofBasis) - return a.dof_to_comp -end - -np = (2,1) -ranks = with_debug() do distribute - distribute(LinearIndices((prod(np),))) -end - -model = CartesianDiscreteModel(ranks,np,(0,1,0,1),(4,2)) -Dc = num_cell_dims(model) - -order = 3 -reffe = ReferenceFE(lagrangian,VectorValue{Dc,Float64},order) -space = FESpace(model,reffe) - -node_coords = get_dof_coordinates(space) diff --git a/Deprecated/permutation_tests.jl b/Deprecated/permutation_tests.jl deleted file mode 100644 index 7fbed8c4..00000000 --- a/Deprecated/permutation_tests.jl +++ /dev/null @@ -1,72 +0,0 @@ -using Gridap -using Gridap.Geometry, Gridap.FESpaces, Gridap.ReferenceFEs, Gridap.Helpers -using GridapDistributed, PartitionedArrays -using CircularArrays - -function create_dof_permutation(model::CartesianDiscreteModel{Dc}, - space::UnconstrainedFESpace, - order::Integer) where Dc - function get_terms(poly::Polytope, orders) - _nodes, facenodes = Gridap.ReferenceFEs._compute_nodes(poly, orders) - terms = Gridap.ReferenceFEs._coords_to_terms(_nodes, orders) - return terms - end - desc = get_cartesian_descriptor(model) - - periodic = desc.isperiodic - ncells = desc.partition - ndofs = order .* ncells .+ 1 .- periodic - @check prod(ndofs) == num_free_dofs(space) - - new_dof_ids = CircularArray(LinearIndices(ndofs)) - n2o_dof_map = fill(-1,num_free_dofs(space)) - - terms = get_terms(first(get_polytopes(model)), fill(order,Dc)) - cell_dof_ids = get_cell_dof_ids(space) - cache_cell_dof_ids = array_cache(cell_dof_ids) - for (iC,cell) in enumerate(CartesianIndices(ncells)) - first_new_dof = order .* (Tuple(cell) .- 1) .+ 1 - new_dofs_range = map(i -> i:i+order,first_new_dof) - new_dofs = view(new_dof_ids,new_dofs_range...) - - cell_dofs = getindex!(cache_cell_dof_ids,cell_dof_ids,iC) - for (iDof, dof) in enumerate(cell_dofs) - t = terms[iDof] - n2o_dof_map[new_dofs[t]] = dof - end - end - - return n2o_dof_map -end - -function create_dof_permutation(model::GridapDistributed.DistributedDiscreteModel, - space::GridapDistributed.DistributedFESpace, - order::Integer) where Dc - local_perms = map(local_views(model),local_views(space)) do model, space - create_dof_permutation(model,space,order) - end - return local_perms -end - -D = 2 -np = Tuple(fill(2,D)) - -ranks = with_debug() do distribute - distribute(LinearIndices((prod(np),))) -end - -nc = (D==2) ? (2,2) : (2,2,2) -domain = (D==2) ? (0,1,0,1) : (0,1,0,1,0,1) -#model = CartesianDiscreteModel(ranks,np,domain,nc) -model = CartesianDiscreteModel(domain,(4,3),isperiodic=(true,false)) - -order = 2 -poly = (D==2) ? QUAD : HEX -reffe = LagrangianRefFE(Float64,poly,order) -space = FESpace(model,reffe) - -perm_gids = create_dof_permutation(model,space,order) - -uh = interpolate(x->x[1]-x[2],space) -x = get_free_dof_values(uh) -x_perm = pfill(0.0,partition(perm_gids)); diff --git a/Deprecated/test_periodic_finitediff.jl b/Deprecated/test_periodic_finitediff.jl deleted file mode 100644 index 08d9b16a..00000000 --- a/Deprecated/test_periodic_finitediff.jl +++ /dev/null @@ -1,160 +0,0 @@ -using SparseMatricesCSR -using SparseArrays -using Gridap, Gridap.TensorValues, Gridap.Geometry -using GridapDistributed -using GridapPETSc -using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code -using PartitionedArrays -using DelimitedFiles -using LinearAlgebra -using Printf - -import GridapDistributed.DistributedCellField -import GridapDistributed.DistributedFESpace -import GridapDistributed.DistributedDiscreteModel -import GridapDistributed.DistributedMeasure - -include("Utilities.jl"); -include("LevelSet.jl"); -include("Setup.jl"); - -function setup_mock_2d() - ## FE setup name and objective - prob = mock_2d - obj = thermal_compliance - vf = 0.5; # Required volume fraction - ## Material and loading - D = 1.0 # Thermal coefficient - g = 1.0; # Heat flow - ## FE Parameters - fe_order = 1; - coord_max=(1.0,1.0); - el=(200,200); # Elements in axial directions - ## LS Paramters - lsf = gen_lsf(4,0.2); # Initial LSF - η_coeff = 2 # Interpolation radius coefficent - α_coeff = 4 # Hilbertian smoothing coefficent - μ=0.005 # Line search parameter - γ,γ_min,γ_max = [0.05,0.001,0.1] # CFL Coefficent - steps = Int(floor(minimum(el)/10)) # Finite diff. steps - reinit_tol = min(4*prod(inv,el),10^-4) # Reinit tol. - - return prob,obj,lsf,vf,D,g,fe_order,coord_max,el, - η_coeff,α_coeff,μ,γ_max,γ_min,γ,steps,reinit_tol -end - -function mock_2d(ranks,mesh_partition,order::T,coord_max::NTuple{2,M}, - el_size::NTuple{2,T},α::M,isperiodic) where {T<:Integer,M<:AbstractFloat} - ## Model - dom = (0,coord_max[1],0,coord_max[2]); - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(isperiodic,isperiodic)); - ## Triangulations and measures - Ω = Triangulation(model) - dΩ = Measure(Ω,2order) - ## Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;conformity=:H1) - U = TrialFESpace(V) - ## Assembler - Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv=Vector{PetscScalar} - assem=SparseMatrixAssembler(Tm,Tv,U,V) - # Space for shape sensitivities - V_L2 = TestFESpace(model,reffe;conformity=:L2) - # Space in Hilb. ext.-reg. endowed with H-regularity - V_reg = TestFESpace(model,reffe;conformity=:H1) - U_reg = TrialFESpace(V_reg) - # FE space for LSF - V_φ = TestFESpace(model,reffe;conformity=:H1) - ## Build stiffness matrix for Hilbertian ext-reg - A(u,v) = α^2*∫(∇(u) ⊙ ∇(v))dΩ + ∫(u ⋅ v)dΩ; - Hilb_assem=SparseMatrixAssembler(Tm,Tv,U_reg,V_reg) - K = assemble_matrix(A,Hilb_assem,U_reg,V_reg) - ## Collect data - solve_data = (U=U,V=V,assem=assem,V_L2=V_L2,dΩ=dΩ,dΓ_N=nothing) - hilb_data = (U_reg=U_reg,V_reg=V_reg,assem=Hilb_assem,dΩ=dΩ,K=K) - return model,Ω,V_φ,solve_data,hilb_data -end - -function setup_mock_3d() - ## FE setup name - prob = mock_3d - obj = thermal_compliance - vf = 0.5; # Required volume fraction - ## Material and loading - D = 1.0 # Thermal coefficient - g = 3.0 # Heat flow - ## FE Parameters - fe_order = 1; - coord_max=(1.0,1.0,1.0); - el=(100,100,100); # Elements in axial directions - ## LS Paramters - lsf = gen_lsf(4,0.2); # Initial LSF - η_coeff = 2 # Interpolation radius coefficent - α_coeff = 4 # Hilbertian smoothing coefficent - μ=0.005 # Line search parameter - γ,γ_min,γ_max = [0.1,0.001,0.1] # CFL Coefficent - steps = Int(floor(minimum(el)/3)); # Finite diff. steps - reinit_tol = min(1000*prod(inv,el),10^-3) # Reinit tol. - - return prob,obj,lsf,vf,D,g,fe_order,coord_max,el, - η_coeff,α_coeff,μ,γ_max,γ_min,γ,steps,reinit_tol -end - -function mock_3d(ranks,mesh_partition,order::T,coord_max::NTuple{3,M}, - el_size::NTuple{3,T},α::M,isperiodic) where {T<:Integer,M<:AbstractFloat} - ## Model - dom = (0,coord_max[1],0,coord_max[2],0,coord_max[3]); - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(isperiodic,isperiodic,isperiodic)); - ## Triangulations and measures - Ω = Triangulation(model) - dΩ = Measure(Ω,2order) - ## Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;conformity=:H1) - U = TrialFESpace(V) - ## Assembler - Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv=Vector{PetscScalar} - assem=SparseMatrixAssembler(Tm,Tv,U,V) - # Space for shape sensitivities - V_L2 = TestFESpace(model,reffe;conformity=:L2) - # Space in Hilb. ext.-reg. endowed with H-regularity - V_reg = TestFESpace(model,reffe;conformity=:H1) - U_reg = TrialFESpace(V_reg) - # FE space for LSF - V_φ = TestFESpace(model,reffe;conformity=:H1) - ## Build stiffness matrix for Hilbertian ext-reg - A(u,v) = α^2*∫(∇(u) ⊙ ∇(v))dΩ + ∫(u ⋅ v)dΩ; - Hilb_assem=SparseMatrixAssembler(Tm,Tv,U_reg,V_reg) - K = assemble_matrix(A,Hilb_assem,U_reg,V_reg) - ## Collect data - solve_data = (U=U,V=V,assem=assem,V_L2=V_L2,dΩ=dΩ,dΓ_N=nothing) - hilb_data = (U_reg=U_reg,V_reg=V_reg,assem=Hilb_assem,dΩ=dΩ,K=K) - return model,Ω,V_φ,solve_data,hilb_data -end - -mesh_partition = (3,3); -isperiodic = false; -prob_setup = setup_mock_2d; - -ranks = with_debug() do distribute - ranks = distribute(LinearIndices((prod(mesh_partition),))); -end - -prob,obj,lsf,vf,mat,g,fe_order,coord_max,el,η_coeff,α_coeff,_,_,_,γ,steps,reinit_tol = prob_setup() -Δ = coord_max./el # Element size -η = η_coeff*maximum(Δ); α = α_coeff*maximum(Δ) # Smoothing parameters -interp = SmoothErsatzMaterialInterpolation(η=η) # Material interpolation -model,Ω,V_φ,solve_data,hilb_data = prob(ranks,mesh_partition,fe_order,coord_max,el,α,isperiodic); - -φh = interpolate(lsf,V_φ) -φ = get_free_dof_values(φh) -reinit!(φ,model,Δ,0.5,2000,reinit_tol) - -vh = interpolate(x->1,V_φ) -v = get_free_dof_values(vh) -advect!(φ,v,model,Δ,γ,50) -reinit!(φ,model,Δ,0.5,2000,reinit_tol) - -writevtk(Ω,(@__DIR__)*"\\Results\\test_reinit_2d_plus_advect",cellfields=["phi"=>φh,"H(phi)"=>(interp.H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))]); diff --git a/Deprecated/tests.jl b/Deprecated/tests.jl deleted file mode 100644 index d0232114..00000000 --- a/Deprecated/tests.jl +++ /dev/null @@ -1,173 +0,0 @@ -using FillArrays - -using Gridap -using Gridap.Geometry, Gridap.Arrays -using Gridap.Geometry: get_faces - -using GridapDistributed, PartitionedArrays - -############################################################################################ - -function EdgeTriangulation(model::DiscreteModel{Dc}) where Dc - EdgeTriangulation(model,Base.OneTo(Geometry.num_faces(model,1))) -end - -function EdgeTriangulation(model::DiscreteModel{Dc},tags) where Dc - labeling = get_face_labeling(model) - face_to_mask = get_face_mask(labeling,tags,1) - face_to_bgface = findall(face_to_mask) - return EdgeTriangulation(model,face_to_bgface) -end - -function EdgeTriangulation( - model::DiscreteModel{Dc}, - face_to_bgface::AbstractVector{<:Integer}) where {Dc} - - topo = get_grid_topology(model) - bgface_grid = Grid(Geometry.ReferenceFE{1},model) - bgface_to_lcell = Fill(1,Geometry.num_faces(model,1)) - - face_grid = view(bgface_grid,face_to_bgface) - cell_grid = get_grid(model) - glue = Geometry.FaceToCellGlue(topo,cell_grid,face_grid,face_to_bgface,bgface_to_lcell) - trian = BodyFittedTriangulation(model,face_grid,face_to_bgface) - - BoundaryTriangulation(trian,glue) -end - -function EdgeTriangulation(model::GridapDistributed.DistributedDiscreteModel) - trians = map(EdgeTriangulation,local_views(model)) - return GridapDistributed.DistributedTriangulation(trians,model) -end - -function get_edge_coordinates(model::DiscreteModel) - topo = get_grid_topology(model) - get_edge_coordinates(topo) -end - -function get_edge_coordinates(topo::GridTopology) - e2n_map = Geometry.get_faces(topo,1,0) - node_coords = Geometry.get_vertex_coordinates(topo) - edge_coords = lazy_map(nodes->lazy_map(Reindex(node_coords),nodes),e2n_map) - return edge_coords -end - -function get_tangent_vector(trian::Triangulation{1}) - function my_tangent(m) - t = m(VectorValue(1.0)) - m(VectorValue(0.0)) - return t/norm(t) - end - cmaps = get_cell_map(trian) - return CellField(lazy_map(my_tangent,cmaps),trian) -end - -function get_tangent_vector(trian::GridapDistributed.DistributedTriangulation) - fields = map(get_tangent_vector,local_views(trian)) - GridapDistributed.DistributedCellField(fields) -end - -""" - `edge_orientation(edge_coords)` - - Returns: - 1 : if the edge is in the x-direction - 2 : if the edge is in the y-direction - 3 : if the edge is in the z-direction (only 3D) -""" -function edge_orientation(edge_coords) - v = edge_coords[1]-edge_coords[2] - return findfirst(x -> abs(x) > 1.e-3,v.data) -end - -""" - Returns a table that for each node contains the adjacent edge ids. - - If the edge is missing (for instance in boundaries), the corresponding entry is -1. - - For each node, the edges are ordered as follows: - [x-outgoing, x-incoming, y-outgoing, y-incoming, z-outgoing, z-incoming] -""" -function get_node_edge_nbors(model::DiscreteModel{Dc}) where Dc - num_edges_x_node = (Dc==2) ? 4 : 6 - ptrs = zeros(Int,num_faces(model,0)+1); ptrs[1] = 1; ptrs[2:end] .= num_edges_x_node; - Gridap.Algebra.length_to_ptrs!(ptrs) - - e2n_map = Geometry.get_faces(get_grid_topology(model),1,0) - orientations = lazy_map(edge_orientation,get_edge_coordinates(model)) - - data = fill(-1,ptrs[end]-1) - e2n_map_cache = array_cache(e2n_map) - orientations_cache = array_cache(orientations) - for E in 1:num_faces(model,1) - E_nodes = getindex!(e2n_map_cache,e2n_map,E) - E_orientation = getindex!(orientations_cache,orientations,E) - for (iN,N) in enumerate(E_nodes) - # Edge ordering in each node: - # [x-outgoing, x-incoming, y-outgoing, y-incoming, z-outgoing, z-incoming] - id = 2*(E_orientation-1) + iN - data[ptrs[N]+id-1] = E - end - end - return Table(data,ptrs) -end - -function get_node_edge_nbors(model::GridapDistributed.DistributedDiscreteModel) - return map(get_node_edge_nbors,local_views(model)) -end - -""" - Returns a table that for each node contains the directional derivatives in adjacent edges: - - If the edge is missing (for instance in boundaries), the corresponding entry is 0.0. - - For each node, the derivatives are ordered as follows: - [d/dx⁺, -d/dx⁻, d/dy⁺, -d/dy⁻, d/dz⁺, -d/dz] -""" -function evaluate_derivatives(φ::FEFunction,Λ::Triangulation,edge_nbors,t) - quad = CellQuadrature(Λ,0) - pts = get_cell_points(quad) - - vals = lazy_map(first,(∇(φ)⋅t)(pts)) - idx = lazy_map(PosNegReindex(vals,[0.0]),edge_nbors.data) - return Table(idx,edge_nbors.ptrs) -end - -function evaluate_derivatives(φ::GridapDistributed.DistributedCellField, - Λ::GridapDistributed.DistributedTriangulation, - edge_nbors, - t) - return map(evaluate_derivatives,local_views(φ),local_views(Λ),edge_nbors,local_views(t)) -end - -############################################################################################ - -parallel = true -D = 3 - -if D == 2 - np = (2,1) - domain = (0,1,0,1) - nc = (4,4) -else - np = (2,1,1) - domain = (0,1,0,1,0,1) - nc = (4,4,4) -end - -if parallel - ranks = with_debug() do distribute - distribute(LinearIndices((prod(np),))) - end - model = CartesianDiscreteModel(ranks,np,domain,nc) -else - model = CartesianDiscreteModel(domain,nc) -end - -Ω = Triangulation(model) -Λ = EdgeTriangulation(model) -t = get_tangent_vector(Λ) -edge_nbors = get_node_edge_nbors(model) - -reffe = ReferenceFE(lagrangian,Float64,1) -V = FESpace(model,reffe) - -x = !parallel ? randn(num_free_dofs(V)) : prandn(partition(get_free_dof_ids(V))) -u = FEFunction(V,x) - -derivatives = evaluate_derivatives(u,Λ,edge_nbors,t) diff --git a/Deprecated/tests2.jl b/Deprecated/tests2.jl deleted file mode 100644 index 3ee428d8..00000000 --- a/Deprecated/tests2.jl +++ /dev/null @@ -1,42 +0,0 @@ -using GridapDistributed -using Gridap -using PartitionedArrays -using Gridap.FESpaces - -np = (2,1) -ranks = with_debug() do distribute - distribute(LinearIndices((prod(np),))) -end -model = CartesianDiscreteModel(ranks,np,(0,1,0,1),(5,1);isperiodic=(true,false)) - -reffe = ReferenceFE(lagrangian,Float64,1) -V = FESpace(model,reffe) - -dim = 2 -trian = Triangulation(model) -coords = map(local_views(trian)) do trian - node_coords = Gridap.Geometry.get_node_coordinates(trian) - coords = Vector{Float64}(undef,dim*length(node_coords)) - k = 1 - for p in node_coords - for d in 1:dim - coords[k] = p[d] - k += 1 - end - end - return coords -end - -x_vals = map(local_to_global,partition(V.gids)) -x = PVector(x_vals,partition(V.gids)) - -local_sizes = DebugArray([(5,2),(6,2)]) -y_vals = map(local_values(x),local_sizes) do x,sz - reshape(circshift(reshape(x,sz),(-1,0)),prod(sz)) -end -y = PVector(y_vals,partition(V.gids)) - -partition(y) -consistent!(y) |> fetch -partition(y) - diff --git a/Deprecated/tests3.jl b/Deprecated/tests3.jl deleted file mode 100644 index e9a31c6f..00000000 --- a/Deprecated/tests3.jl +++ /dev/null @@ -1,43 +0,0 @@ - -using Gridap, GridapDistributed, PartitionedArrays -using Gridap.Geometry, Gridap.FESpaces, Gridap.ReferenceFEs, Gridap.Adaptivity - -function get_terms(poly::Polytope, orders) - _nodes, facenodes = Gridap.ReferenceFEs._compute_nodes(poly, orders) - terms = Gridap.ReferenceFEs._coords_to_terms(_nodes, orders) - return terms -end - -function get_dof_map(poly::Polytope, orders) - maps1D = map(ord -> map(t -> t[1], get_terms(SEGMENT, [ord])), orders) - terms = get_terms(poly, orders) - dofmap = map(t -> CartesianIndex(map((x, m) -> findfirst(mi -> mi == x, m), Tuple(t), maps1D)), terms) - return dofmap -end - -model = CartesianDiscreteModel((0,1,0,1),(4,4)) - -order = 2 -reffe = ReferenceFE(lagrangian,Float64,order) -V = FESpace(model,reffe) - -reffe2 = LagrangianRefFE(Float64,QUAD,(2,1)) - -cell_dof_ids = get_cell_dof_ids(V) -n2c_map = Geometry.get_faces(get_grid_topology(model),0,2) - -rr = RefinementRule(QUAD,(2,2)) -rr_grid = Adaptivity.get_ref_grid(rr) -node_ids = get_cell_node_ids(rr_grid) - - -terms = get_terms(QUAD,(2*order,2*order)) -lindices = LinearIndices((2*order+1,2*order+1)) - -dof_to_node_layout = map(t -> lindices[t],terms) -node_to_dof_layout = Vector{Int}(undef,length(dof_to_node_layout)) -for (dof,node) in enumerate(dof_to_node_layout) - node_to_dof_layout[node] = dof -end - -cell_dofs = map(nodes -> node_to_dof_layout[nodes],node_ids) diff --git a/Deprecated/tests4.jl b/Deprecated/tests4.jl deleted file mode 100644 index e6646b9f..00000000 --- a/Deprecated/tests4.jl +++ /dev/null @@ -1,203 +0,0 @@ - -using Gridap -using Gridap.Arrays -using BenchmarkTools - -struct Stencil{D,S,T} <: Map - Δ::NTuple{D,T} - function Stencil(D::Integer,S::Tuple,Δ::Tuple) - T = eltype(Δ) - new{D,S,T}(Δ) - end -end - -@generated function get_stencil_indexes(::Stencil{2,S}, idx) where {S} - ileft = "(idx-1) % $(S[1]) == 0 ? -1 : idx - 1" - iright = "(idx-1) % $(S[1]) == $(S[1]-1) ? -1 : idx + 1" - idown = "(idx-1) ÷ $(S[1]) == 0 ? -1 : idx - $(S[1])" - iup = "(idx-1) ÷ $(S[1]) == $(S[2]-1) ? - 1 : idx + $(S[1])" - return Meta.parse("return ($ileft, $iright, $idown, $iup)") -end - -@generated function compute_derivatives(s::Stencil{2,S},i,x) where S - im = "i - 1" - ip = "i + 1" - jm = "i - $(S[1])" - jp = "i + $(S[1])" - - dx⁻ = "(i-1) % $(S[1]) == 0 ? 0.0 : (x[i]-x[$im])/s.Δ[1]" - dx⁺ = "(i-1) % $(S[1]) == $(S[1]-1) ? 0.0 : (x[$ip]-x[i])/s.Δ[1]" - dy⁻ = "(i-1) ÷ $(S[1]) == 0 ? 0.0 : (x[i]-x[$jm])/s.Δ[2]" - dy⁺ = "(i-1) ÷ $(S[1]) == $(S[2]-1) ? 0.0 : (x[$jp]-x[i])/s.Δ[2]" - return Meta.parse("return ($dx⁻,$dx⁺,$dy⁻,$dy⁺)") -end - -@generated function compute_derivatives(::Stencil{3,S},i,x) where S - im = "i - 1" - ip = "i + 1" - jm = "i - $(S[1])" - jp = "i + $(S[1])" - km = "i - $(S[1])*$(S[2])" - kp = "i + $(S[1])*$(S[2])" - - dx⁻ = "(i-1) % $(S[1]) == 0 ? 0.0 : (x[i]-x[$im])/s.Δ[1]" - dx⁺ = "(i-1) % $(S[1]) == $(S[1]-1) ? 0.0 : (x[$ip]-x[i])/s.Δ[1]" - dy⁻ = "((i-1) ÷ $(S[1]) % $(S[2])) == 0 ? 0.0 : (x[i]-x[$jm])/s.Δ[2]" - dy⁺ = "((i-1) ÷ $(S[1]) % $(S[2])) == $(S[2]-1) ? 0.0 : (x[$jp]-x[i])/s.Δ[2]" - dz⁻ = "(i-1) ÷ $(S[1]*S[2]) == 0 ? 0.0 : (x[i]-x[$km])/s.Δ[3]" - dz⁺ = "(i-1) ÷ $(S[1]*S[2]) == $(S[3]-1) ? 0.0 : (x[$kp]-x[i])/s.Δ[3]" - return Meta.parse("return ($dx⁻,$dx⁺,$dy⁻,$dy⁺,$dz⁻,$dz⁺)") -end - -@generated function compute_derivatives(::Stencil{3,S},i,x,dx) where S - im = "i - 1" - ip = "i + 1" - jm = "i - $(S[1])" - jp = "i + $(S[1])" - km = "i - $(S[1])*$(S[2])" - kp = "i + $(S[1])*$(S[2])" - - body = "" - body *= "dx[1] = (i-1) % $(S[1]) == 0 ? 0.0 : (x[i]-x[$im])/s.Δ[1]; " - body *= "dx[2] = (i-1) % $(S[1]) == $(S[1]-1) ? 0.0 : (x[$ip]-x[i])/s.Δ[1]; " - body *= "dx[3] = ((i-1) ÷ $(S[1]) % $(S[2])) == 0 ? 0.0 : (x[i]-x[$jm])/s.Δ[2]; " - body *= "dx[4] = ((i-1) ÷ $(S[1]) % $(S[2])) == $(S[2]-1) ? 0.0 : (x[$jp]-x[i])/s.Δ[2]; " - body *= "dx[5] = (i-1) ÷ $(S[1]*S[2]) == 0 ? 0.0 : (x[i]-x[$km])/s.Δ[3]; " - body *= "dx[6] = (i-1) ÷ $(S[1]*S[2]) == $(S[3]-1) ? 0.0 : (x[$kp]-x[i])/s.Δ[3]; " - return Meta.parse("begin $body return dx end") -end - -macro index_to_tuple(idx, D1, D2, D3) - return esc(:( - ($idx - 1) % $D1 + 1, - (($idx - 1) ÷ $D1) % $D2 + 1, - ($idx - 1) ÷ ($D1 * $D2) + 1)) -end - -function reinit!(s::Stencil{2},φ_out,φ_in,S,Δt,caches) - D⁻ˣ,D⁺ˣ,D⁻ʸ,D⁺ʸ,∇⁺,∇⁻ = caches - for i in 1:length(φ_in) - D⁻ˣ[i],D⁺ˣ[i],D⁻ʸ[i],D⁺ʸ[i] = compute_derivatives(s,i,φ_in) - end - - ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2) - ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2) - φ_out .= @. φ_in - Δt*(max(S,0)*∇⁺ + min(S,0)*∇⁻ - S) - return φ_out -end - -function reinit!(s::Stencil{3},φ_out,φ_in,S,Δt,caches) - D⁻ˣ,D⁺ˣ,D⁻ʸ,D⁺ʸ,D⁻ᶻ,D⁺ᶻ,∇⁺,∇⁻ = caches - res = zeros(6) - for i in 1:length(φ_in) - compute_derivatives(s,i,φ_in,res) - D⁻ˣ[i],D⁺ˣ[i],D⁻ʸ[i],D⁺ʸ[i],D⁻ᶻ[i],D⁺ᶻ[i] = res[1], res[2], res[3], res[4], res[5], res[6] - end - - #∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2 + max(D⁻ᶻ,0)^2 + min(D⁺ᶻ,0)^2); - #∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2 + max(D⁺ᶻ,0)^2 + min(D⁻ᶻ,0)^2); - #φ_out .= @. φ_in - Δt*(max(S,0)*∇⁺ + min(S,0)*∇⁻ - S) - return φ_out -end - -function reinit_step!(φ::T,φ_tmp::T,S::T,g_loc::NTuple{4,Bool},Δ::NTuple{2,M},Δt::M,caches) where {M,T<:Array{M,2}} - (X⁻,X⁺,Y⁻,Y⁺) = g_loc - D⁻ˣ,D⁺ˣ,D⁻ʸ,D⁺ʸ,∇⁺,∇⁻ = caches - Δx,Δy = Δ - # Prepare shifted lsf - circshift!(D⁺ʸ,φ,(0,-1)); circshift!(D⁻ʸ,φ,(0,1)); - circshift!(D⁺ˣ,φ,(-1,0)); circshift!(D⁻ˣ,φ,(1,0)); - # Forward (+) & Backward (-) - D⁺ʸ .= @. (D⁺ʸ - φ)/Δy; - D⁺ˣ .= @. (D⁺ˣ - φ)/Δx; - D⁻ʸ .= @. (φ - D⁻ʸ)/Δy; - D⁻ˣ .= @. (φ - D⁻ˣ)/Δx; - # Check for boundaries with ghost nodes - (~Y⁺) ? D⁺ʸ[:,end] .= zero(M) : 0; - (~X⁺) ? D⁺ˣ[end,:] .= zero(M) : 0; - (~Y⁻) ? D⁻ʸ[:,1] .= zero(M) : 0; - (~X⁻) ? D⁻ˣ[1,:] .= zero(M) : 0; - # Operators - ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2); - ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2); - # Update - φ_tmp .= @. φ - Δt*(max(S,0)*∇⁺ + min(S,0)*∇⁻ - S); - return nothing -end - -function reinit_step!(φ::T,φ_tmp::T,S::T,g_loc::NTuple{6,Bool},Δ::NTuple{3,M},Δt::M,caches) where {M,T<:Array{M,3}} - (X⁻,X⁺,Y⁻,Y⁺,Z⁻,Z⁺) = g_loc - D⁻ˣ,D⁺ˣ,D⁻ʸ,D⁺ʸ,D⁻ᶻ,D⁺ᶻ,∇⁺,∇⁻ = caches - Δx,Δy,Δz = Δ - # Prepare shifted lsf - circshift!(D⁺ʸ,φ,(0,-1)); circshift!(D⁻ʸ,φ,(0,1)); - circshift!(D⁺ˣ,φ,(-1,0)); circshift!(D⁻ˣ,φ,(1,0)); - circshift!(D⁺ᶻ,φ,(0,0,-1)); circshift!(D⁻ᶻ,φ,(0,0,1)); - # Forward (+) & Backward (-) - D⁺ʸ .= (D⁺ʸ - φ)/Δy; - D⁺ˣ .= (D⁺ˣ - φ)/Δx; - D⁺ᶻ .= (D⁺ᶻ - φ)/Δz; - D⁻ʸ .= (φ - D⁻ʸ)/Δy; - D⁻ˣ .= (φ - D⁻ˣ)/Δx; - D⁻ᶻ .= (φ - D⁻ᶻ)/Δz; - # Check for boundaries with ghost nodes - (~Y⁺) ? D⁺ʸ[:,end,:] .= zero(M) : 0; - (~X⁺) ? D⁺ˣ[end,:,:] .= zero(M) : 0; - (~Z⁺) ? D⁺ᶻ[:,:,end] .= zero(M) : 0; - (~Y⁻) ? D⁻ʸ[:,1,:] .= zero(M) : 0; - (~X⁻) ? D⁻ˣ[1,:,:] .= zero(M) : 0; - (~Z⁻) ? D⁻ᶻ[:,:,1] .= zero(M) : 0; - # Operators - ∇⁺ .= @. sqrt(max(D⁻ʸ,0)^2 + min(D⁺ʸ,0)^2 + max(D⁻ˣ,0)^2 + min(D⁺ˣ,0)^2 + max(D⁻ᶻ,0)^2 + min(D⁺ᶻ,0)^2); - ∇⁻ .= @. sqrt(max(D⁺ʸ,0)^2 + min(D⁻ʸ,0)^2 + max(D⁺ˣ,0)^2 + min(D⁻ˣ,0)^2 + max(D⁺ᶻ,0)^2 + min(D⁻ᶻ,0)^2); - # Update - φ_tmp .= @. φ - Δt*(max(S,0)*∇⁺ + min(S,0)*∇⁻ - S); - return nothing -end - -# 2D -sz = (1000,1012); n = prod(sz) -s = Stencil(2,sz,(0.5,0.5)) - -x = randn(n) -vel = ones(n); vel[[1,3,6,8,12,14]] .= 0; - -y1 = zeros(n) -caches = zeros(n),zeros(n),zeros(n),zeros(n),zeros(n),zeros(n) -y1 = reinit!(s,y1,x,vel,0.1,caches) - -y2 = reshape(copy(x),sz) -y_tmp = reshape(zeros(n),sz) -caches2 = zeros(sz),zeros(sz),zeros(sz),zeros(sz),zeros(sz),zeros(sz) -reinit_step!(y2,y_tmp,reshape(vel,sz),(false,false,false,false),(0.5,0.5),0.1,caches2) -#y_tmp = reshape(y_tmp,n) -#y_tmp ≈ y1 - -vel2 = reshape(vel,sz); - -@benchmark reinit!(s,$y1,$x,$vel,0.1,$caches) -@benchmark reinit_step!($y2,$y_tmp,$vel2,(false,false,false,false),(0.5,0.5),0.1,$caches2) - -# 3D - -sz = (104,108,10); n = prod(sz) -s = Stencil(3,sz,(0.5,0.5,0.5)) - -x = randn(n) -vel = ones(n); vel[[1,3,6,8,12,14]] .= 0; - -y1 = zeros(n) -caches = zeros(n),zeros(n),zeros(n),zeros(n),zeros(n),zeros(n),zeros(n),zeros(n) -y1 = reinit!(s,y1,x,vel,0.1,caches) - -y2 = reshape(copy(x),sz) -y_tmp = reshape(zeros(n),sz) -caches2 = zeros(sz),zeros(sz),zeros(sz),zeros(sz),zeros(sz),zeros(sz),zeros(sz),zeros(sz) -reinit_step!(y2,y_tmp,reshape(vel,sz),(false,false,false,false,false,false),(0.5,0.5,0.5),0.1,caches2) -#y_tmp = reshape(y_tmp,n) -#y_tmp ≈ y1 - -vel2 = reshape(vel,sz) - -@benchmark reinit!($s,$y1,$x,$vel,0.1,$caches) -@benchmark reinit_step!($y2,$y_tmp,$vel2,(false,false,false,false,false,false),(0.5,0.5,0.5),0.1,$caches2) diff --git a/Deprecated/tests_solver.jl b/Deprecated/tests_solver.jl deleted file mode 100644 index f418acb3..00000000 --- a/Deprecated/tests_solver.jl +++ /dev/null @@ -1,128 +0,0 @@ -using Gridap, Gridap.TensorValues, Gridap.Geometry -using GridapDistributed -using GridapPETSc -using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code -using PartitionedArrays -using SparseMatricesCSR - -import GridapDistributed.DistributedCellField -import GridapDistributed.DistributedFESpace -import GridapDistributed.DistributedDiscreteModel -import GridapDistributed.DistributedMeasure -import GridapDistributed.DistributedTriangulation - -include("Utilities.jl"); # <- For some useful functions -include("src/Solvers.jl") - -function elastic_compliance(φh,g,C,solve_data,interp,t,solver) - I = interp.I; dΩ=solve_data.dΩ; dΓ_N=solve_data.dΓ_N; - ## Weak form - a(u,v) = ∫((I ∘ φh)*(C ⊙ ε(u) ⊙ ε(v)))dΩ - l(v) = ∫(v ⋅ g)dΓ_N - ## Solve finite element problem - tic!(t) - op = AffineFEOperator(a,l,solve_data.U,solve_data.V,solve_data.assem) - toc!(t,"Assembly time") - K = op.op.matrix; - ## Solve - tic!(t) - uh = solve(solver,op) - toc!(t,"Solve time") - u = correct_ghost_layout(uh,K.col_partition) - ## Compute J and v_J - J = dot(u,(K*u)) - tic!(t) - v_J = interpolate(-C ⊙ ε(uh) ⊙ ε(uh),solve_data.V_L2) - toc!(t,"Interpolate shape sensitivity") - return J,v_J,uh -end - -function fe_setup(ranks,mesh_partition,order::T,coord_max::NTuple{3,M}, - el_size::NTuple{3,T}) where {T<:Integer,M<:AbstractFloat} - ## Model - dom = (0,coord_max[1],0,coord_max[2],0,coord_max[3]); - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - ## Define Γ_N and Γ_D - xmax,ymax,zmax = coord_max - prop_Γ_N = 0.4 - f_Γ_D(x) = (x[1] ≈ 0.0) ? true : false; - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/4 - eps() <= x[2] <= - ymax/2+ymax*prop_Γ_N/4 + eps() && zmax/2-zmax*prop_Γ_N/4 - eps() <= x[3] - <= zmax/2+zmax*prop_Γ_N/4 + eps()) ? true : false; - update_labels!(1,model,f_Γ_D,coord_max,"Gamma_D") - update_labels!(2,model,f_Γ_N,coord_max,"Gamma_N") - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,[VectorValue(0.0,0.0,0.0)]) - ## Assembler - Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv=Vector{PetscScalar} - assem=SparseMatrixAssembler(Tm,Tv,U,V) - # Space for shape sensitivities - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V_L2 = TestFESpace(model,reffe_scalar;conformity=:L2) - # FE space for LSF - V_φ = TestFESpace(model,reffe_scalar;conformity=:H1) - ## Collect data - solve_data = (U=U,V=V,assem=assem,V_L2=V_L2,dΩ=dΩ,dΓ_N=dΓ_N) - return model,Ω,V_φ,solve_data -end - -function _isotropic_3d(E::M,nu::M) where M<:AbstractFloat - λ = E*nu/((1+nu)*(1-2nu)); μ = E/(2*(1+nu)) - C =[λ+2μ λ λ 0 0 0 - λ λ+2μ λ 0 0 0 - λ λ λ+2μ 0 0 0 - 0 0 0 μ 0 0 - 0 0 0 0 μ 0 - 0 0 0 0 0 μ]; - return SymFourthOrderTensorValue( - C[1,1], C[6,1], C[5,1], C[2,1], C[4,1], C[3,1], - C[1,6], C[6,6], C[5,6], C[2,6], C[4,6], C[3,6], - C[1,5], C[6,5], C[5,5], C[2,5], C[4,5], C[3,5], - C[1,2], C[6,2], C[5,2], C[2,2], C[4,2], C[3,2], - C[1,4], C[6,4], C[5,4], C[2,4], C[4,4], C[3,4], - C[1,3], C[6,3], C[5,3], C[2,3], C[4,3], C[3,3]) -end - -############################################################################################ - -function main(mesh_partition,distribute) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - options = " - -ksp_type cg -ksp_rtol 1.0e-12 -ksp_norm_type unpreconditioned - -pc_type gamg -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky - -ksp_converged_reason -ksp_error_if_not_converged true - " - el_size = (20,20,20) - coord_max = (2.,1.,1.) - order = 1; - Δ = coord_max./el_size; - path = (@__DIR__)*"/Results/LinearElastic3DSolverTesting"; - t = PTimer(ranks;verbose=true) - GridapPETSc.with(args=split(options)) do - model,Ω,V_φ,solve_data = fe_setup(ranks,mesh_partition,order,coord_max,el_size) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(Δ)) - C = _isotropic_3d(1.,0.3) - g = VectorValue(0.,0.,-1.0) - φh = interpolate(x->-sqrt((x[1]-0.5)^2+(x[2]-0.5)^2+(x[3]-0.5)^2)+0.25,V_φ) - - solver = ElasticitySolver(solve_data.V) - J,v_J,uh = elastic_compliance(φh,g,C,solve_data,interp,t,solver) - display("Objective = $J") - writevtk(Ω,path,cellfields=["phi"=>φh,"H(phi)"=>(interp.H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) - end - t -end - -t = with_mpi() do distribute - main((2,1,1),distribute) -end; -display(t) diff --git a/Deprecated/tests_solver2_mpi.jl b/Deprecated/tests_solver2_mpi.jl deleted file mode 100644 index 1589a392..00000000 --- a/Deprecated/tests_solver2_mpi.jl +++ /dev/null @@ -1,96 +0,0 @@ -using Gridap, Gridap.TensorValues, Gridap.Geometry, Gridap.ReferenceFEs -using GridapDistributed -using GridapPETSc -using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code -using PartitionedArrays -using SparseMatricesCSR -using MPI - -import GridapDistributed.DistributedCellField -import GridapDistributed.DistributedFESpace -import GridapDistributed.DistributedDiscreteModel -import GridapDistributed.DistributedMeasure -import GridapDistributed.DistributedTriangulation - -using LevelSetTopOpt - -function isotropic_3d(E::M,nu::M) where M<:AbstractFloat - λ = E*nu/((1+nu)*(1-2nu)); μ = E/(2*(1+nu)) - C =[λ+2μ λ λ 0 0 0 - λ λ+2μ λ 0 0 0 - λ λ λ+2μ 0 0 0 - 0 0 0 μ 0 0 - 0 0 0 0 μ 0 - 0 0 0 0 0 μ]; - return SymFourthOrderTensorValue( - C[1,1], C[6,1], C[5,1], C[2,1], C[4,1], C[3,1], - C[1,6], C[6,6], C[5,6], C[2,6], C[4,6], C[3,6], - C[1,5], C[6,5], C[5,5], C[2,5], C[4,5], C[3,5], - C[1,2], C[6,2], C[5,2], C[2,2], C[4,2], C[3,2], - C[1,4], C[6,4], C[5,4], C[2,4], C[4,4], C[3,4], - C[1,3], C[6,3], C[5,3], C[2,3], C[4,3], C[3,3]) -end - -function isotropic_2d(E::M,nu::M) where M<:AbstractFloat - λ = E*nu/((1+nu)*(1-nu)); μ = E/(2*(1+nu)) - C = [λ+2μ λ 0 - λ λ+2μ 0 - 0 0 μ]; - SymFourthOrderTensorValue(C[1,1],C[3,1],C[2,1],C[1,3], - C[3,3],C[2,3],C[1,2],C[3,2],C[2,2]) -end - -############################################################################################ - -function main(distribute,np,n,order) - D = length(np) - ranks = distribute(LinearIndices((prod(np),))) - - n_tags = (D==2) ? "tag_6" : "tag_22" - d_tags = (D==2) ? ["tag_5"] : ["tag_21"] - - nc = (D==2) ? (n,n) : (n,n,n) - domain = (D==2) ? (0,1,0,1) : (0,1,0,1,0,1) - model = CartesianDiscreteModel(ranks,np,domain,nc) - Ω = Triangulation(model) - Γ = Boundary(model,tags=n_tags) - - poly = (D==2) ? QUAD : HEX - reffe = LagrangianRefFE(VectorValue{D,Float64},poly,order) - V = TestFESpace(model,reffe;dirichlet_tags="boundary") - U = TrialFESpace(V) - assem = SparseMatrixAssembler(SparseMatrixCSR{0,PetscScalar,PetscInt},Vector{PetscScalar},U,V,FullyAssembledRows()) - - dΩ = Measure(Ω,2*order) - dΓ = Measure(Γ,2*order) - C = (D == 2) ? isotropic_2d(1.,0.3) : isotropic_3d(1.,0.3) - g = (D == 2) ? VectorValue(0.0,1.0) : VectorValue(1.0,1.0,1.0) - a(u,v) = ∫((C ⊙ ε(u) ⊙ ε(v)))dΩ - l(v) = ∫(v ⋅ g)dΓ - - op = AffineFEOperator(a,l,U,V,assem) - A, b = get_matrix(op), get_vector(op); - - options = " - -ksp_type gmres -ksp_rtol 1.0e-12 -ksp_max_it 200 - -pc_type gamg - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg - -ksp_converged_reason -ksp_error_if_not_converged true -ksp_monitor_short - -mat_use - " - GridapPETSc.with(args=split(options)) do - solver = ElasticitySolver(V;rtol=1.e-12,maxits=500) - ss = symbolic_setup(solver,A) - ns = numerical_setup(ss,A) - - x = pfill(PetscScalar(0.0),partition(axes(A,2))) - solve!(x,ns,b) - end -end - -with_mpi() do distribute - np = (2,2) - n = 100 - order = 1 - main(distribute,np,n,order) -end \ No newline at end of file diff --git a/Deprecated/tests_solvers2.jl b/Deprecated/tests_solvers2.jl deleted file mode 100644 index f6c872c2..00000000 --- a/Deprecated/tests_solvers2.jl +++ /dev/null @@ -1,150 +0,0 @@ -using Gridap, Gridap.TensorValues, Gridap.Geometry, Gridap.ReferenceFEs -using GridapDistributed -using GridapPETSc -using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code -using PartitionedArrays -using SparseMatricesCSR -using MPI - -import GridapDistributed.DistributedCellField -import GridapDistributed.DistributedFESpace -import GridapDistributed.DistributedDiscreteModel -import GridapDistributed.DistributedMeasure -import GridapDistributed.DistributedTriangulation - -function isotropic_3d(E::M,nu::M) where M<:AbstractFloat - λ = E*nu/((1+nu)*(1-2nu)); μ = E/(2*(1+nu)) - C =[λ+2μ λ λ 0 0 0 - λ λ+2μ λ 0 0 0 - λ λ λ+2μ 0 0 0 - 0 0 0 μ 0 0 - 0 0 0 0 μ 0 - 0 0 0 0 0 μ]; - return SymFourthOrderTensorValue( - C[1,1], C[6,1], C[5,1], C[2,1], C[4,1], C[3,1], - C[1,6], C[6,6], C[5,6], C[2,6], C[4,6], C[3,6], - C[1,5], C[6,5], C[5,5], C[2,5], C[4,5], C[3,5], - C[1,2], C[6,2], C[5,2], C[2,2], C[4,2], C[3,2], - C[1,4], C[6,4], C[5,4], C[2,4], C[4,4], C[3,4], - C[1,3], C[6,3], C[5,3], C[2,3], C[4,3], C[3,3]) -end - -function isotropic_2d(E::M,nu::M) where M<:AbstractFloat - λ = E*nu/((1+nu)*(1-nu)); μ = E/(2*(1+nu)) - C = [λ+2μ λ 0 - λ λ+2μ 0 - 0 0 μ]; - SymFourthOrderTensorValue(C[1,1],C[3,1],C[2,1],C[1,3], - C[3,3],C[2,3],C[1,2],C[3,2],C[2,2]) -end - -############################################################################################ - -function ksp_setup(ksp) - rtol = PetscScalar(1.e-12) - atol = GridapPETSc.PETSC.PETSC_DEFAULT - dtol = GridapPETSc.PETSC.PETSC_DEFAULT - maxits = GridapPETSc.PETSC.PETSC_DEFAULT - - @check_error_code GridapPETSc.PETSC.KSPView(ksp[],C_NULL) - @check_error_code GridapPETSc.PETSC.KSPSetType(ksp[],GridapPETSc.PETSC.KSPCG) - @check_error_code GridapPETSc.PETSC.KSPSetTolerances(ksp[], rtol, atol, dtol, maxits) - - pc = Ref{GridapPETSc.PETSC.PC}() - @check_error_code GridapPETSc.PETSC.KSPGetPC(ksp[],pc) - @check_error_code GridapPETSc.PETSC.PCSetType(pc[],GridapPETSc.PETSC.PCGAMG) -end - -function get_coords(trian::DistributedTriangulation{Dc},V) where Dc - coords = map(local_views(trian),local_views(V),partition(V.gids)) do trian, V, dof_indices - node_coords = Gridap.Geometry.get_node_coordinates(trian) - dof_to_node = V.metadata.free_dof_to_node - dof_to_comp = V.metadata.free_dof_to_comp - - o2l_dofs = own_to_local(dof_indices) - coords = Vector{PetscScalar}(undef,length(o2l_dofs)) - for (i,dof) in enumerate(o2l_dofs) - node = dof_to_node[dof] - comp = dof_to_comp[dof] - coords[i] = node_coords[node][comp] - end - return coords - end - return Dc, coords -end - -function my_numerical_setup(ss::GridapPETSc.PETScLinearSolverSS,A::AbstractMatrix,coords,dim) - pcoords = convert(PETScVector,coords) - @check_error_code GridapPETSc.PETSC.VecSetBlockSize(pcoords.vec[],dim) - - B = convert(PETScMatrix,A) - null = Ref{GridapPETSc.PETSC.MatNullSpace}() - #@check_error_code GridapPETSc.PETSC.MatSetBlockSize(B.mat[],dim) - @check_error_code GridapPETSc.PETSC.MatNullSpaceCreateRigidBody(pcoords.vec[],null) - @check_error_code GridapPETSc.PETSC.MatSetNearNullSpace(B.mat[],null[]) - - ns = GridapPETSc.PETScLinearSolverNS(A,B) - @check_error_code GridapPETSc.PETSC.KSPCreate(B.comm,ns.ksp) - @check_error_code GridapPETSc.PETSC.KSPSetOperators(ns.ksp[],ns.B.mat[],ns.B.mat[]) - ss.solver.setup(ns.ksp) - @check_error_code GridapPETSc.PETSC.KSPSetUp(ns.ksp[]) - GridapPETSc.Init(ns) -end - -############################################################################################ -D = 3 -order = 1 -n = 20 - -np_x_dim = 1 -np = Tuple(fill(np_x_dim,D)) #Tuple([fill(np_x_dim,D-1)...,1]) -ranks = with_debug() do distribute - distribute(LinearIndices((prod(np),))) -end - -n_tags = (D==2) ? "tag_6" : "tag_22" -d_tags = (D==2) ? ["tag_5"] : ["tag_21"] - -nc = (D==2) ? (n,n) : (n,n,n) -domain = (D==2) ? (0,1,0,1) : (0,1,0,1,0,1) -model = CartesianDiscreteModel(domain,nc) -Ω = Triangulation(model) -Γ = Boundary(model,tags=n_tags) -ΓD = Boundary(model,tags=d_tags) - -poly = (D==2) ? QUAD : HEX -reffe = LagrangianRefFE(VectorValue{D,Float64},poly,order) -V = TestFESpace(model,reffe;dirichlet_tags=d_tags) -U = TrialFESpace(V) -assem = SparseMatrixAssembler(SparseMatrixCSR{0,PetscScalar,PetscInt},Vector{PetscScalar},U,V)#,FullyAssembledRows()) - -dΩ = Measure(Ω,2*order) -dΓ = Measure(Γ,2*order) -C = (D == 2) ? isotropic_2d(1.,0.3) : isotropic_3d(1.,0.3) -g = (D == 2) ? VectorValue(0.0,1.0) : VectorValue(0.0,0.0,1.0) -a(u,v) = ∫((C ⊙ ε(u) ⊙ ε(v)))dΩ -l(v) = ∫(v ⋅ g)dΓ - -op = AffineFEOperator(a,l,U,V,assem) -A, b = get_matrix(op), get_vector(op); - -dim, coords = get_coords(Ω,V); -pcoords = PVector(coords,partition(axes(A,1))) - -#pcoords = pfill(0.0,partition(axes(A,2))) -#copy!(pcoords,_pcoords) -#consistent!(pcoords) |> fetch - -options = " - -ksp_type cg -ksp_rtol 1.0e-12 - -pc_type gamg -mat_block_size $D - -ksp_converged_reason -ksp_error_if_not_converged true - " -GridapPETSc.with(args=split(options)) do - solver = PETScLinearSolver(ksp_setup) - ss = symbolic_setup(solver,A) - ns = my_numerical_setup(ss,A,pcoords,dim) - - x = pfill(PetscScalar(1.0),partition(axes(A,2))) - solve!(x,ns,b) -end diff --git a/README.md b/README.md index 8fa50d55..f49144ea 100755 --- a/README.md +++ b/README.md @@ -4,9 +4,12 @@ LevelSetTopOpt is computational toolbox for level set-based topology optimisation implemented in Julia and the [Gridap](https://github.com/gridap/Gridap.jl) package ecosystem. See the documentation and following publication for further details: -> Zachary J. Wegert, Jordi Manyer, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. +> Zachary J. Wegert, Jordi Manyer, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable Julia toolbox for level set-based topology optimisation". In preparation. ## Documentation - [**STABLE**](...) — **Documentation for the most recently tagged version.** -- [**LATEST**](...) — *Documentation for the in-development version.* \ No newline at end of file +- [**LATEST**](...) — *Documentation for the in-development version.* + +## Citation +In order to give credit to the `LevelSetTopOpt` contributors, we ask that you please reference the above paper along with the required citations for [Gridap](https://github.com/gridap/Gridap.jl?tab=readme-ov-file#how-to-cite-gridap). \ No newline at end of file diff --git a/results/.gitignore b/results/.gitignore deleted file mode 100644 index c96a04f0..00000000 --- a/results/.gitignore +++ /dev/null @@ -1,2 +0,0 @@ -* -!.gitignore \ No newline at end of file diff --git a/scripts/Benchmarks/benchmark.jl b/scripts/Benchmarks/benchmark.jl index cd4126b4..c3dc701c 100644 --- a/scripts/Benchmarks/benchmark.jl +++ b/scripts/Benchmarks/benchmark.jl @@ -11,11 +11,13 @@ global NAME = ARGS[1] global WRITE_DIR = ARGS[2] global PROB_TYPE = ARGS[3] global BMARK_TYPE = ARGS[4] -global N = parse(Int,ARGS[5]) -global N_EL = parse(Int,ARGS[6]) -global ORDER = parse(Int,ARGS[7]) -global VERBOSE = parse(Int,ARGS[8]) -global NREPS = parse(Int,ARGS[9]) +global Nx = parse(Int,ARGS[5]) +global Ny = parse(Int,ARGS[6]) +global Nz = parse(Int,ARGS[7]) +global N_EL = parse(Int,ARGS[8]) +global ORDER = parse(Int,ARGS[9]) +global VERBOSE = parse(Int,ARGS[10]) +global NREPS = parse(Int,ARGS[11]) function nl_elast(mesh_partition,ranks,el_size,order,verbose) # FE parameters @@ -360,7 +362,7 @@ end with_mpi() do distribute # Setup - mesh_partition = (N,N,N) + mesh_partition = (Nx,Ny,Nz) ranks = distribute(LinearIndices((prod(mesh_partition),))) el_size = (N_EL,N_EL,N_EL) verbose = Bool(VERBOSE) ? i_am_main(ranks) : false; diff --git a/scripts/Benchmarks/benchmark_gadi.jl b/scripts/Benchmarks/benchmark_gadi.jl deleted file mode 100644 index c3dc701c..00000000 --- a/scripts/Benchmarks/benchmark_gadi.jl +++ /dev/null @@ -1,460 +0,0 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR - -using LevelSetTopOpt: get_deriv_space, get_aux_space,benchmark_optimizer, - benchmark_forward_problem,benchmark_advection,benchmark_reinitialisation, - benchmark_velocity_extension,benchmark_hilbertian_projection_map,benchmark_single_iteration - -using GridapSolvers: NewtonSolver - -global NAME = ARGS[1] -global WRITE_DIR = ARGS[2] -global PROB_TYPE = ARGS[3] -global BMARK_TYPE = ARGS[4] -global Nx = parse(Int,ARGS[5]) -global Ny = parse(Int,ARGS[6]) -global Nz = parse(Int,ARGS[7]) -global N_EL = parse(Int,ARGS[8]) -global ORDER = parse(Int,ARGS[9]) -global VERBOSE = parse(Int,ARGS[10]) -global NREPS = parse(Int,ARGS[11]) - -function nl_elast(mesh_partition,ranks,el_size,order,verbose) - # FE parameters - xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size - dom = (0,xmax,0,ymax,0,zmax) # Bounding domain - prop_Γ_N = 0.2 # Γ_N size parameter - f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function - (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0) # Γ_D indicator function - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance - # Problem parameters - E = 1000 # Young's modulus - ν = 0.3 # Poisson's ratio - μ, λ = E/(2*(1 + ν)), E*ν/((1 + ν)*(1 - 2*ν)) # Lame constants - g = VectorValue(0,0,-1) # Applied load on Γ_N - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - # Model - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - ## Piola-Kirchhoff tensor - function S(∇u) - Cinv = inv(C(F(∇u))) - μ*(one(∇u)-Cinv) + λ*log(J(F(∇u)))*Cinv - end - ## Derivative of Green strain - dE(∇du,∇u) = 0.5*( ∇du⋅F(∇u) + (∇du⋅F(∇u))' ) - ## Right Cauchy-Green deformation tensor - C(F) = (F')⋅F - ## Deformation gradient tensor - F(∇u) = one(∇u) + ∇u' - ## Volume change - J(F) = sqrt(det(C(F))) - ## Residual - res(u,v,φ,dΩ,dΓ_N) = ∫( (I ∘ φ)*((dE ∘ (∇(v),∇(u))) ⊙ (S ∘ ∇(u))) )*dΩ - ∫(g⋅v)dΓ_N - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - lin_solver = ElasticitySolver(V) - nl_solver = NewtonSolver(lin_solver;maxiter=50,rtol=10^-8,verbose) - state_map = NonlinearFEStateMap( - res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - nls = nl_solver, adjoint_ls = lin_solver - ) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*((dE ∘ (∇(u),∇(u))) ⊙ (S ∘ ∇(u))))dΩ - vol_D = sum(∫(1)dΩ) - C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C1],state_map,analytic_dC=[dC1]) - # Velocity extension - α = 4max_steps*γ*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = PETScLinearSolver() - ) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose) -end - -function therm(mesh_partition,ranks,el_size,order,verbose) - # FE parameters - xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size - dom = (0,xmax,0,ymax,0,zmax) # Bounding domain - prop_Γ_N = 0.2 # Γ_N size parameter - prop_Γ_D = 0.2 # Γ_D size parameter - f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function - (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps()) && - (x[3] <= zmax*prop_Γ_D + eps() || x[3] >= zmax-zmax*prop_Γ_D - eps()) - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance - # Problem parameters - κ = 1 # Diffusivity - g = 1 # Heat flow in - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - # Model - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe) - V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - solver = PETScLinearSolver() - state_map = AffineFEStateMap( - a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver,adjoint_ls = solver - ) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - vol_D = sum(∫(1)dΩ) - C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C1],state_map, - analytic_dJ=dJ,analytic_dC=[dC1]) - # Velocity extension - α = 4max_steps*γ*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = solver - ) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose) -end - -function elast(mesh_partition,ranks,el_size,order,verbose) - # FE parameters - xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size - dom = (0,xmax,0,ymax,0,zmax) # Bounding domain - prop_Γ_N = 0.2 # Γ_N size parameter - f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function - (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0) # Γ_D indicator function - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance - # Problem parameters - C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor - g = VectorValue(0,0,-1) # Applied load on Γ_N - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - # Model - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(v⋅g)dΓ_N - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - solver = ElasticitySolver(V) - state_map = AffineFEStateMap( - a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver,adjoint_ls = solver - ) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(u)))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫((C ⊙ ε(u) ⊙ ε(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - vol_D = sum(∫(1)dΩ) - C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C1],state_map, - analytic_dJ=dJ,analytic_dC=[dC1]) - # Velocity extension - α = 4max_steps*γ*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = PETScLinearSolver() - ) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose) -end - -function inverter_HPM(mesh_partition,ranks,el_size,order,verbose) - ## Parameters - dom = (0,1,0,1,0,1) - γ = 0.05 - γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/3) - tol = 1/(2order^2)/minimum(el_size) - C = isotropic_elast_tensor(3,1.0,0.3) - η_coeff = 2 - α_coeff = 4 - vf=0.4 - δₓ=0.5 - ks = 0.01 - g = VectorValue(1,0,0) - - ## FE Setup - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - el_Δ = get_el_Δ(model) - f_Γ_in(x) = (x[1] ≈ 0.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && - (0.4 - eps() <= x[3] <= 0.6 + eps()) - f_Γ_out(x) = (x[1] ≈ 1.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && - (0.4 - eps() <= x[3] <= 0.6 + eps()) - f_Γ_out_ext(x) = ~f_Γ_out(x) && (0.9 <= x[1] <= 1.0) && (0.3 - eps() <= x[2] <= 0.7 + eps()) && - (0.3 - eps() <= x[3] <= 0.7 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0) && (x[2] <= 0.1 || x[2] >= 0.9) && (x[3] <= 0.1 || x[3] >= 0.9) - update_labels!(1,model,f_Γ_in,"Gamma_in") - update_labels!(2,model,f_Γ_out,"Gamma_out") - update_labels!(3,model,f_Γ_out_ext,"Gamma_out_ext") - update_labels!(4,model,f_Γ_D,"Gamma_D") - - ## Triangulations and measures - Ω = Triangulation(model) - Γ_in = BoundaryTriangulation(model,tags="Gamma_in") - Γ_out = BoundaryTriangulation(model,tags="Gamma_out") - dΩ = Measure(Ω,2*order) - dΓ_in = Measure(Γ_in,2*order) - dΓ_out = Measure(Γ_out,2*order) - vol_D = sum(∫(1)dΩ) - vol_Γ_in = sum(∫(1)dΓ_in) - vol_Γ_out = sum(∫(1)dΓ_out) - - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_in","Gamma_out","Gamma_out_ext"]) - U_reg = TrialFESpace(V_reg,[0,0,0]) - - ## Create FE functions - φh = interpolate(initial_lsf(4,0.1),V_φ); - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - a(u,v,φ,dΩ,dΓ_in,dΓ_out) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ + ∫(ks*(u⋅v))dΓ_out - l(v,φ,dΩ,dΓ_in,dΓ_out) = ∫(v⋅g)dΓ_in - - ## Optimisation functionals - e₁ = VectorValue(1,0,0) - J(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅e₁)/vol_Γ_in)dΓ_in - Vol(u,φ,dΩ,dΓ_in,dΓ_out) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; - dVol(q,u,φ,dΩ,dΓ_in,dΓ_out) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - UΓ_out(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out - - ## Finite difference solver - ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) - - ## Setup solver and FE operators - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - solver = ElasticitySolver(V) - - state_map = AffineFEStateMap( - a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver, adjoint_ls = solver - ) - pcfs = PDEConstrainedFunctionals(J,[Vol,UΓ_out],state_map,analytic_dC=[dVol,nothing]) - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(el_Δ) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; - vel_ext = VelocityExtension( - a_hilb,U_reg,V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = PETScLinearSolver() - ) - - ## Optimiser - return HilbertianProjection(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=verbose) -end - -with_mpi() do distribute - # Setup - mesh_partition = (Nx,Ny,Nz) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - el_size = (N_EL,N_EL,N_EL) - verbose = Bool(VERBOSE) ? i_am_main(ranks) : false; - if PROB_TYPE == "NLELAST" - options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - opt = nl_elast - elseif PROB_TYPE == "THERM" - options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - opt = therm - elseif PROB_TYPE == "ELAST" - options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - opt = elast - elseif PROB_TYPE == "INVERTER_HPM" - options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - opt = inverter_HPM - else - error("Problem not defined") - end - - # Output - i_am_main(ranks) && ~isdir(WRITE_DIR) && mkpath(WRITE_DIR) - # Run - t_start = PTimer(ranks); - GridapPETSc.with(args=split(options)) do - tic!(t_start;barrier=true) - optim = opt(mesh_partition,ranks,el_size,ORDER,verbose) - toc!(t_start,"startup") - startup_time = map_main(t_start.data) do data - map(x -> x.max,values(data)) - end |> PartitionedArrays.getany - bstart = i_am_main(ranks) && [startup_time; zeros(NREPS-1)] - ## Benchmark optimiser - if occursin("bopt0",BMARK_TYPE) - bopt0 = benchmark_optimizer(optim, 0, ranks; nreps=NREPS) - else - bopt0 = i_am_main(ranks) && zeros(NREPS) - end - if occursin("bopt1",BMARK_TYPE) - bopt1 = benchmark_single_iteration(optim, ranks; nreps = NREPS) - else - bopt1 = i_am_main(ranks) && zeros(NREPS) - end - ## Benchmark reinitialisation - if occursin("breinit",BMARK_TYPE) - breinit = benchmark_reinitialisation(optim.ls_evolver, get_free_dof_values(optim.φ0), 0.1, ranks; nreps=NREPS) - else - breinit = i_am_main(ranks) && zeros(NREPS) - end - ## Benchmark forward problem - if occursin("bfwd",BMARK_TYPE) - bfwd = benchmark_forward_problem(optim.problem.state_map, optim.φ0, ranks; nreps=NREPS) - else - bfwd = i_am_main(ranks) && zeros(NREPS) - end - ## Benchmark advection - reinit!(optim.ls_evolver,optim.φ0,optim.params.γ_reinit) - if occursin("badv",BMARK_TYPE) - vh = interpolate(FEFunction(get_deriv_space(optim.problem.state_map),optim.problem.dJ), - get_aux_space(optim.problem.state_map)) - v = get_free_dof_values(vh) - badv = benchmark_advection(optim.ls_evolver, get_free_dof_values(optim.φ0), v, 0.1, ranks; nreps=NREPS) - else - badv = i_am_main(ranks) && zeros(NREPS) - end - ## Benchmark velocity extension - if occursin("bvelext",BMARK_TYPE) - bvelext = benchmark_velocity_extension(optim.vel_ext, optim.problem.dJ, ranks; nreps=NREPS) - else - bvelext = i_am_main(ranks) && zeros(NREPS) - end - ## HPM - if occursin("bhpm",BMARK_TYPE) - @assert typeof(optim) <: HilbertianProjection - J, C, dJ, dC = Gridap.evaluate!(optim.problem,optim.φ0) - optim.projector,dJ,C,dC,optim.vel_ext.K - bhpm = benchmark_hilbertian_projection_map(optim.projector,dJ,C,dC,optim.vel_ext.K,ranks) - else - bhpm = i_am_main(ranks) && zeros(NREPS) - end - ## Write results - if i_am_main(ranks) - open(WRITE_DIR*NAME*".txt","w") do f - bcontent = "startup,bopt(0),bopt(1),bfwd,badv,breinit,bvelext,bhpm\n" - for i = 1:NREPS - bcontent *= "$(bstart[i]),$(bopt0[i]),$(bopt1[i]),$(bfwd[i]),$(badv[i]),$(breinit[i]),$(bvelext[i]),$(bhpm[i])\n" - end - write(f,bcontent) - end - end - end -end \ No newline at end of file diff --git a/scripts/Benchmarks/generate_benchmark_scripts.jl b/scripts/Benchmarks/generate_benchmark_scripts.jl index 4ad06b06..f142b86b 100644 --- a/scripts/Benchmarks/generate_benchmark_scripts.jl +++ b/scripts/Benchmarks/generate_benchmark_scripts.jl @@ -2,6 +2,21 @@ using Pkg Pkg.activate() using Mustache +# These are generated by solving +# Minimise X + Y + Z s.t. X*Y*Z=i*48 for X,Y,Z∈ℤ⁺ (See bottom) +mesh_partitions = [(4, 4, 3),(4, 4, 6),(4, 6, 6),(4, 6, 8),(5, 6, 8),(6, 6, 8),(7, 6, 8),(6, 8, 8),(6, 9, 8),(10, 6, 8), + (11, 6, 8),(9, 8, 8),(13, 6, 8),(12, 7, 8),(10, 9, 8),(12, 8, 8),(6, 8, 17),(12, 9, 8),(6, 8, 19), + (10, 12, 8),(14, 9, 8),(11, 12, 8),(6, 8, 23),(12, 12, 8),(10, 10, 12),(13, 12, 8),(12, 12, 9),(12, 14, 8), + (6, 8, 29),(10, 12, 12),(6, 8, 31),(8, 12, 16),(11, 12, 12),(8, 12, 17),(10, 12, 14),(12, 12, 12),(6, 8, 37), + (8, 12, 19),(13, 12, 12),(10, 12, 16),(6, 8, 41),(12, 12, 14),(6, 8, 43),(11, 12, 16),(12, 12, 15),(8, 12, 23), + (6, 8, 47),(12, 12, 16),(12, 14, 14),(10, 15, 16),(12, 12, 17),(12, 13, 16),(6, 8, 53),(12, 12, 18),(11, 15, 16), + (12, 14, 16),(12, 12, 19),(8, 12, 29),(6, 8, 59),(12, 15, 16),(6, 8, 61),(8, 12, 31),(12, 14, 18),(12, 16, 16), + (13, 15, 16),(11, 16, 18),(6, 8, 67),(12, 16, 17),(12, 12, 23),(14, 15, 16),(6, 8, 71),(12, 16, 18),(6, 8, 73), + (8, 12, 37),(15, 15, 16),(12, 16, 19),(11, 16, 21),(13, 16, 18),(6, 8, 79),(15, 16, 16),(12, 18, 18),(8, 12, 41), + (6, 8, 83),(14, 16, 18),(15, 16, 17),(8, 12, 43),(12, 12, 29),(12, 16, 22),(6, 8, 89),(15, 16, 18)] + +@assert Int.(prod.(mesh_partitions)/48) == collect(1:length(mesh_partitions)) + function generate( template, name, @@ -9,7 +24,7 @@ function generate( bmark_type, cputype, wallhr, - n_mesh_partition, + mesh_partition, n_el_size, fe_order, verbose, @@ -18,53 +33,58 @@ function generate( nreps ) - ncpus = n_mesh_partition^3 - wallhr = occursin("STRONG",name) && n_mesh_partition <= 3 ? 100 : wallhr - mem = occursin("STRONG",name) && n_mesh_partition == 1 ? 256 : - occursin("STRONG",name) && n_mesh_partition == 2 ? 32 : gb_per_cpu; + ncpus = prod(mesh_partition) + wallhr = occursin("STRONG",name) && ncpus == 1 ? 100 : + occursin("STRONG",name) && ncpus == 8 ? 24 : + occursin("STRONG",name) && ncpus == 27 ? 10 : wallhr + mem = occursin("STRONG",name) && ncpus == 1 ? 100 : + occursin("STRONG",name) && ncpus == 8 ? 128 : + occursin("STRONG",name) && ncpus == 27 ? 192 : Int(gb_per_node*ncpus/cps_per_node); + Nx_partition, Ny_partition, Nz_partition = mesh_partition settings = (;name,type,bmark_type,cputype,wallhr,ncpus,mem, - n_mesh_partition,n_el_size,fe_order,verbose,dir_name,write_dir,nreps) + Nx_partition,Ny_partition,Nz_partition,n_el_size,fe_order,verbose,dir_name,write_dir,nreps) Mustache.render(template, settings) end function generate_jobs(template,phys_type,ndof_per_node,bmark_types) - npart = (N).^3; + npart = prod.(parts) weak_el_x = @. floor(Int,(dofs_per_proc*npart/ndof_per_node)^(1/3)-1); dof_sanity_check = @.(floor(Int,ndof_per_node*(weak_el_x+1)^3/npart)), maximum(abs,@. ndof_per_node*(weak_el_x+1)^3/npart/dofs_per_proc - 1) - sname(phys_type,ndof_per_node,n,elx) = "STRONG_$(phys_type)_dof$(ndof_per_node)_N$(n)_elx$(elx)" - wname(phys_type,ndof_per_node,n,elx) = "WEAK_$(phys_type)_dof$(ndof_per_node)_N$(n)_elx$(elx)" + sname(phys_type,ndof_per_node,n,elx) = "STRONG_$(phys_type)_dof$(ndof_per_node)_N$(prod(n))_elx$(elx)" + wname(phys_type,ndof_per_node,n,elx) = "WEAK_$(phys_type)_dof$(ndof_per_node)_N$(prod(n))_elx$(elx)" strong_el_x = ceil(Int,(strong_dof/ndof_per_node)^(1/3)); strong_jobs = map(n->(sname(phys_type,ndof_per_node,n,strong_el_x), generate(template,sname(phys_type,ndof_per_node,n,strong_el_x),phys_type,bmark_types, - cputype,wallhr,n,strong_el_x,fe_order,verbose,dir_name,write_dir,nreps)),N) + cputype,wallhr,n,strong_el_x,fe_order,verbose,dir_name,write_dir,nreps)),parts) weak_jobs = map((n,elx)->(wname(phys_type,ndof_per_node,n,elx), generate(template,wname(phys_type,ndof_per_node,n,elx),phys_type,bmark_types, - cputype,wallhr,n,elx,fe_order,verbose,dir_name,write_dir,nreps)),N,weak_el_x) + cputype,wallhr,n,elx,fe_order,verbose,dir_name,write_dir,nreps)),parts,weak_el_x) strong_jobs,weak_jobs,dof_sanity_check end -job_output_path = "./scripts/Benchmarks/jobs/"; +dir_name= "LevelSetTopOpt"; +job_output_path = "$(ENV["SCRATCH"])/$dir_name/scripts/Benchmarks/jobs-gadi/"; mkpath(job_output_path); # SETUP PARAMETERS -cputype="6140"; -gb_per_cpu = 8 # GB +cputype=""; # Not needed here +gb_per_node = 192 # GB +cps_per_node = 48 wallhr = 3 ; # Hours (Note may want to manually change some afterwards) nreps = 10; # Number of benchmark repetitions dofs_per_proc = 32000; fe_order= 1; verbose= 1; -dir_name= "LevelSetTopOpt"; -write_dir = "\$HOME/$dir_name/results/benchmarks/" +write_dir = "\$SCRATCH/$dir_name/results/benchmarks/" -N = 1:10; # Number of partitions in x-axis +parts = [(2,2,2);(3,3,3);mesh_partitions[[1,2,3,5]];mesh_partitions[8:5:23]] strong_dof=(100+1)^3*3; # Number of dofs for strong scaling # Phys type and number of dofs per node, and what to benchmark @@ -76,7 +96,7 @@ phys_types = [ ]; # Template -template = read("./scripts/Benchmarks/jobtemplate.sh",String) +template = read("$(ENV["SCRATCH"])/$dir_name/scripts/Benchmarks/jobtemplate_gadi.sh",String) ## Generate Jobs jobs_by_phys = map(x->(x[1],generate_jobs(template,x[1],x[2],x[3])),phys_types); @@ -92,4 +112,9 @@ for jobs in jobs_by_phys write(f,content) end end -end \ No newline at end of file +end + +# Mathematica code: +# F[N_]:=Minimize[{X+Y+Z,X*Y*Z==N*48, X>0, Y>0, Z>0,X\[Element] Integers,Y\[Element] Integers,Z\[Element] Integers},{X,Y,Z}] +# For[i=1,i<=50,i++,X[i]=F[i]]; +# For[i=1,i<=90,i++,Print[{X[i][[2]][[1]][[2]],X[i][[2]][[2]][[2]],X[i][[2]][[3]][[2]]}]] \ No newline at end of file diff --git a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl b/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl deleted file mode 100644 index f142b86b..00000000 --- a/scripts/Benchmarks/generate_benchmark_scripts_gadi.jl +++ /dev/null @@ -1,120 +0,0 @@ -using Pkg -Pkg.activate() -using Mustache - -# These are generated by solving -# Minimise X + Y + Z s.t. X*Y*Z=i*48 for X,Y,Z∈ℤ⁺ (See bottom) -mesh_partitions = [(4, 4, 3),(4, 4, 6),(4, 6, 6),(4, 6, 8),(5, 6, 8),(6, 6, 8),(7, 6, 8),(6, 8, 8),(6, 9, 8),(10, 6, 8), - (11, 6, 8),(9, 8, 8),(13, 6, 8),(12, 7, 8),(10, 9, 8),(12, 8, 8),(6, 8, 17),(12, 9, 8),(6, 8, 19), - (10, 12, 8),(14, 9, 8),(11, 12, 8),(6, 8, 23),(12, 12, 8),(10, 10, 12),(13, 12, 8),(12, 12, 9),(12, 14, 8), - (6, 8, 29),(10, 12, 12),(6, 8, 31),(8, 12, 16),(11, 12, 12),(8, 12, 17),(10, 12, 14),(12, 12, 12),(6, 8, 37), - (8, 12, 19),(13, 12, 12),(10, 12, 16),(6, 8, 41),(12, 12, 14),(6, 8, 43),(11, 12, 16),(12, 12, 15),(8, 12, 23), - (6, 8, 47),(12, 12, 16),(12, 14, 14),(10, 15, 16),(12, 12, 17),(12, 13, 16),(6, 8, 53),(12, 12, 18),(11, 15, 16), - (12, 14, 16),(12, 12, 19),(8, 12, 29),(6, 8, 59),(12, 15, 16),(6, 8, 61),(8, 12, 31),(12, 14, 18),(12, 16, 16), - (13, 15, 16),(11, 16, 18),(6, 8, 67),(12, 16, 17),(12, 12, 23),(14, 15, 16),(6, 8, 71),(12, 16, 18),(6, 8, 73), - (8, 12, 37),(15, 15, 16),(12, 16, 19),(11, 16, 21),(13, 16, 18),(6, 8, 79),(15, 16, 16),(12, 18, 18),(8, 12, 41), - (6, 8, 83),(14, 16, 18),(15, 16, 17),(8, 12, 43),(12, 12, 29),(12, 16, 22),(6, 8, 89),(15, 16, 18)] - -@assert Int.(prod.(mesh_partitions)/48) == collect(1:length(mesh_partitions)) - -function generate( - template, - name, - type, - bmark_type, - cputype, - wallhr, - mesh_partition, - n_el_size, - fe_order, - verbose, - dir_name, - write_dir, - nreps - ) - - ncpus = prod(mesh_partition) - wallhr = occursin("STRONG",name) && ncpus == 1 ? 100 : - occursin("STRONG",name) && ncpus == 8 ? 24 : - occursin("STRONG",name) && ncpus == 27 ? 10 : wallhr - mem = occursin("STRONG",name) && ncpus == 1 ? 100 : - occursin("STRONG",name) && ncpus == 8 ? 128 : - occursin("STRONG",name) && ncpus == 27 ? 192 : Int(gb_per_node*ncpus/cps_per_node); - Nx_partition, Ny_partition, Nz_partition = mesh_partition - - settings = (;name,type,bmark_type,cputype,wallhr,ncpus,mem, - Nx_partition,Ny_partition,Nz_partition,n_el_size,fe_order,verbose,dir_name,write_dir,nreps) - Mustache.render(template, settings) -end - -function generate_jobs(template,phys_type,ndof_per_node,bmark_types) - npart = prod.(parts) - weak_el_x = @. floor(Int,(dofs_per_proc*npart/ndof_per_node)^(1/3)-1); - dof_sanity_check = @.(floor(Int,ndof_per_node*(weak_el_x+1)^3/npart)), - maximum(abs,@. ndof_per_node*(weak_el_x+1)^3/npart/dofs_per_proc - 1) - - sname(phys_type,ndof_per_node,n,elx) = "STRONG_$(phys_type)_dof$(ndof_per_node)_N$(prod(n))_elx$(elx)" - wname(phys_type,ndof_per_node,n,elx) = "WEAK_$(phys_type)_dof$(ndof_per_node)_N$(prod(n))_elx$(elx)" - - strong_el_x = ceil(Int,(strong_dof/ndof_per_node)^(1/3)); - - strong_jobs = map(n->(sname(phys_type,ndof_per_node,n,strong_el_x), - generate(template,sname(phys_type,ndof_per_node,n,strong_el_x),phys_type,bmark_types, - cputype,wallhr,n,strong_el_x,fe_order,verbose,dir_name,write_dir,nreps)),parts) - weak_jobs = map((n,elx)->(wname(phys_type,ndof_per_node,n,elx), - generate(template,wname(phys_type,ndof_per_node,n,elx),phys_type,bmark_types, - cputype,wallhr,n,elx,fe_order,verbose,dir_name,write_dir,nreps)),parts,weak_el_x) - - strong_jobs,weak_jobs,dof_sanity_check -end - -dir_name= "LevelSetTopOpt"; -job_output_path = "$(ENV["SCRATCH"])/$dir_name/scripts/Benchmarks/jobs-gadi/"; -mkpath(job_output_path); - -# SETUP PARAMETERS -cputype=""; # Not needed here -gb_per_node = 192 # GB -cps_per_node = 48 -wallhr = 3 ; # Hours (Note may want to manually change some afterwards) - -nreps = 10; # Number of benchmark repetitions -dofs_per_proc = 32000; -fe_order= 1; -verbose= 1; -write_dir = "\$SCRATCH/$dir_name/results/benchmarks/" - -parts = [(2,2,2);(3,3,3);mesh_partitions[[1,2,3,5]];mesh_partitions[8:5:23]] -strong_dof=(100+1)^3*3; # Number of dofs for strong scaling - -# Phys type and number of dofs per node, and what to benchmark -phys_types = [ - ("THERM",1,"bopt0,bopt1,bfwd,badv,breinit,bvelext"), - ("ELAST",3,"bopt0,bopt1,bfwd,badv,breinit,bvelext"), - ("NLELAST",3,"bopt0,bopt1,bfwd"), - # ("INVERTER_HPM",3,"bhpm"), -]; - -# Template -template = read("$(ENV["SCRATCH"])/$dir_name/scripts/Benchmarks/jobtemplate_gadi.sh",String) - -## Generate Jobs -jobs_by_phys = map(x->(x[1],generate_jobs(template,x[1],x[2],x[3])),phys_types); - -for jobs in jobs_by_phys - strong_jobs,weak_jobs,dof_sanity_check = jobs[2] - - println("$(jobs[1]): Weak dofs = $(dof_sanity_check[1])\n Error = $(dof_sanity_check[2])\n") - for job in vcat(strong_jobs,weak_jobs) - name = job[1] - content = job[2] - open(job_output_path*"$name.pbs","w") do f - write(f,content) - end - end -end - -# Mathematica code: -# F[N_]:=Minimize[{X+Y+Z,X*Y*Z==N*48, X>0, Y>0, Z>0,X\[Element] Integers,Y\[Element] Integers,Z\[Element] Integers},{X,Y,Z}] -# For[i=1,i<=50,i++,X[i]=F[i]]; -# For[i=1,i<=90,i++,Print[{X[i][[2]][[1]][[2]],X[i][[2]][[2]][[2]],X[i][[2]][[3]][[2]]}]] \ No newline at end of file diff --git a/scripts/Benchmarks/jobtemplate.sh b/scripts/Benchmarks/jobtemplate.sh index 049acb79..4bee92f9 100644 --- a/scripts/Benchmarks/jobtemplate.sh +++ b/scripts/Benchmarks/jobtemplate.sh @@ -1,32 +1,26 @@ -#!/bin/bash -l +#!/bin/bash -#PBS -P LSTO +#PBS -P np01 +#PBS -q normal #PBS -N "{{:name}}" -#PBS -l select={{:ncpus}}:ncpus=1:mpiprocs=1:ompthreads=1:mem={{:mem}}GB:cputype={{:cputype}} +#PBS -l ncpus={{:ncpus}} +#PBS -l mem={{:mem}}GB #PBS -l walltime={{:wallhr}}:00:00 #PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/{{:dir_name}}/ +source $HOME/hpc-environments/gadi/load-intel.sh +PROJECT_DIR=$SCRATCH/{{:dir_name}}/ -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n {{:ncpus}} julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/Benchmarks/benchmark.jl \ +mpiexec -n {{:ncpus}} julia --project=$PROJECT_DIR --check-bounds no -O3 \ + $PROJECT_DIR/scripts/Benchmarks/benchmark_gadi.jl \ {{:name}} \ {{{:write_dir}}} \ {{:type}} \ {{:bmark_type}} \ - {{:n_mesh_partition}} \ + {{:Nx_partition}} \ + {{:Ny_partition}} \ + {{:Nz_partition}} \ {{:n_el_size}} \ {{:fe_order}} \ {{:verbose}} \ - {{:nreps}} - -read _ _ PBS_WALLTIME <<< `qstat -f $PBS_JOBID | grep "resources_used.walltime"` -PBS_WALLTIME_SECS=$(echo $PBS_WALLTIME | awk -F: '{ print ($1 * 3600) + ($2 * 60) + $3 }') -echo $PBS_WALLTIME_SECS >> {{{:write_dir}}}/{{:name}}_walltime.txt \ No newline at end of file + {{:nreps}} \ No newline at end of file diff --git a/scripts/Benchmarks/jobtemplate_gadi.sh b/scripts/Benchmarks/jobtemplate_gadi.sh deleted file mode 100644 index 4bee92f9..00000000 --- a/scripts/Benchmarks/jobtemplate_gadi.sh +++ /dev/null @@ -1,26 +0,0 @@ -#!/bin/bash - -#PBS -P np01 -#PBS -q normal -#PBS -N "{{:name}}" -#PBS -l ncpus={{:ncpus}} -#PBS -l mem={{:mem}}GB -#PBS -l walltime={{:wallhr}}:00:00 -#PBS -j oe - -source $HOME/hpc-environments/gadi/load-intel.sh -PROJECT_DIR=$SCRATCH/{{:dir_name}}/ - -mpiexec -n {{:ncpus}} julia --project=$PROJECT_DIR --check-bounds no -O3 \ - $PROJECT_DIR/scripts/Benchmarks/benchmark_gadi.jl \ - {{:name}} \ - {{{:write_dir}}} \ - {{:type}} \ - {{:bmark_type}} \ - {{:Nx_partition}} \ - {{:Ny_partition}} \ - {{:Nz_partition}} \ - {{:n_el_size}} \ - {{:fe_order}} \ - {{:verbose}} \ - {{:nreps}} \ No newline at end of file diff --git a/scripts/MPI/3d_elastic_compliance_ALM.jl b/scripts/MPI/3d_elastic_compliance_ALM.jl index 558d05d8..cb221837 100644 --- a/scripts/MPI/3d_elastic_compliance_ALM.jl +++ b/scripts/MPI/3d_elastic_compliance_ALM.jl @@ -1,12 +1,13 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR -global elx = parse(Int,ARGS[1]) -global ely = parse(Int,ARGS[2]) -global elz = parse(Int,ARGS[3]) -global Px = parse(Int,ARGS[4]) -global Py = parse(Int,ARGS[5]) -global Pz = parse(Int,ARGS[6]) +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) +global write_dir = ARGS[7] """ (MPI) Minimum elastic compliance with augmented Lagrangian method in 3D. @@ -15,10 +16,10 @@ global Pz = parse(Int,ARGS[6]) Min J(Ω) = ∫ C ⊙ ε(u) ⊙ ε(v) dΩ Ω s.t., Vol(Ω) = vf, - ⎡u∈V=H¹(Ω;u(Γ_D)=0)³, + ⎡u∈V=H¹(Ω;u(Γ_D)=0)³, ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ = ∫ v⋅g dΓ_N, ∀v∈V. """ -function main(mesh_partition,distribute,el_size) +function main(mesh_partition,distribute,el_size,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -35,9 +36,8 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_elastic_compliance_ALM_Nx$(el_size[1])/" iter_mod = 10 - i_am_main(ranks) && mkdir(path) + i_am_main(ranks) && mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -87,7 +87,7 @@ function main(mesh_partition,distribute,el_size) Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} Tv = Vector{PetscScalar} solver = ElasticitySolver(V) - + state_map = AffineFEStateMap( a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), @@ -121,10 +121,10 @@ end with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) - hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" - + GridapPETSc.with(args=split(hilb_solver_options)) do - main(mesh_partition,distribute,el_size) + main(mesh_partition,distribute,el_size,write_dir) end end; \ No newline at end of file diff --git a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl index 6cd67d04..fe6d8f61 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl @@ -1,19 +1,20 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR using GridapSolvers: NewtonSolver -global elx = parse(Int,ARGS[1]) -global ely = parse(Int,ARGS[2]) -global elz = parse(Int,ARGS[3]) -global Px = parse(Int,ARGS[4]) -global Py = parse(Int,ARGS[5]) -global Pz = parse(Int,ARGS[6]) +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) +global write_dir = ARGS[7] """ (MPI) Minimum hyperelastic compliance with augmented Lagrangian method in 3D. -""" -function main(mesh_partition,distribute,el_size) +""" +function main(mesh_partition,distribute,el_size,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -28,9 +29,8 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_hyperelastic_compliance_ALM_Nx$(el_size[1])/" iter_mod = 10 - i_am_main(ranks) && mkdir(path) + i_am_main(ranks) && mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size) @@ -108,7 +108,7 @@ function main(mesh_partition,distribute,el_size) assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), ls = PETScLinearSolver() ) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) @@ -124,10 +124,10 @@ end with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) - hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" - + GridapPETSc.with(args=split(hilb_solver_options)) do - main(mesh_partition,distribute,el_size) + main(mesh_partition,distribute,el_size,write_dir) end end \ No newline at end of file diff --git a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl index 8ad44dc4..7d781947 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl @@ -1,19 +1,20 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR using GridapSolvers: NewtonSolver -global elx = parse(Int,ARGS[1]) -global ely = parse(Int,ARGS[2]) -global elz = parse(Int,ARGS[3]) -global Px = parse(Int,ARGS[4]) -global Py = parse(Int,ARGS[5]) -global Pz = parse(Int,ARGS[6]) +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) +global write_dir = ARGS[7] """ (MPI) Minimum hyperelastic compliance with augmented Lagrangian method in 3D. -""" -function main(mesh_partition,distribute,el_size) +""" +function main(mesh_partition,distribute,el_size,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -28,9 +29,8 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_hyperelastic_compliance_neohook_ALM_Nx$(el_size[1])/" iter_mod = 10 - i_am_main(ranks) && mkdir(path) + i_am_main(ranks) && mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size) @@ -122,7 +122,7 @@ function main(mesh_partition,distribute,el_size) assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), ls = PETScLinearSolver() ) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) @@ -138,10 +138,10 @@ end with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) - hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" - + GridapPETSc.with(args=split(hilb_solver_options)) do - main(mesh_partition,distribute,el_size) + main(mesh_partition,distribute,el_size,write_dir) end end \ No newline at end of file diff --git a/scripts/MPI/3d_inverse_homenisation_ALM.jl b/scripts/MPI/3d_inverse_homenisation_ALM.jl index 1746a942..087372b4 100644 --- a/scripts/MPI/3d_inverse_homenisation_ALM.jl +++ b/scripts/MPI/3d_inverse_homenisation_ALM.jl @@ -1,13 +1,14 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR -global elx = parse(Int,ARGS[1]) -global ely = parse(Int,ARGS[2]) -global elz = parse(Int,ARGS[3]) -global Px = parse(Int,ARGS[4]) -global Py = parse(Int,ARGS[5]) -global Pz = parse(Int,ARGS[6]) - +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) +global write_dir = ARGS[7] + """ (MPI) Maximum bulk modulus inverse homogenisation with augmented Lagrangian method in 3D. @@ -15,10 +16,10 @@ global Pz = parse(Int,ARGS[6]) Min J(Ω) = -κ(Ω) Ω s.t., Vol(Ω) = vf, - ⎡For unique εᴹᵢ, find uᵢ∈V=H¹ₚₑᵣ(Ω)ᵈ, + ⎡For unique εᴹᵢ, find uᵢ∈V=H¹ₚₑᵣ(Ω)ᵈ, ⎣∫ ∑ᵢ C ⊙ ε(uᵢ) ⊙ ε(vᵢ) dΩ = ∫ -∑ᵢ C ⊙ ε⁰ᵢ ⊙ ε(vᵢ) dΩ, ∀v∈V. -""" -function main(mesh_partition,distribute,el_size) +""" +function main(mesh_partition,distribute,el_size,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -33,9 +34,8 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.5 - path = dirname(dirname(@__DIR__))*"/results/3d_inverse_homenisation_ALM_Nx$(el_size[1])/" iter_mod = 10 - i_am_main(ranks) && mkdir(path) + i_am_main(ranks) && mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true,true)) @@ -109,7 +109,7 @@ function main(mesh_partition,distribute,el_size) assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), ls = PETScLinearSolver() ) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) @@ -125,10 +125,10 @@ end with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) - hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" - + GridapPETSc.with(args=split(hilb_solver_options)) do - main(mesh_partition,distribute,el_size) + main(mesh_partition,distribute,el_size,write_dir) end end \ No newline at end of file diff --git a/scripts/MPI/3d_inverter_ALM.jl b/scripts/MPI/3d_inverter_ALM.jl index 4fa6ee26..aa7fb6fd 100644 --- a/scripts/MPI/3d_inverter_ALM.jl +++ b/scripts/MPI/3d_inverter_ALM.jl @@ -1,12 +1,13 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR -global elx = parse(Int,ARGS[1]) -global ely = parse(Int,ARGS[2]) -global elz = parse(Int,ARGS[3]) -global Px = parse(Int,ARGS[4]) -global Py = parse(Int,ARGS[5]) -global Pz = parse(Int,ARGS[6]) +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) +global write_dir = ARGS[7] """ (MPI) Inverter mechanism with Hilbertian projection method in 3D. @@ -15,14 +16,14 @@ global Pz = parse(Int,ARGS[6]) Min J(Ω) = ηᵢₙ*∫ u⋅e₁ dΓᵢₙ Ω s.t., Vol(Ω) = vf, - C(Ω) = 0, - ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, + C(Ω) = 0, + ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ + ∫ kₛv⋅u dΓₒᵤₜ = ∫ v⋅g dΓᵢₙ , ∀v∈V. - + where C(Ω) = ∫ -u⋅e₁-δₓ dΓₒᵤₜ. We assume symmetry in the problem to aid convergence. -""" -function main(mesh_partition,distribute,el_size) +""" +function main(mesh_partition,distribute,el_size,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -39,18 +40,17 @@ function main(mesh_partition,distribute,el_size) δₓ=0.5 ks = 0.01 g = VectorValue(1,0,0) - path = dirname(dirname(@__DIR__))*"/results/3d_inverter_ALM_Nx$(el_size[1])/" iter_mod = 10 - i_am_main(ranks) && mkdir(path) + i_am_main(ranks) && mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); el_Δ = get_el_Δ(model) - f_Γ_in(x) = (x[1] ≈ 0.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && + f_Γ_in(x) = (x[1] ≈ 0.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) - f_Γ_out(x) = (x[1] ≈ 1.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && + f_Γ_out(x) = (x[1] ≈ 1.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) - f_Γ_out_ext(x) = ~f_Γ_out(x) && (0.9 <= x[1] <= 1.0) && (0.3 - eps() <= x[2] <= 0.7 + eps()) && + f_Γ_out_ext(x) = ~f_Γ_out(x) && (0.9 <= x[1] <= 1.0) && (0.3 - eps() <= x[2] <= 0.7 + eps()) && (0.3 - eps() <= x[3] <= 0.7 + eps()) f_Γ_D(x) = (x[1] ≈ 0.0) && (x[2] <= 0.1 || x[2] >= 0.9) && (x[3] <= 0.1 || x[3] >= 0.9) update_labels!(1,model,f_Γ_in,"Gamma_in") @@ -105,7 +105,7 @@ function main(mesh_partition,distribute,el_size) Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} Tv = Vector{PetscScalar} solver = ElasticitySolver(V) - + state_map = AffineFEStateMap( a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), @@ -123,7 +123,7 @@ function main(mesh_partition,distribute,el_size) assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), ls = PETScLinearSolver() ) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol,:UΓ_out]) @@ -139,10 +139,10 @@ end with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) - hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" - + GridapPETSc.with(args=split(hilb_solver_options)) do - main(mesh_partition,distribute,el_size) + main(mesh_partition,distribute,el_size,write_dir) end end \ No newline at end of file diff --git a/scripts/MPI/3d_inverter_HPM.jl b/scripts/MPI/3d_inverter_HPM.jl index 3aacbfe1..681450d0 100644 --- a/scripts/MPI/3d_inverter_HPM.jl +++ b/scripts/MPI/3d_inverter_HPM.jl @@ -1,12 +1,13 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR -global elx = parse(Int,ARGS[1]) -global ely = parse(Int,ARGS[2]) -global elz = parse(Int,ARGS[3]) -global Px = parse(Int,ARGS[4]) -global Py = parse(Int,ARGS[5]) -global Pz = parse(Int,ARGS[6]) +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) +global write_dir = ARGS[7] """ (MPI) Inverter mechanism with Hilbertian projection method in 3D. @@ -15,14 +16,14 @@ global Pz = parse(Int,ARGS[6]) Min J(Ω) = ηᵢₙ*∫ u⋅e₁ dΓᵢₙ Ω s.t., Vol(Ω) = vf, - C(Ω) = 0, - ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, + C(Ω) = 0, + ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ + ∫ kₛv⋅u dΓₒᵤₜ = ∫ v⋅g dΓᵢₙ , ∀v∈V. - + where C(Ω) = ∫ -u⋅e₁-δₓ dΓₒᵤₜ. We assume symmetry in the problem to aid convergence. -""" -function main(mesh_partition,distribute,el_size) +""" +function main(mesh_partition,distribute,el_size,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -39,18 +40,17 @@ function main(mesh_partition,distribute,el_size) δₓ=0.5 ks = 0.01 g = VectorValue(1,0,0) - path = dirname(dirname(@__DIR__))*"/results/3d_inverter_HPM_Nx$(el_size[1])/" iter_mod = 10 - i_am_main(ranks) && mkdir(path) + i_am_main(ranks) && mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); el_Δ = get_el_Δ(model) - f_Γ_in(x) = (x[1] ≈ 0.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && + f_Γ_in(x) = (x[1] ≈ 0.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) - f_Γ_out(x) = (x[1] ≈ 1.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && + f_Γ_out(x) = (x[1] ≈ 1.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) - f_Γ_out_ext(x) = ~f_Γ_out(x) && (0.9 <= x[1] <= 1.0) && (0.3 - eps() <= x[2] <= 0.7 + eps()) && + f_Γ_out_ext(x) = ~f_Γ_out(x) && (0.9 <= x[1] <= 1.0) && (0.3 - eps() <= x[2] <= 0.7 + eps()) && (0.3 - eps() <= x[3] <= 0.7 + eps()) f_Γ_D(x) = (x[1] ≈ 0.0) && (x[2] <= 0.1 || x[2] >= 0.9) && (x[3] <= 0.1 || x[3] >= 0.9) update_labels!(1,model,f_Γ_in,"Gamma_in") @@ -105,7 +105,7 @@ function main(mesh_partition,distribute,el_size) Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} Tv = Vector{PetscScalar} solver = ElasticitySolver(V) - + state_map = AffineFEStateMap( a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), @@ -123,7 +123,7 @@ function main(mesh_partition,distribute,el_size) assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), ls = PETScLinearSolver() ) - + ## Optimiser ls_enabled=false # Setting to true will use a line search instead of oscillation detection optimiser = HilbertianProjection(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,ls_enabled,α_min=0.7, @@ -140,10 +140,10 @@ end with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) - hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" - + GridapPETSc.with(args=split(hilb_solver_options)) do - main(mesh_partition,distribute,el_size) + main(mesh_partition,distribute,el_size,write_dir) end end \ No newline at end of file diff --git a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl index e3bbfde2..08bcb6f2 100644 --- a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl @@ -1,14 +1,15 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR using GridapSolvers: NewtonSolver -global elx = parse(Int,ARGS[1]) -global ely = parse(Int,ARGS[2]) -global elz = parse(Int,ARGS[3]) -global Px = parse(Int,ARGS[4]) -global Py = parse(Int,ARGS[5]) -global Pz = parse(Int,ARGS[6]) +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) +global write_dir = ARGS[7] """ (MPI) Minimum thermal compliance with augmented Lagrangian method in 3D with nonlinear diffusivity. @@ -19,10 +20,10 @@ global Pz = parse(Int,ARGS[6]) s.t., Vol(Ω) = vf, ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ(u)*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. - + In this example κ(u) = κ0*(exp(ξ*u)) -""" -function main(mesh_partition,distribute,el_size) +""" +function main(mesh_partition,distribute,el_size,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -38,9 +39,8 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_nonlinear_thermal_compliance_ALM_Nx$(el_size[1])/" iter_mod = 10 - i_am_main(ranks) && mkdir(path) + i_am_main(ranks) && mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -92,7 +92,7 @@ function main(mesh_partition,distribute,el_size) Tv = Vector{PetscScalar} lin_solver = PETScLinearSolver() nl_solver = NewtonSolver(lin_solver;maxiter=50,rtol=10^-8,verbose=i_am_main(ranks)) - + state_map = NonlinearFEStateMap( res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), @@ -111,7 +111,7 @@ function main(mesh_partition,distribute,el_size) assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), ls = lin_solver ) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) @@ -127,10 +127,10 @@ end with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) - options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" - + GridapPETSc.with(args=split(options)) do - main(mesh_partition,distribute,el_size) + main(mesh_partition,distribute,el_size,write_dir) end end; \ No newline at end of file diff --git a/scripts/MPI/3d_thermal_compliance_ALM.jl b/scripts/MPI/3d_thermal_compliance_ALM.jl index ce4849db..4bf81ede 100644 --- a/scripts/MPI/3d_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_thermal_compliance_ALM.jl @@ -1,12 +1,13 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR -global elx = parse(Int,ARGS[1]) -global ely = parse(Int,ARGS[2]) -global elz = parse(Int,ARGS[3]) -global Px = parse(Int,ARGS[4]) -global Py = parse(Int,ARGS[5]) -global Pz = parse(Int,ARGS[6]) +global elx = parse(Int,ARGS[1]) +global ely = parse(Int,ARGS[2]) +global elz = parse(Int,ARGS[3]) +global Px = parse(Int,ARGS[4]) +global Py = parse(Int,ARGS[5]) +global Pz = parse(Int,ARGS[6]) +global write_dir = ARGS[7] """ (MPI) Minimum thermal compliance with augmented Lagrangian method in 3D. @@ -18,7 +19,7 @@ global Pz = parse(Int,ARGS[6]) ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. """ -function main(mesh_partition,distribute,el_size) +function main(mesh_partition,distribute,el_size,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -35,9 +36,8 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/3d_thermal_compliance_ALM_Nx$(el_size[1])/" iter_mod = 10 - i_am_main(ranks) && mkdir(path) + i_am_main(ranks) && mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -87,7 +87,7 @@ function main(mesh_partition,distribute,el_size) Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} Tv = Vector{PetscScalar} solver = PETScLinearSolver() - + state_map = AffineFEStateMap( a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), @@ -121,10 +121,10 @@ end with_mpi() do distribute mesh_partition = (Px,Py,Pz) el_size = (elx,ely,elz) - all_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + all_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" - + GridapPETSc.with(args=split(all_solver_options)) do - main(mesh_partition,distribute,el_size) + main(mesh_partition,distribute,el_size,write_dir) end end; \ No newline at end of file diff --git a/scripts/MPI/elastic_compliance_ALM.jl b/scripts/MPI/elastic_compliance_ALM.jl index 48bacf32..2c434df7 100644 --- a/scripts/MPI/elastic_compliance_ALM.jl +++ b/scripts/MPI/elastic_compliance_ALM.jl @@ -1,6 +1,8 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR +global write_dir = ARGS[1] + """ (MPI) Minimum elastic compliance with augmented Lagrangian method in 2D. @@ -8,10 +10,10 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, Min J(Ω) = ∫ C ⊙ ε(u) ⊙ ε(v) + ξ dΩ Ω s.t., Vol(Ω) = vf, - ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, + ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ = ∫ v⋅g dΓ_N, ∀v∈V. """ -function main(mesh_partition,distribute,el_size) +function main(mesh_partition,distribute,el_size,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -28,9 +30,8 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_ALM_MPI/" iter_mod = 10 - i_am_main(ranks) && mkdir(path) + i_am_main(ranks) && mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size) @@ -80,7 +81,7 @@ function main(mesh_partition,distribute,el_size) Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} Tv = Vector{PetscScalar} solver = ElasticitySolver(V) - + state_map = AffineFEStateMap( a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), @@ -112,10 +113,10 @@ end with_mpi() do distribute mesh_partition = (2,2) el_size = (200,100) - hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" - + GridapPETSc.with(args=split(hilb_solver_options)) do - main(mesh_partition,distribute,el_size) + main(mesh_partition,distribute,el_size,write_dir) end end \ No newline at end of file diff --git a/scripts/MPI/inverse_homenisation_ALM.jl b/scripts/MPI/inverse_homenisation_ALM.jl index 6cbe688b..032e93c8 100644 --- a/scripts/MPI/inverse_homenisation_ALM.jl +++ b/scripts/MPI/inverse_homenisation_ALM.jl @@ -1,6 +1,8 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR +global write_dir = ARGS[1] + """ (MPI) Maximum bulk modulus inverse homogenisation with augmented Lagrangian method in 2D. @@ -8,10 +10,10 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, Min J(Ω) = -κ(Ω) Ω s.t., Vol(Ω) = vf, - ⎡For unique εᴹᵢ, find uᵢ∈V=H¹ₚₑᵣ(Ω)ᵈ, + ⎡For unique εᴹᵢ, find uᵢ∈V=H¹ₚₑᵣ(Ω)ᵈ, ⎣∫ ∑ᵢ C ⊙ ε(uᵢ) ⊙ ε(vᵢ) dΩ = ∫ -∑ᵢ C ⊙ ε⁰ᵢ ⊙ ε(vᵢ) dΩ, ∀v∈V. -""" -function main(mesh_partition,distribute,el_size) +""" +function main(mesh_partition,distribute,el_size,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -26,9 +28,8 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4*max_steps*γ vf = 0.5 - path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM_MPI/" iter_mod = 10 - #i_am_main(ranks) && mkdir(path) + #i_am_main(ranks) && mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true)); @@ -79,7 +80,7 @@ function main(mesh_partition,distribute,el_size) Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} Tv = Vector{PetscScalar} solver = ElasticitySolver(V) - + state_map = RepeatingAffineFEStateMap( 3,a,l,U,V,V_φ,U_reg,φh,dΩ; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), @@ -97,7 +98,7 @@ function main(mesh_partition,distribute,el_size) assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), ls = PETScLinearSolver() ) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) @@ -113,10 +114,10 @@ end with_mpi() do distribute mesh_partition = (2,2) el_size = (200,200) - hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" - + GridapPETSc.with(args=split(hilb_solver_options)) do - main(mesh_partition,distribute,el_size) + main(mesh_partition,distribute,el_size,write_dir) end end; \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs b/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs deleted file mode 100644 index 9ab66596..00000000 --- a/scripts/MPI/jobs/3d_elastic_compliance_ALM.pbs +++ /dev/null @@ -1,25 +0,0 @@ -#!/bin/bash -l -#PBS -P LSTO -#PBS -N 3d_elastic_compliance_ALM - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_elastic_compliance_ALM.jl \ - 160 \ - 80 \ - 80 \ - 5 \ - 5 \ - 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs b/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs deleted file mode 100644 index 58b91b3a..00000000 --- a/scripts/MPI/jobs/3d_hyperelastic_compliance_ALM.pbs +++ /dev/null @@ -1,25 +0,0 @@ -#!/bin/bash -l -#PBS -P LSTO -#PBS -N 3d_hyperelastic_compliance_ALM - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_hyperelastic_compliance_ALM.jl \ - 160 \ - 80 \ - 80 \ - 5 \ - 5 \ - 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs b/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs deleted file mode 100644 index 67935f3b..00000000 --- a/scripts/MPI/jobs/3d_hyperelastic_compliance_neohook_ALM.pbs +++ /dev/null @@ -1,25 +0,0 @@ -#!/bin/bash -l -#PBS -P LSTO -#PBS -N 3d_hyperelastic_compliance_neohook_ALM - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl \ - 160 \ - 80 \ - 80 \ - 5 \ - 5 \ - 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs b/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs deleted file mode 100644 index 5a1e636d..00000000 --- a/scripts/MPI/jobs/3d_inverse_homenisation_ALM.pbs +++ /dev/null @@ -1,25 +0,0 @@ -#!/bin/bash -l -#PBS -P LSTO -#PBS -N 3d_inverse_homenisation_ALM - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_inverse_homenisation_ALM.jl \ - 100 \ - 100 \ - 100 \ - 5 \ - 5 \ - 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_inverter_ALM.pbs b/scripts/MPI/jobs/3d_inverter_ALM.pbs deleted file mode 100644 index 1eb0f7f2..00000000 --- a/scripts/MPI/jobs/3d_inverter_ALM.pbs +++ /dev/null @@ -1,26 +0,0 @@ -#!/bin/bash -l - -#PBS -P LSTO -#PBS -N 3d_inverter_ALM - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_inverter_ALM.jl \ - 100 \ - 100 \ - 100 \ - 5 \ - 5 \ - 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_inverter_HPM.pbs b/scripts/MPI/jobs/3d_inverter_HPM.pbs deleted file mode 100644 index 66365043..00000000 --- a/scripts/MPI/jobs/3d_inverter_HPM.pbs +++ /dev/null @@ -1,26 +0,0 @@ -#!/bin/bash -l - -#PBS -P LSTO -#PBS -N 3d_inverter_HPM - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_inverter_HPM.jl \ - 100 \ - 100 \ - 100 \ - 5 \ - 5 \ - 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs b/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs deleted file mode 100644 index 985235f3..00000000 --- a/scripts/MPI/jobs/3d_nonlinear_thermal_compliance_ALM.pbs +++ /dev/null @@ -1,26 +0,0 @@ -#!/bin/bash -l - -#PBS -P LSTO -#PBS -N 3d_nonlinear_thermal_compliance_ALM - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl \ - 100 \ - 100 \ - 100 \ - 5 \ - 5 \ - 5 \ No newline at end of file diff --git a/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs b/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs deleted file mode 100644 index 5d69d821..00000000 --- a/scripts/MPI/jobs/3d_thermal_compliance_ALM.pbs +++ /dev/null @@ -1,26 +0,0 @@ -#!/bin/bash -l - -#PBS -P LSTO -#PBS -N 3d_thermal_compliance_ALM - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/MPI/3d_thermal_compliance_ALM.jl \ - 150 \ - 150 \ - 150 \ - 5 \ - 5 \ - 5 \ No newline at end of file diff --git a/scripts/MPI/nonlinear_thermal_compliance_ALM.jl b/scripts/MPI/nonlinear_thermal_compliance_ALM.jl index a4a835e5..ceb760da 100644 --- a/scripts/MPI/nonlinear_thermal_compliance_ALM.jl +++ b/scripts/MPI/nonlinear_thermal_compliance_ALM.jl @@ -1,6 +1,8 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR +global write_dir = ARGS[1] + """ (MPI) Minimum thermal compliance with augmented Lagrangian method in 2D with nonlinear diffusivity. @@ -10,10 +12,10 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, s.t., Vol(Ω) = vf, ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ(u)*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. - + In this example κ(u) = κ0*(exp(ξ*u)) -""" -function main(mesh_partition,distribute,el_size) +""" +function main(mesh_partition,distribute,el_size,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters order = 1 @@ -28,16 +30,15 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/nonlinear_thermal_compliance_ALM_MPI/" iter_mod = 10 - mkdir(path) + mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || + f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())); - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= + f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()); update_labels!(1,model,f_Γ_D,"Gamma_D") update_labels!(2,model,f_Γ_N,"Gamma_N") @@ -85,7 +86,7 @@ function main(mesh_partition,distribute,el_size) α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) @@ -99,5 +100,5 @@ function main(mesh_partition,distribute,el_size) end with_mpi() do distribute - main((2,2),distribute,(200,200)) + main((2,2),distribute,(200,200),write_dir) end \ No newline at end of file diff --git a/scripts/MPI/thermal_compliance_ALM.jl b/scripts/MPI/thermal_compliance_ALM.jl index db881e3e..a90225d5 100644 --- a/scripts/MPI/thermal_compliance_ALM.jl +++ b/scripts/MPI/thermal_compliance_ALM.jl @@ -1,5 +1,7 @@ using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, LevelSetTopOpt +global write_dir = ARGS[1] + """ (MPI) Minimum thermal compliance with augmented Lagrangian method in 2D. @@ -10,7 +12,7 @@ using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, LevelSetTopOpt ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. """ -function main(mesh_partition,distribute) +function main(mesh_partition,distribute,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -28,9 +30,8 @@ function main(mesh_partition,distribute) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM_MPI/" iter_mod = 10 - i_am_main(ranks) && mkdir(path) + i_am_main(ranks) && mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -96,5 +97,5 @@ function main(mesh_partition,distribute) end with_mpi() do distribute - main((2,2),distribute) + main((2,2),distribute,write_dir) end \ No newline at end of file diff --git a/scripts/MPI/thermal_compliance_ALM_PETSc.jl b/scripts/MPI/thermal_compliance_ALM_PETSc.jl index 366f13ef..0344f063 100644 --- a/scripts/MPI/thermal_compliance_ALM_PETSc.jl +++ b/scripts/MPI/thermal_compliance_ALM_PETSc.jl @@ -1,6 +1,8 @@ -using Gridap, GridapDistributed, GridapPETSc, GridapSolvers, +using Gridap, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR +global write_dir = ARGS[1] + """ (MPI) Minimum thermal compliance with augmented Lagrangian method in 2D. @@ -11,7 +13,7 @@ using Gridap, GridapDistributed, GridapPETSc, GridapSolvers, ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. """ -function main(mesh_partition,distribute,el_size) +function main(mesh_partition,distribute,el_size,path) ranks = distribute(LinearIndices((prod(mesh_partition),))) ## Parameters @@ -28,9 +30,8 @@ function main(mesh_partition,distribute,el_size) η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM_MPI+PETSc/" iter_mod = 10 - i_am_main(ranks) && mkdir(path) + i_am_main(ranks) && mkpath(path) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); @@ -78,7 +79,7 @@ function main(mesh_partition,distribute,el_size) Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} Tv = Vector{PetscScalar} solver = PETScLinearSolver() - + state_map = AffineFEStateMap( a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), @@ -112,10 +113,10 @@ end with_mpi() do distribute mesh_partition = (2,2) el_size = (400,400) - solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" - + GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute,el_size) + main(mesh_partition,distribute,el_size,write_dir) end end \ No newline at end of file diff --git a/scripts/Serial/elastic_compliance_ALM.jl b/scripts/Serial/elastic_compliance_ALM.jl index 6b8e4d17..25c7aeb7 100644 --- a/scripts/Serial/elastic_compliance_ALM.jl +++ b/scripts/Serial/elastic_compliance_ALM.jl @@ -7,10 +7,10 @@ using Gridap, LevelSetTopOpt Min J(Ω) = ∫ C ⊙ ε(u) ⊙ ε(v) dΩ Ω s.t., Vol(Ω) = vf, - ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, + ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ = ∫ v⋅g dΓ_N, ∀v∈V. -""" -function main() +""" +function main(path="./results/elastic_compliance_ALM/") ## Parameters order = 1 xmax,ymax=(2.0,1.0) @@ -26,9 +26,8 @@ function main() α_coeff = 4max_steps*γ vf = 0.4 g = VectorValue(0,-1) - path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_ALM/" iter_mod = 10 - mkdir(path) + mkpath(path) ## FE Setup model = CartesianDiscreteModel(dom,el_size) @@ -81,7 +80,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) diff --git a/scripts/Serial/elastic_compliance_HPM.jl b/scripts/Serial/elastic_compliance_HPM.jl index d13be2c1..14e734fe 100644 --- a/scripts/Serial/elastic_compliance_HPM.jl +++ b/scripts/Serial/elastic_compliance_HPM.jl @@ -7,10 +7,10 @@ using Gridap, LevelSetTopOpt Min J(Ω) = ∫ C ⊙ ε(u) ⊙ ε(v) dΩ Ω s.t., Vol(Ω) = vf, - ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, + ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ = ∫ v⋅g dΓ_N, ∀v∈V. -""" -function main() +""" +function main(path="./results/elastic_compliance_HPM/") ## Parameters order = 1 xmax,ymax=(2.0,1.0) @@ -26,15 +26,14 @@ function main() α_coeff = 4max_steps*γ vf = 0.4 g = VectorValue(0,-1) - path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_HPM/" iter_mod = 10 - mkdir(path) + mkpath(path) ## FE Setup model = CartesianDiscreteModel(dom,el_size) el_Δ = get_el_Δ(model) f_Γ_D(x) = (x[1] ≈ 0.0) - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= + f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) update_labels!(1,model,f_Γ_D,"Gamma_D") update_labels!(2,model,f_Γ_N,"Gamma_N") @@ -82,7 +81,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = HilbertianProjection(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) diff --git a/scripts/Serial/elastic_compliance_LM.jl b/scripts/Serial/elastic_compliance_LM.jl index 3accdfac..135cccd8 100644 --- a/scripts/Serial/elastic_compliance_LM.jl +++ b/scripts/Serial/elastic_compliance_LM.jl @@ -6,10 +6,10 @@ using Gridap, LevelSetTopOpt Optimisation problem: Min J(Ω) = ∫ C ⊙ ε(u) ⊙ ε(v) + ξ dΩ Ω - s.t., ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, + s.t., ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ = ∫ v⋅g dΓ_N, ∀v∈V. -""" -function main() +""" +function main(path="./results/elastic_compliance_LM/") ## Parameters order = 1 xmax,ymax=(2.0,1.0) @@ -24,15 +24,14 @@ function main() η_coeff = 2 α_coeff = 4max_steps*γ g = VectorValue(0,-1) - path = dirname(dirname(@__DIR__))*"/results/elastic_compliance_LM/" iter_mod = 10 - mkdir(path) + mkpath(path) ## FE Setup model = CartesianDiscreteModel(dom,el_size) el_Δ = get_el_Δ(model) f_Γ_D(x) = iszero(x[1]) - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= + f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) update_labels!(1,model,f_Γ_D,"Gamma_D") update_labels!(2,model,f_Γ_N,"Gamma_N") @@ -78,7 +77,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true) for (it, uh, φh) in optimiser diff --git a/scripts/Serial/hyperelastic_compliance_ALM.jl b/scripts/Serial/hyperelastic_compliance_ALM.jl index 63b9e1bf..e3f15cfd 100644 --- a/scripts/Serial/hyperelastic_compliance_ALM.jl +++ b/scripts/Serial/hyperelastic_compliance_ALM.jl @@ -2,8 +2,8 @@ using Gridap, LevelSetTopOpt """ (Serial) Minimum hyperelastic compliance with augmented Lagrangian method in 2D. -""" -function main() +""" +function main(path="./results/hyperelastic_compliance_ALM/") ## Parameters order = 1 xmax,ymax=2.0,1.0 @@ -17,9 +17,8 @@ function main() η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.6 - path = dirname(dirname(@__DIR__))*"/results/hyperelastic_compliance_ALM/" iter_mod = 10 - mkdir(path) + mkpath(path) ## FE Setup model = CartesianDiscreteModel(dom,el_size); @@ -81,7 +80,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) diff --git a/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl b/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl index 72738c4e..d6ae9163 100644 --- a/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl @@ -2,8 +2,8 @@ using Gridap, LevelSetTopOpt """ (Serial) Minimum hyperelastic (neohookean) compliance with augmented Lagrangian method in 2D. -""" -function main() +""" +function main(path="./results/hyperelastic_compliance_neohook_ALM/") ## Parameters order = 1 xmax,ymax=2.0,1.0 @@ -17,9 +17,8 @@ function main() η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.6 - path = dirname(dirname(@__DIR__))*"/results/hyperelastic_compliance_neohook_ALM/" iter_mod = 10 - mkdir(path) + mkpath(path) ## FE Setup model = CartesianDiscreteModel(dom,el_size); @@ -95,7 +94,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) diff --git a/scripts/Serial/inverse_homenisation_ALM.jl b/scripts/Serial/inverse_homenisation_ALM.jl index 0ffdd411..d06b2d47 100644 --- a/scripts/Serial/inverse_homenisation_ALM.jl +++ b/scripts/Serial/inverse_homenisation_ALM.jl @@ -7,10 +7,10 @@ using Gridap, LevelSetTopOpt Min J(Ω) = -κ(Ω) Ω s.t., Vol(Ω) = vf, - ⎡For unique εᴹᵢ, find uᵢ∈V=H¹ₚₑᵣ(Ω)ᵈ, + ⎡For unique εᴹᵢ, find uᵢ∈V=H¹ₚₑᵣ(Ω)ᵈ, ⎣∫ ∑ᵢ C ⊙ ε(uᵢ) ⊙ ε(vᵢ) dΩ = ∫ -∑ᵢ C ⊙ ε⁰ᵢ ⊙ ε(vᵢ) dΩ, ∀v∈V. -""" -function main() +""" +function main(path="./results/inverse_homenisation_ALM/") ## Parameters order = 1 xmax,ymax=(1.0,1.0) @@ -24,9 +24,8 @@ function main() η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.5 - path = dirname(dirname(@__DIR__))*"/results/inverse_homenisation_ALM/" iter_mod = 10 - mkdir(path) + mkpath(path) ## FE Setup model = CartesianDiscreteModel(dom,el_size,isperiodic=(true,true)) @@ -81,7 +80,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) diff --git a/scripts/Serial/inverter_ALM.jl b/scripts/Serial/inverter_ALM.jl index 132a32e3..f9a8e3be 100644 --- a/scripts/Serial/inverter_ALM.jl +++ b/scripts/Serial/inverter_ALM.jl @@ -7,14 +7,14 @@ using Gridap, LevelSetTopOpt Min J(Ω) = ηᵢₙ*∫ u⋅e₁ dΓᵢₙ/Vol(Γᵢₙ) Ω s.t., Vol(Ω) = vf, - C(Ω) = 0, - ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, + C(Ω) = 0, + ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ + ∫ kₛv⋅u dΓₒᵤₜ = ∫ v⋅g dΓᵢₙ , ∀v∈V. - + where C(Ω) = ∫ -u⋅e₁-δₓ dΓₒᵤₜ/Vol(Γₒᵤₜ). We assume symmetry in the problem to aid convergence. -""" -function main() +""" +function main(path="./results/inverter_ALM/") ## Parameters order = 1 dom = (0,1,0,0.5) @@ -30,10 +30,9 @@ function main() δₓ = 0.2 ks = 0.1 g = VectorValue(0.5,0) - path = dirname(dirname(@__DIR__))*"/results/inverter_ALM/" iter_mod = 10 - mkdir(path) - + mkpath(path) + ## FE Setup model = CartesianDiscreteModel(dom,el_size) el_Δ = get_el_Δ(model) @@ -96,7 +95,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol,:UΓ_out]) diff --git a/scripts/Serial/inverter_HPM.jl b/scripts/Serial/inverter_HPM.jl index 39ed22a0..2274a2f4 100644 --- a/scripts/Serial/inverter_HPM.jl +++ b/scripts/Serial/inverter_HPM.jl @@ -7,14 +7,14 @@ using Gridap, LevelSetTopOpt Min J(Ω) = ηᵢₙ*∫ u⋅e₁ dΓᵢₙ/Vol(Γᵢₙ) Ω s.t., Vol(Ω) = vf, - C(Ω) = 0, - ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, + C(Ω) = 0, + ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ + ∫ kₛv⋅u dΓₒᵤₜ = ∫ v⋅g dΓᵢₙ , ∀v∈V. - + where C(Ω) = ∫ -u⋅e₁-δₓ dΓₒᵤₜ/Vol(Γₒᵤₜ). We assume symmetry in the problem to aid convergence. -""" -function main() +""" +function main(path="./results/inverter_HPM/") ## Parameters order = 1 dom = (0,1,0,0.5) @@ -30,10 +30,9 @@ function main() δₓ = 0.2 ks = 0.1 g = VectorValue(0.5,0) - path = dirname(dirname(@__DIR__))*"/results/inverter_HPM/" iter_mod = 10 - mkdir(path) - + mkpath(path) + ## FE Setup model = CartesianDiscreteModel(dom,el_size) el_Δ = get_el_Δ(model) @@ -97,7 +96,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser ls_enabled=false # Setting to true will use a line search instead of oscillation detection optimiser = HilbertianProjection(pcfs,ls_evo,vel_ext,φh; diff --git a/scripts/Serial/nonlinear_thermal_compliance_ALM.jl b/scripts/Serial/nonlinear_thermal_compliance_ALM.jl index 621060a2..16ffa9b4 100644 --- a/scripts/Serial/nonlinear_thermal_compliance_ALM.jl +++ b/scripts/Serial/nonlinear_thermal_compliance_ALM.jl @@ -9,10 +9,10 @@ using Gridap, LevelSetTopOpt s.t., Vol(Ω) = vf, ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ(u)*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. - + In this example κ(u) = κ0*(exp(ξ*u)) -""" -function main() +""" +function main(path="./results/nonlinear_thermal_compliance_ALM/") ## Parameters order = 1 xmax=ymax=1.0 @@ -27,16 +27,15 @@ function main() η_coeff = 2 α_coeff = 4max_steps*γ vf = 0.4 - path = dirname(dirname(@__DIR__))*"/results/nonlinear_thermal_compliance_ALM/" iter_mod = 10 - mkdir(path) + mkpath(path) ## FE Setup model = CartesianDiscreteModel(dom,el_size); el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || + f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())); - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= + f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()); update_labels!(1,model,f_Γ_D,"Gamma_D") update_labels!(2,model,f_Γ_N,"Gamma_N") @@ -84,7 +83,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) diff --git a/scripts/Serial/thermal_compliance_ALM.jl b/scripts/Serial/thermal_compliance_ALM.jl index 9cd0883e..1201db0d 100644 --- a/scripts/Serial/thermal_compliance_ALM.jl +++ b/scripts/Serial/thermal_compliance_ALM.jl @@ -9,8 +9,8 @@ using Gridap, LevelSetTopOpt s.t., Vol(Ω) = vf, ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. -""" -function main() +""" +function main(path="./results/thermal_compliance_ALM/") ## Parameters order = 1 xmax=ymax=1.0 @@ -26,16 +26,15 @@ function main() vf = 0.4 η_coeff = 2 α_coeff = 4max_steps*γ - path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM/" iter_mod = 10 - mkdir(path) + mkpath(path) ## FE Setup model = CartesianDiscreteModel(dom,el_size); el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || + f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= + f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) update_labels!(1,model,f_Γ_D,"Gamma_D") update_labels!(2,model,f_Γ_N,"Gamma_N") @@ -82,7 +81,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) diff --git a/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl b/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl index 1cbc6344..3db4ea46 100644 --- a/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl +++ b/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl @@ -3,8 +3,8 @@ using Gridap, LevelSetTopOpt """ (Serial) Minimum thermal compliance with augmented Lagrangian method in 2D. - This problem uses a higher order level set function than the FE solution for - the state equation. In future, second order upwind schemes will require a + This problem uses a higher order level set function than the FE solution for + the state equation. In future, second order upwind schemes will require a higher order FE function. Optimisation problem: @@ -13,8 +13,8 @@ using Gridap, LevelSetTopOpt s.t., Vol(Ω) = vf, ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. -""" -function main() +""" +function main(path="./results/thermal_compliance_ALM_higherorderlsf/") ## Parameters fe_order = 1 order = 2 @@ -31,16 +31,15 @@ function main() vf = 0.4 η_coeff = 2 α_coeff = 4max_steps*γ - path = dirname(dirname(@__DIR__))*"/results/thermal_compliance_ALM_higherorderlsf/" iter_mod = 10 - mkdir(path) + mkpath(path) ## FE Setup model = CartesianDiscreteModel(dom,el_size); el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || + f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= + f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) update_labels!(1,model,f_Γ_D,"Gamma_D") update_labels!(2,model,f_Γ_N,"Gamma_N") @@ -88,7 +87,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) diff --git a/scripts/_dev/3d_hyperelastic_compliance_ALM.jl b/scripts/_dev/3d_hyperelastic_compliance_ALM.jl deleted file mode 100644 index ddc16243..00000000 --- a/scripts/_dev/3d_hyperelastic_compliance_ALM.jl +++ /dev/null @@ -1,203 +0,0 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR -using GridapSolvers: NewtonSolver - -function main(mesh_partition,distribute,el_size,δₓ) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - - ## Parameters - order = 1 - xmax,ymax,zmax=(1.0,1.0,1.0) - dom = (0,xmax,0,ymax,0,zmax) - η_coeff = 2 - prop_Γ_N = 0.2; - path = dirname(dirname(@__DIR__))*"/results/testing_hyper_elast" - i_am_main(ranks) && ~isdir(path) && mkdir(path) - - ## FE Setup - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size) - el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0) - f_Γ_N(x) = (x[1] ≈ xmax) && (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) && - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - - ## Triangulations and measures - Ω = Triangulation(model) - dΩ = Measure(Ω,2order) - - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D","Gamma_N"]) - U = TrialFESpace(V,[VectorValue(0.0,0.0,0.0),VectorValue(δₓ,0.0,0.0)]) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - - ## Create FE functions - # φh = interpolate(initial_lsf(4,0.2),V_φ) - φh = interpolate(x->-1,V_φ) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - ## Material properties and loading - _E = 1000 - ν = 0.3 - μ, λ = _E/(2*(1 + ν)), _E*ν/((1 + ν)*(1 - 2*ν)) - - ## Saint Venant–Kirchhoff law - F(∇u) = one(∇u) + ∇u' - E(F) = 0.5*( F' ⋅ F - one(F) ) - Σ(∇u) = λ*tr(E(F(∇u)))*one(∇u)+2*μ*E(F(∇u)) - T(∇u) = F(∇u) ⋅ Σ(∇u) - res(u,v,φ,dΩ) = ∫((I ∘ φ)*((T ∘ ∇(u)) ⊙ ∇(v)))dΩ - - ## Setup solver and FE operators - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - lin_solver = MUMPSSolver() - nl_solver = NewtonSolver(lin_solver;maxiter=50,rtol=10^-8,verbose=i_am_main(ranks)) - - state_map = NonlinearFEStateMap( - res,U,V,V_φ,U_reg,φh,dΩ; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - nls = nl_solver, adjoint_ls = lin_solver - ) - - ## Optimiser - u = LevelSetTopOpt.forward_solve!(state_map,φh) - uh = FEFunction(U,u) - writevtk(Ω,path*"/struc_$δₓ",cellfields=["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -function main_alt(mesh_partition,distribute,el_size,gz) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - - ## Parameters - order = 1 - xmax,ymax,zmax=(2.0,1.0,1.0) - dom = (0,xmax,0,ymax,0,zmax) - η_coeff = 2 - prop_Γ_N = 0.8; - γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/3) - tol = 1/(5order^2)/minimum(el_size) - path = dirname(dirname(@__DIR__))*"/results/testing_hyper_elast" - i_am_main(ranks) && ~isdir(path) && mkdir(path) - - ## FE Setup - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size) - el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0) - f_Γ_N(x) = (x[1] ≈ xmax) && (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) && - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - - ## Create FE functions - # φh = interpolate(initial_lsf(4,0.2),V_φ) - φh = interpolate(x->-1,V_φ) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - ## Material properties and loading - _E = 1000 - ν = 0.3 - μ, λ = _E/(2*(1 + ν)), _E*ν/((1 + ν)*(1 - 2*ν)) - g = VectorValue(-gz,0,0) - - # Deformation gradient - # F(∇u) = one(∇u) + ∇u' - # J(F) = sqrt(det(C(F))) - # # Derivative of green Strain - # dE(∇du,∇u) = 0.5*( ∇du⋅F(∇u) + (∇du⋅F(∇u))' ) - # # Right Caughy-green deformation tensor - # C(F) = (F')⋅F - # # Constitutive law (Neo hookean) - # function S(∇u) - # Cinv = inv(C(F(∇u))) - # μ*(one(∇u)-Cinv) + λ*log(J(F(∇u)))*Cinv - # end - # # Cauchy stress tensor - # σ(∇u) = (1.0/J(F(∇u)))*F(∇u)⋅S(∇u)⋅(F(∇u))' - # res(u,v,φ,dΩ,dΓ_N) = ∫( (I ∘ φ)*((dE∘(∇(v),∇(u))) ⊙ (S∘∇(u))) )*dΩ - ∫(g⋅v)dΓ_N - - # ALT - F(∇u) = one(∇u) + ∇u' - E(F) = 0.5*( F' ⋅ F - one(F) ) - Σ(∇u) = λ*tr(E(F(∇u)))*one(∇u)+2*μ*E(F(∇u)) - T(∇u) = F(∇u) ⋅ Σ(∇u) - res(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*((T ∘ ∇(u)) ⊙ ∇(v)))dΩ - ∫(g⋅v)dΓ_N - - ## Finite difference solver and level set function - # ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) - # reinit!(stencil,φh,γ_reinit) - - ## Setup solver and FE operators - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - lin_solver = MUMPSSolver() - nl_solver = NewtonSolver(lin_solver;maxiter=50,rtol=10^-8,verbose=i_am_main(ranks)) - - state_map = NonlinearFEStateMap( - res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - nls = nl_solver, adjoint_ls = lin_solver - ) - - ## Optimiser - u = LevelSetTopOpt.forward_solve!(state_map,φh) - uh = FEFunction(U,u) - writevtk(Ω,path*"/struc_neohook_$gz",cellfields=["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -with_mpi() do distribute - mesh_partition = (2,2,2) - el_size = (43,43,43) - # solver = "-pc_type jacobi -ksp_type cg -ksp_monitor_short - # -ksp_converged_reason -ksp_rtol 1.0e-3 -mat_block_size 3" - # solver = "-pc_type mg -mg_levels_ksp_max_it 2 -snes_monitor_short -ksp_monitor_short -npc_snes_type fas - # -npc_fas_levels_snes_type ncg -npc_fas_levels_snes_max_it 3 -npc_snes_monitor_short -snes_max_it 2" - # solver = "-snes_type aspin -snes_monitor_short -ksp_monitor_short -npc_sub_snes_rtol 1e-2 -ksp_rtol 1e-2 -ksp_max_it 14 - # -snes_converged_reason -snes_max_linear_solve_fail 100 -snes_max_it 4 -npc_sub_ksp_type preonly -npc_sub_pc_type lu" - # solver = "-snes_rtol 1e-05 -snes_monitor_short -snes_converged_reason - # -ksp_type fgmres -ksp_rtol 1e-10 -ksp_monitor_short -ksp_converged_reason - # -pc_type fieldsplit -pc_fieldsplit_type schur -pc_fieldsplit_schur_factorization_type upper - # -fieldsplit_deformation_ksp_type preonly -fieldsplit_deformation_pc_type lu - # -fieldsplit_pressure_ksp_rtol 1e-10 -fieldsplit_pressure_pc_type jacobi" - - GridapPETSc.with() do #args=split(solver)) do - # main(mesh_partition,distribute,el_size,0.02) - # main(mesh_partition,distribute,el_size,0.05) - main(mesh_partition,distribute,el_size,0.1) - # main_alt(mesh_partition,distribute,el_size,-20) - # main_alt(mesh_partition,distribute,el_size,-50) - # main_alt(mesh_partition,distribute,el_size,-100) - # main_alt(mesh_partition,distribute,el_size,-150) - end -end \ No newline at end of file diff --git a/scripts/_dev/OptimiserHistoryTests.jl b/scripts/_dev/OptimiserHistoryTests.jl deleted file mode 100644 index 4e4b64a8..00000000 --- a/scripts/_dev/OptimiserHistoryTests.jl +++ /dev/null @@ -1,8 +0,0 @@ - -using LevelSetTopOpt - -h = LevelSetTopOpt.OptimiserHistory(Float64,[:L,:J,:C1,:C2,:C3],Dict(:C => [:C1,:C2,:C3]),100,true) - -push!(h,(1.0,2.0,3.0,4.0,5.0)) - -write_history("results/tmp.txt",h) \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl deleted file mode 100644 index f3e23201..00000000 --- a/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl +++ /dev/null @@ -1,105 +0,0 @@ -using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, - SparseMatricesCSR - -function main(mesh_partition,distribute,write_dir) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - # FE parameters - order = 1 # Finite element order - xmax,ymax,zmax = (2.0,1.0,1.0) # Domain size - dom = (0,xmax,0,ymax,0,zmax) # Bounding domain - el_size = (160,80,80) # Mesh partition size - prop_Γ_N = 0.2 # Γ_N size parameter - f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function - (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0) # Γ_D indicator function - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance - # Problem parameters - C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor - g = VectorValue(0,0,-1) # Applied load on Γ_N - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - iter_mod = 10 # VTK Output modulo - path = "$write_dir/elast_comp_MPI_3D/" # Output path - i_am_main(ranks) && mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(v⋅g)dΓ_N - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - solver = ElasticitySolver(V) - state_map = AffineFEStateMap( - a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver,adjoint_ls = solver - ) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(u)))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫((C ⊙ ε(u) ⊙ ε(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - vol_D = sum(∫(1)dΩ) - C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C1],state_map, - analytic_dJ=dJ,analytic_dC=[dC1]) - # Velocity extension - α = 4max_steps*γ*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = PETScLinearSolver() - ) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, - verbose=i_am_main(ranks)) - # Solve - for (it,uh,φh) in optimiser - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) - write_history(path*"/history.txt",get_history(optimiser);ranks) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, - "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -with_mpi() do distribute - mesh_partition = (4,6,6) - write_dir = ARGS[1] - solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute,write_dir) - end -end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl deleted file mode 100644 index d164c73d..00000000 --- a/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl +++ /dev/null @@ -1,121 +0,0 @@ -using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, - SparseMatricesCSR - -using GridapSolvers: NewtonSolver - -function main(mesh_partition,distribute,write_dir) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - # FE parameters - order = 1 # Finite element order - xmax,ymax,zmax = (2.0,1.0,1.0) # Domain size - dom = (0,xmax,0,ymax,0,zmax) # Bounding domain - el_size = (160,80,80) # Mesh partition size - prop_Γ_N = 0.2 # Γ_N size parameter - f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function - (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0) # Γ_D indicator function - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance - # Problem parameters - E = 1000 # Young's modulus - ν = 0.3 # Poisson's ratio - μ, λ = E/(2*(1 + ν)), E*ν/((1 + ν)*(1 - 2*ν)) # Lame constants - g = VectorValue(0,0,-1) # Applied load on Γ_N - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - iter_mod = 10 # VTK Output modulo - path = "$write_dir/hyperelast_comp_MPI_3D/" # Output path - i_am_main(ranks) && mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - ## Piola-Kirchhoff tensor - function S(∇u) - Cinv = inv(C(F(∇u))) - μ*(one(∇u)-Cinv) + λ*log(J(F(∇u)))*Cinv - end - ## Derivative of Green strain - dE(∇du,∇u) = 0.5*( ∇du⋅F(∇u) + (∇du⋅F(∇u))' ) - ## Right Cauchy-Green deformation tensor - C(F) = (F')⋅F - ## Deformation gradient tensor - F(∇u) = one(∇u) + ∇u' - ## Volume change - J(F) = sqrt(det(C(F))) - ## Residual - res(u,v,φ,dΩ,dΓ_N) = ∫( (I ∘ φ)*((dE ∘ (∇(v),∇(u))) ⊙ (S ∘ ∇(u))) )*dΩ - ∫(g⋅v)dΓ_N - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - lin_solver = ElasticitySolver(V) - nl_solver = NewtonSolver(lin_solver;maxiter=50,rtol=10^-8,verbose=i_am_main(ranks)) - state_map = NonlinearFEStateMap( - res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - nls = nl_solver, adjoint_ls = lin_solver - ) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*((dE ∘ (∇(u),∇(u))) ⊙ (S ∘ ∇(u))))dΩ - vol_D = sum(∫(1)dΩ) - C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C1],state_map,analytic_dC=[dC1]) - # Velocity extension - α = 4max_steps*γ*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = PETScLinearSolver() - ) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, - verbose=i_am_main(ranks)) - # Solve - for (it,uh,φh) in optimiser - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) - write_history(path*"/history.txt",get_history(optimiser);ranks) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, - "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -with_mpi() do distribute - mesh_partition = (4,6,6) - write_dir = ARGS[1] - solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute,write_dir) - end -end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl deleted file mode 100644 index 83175010..00000000 --- a/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl +++ /dev/null @@ -1,108 +0,0 @@ -using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, - SparseMatricesCSR - -function main(mesh_partition,distribute,write_dir) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - # FE parameters - order = 1 # Finite element order - xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size - dom = (0,xmax,0,ymax,0,zmax) # Bounding domain - el_size = (100,100,100) # Mesh partition size - f_Γ_D(x) = iszero(x) # Γ_D indicator function - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance - # Problem parameters - C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor - vf = 0.4 # Volume fraction constraint - lsf_func(x) = cos(2π*x[1]) + cos(2π*x[2]) + # Initial level set function - cos(2π*x[3]) - iter_mod = 10 # VTK Output modulo - path = "$write_dir/inverse_hom_MPI_3D/" # Output path - i_am_main(ranks) && mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true,true)); - update_labels!(1,model,f_Γ_D,"origin") - # Triangulation and measures - Ω = Triangulation(model) - dΩ = Measure(Ω,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["origin"]) - U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar) - U_reg = TrialFESpace(V_reg) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - εᴹ = (TensorValue(1.,0.,0.,0.,0.,0.,0.,0.,0.), - TensorValue(0.,0.,0.,0.,1.,0.,0.,0.,0.), - TensorValue(0.,0.,0.,0.,0.,0.,0.,0.,1.), - TensorValue(0.,0.,0.,0.,0.,1/2,0.,1/2,0.), - TensorValue(0.,0.,1/2,0.,0.,0.,1/2,0.,0.), - TensorValue(0.,1/2,0.,1/2,0.,0.,0.,0.,0.)) - a(u,v,φ,dΩ) = ∫((I ∘ φ) * C ⊙ ε(u) ⊙ ε(v))dΩ - l = [(v,φ,dΩ) -> ∫(-(I ∘ φ) * C ⊙ εᴹ[i] ⊙ ε(v))dΩ for i in 1:6] - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - solver = ElasticitySolver(V) - state_map = RepeatingAffineFEStateMap( - 6,a,l,U,V,V_φ,U_reg,φh,dΩ; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver, adjoint_ls = solver - ) - # Objective and constraints - Cᴴ(r,s,u,φ,dΩ) = ∫((I ∘ φ)*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ εᴹ[s]))dΩ - dCᴴ(r,s,q,u,φ,dΩ) = ∫(-q*(C ⊙ (ε(u[r])+εᴹ[r]) ⊙ (ε(u[s])+εᴹ[s]))*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - κ(u,φ,dΩ) = -1/9*(Cᴴ(1,1,u,φ,dΩ)+Cᴴ(2,2,u,φ,dΩ)+Cᴴ(3,3,u,φ,dΩ)+ - 2*(Cᴴ(1,2,u,φ,dΩ)+Cᴴ(1,3,u,φ,dΩ)+Cᴴ(2,3,u,φ,dΩ))) - dκ(q,u,φ,dΩ) = -1/9*(dCᴴ(1,1,q,u,φ,dΩ)+dCᴴ(2,2,q,u,φ,dΩ)+dCᴴ(3,3,q,u,φ,dΩ)+ - 2*(dCᴴ(1,2,q,u,φ,dΩ)+dCᴴ(1,3,q,u,φ,dΩ)+dCᴴ(2,3,q,u,φ,dΩ))) - vol_D = sum(∫(1)dΩ) - C1(u,φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC1(q,u,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(κ,[C1],state_map, - analytic_dJ=dκ,analytic_dC=[dC1]) - # Velocity extension - α = 4max_steps*γ*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = PETScLinearSolver() - ) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, - verbose=i_am_main(ranks)) - # Solve - for (it,uh,φh) in optimiser - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))] - iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) - write_history(path*"/history.txt",get_history(optimiser);ranks) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, - "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))]) -end - -with_mpi() do distribute - mesh_partition = (4,6,6) - write_dir = ARGS[1] - solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute,write_dir) - end -end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl b/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl deleted file mode 100644 index 5ecde638..00000000 --- a/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl +++ /dev/null @@ -1,120 +0,0 @@ -using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, - SparseMatricesCSR - -function main(mesh_partition,distribute,write_dir) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - # FE parameters - order = 1 # Finite element order - xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size - dom = (0,xmax,0,ymax,0,zmax) # Bounding domain - el_size = (100,100,100) # Mesh partition size - f_Γ_in(x) = (x[1] ≈ 0.0) && # Γ_in indicator function - (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) - f_Γ_out(x) = (x[1] ≈ 1.0) && # Γ_out indicator function - (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) - f_Γ_out_ext(x) = ~f_Γ_out(x) && # Γ_out_ext indicator function - (0.9 <= x[1] <= 1.0) && (0.35 - eps() <= x[2] <= 0.65 + eps()) && - (0.35 - eps() <= x[3] <= 0.65 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function - (x[2] <= 0.1 || x[2] >= 0.9) && (x[3] <= 0.1 || x[3] >= 0.9) - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance - # Problem parameters - C = isotropic_elast_tensor(3,1.,0.3) # Stiffness tensor - g = VectorValue(1,0,0) # Applied load on Γ_N - ks = 0.01 # Artificial spring stiffness - δₓ = 0.4 # Required displacement - vf = 0.4 # Volume fraction constraint - sphere(x,(xc,yc,zc)) = -sqrt((x[1]-xc)^2+(x[2]-yc)^2+(x[3]-zc)^2) + 0.2 - lsf_func(x) = max(initial_lsf(4,0.2)(x), # Initial level set function - sphere(x,(1,0,0)),sphere(x,(1,0,1)),sphere(x,(1,1,0)),sphere(x,(1,1,1))) - iter_mod = 10 # VTK Output modulo - path = "$write_dir/inverter_MPI_3D/" # Output path - i_am_main(ranks) && mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - update_labels!(1,model,f_Γ_in,"Gamma_in") - update_labels!(2,model,f_Γ_out,"Gamma_out") - update_labels!(3,model,f_Γ_out_ext,"Gamma_out_ext") - update_labels!(4,model,f_Γ_D,"Gamma_D") - # Triangulation and measures - Ω = Triangulation(model) - Γ_in = BoundaryTriangulation(model,tags="Gamma_in") - Γ_out = BoundaryTriangulation(model,tags="Gamma_out") - dΩ = Measure(Ω,2*order) - dΓ_in = Measure(Γ_in,2*order) - dΓ_out = Measure(Γ_out,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=[ - "Gamma_in","Gamma_out","Gamma_out_ext"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ); - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_in,dΓ_out) = ∫((I ∘ φ)*(C ⊙ ε(u) ⊙ ε(v)))dΩ + ∫(ks*(u⋅v))dΓ_out - l(v,φ,dΩ,dΓ_in,dΓ_out) = ∫(v⋅g)dΓ_in - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - solver = ElasticitySolver(V) - state_map = AffineFEStateMap( - a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver,adjoint_ls = solver - ) - # Objective and constraints - e₁ = VectorValue(1,0,0) - vol_Γ_in = sum(∫(1)dΓ_in) - vol_Γ_out = sum(∫(1)dΓ_out) - vol_D = sum(∫(1)dΩ) - J(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅e₁)/vol_Γ_in)dΓ_in - C1(u,φ,dΩ,dΓ_in,dΓ_out) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC1(q,u,φ,dΩ,dΓ_in,dΓ_out) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - C2(u,φ,dΩ,dΓ_in,dΓ_out) = ∫((u⋅-e₁-δₓ)/vol_Γ_out)dΓ_out - pcfs = PDEConstrainedFunctionals(J,[C1,C2],state_map,analytic_dC=[dC1,nothing]) - # Velocity extension - α = 4max_steps*γ*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = PETScLinearSolver() - ) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, - verbose=i_am_main(ranks)) - # Solve - for (it,uh,φh) in optimiser - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) - write_history(path*"/history.txt",get_history(optimiser);ranks) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, - "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -with_mpi() do distribute - mesh_partition = (4,6,6) - write_dir = ARGS[1] - solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute,write_dir) - end -end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs deleted file mode 100644 index 9fb3b55b..00000000 --- a/scripts/_dev/Paper_scripts/jobs-gadi/elast_comp_MPI_3D.pbs +++ /dev/null @@ -1,15 +0,0 @@ -#!/bin/bash -l -#PBS -P np01 -#PBS -q normal -#PBS -N elast_comp_MPI_3D -#PBS -l ncpus=144 -#PBS -l mem=576GB -#PBS -l walltime=10:00:00 -#PBS -j oe - -source $HOME/hpc-environments/gadi/load-intel.sh -PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ - -mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl \ - $PROJECT_DIR/results diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs deleted file mode 100644 index f9b7897f..00000000 --- a/scripts/_dev/Paper_scripts/jobs-gadi/hyperelast_comp_MPI_3D.pbs +++ /dev/null @@ -1,15 +0,0 @@ -#!/bin/bash -l -#PBS -P np01 -#PBS -q normal -#PBS -N hyperelast_comp_MPI_3D -#PBS -l ncpus=144 -#PBS -l mem=576GB -#PBS -l walltime=10:00:00 -#PBS -j oe - -source $HOME/hpc-environments/gadi/load-intel.sh -PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ - -mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl \ - $PROJECT_DIR/results diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs deleted file mode 100644 index 9cbe2ad9..00000000 --- a/scripts/_dev/Paper_scripts/jobs-gadi/inverse_hom_MPI_3D.pbs +++ /dev/null @@ -1,15 +0,0 @@ -#!/bin/bash -l -#PBS -P np01 -#PBS -q normal -#PBS -N inverse_hom_MPI_3D -#PBS -l ncpus=144 -#PBS -l mem=576GB -#PBS -l walltime=24:00:00 -#PBS -j oe - -source $HOME/hpc-environments/gadi/load-intel.sh -PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ - -mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl \ - $PROJECT_DIR/results diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs deleted file mode 100644 index d16868d7..00000000 --- a/scripts/_dev/Paper_scripts/jobs-gadi/inverter_MPI_3D.pbs +++ /dev/null @@ -1,15 +0,0 @@ -#!/bin/bash -l -#PBS -P np01 -#PBS -q normal -#PBS -N inverter_MPI_3D -#PBS -l ncpus=144 -#PBS -l mem=576GB -#PBS -l walltime=16:00:00 -#PBS -j oe - -source $HOME/hpc-environments/gadi/load-intel.sh -PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ - -mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl \ - $PROJECT_DIR/results diff --git a/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs deleted file mode 100644 index d859dc27..00000000 --- a/scripts/_dev/Paper_scripts/jobs-gadi/therm_comp_MPI_3D.pbs +++ /dev/null @@ -1,15 +0,0 @@ -#!/bin/bash -l -#PBS -P np01 -#PBS -q normal -#PBS -N therm_comp_MPI_3D -#PBS -l ncpus=144 -#PBS -l mem=576GB -#PBS -l walltime=3:00:00 -#PBS -j oe - -source $HOME/hpc-environments/gadi/load-intel.sh -PROJECT_DIR=$SCRATCH/LevelSetTopOpt/ - -mpirun -n 144 julia --project=$PROJECT_DIR --check-bounds no -O3 \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl \ - $PROJECT_DIR/results diff --git a/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs deleted file mode 100644 index b257f199..00000000 --- a/scripts/_dev/Paper_scripts/jobs/elast_comp_MPI_3D.pbs +++ /dev/null @@ -1,20 +0,0 @@ -#!/bin/bash -l - -#PBS -P LSTO -#PBS -N elast_comp_MPI_3D - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/elast_comp_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs deleted file mode 100644 index c2fd001a..00000000 --- a/scripts/_dev/Paper_scripts/jobs/hyperelast_comp_MPI_3D.pbs +++ /dev/null @@ -1,20 +0,0 @@ -#!/bin/bash -l - -#PBS -P LSTO -#PBS -N hyperelast_comp_MPI_3D - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/hyperelast_comp_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs deleted file mode 100644 index e56cd3d1..00000000 --- a/scripts/_dev/Paper_scripts/jobs/inverse_hom_MPI_3D.pbs +++ /dev/null @@ -1,20 +0,0 @@ -#!/bin/bash -l - -#PBS -P LSTO -#PBS -N inverse_hom_MPI_3D - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/inverse_hom_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs deleted file mode 100644 index a2c4e55c..00000000 --- a/scripts/_dev/Paper_scripts/jobs/inverter_MPI_3D.pbs +++ /dev/null @@ -1,20 +0,0 @@ -#!/bin/bash -l - -#PBS -P LSTO -#PBS -N inverter_MPI_3D - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/inverter_MPI_3D.jl diff --git a/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs b/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs deleted file mode 100644 index 775f4a00..00000000 --- a/scripts/_dev/Paper_scripts/jobs/therm_comp_MPI_3D.pbs +++ /dev/null @@ -1,20 +0,0 @@ -#!/bin/bash -l - -#PBS -P LSTO -#PBS -N therm_comp_MPI_3D - -#PBS -l select=125:ncpus=1:mpiprocs=1:ompthreads=1:mem=8GB:cputype=6140 -#PBS -l walltime=23:00:00 -#PBS -j oe -#PBS -v I_MPI_HYDRA_BOOTSTRAP=rsh -#PBS -v I_MPI_HYDRA_BOOTSTRAP_EXEC=pbs_tmrsh -#PBS -v I_MPI_HYDRA_IFACE=ib0 -#PBS -v OMP_NUM_THREADS=1 - -source $HOME/hpc-environments-main/lyra/load-intel.sh -PROJECT_DIR=$HOME/LevelSetTopOpt/ - -julia --project=$PROJECT_DIR -e "using Pkg; Pkg.precompile()" - -mpirun -n 125 julia --project=$PROJECT_DIR --check-bounds no -O3 --compiled-modules=no \ - $PROJECT_DIR/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/therm_comp_MPI.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI.jl deleted file mode 100644 index a5476e50..00000000 --- a/scripts/_dev/Paper_scripts/therm_comp_MPI.jl +++ /dev/null @@ -1,104 +0,0 @@ -using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, - SparseMatricesCSR - -function main(mesh_partition,distribute,write_dir) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - # FE parameters - order = 1 # Finite element order - xmax,ymax = (1.0,1.0) # Domain size - dom = (0,xmax,0,ymax) # Bounding domain - el_size = (200,200) # Mesh partition size - prop_Γ_N = 0.2 # Γ_N size parameter - prop_Γ_D = 0.2 # Γ_D size parameter - f_Γ_N(x) = (x[1] ≈ xmax && # Γ_N indicator function - ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0 && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,order*minimum(el_size)/10)# Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance - # Problem parameters - κ = 1 # Diffusivity - g = 1 # Heat flow in - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - iter_mod = 10 # VTK Output modulo - path = "$write_dir/results/therm_comp_MPI/" # Output path - i_am_main(ranks) && mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe) - V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - solver = PETScLinearSolver() - state_map = AffineFEStateMap( - a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver,adjoint_ls = solver - ) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - vol_D = sum(∫(1)dΩ) - C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C1],state_map, - analytic_dJ=dJ,analytic_dC=[dC1]) - # Velocity extension - α = 4max_steps*γ*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = solver - ) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=i_am_main(ranks)) - # Solve - for (it,uh,φh) in optimiser - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) - write_history(path*"/history.txt",get_history(optimiser);ranks) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, - "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -with_mpi() do distribute - mesh_partition = (2,2) - write_dir = ARGS[1] - solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute,write_dir) - end -end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl b/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl deleted file mode 100644 index be63b8db..00000000 --- a/scripts/_dev/Paper_scripts/therm_comp_MPI_3D.jl +++ /dev/null @@ -1,107 +0,0 @@ -using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, - SparseMatricesCSR - -function main(mesh_partition,distribute,write_dir) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - # FE parameters - order = 1 # Finite element order - xmax,ymax,zmax = (1.0,1.0,1.0) # Domain size - dom = (0,xmax,0,ymax,0,zmax) # Bounding domain - el_size = (150,150,150) # Mesh partition size - prop_Γ_N = 0.2 # Γ_N size parameter - prop_Γ_D = 0.2 # Γ_D size parameter - f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function - (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps())&& - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps()) && - (x[3] <= zmax*prop_Γ_D + eps() || x[3] >= zmax-zmax*prop_Γ_D - eps()) - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,order*minimum(el_size)/5) # Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance - # Problem parameters - κ = 1 # Diffusivity - g = 1 # Heat flow in - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - iter_mod = 10 # VTK Output modulo - path = "$write_dir/therm_comp_MPI_3D/" # Output path - i_am_main(ranks) && mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe) - V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - solver = PETScLinearSolver() - state_map = AffineFEStateMap( - a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver,adjoint_ls = solver - ) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - vol_D = sum(∫(1)dΩ) - C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C1],state_map, - analytic_dJ=dJ,analytic_dC=[dC1]) - # Velocity extension - α = 4max_steps*γ*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = solver - ) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, - verbose=i_am_main(ranks)) - # Solve - for (it,uh,φh) in optimiser - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) - write_history(path*"/history.txt",get_history(optimiser);ranks) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, - "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -with_mpi() do distribute - mesh_partition = (4,6,6) - write_dir = ARGS[1] - solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute,write_dir) - end -end \ No newline at end of file diff --git a/scripts/_dev/Paper_scripts/therm_comp_serial.jl b/scripts/_dev/Paper_scripts/therm_comp_serial.jl deleted file mode 100644 index 69fc7d73..00000000 --- a/scripts/_dev/Paper_scripts/therm_comp_serial.jl +++ /dev/null @@ -1,82 +0,0 @@ -using LevelSetTopOpt, Gridap - -function main(write_dir) - # FE parameters - order = 1 # Finite element order - xmax,ymax = (1.0,1.0) # Domain size - dom = (0,xmax,0,ymax) # Bounding domain - el_size = (200,200) # Mesh partition size - prop_Γ_N = 0.2 # Γ_N size parameter - prop_Γ_D = 0.2 # Γ_D size parameter - f_Γ_N(x) = (x[1] ≈ xmax && # Γ_N indicator function - ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0 && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,order*minimum(el_size)/10)# Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance - # Problem parameters - κ = 1 # Diffusivity - g = 1 # Heat flow in - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - iter_mod = 10 # VTK Output modulo - path = "$write_dir/therm_comp_serial/" # Output path - mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe) - V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N - state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - vol_D = sum(∫(1)dΩ) - C1(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC1(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C1],state_map, - analytic_dJ=dJ,analytic_dC=[dC1]) - # Velocity extension - α = 4max_steps*γ*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit, - verbose=true) - # Solve - for (it,uh,φh) in optimiser - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && writevtk(Ω,path*"out$it",cellfields=data) - write_history(path*"/history.txt",get_history(optimiser)) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, - "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -main("results/") \ No newline at end of file diff --git a/scripts/_dev/benchmark_tests/MPI_benchmark_test_2D_themal.jl b/scripts/_dev/benchmark_tests/MPI_benchmark_test_2D_themal.jl deleted file mode 100644 index 9a0c3e3f..00000000 --- a/scripts/_dev/benchmark_tests/MPI_benchmark_test_2D_themal.jl +++ /dev/null @@ -1,108 +0,0 @@ -using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, LevelSetTopOpt - -""" -(MPI) Minimum thermal compliance with Lagrangian method in 2D. - -Optimisation problem: - Min J(Ω) = ∫ D*∇(u)⋅∇(u) + ξ dΩ - Ω - s.t., ⎡u∈V=H¹(Ω;u(Γ_D)=0), - ⎣∫ D*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. -""" -function main(mesh_partition,el_size,ranks) - ## Parameters - order = 1 - xmax=ymax=1.0 - prop_Γ_N = 0.2 - prop_Γ_D = 0.2 - dom = (0,xmax,0,ymax) - γ = 0.1 - γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) - tol = 1/(order^2*10)/minimum(el_size) - D = 1 - η_coeff = 2 - α_coeff = 4 - - ## FE Setup - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0) && ((x[2] <= ymax*prop_Γ_D + eps()) || (x[2] >= ymax-ymax*prop_Γ_D - eps())) - f_Γ_N(x) = (x[1] ≈ xmax) && (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - - ## Spaces - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - - ## Create FE functions - φh = interpolate(initial_lsf(4,0.2),V_φ) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*D*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(v)dΓ_N - - ## Optimisation functionals - ξ = 0.3 - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*D*∇(u)⋅∇(u) + ξ*(ρ ∘ φ))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫((-ξ+D*∇(u)⋅∇(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; - - ## Finite difference solver and level set function - ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) - reinit!(stencil,φh,γ_reinit) - - ## Setup solver and FE operators - state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) - pcfs = PDEConstrainedFunctionals(J,state_map,analytic_dJ=dJ) - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(el_Δ) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; - vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - - ## Optimiser - return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit) -end - -with_debug() do distribute - mesh_partition = (2,2) - el_size = (50,50) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - opt = main(mesh_partition,el_size,ranks) - ## Benchmark optimiser - bopt = benchmark_optimizer(opt, 1, ranks) - ## Benchmark forward problem - bfwd = benchmark_forward_problem(opt.problem.state_map, opt.φ0, ranks) - ## Benchmark advection - v = get_free_dof_values(interpolate(FEFunction(LevelSetTopOpt.get_deriv_space(opt.problem.state_map), - opt.problem.dJ),LevelSetTopOpt.get_aux_space(opt.problem.state_map))) - badv = benchmark_advection(opt.stencil, get_free_dof_values(opt.φ0), v, 0.1, ranks) - ## Benchmark reinitialisation - brinit = benchmark_reinitialisation(opt.stencil, get_free_dof_values(opt.φ0), 0.1, ranks) - ## Benchmark velocity extension - bvelext = benchmark_velocity_extension(opt.vel_ext, opt.problem.dJ, ranks) - ## Printing - if i_am_main(ranks) - open("TEST.txt","w") do f - bcontent = "bopt,bfwd,badv,brinit,bvelext\n" - for i ∈ eachindex(bopt) - bcontent *= "$(bopt[i]),$(bfwd[i]),$(badv[i]),$(brinit[i]),$(bvelext[i])\n" - end - write(f,bcontent) - end - end -end \ No newline at end of file diff --git a/scripts/_dev/benchmark_tests/MPI_benchmark_test_3D_themal.jl b/scripts/_dev/benchmark_tests/MPI_benchmark_test_3D_themal.jl deleted file mode 100644 index b04bbac8..00000000 --- a/scripts/_dev/benchmark_tests/MPI_benchmark_test_3D_themal.jl +++ /dev/null @@ -1,134 +0,0 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR - -""" - (MPI) Minimum thermal compliance with Lagrangian method in 3D. - - Optimisation problem: - Min J(Ω) = ∫ D*∇(u)⋅∇(u) + ξ dΩ - Ω - s.t., ⎡u∈V=H¹(Ω;u(Γ_D)=0), - ⎣∫ D*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. -""" -function main(mesh_partition,distribute,el_size) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - - ## Parameters - order = 1 - xmax=ymax=zmax=1.0 - prop_Γ_N = 0.2 - prop_Γ_D = 0.2 - dom = (0,xmax,0,ymax,0,zmax) - γ = 0.1 - γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/3) - tol = 1/(order^2*10)/minimum(el_size) - D = 1 - η_coeff = 2 - α_coeff = 4 - path = dirname(dirname(@__DIR__))*"/results/MPI_main_3d" - - ## FE Setup - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0) && (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps()) && - (x[3] <= zmax*prop_Γ_D + eps() || x[3] >= zmax-zmax*prop_Γ_D - eps()) - f_Γ_N(x) = (x[1] ≈ xmax) && (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) && - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - - ## Spaces - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - - ## Create FE functions - φh = interpolate(initial_lsf(4,0.2),V_φ); - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*D*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(v)dΓ_N - - ## Optimisation functionals - ξ = 0.1 - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*D*∇(u)⋅∇(u) + ξ*(ρ ∘ φ))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫((ξ-D*∇(u)⋅∇(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - - ## Finite difference solver and level set function - ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) - reinit!(stencil,φh,γ_reinit) - - ## Setup solver and FE operators - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - solver = PETScLinearSolver() - - state_map = AffineFEStateMap( - a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver,adjoint_ls = solver - ) - pcfs = PDEConstrainedFunctionals(J,state_map,analytic_dJ=dJ) - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(el_Δ) - a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = solver - ) - - ## Optimiser - make_dir(path;ranks=ranks) - return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit) -end - -with_mpi() do distribute - mesh_partition = (3,3,2) - el_size = (100,100,100) - all_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - - GridapPETSc.with(args=split(all_solver_options)) do - opt = main(mesh_partition,distribute,el_size) - ## Benchmark optimiser - bopt = benchmark_optimizer(opt, 1, nothing) - ## Benchmark forward problem - bfwd = benchmark_forward_problem(opt.problem.state_map, opt.φ0, nothing) - ## Benchmark advection - v = get_free_dof_values(interpolate(FEFunction(LevelSetTopOpt.get_deriv_space(opt.problem.state_map), - opt.problem.dJ),LevelSetTopOpt.get_aux_space(opt.problem.state_map))) - badv = benchmark_advection(opt.stencil, get_free_dof_values(opt.φ0), v, 0.1, nothing) - ## Benchmark reinitialisation - brinit = benchmark_reinitialisation(opt.stencil, get_free_dof_values(opt.φ0), 0.1, nothing) - ## Benchmark velocity extension - bvelext = benchmark_velocity_extension(opt.vel_ext, opt.problem.dJ, nothing) - ## Printing - ranks = distribute(LinearIndices((prod(mesh_partition),))) - if i_am_main(ranks) - println("bopt => $bopt") - println("bfwd => $bfwd") - println("badv => $badv") - println("brinit => $brinit") - println("bvelext => $bvelext") - end - nothing - end -end; - diff --git a/scripts/_dev/benchmark_tests/serial_benchmark_test.jl b/scripts/_dev/benchmark_tests/serial_benchmark_test.jl deleted file mode 100644 index 6ad4eec8..00000000 --- a/scripts/_dev/benchmark_tests/serial_benchmark_test.jl +++ /dev/null @@ -1,101 +0,0 @@ -using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, LevelSetTopOpt - -function main() - ## Parameters - order = 1 - xmax = ymax = 1.0 - prop_Γ_N = 0.2 - prop_Γ_D = 0.2 - dom = (0,xmax,0,ymax) - el_size = (200,200) - γ = 0.1 - γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/10) - tol = 1/(order^2*10)/minimum(el_size) # <- We can do better than this I think - D = 1 - η_coeff = 2 - α_coeff = 4 - - ## FE Setup - model = CartesianDiscreteModel(dom,el_size); - el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || - x[2] >= ymax-ymax*prop_Γ_D - eps())) ? true : false - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= - ymax/2+ymax*prop_Γ_N/2 + eps()) ? true : false - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - - ## Spaces - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - - ## Create FE functions - φh = interpolate(initial_lsf(4,0.2),V_φ) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*D*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(v)dΓ_N - - ## Optimisation functionals - ξ = 0.2; - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*D*∇(u)⋅∇(u) + ξ*(ρ ∘ φ))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫((ξ-D*∇(u)⋅∇(u))*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - - ## Finite difference solver and level set function - ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) - - ## Setup solver and FE operators - state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) - pcfs = PDEConstrainedFunctionals(J,state_map,analytic_dJ=dJ) - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(el_Δ) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - - ## Optimiser - return AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true) -end - -function main_benchmark() - opt = main() - ## Benchmark optimiser - bopt = benchmark_optimizer(opt, 1, nothing) - ## Benchmark forward problem - bfwd = benchmark_forward_problem(opt.problem.state_map, opt.φ0, nothing) - ## Benchmark advection - v = get_free_dof_values(interpolate(FEFunction(LevelSetTopOpt.get_deriv_space(opt.problem.state_map), - opt.problem.dJ),LevelSetTopOpt.get_aux_space(opt.problem.state_map))) - badv = benchmark_advection(opt.stencil, get_free_dof_values(opt.φ0), v, 0.1, nothing) - ## Benchmark reinitialisation - brinit = benchmark_reinitialisation(opt.stencil, get_free_dof_values(opt.φ0), 0.1, nothing) - ## Benchmark velocity extension - bvelext = benchmark_velocity_extension(opt.vel_ext, opt.problem.dJ, nothing) - return bopt,bfwd,badv,brinit,bvelext -end -bopt,bfwd,badv,brinit,bvelext = main_benchmark(); - -bopt -bfwd -badv -brinit -bvelext - -opt = main() - ## Benchmark optimiser -bopt0 = LevelSetTopOpt.benchmark_optimizer(opt,0, nothing; nreps = 10) -bopt = LevelSetTopOpt.benchmark_single_iteration(opt, nothing; nreps = 10) \ No newline at end of file diff --git a/scripts/_dev/bug_issue_46/thermal_MPI.jl b/scripts/_dev/bug_issue_46/thermal_MPI.jl deleted file mode 100644 index f318893d..00000000 --- a/scripts/_dev/bug_issue_46/thermal_MPI.jl +++ /dev/null @@ -1,91 +0,0 @@ -using LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, - SparseMatricesCSR - -function main(mesh_partition,distribute,use_l::Bool) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - # FE parameters - order = 1 # Finite element order - xmax = ymax = 1.0 # Domain size - dom = (0,xmax,0,ymax) # Bounding domain - el_size = (200,200) # Mesh partition size - prop_Γ_N = 0.2 # Γ_N size parameter - prop_Γ_D = 0.2 # Γ_D size parameter - f_Γ_N(x) = (x[1] ≈ xmax && # Γ_N indicator function - ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0 && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) # @$\lvert\lvert$@ - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Advection tolerance - # Problem parameters - κ = 1 # Diffusivity - g = 1 # Heat flow in - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - iter_mod = 10 # VTK Output modulo - path = "./results/AD_tut1_MPI_lobj_$use_l/" # Output path - i_am_main(ranks) && mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe) - V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N - state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = if use_l - ∫(g*u)dΓ_N #+ ∫(0)dΩ - else - ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ - end - dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - vol_D = sum(∫(1)dΩ) - C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C],state_map) - # Velocity extension - α = 4*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension(a_hilb, U_reg, V_reg) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; - γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) - # Solve - for (it,uh,φh) in optimiser - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|nabla(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && (writevtk(Ω,path*"out$it",cellfields=data);GC.gc()) - write_history(path*"/history.txt",get_history(optimiser);ranks) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, - "H(φ)"=>(H ∘ φh),"|nabla(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -with_mpi() do distribute - mesh_partition = (2,2) - main(mesh_partition,distribute,false) - main(mesh_partition,distribute,true) # <- this should crash -end \ No newline at end of file diff --git a/scripts/_dev/bug_issue_46/thermal_serial.jl b/scripts/_dev/bug_issue_46/thermal_serial.jl deleted file mode 100644 index 2d0e2017..00000000 --- a/scripts/_dev/bug_issue_46/thermal_serial.jl +++ /dev/null @@ -1,87 +0,0 @@ -using LevelSetTopOpt, Gridap - -function main(use_l::Bool) - # FE parameters - order = 1 # Finite element order - xmax = ymax = 1.0 # Domain size - dom = (0,xmax,0,ymax) # Bounding domain - el_size = (200,200) # Mesh partition size - prop_Γ_N = 0.2 # Γ_N size parameter - prop_Γ_D = 0.2 # Γ_D size parameter - f_Γ_N(x) = (x[1] ≈ xmax && # Γ_N indicator function - ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0 && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) - # FD parameters - γ = 0.1 # HJ eqn time step coeff - γ_reinit = 0.5 # Reinit. eqn time step coeff - max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection - tol = 1/(5order^2)/minimum(el_size) # Reinitialisation tolerance - # Problem parameters - κ = 1 # Diffusivity - g = 1 # Heat flow in - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - iter_mod = 10 # VTK Output modulo - path = "./results/tut1_lobj_$use_l/" # Output path - mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe) - V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N - state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = if use_l - ∫(g*u)dΓ_N - else - ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ - end - dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - vol_D = sum(∫(1)dΩ) - C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C],state_map, - analytic_dJ=dJ,analytic_dC=[dC]) - # Velocity extension - α = 4*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; - γ,γ_reinit,verbose=true,constraint_names=[:Vol]) - # Solve - for (it,uh,φh) in optimiser - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && (writevtk(Ω,path*"out$it",cellfields=data);GC.gc()) - write_history(path*"/history.txt",get_history(optimiser)) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"out$it",cellfields=["φ"=>φh, - "H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -main(false) -main(true) \ No newline at end of file diff --git a/scripts/_dev/fileio_testing.jl b/scripts/_dev/fileio_testing.jl deleted file mode 100644 index 4562d157..00000000 --- a/scripts/_dev/fileio_testing.jl +++ /dev/null @@ -1,52 +0,0 @@ -using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, LevelSetTopOpt - -using LevelSetTopOpt: save, load, load!, psave, pload, pload! - -with_debug() do distribute - mesh_partition = (2,2) - el_size = (10,10) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - model = CartesianDiscreteModel(ranks,mesh_partition,(0,1,0,1),el_size) - Ω = Triangulation(model) - reffe_scalar = ReferenceFE(lagrangian,Float64,1) - V_φ = TestFESpace(model,reffe_scalar) - - φh = interpolate(x->x[1]^2*x[2]^2,V_φ) - φ = get_free_dof_values(φh) - φ0 = copy(get_free_dof_values(φh)) - - linear_indices(φ) - - #save_object("./results/afolder/LSF_Data_1",φ) - #fill!(φ,0.0) - #load_object!("./results/afolder/LSF_Data_1",φ) - #@assert φ == φ0 - - psave("./results/afolder/LSF_Data_1",φ) - fill!(φ,0.0) - pload!("./results/afolder/LSF_Data_1",φ) - @assert φ == φ0 - -end - -begin - el_size = (10,10) - model = CartesianDiscreteModel((0,1,0,1),el_size) - Ω = Triangulation(model) - reffe_scalar = ReferenceFE(lagrangian,Float64,1) - V_φ = TestFESpace(model,reffe_scalar) - - φh = interpolate(x->x[1]^2*x[2]^2,V_φ) - φ = get_free_dof_values(φh) - φ0 = copy(get_free_dof_values(φh)) - - #save_object("./results/afolder/LSF_Data_1",φ) - #fill!(φ,0.0) - #load_object!("./results/afolder/LSF_Data_1",φ) - #@assert φ == φ0 - - save("./results/afolder/serial_LSF_Data_1.jld2",φ) - fill!(φ,0.0) - load!("./results/afolder/serial_LSF_Data_1.jld2",φ) - @assert φ == φ0 -end diff --git a/scripts/_dev/full_piezo_script.jl b/scripts/_dev/full_piezo_script.jl deleted file mode 100644 index 7ed4c1ab..00000000 --- a/scripts/_dev/full_piezo_script.jl +++ /dev/null @@ -1,236 +0,0 @@ -using Gridap, Gridap.TensorValues, Gridap.Geometry, Gridap.FESpaces, Gridap.Helpers, Gridap.Algebra -using GridapDistributed -using GridapPETSc -using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code -using PartitionedArrays -using SparseMatricesCSR -using ChainRulesCore -using LevelSetTopOpt - -using GridapSolvers -using Gridap.MultiField - -function main(mesh_partition,distribute,el_size) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - - ## Parameters - order = 1 - xmax,ymax,zmax=(1.0,1.0,1.0) - dom = (0,xmax,0,ymax,0,zmax) - γ = 0.05 - γ_reinit = 0.5 - max_steps = floor(Int,minimum(el_size)/3) - tol = 1/(2order^2)/minimum(el_size) - C = isotropic_elast_tensor(3,1.,0.3) - η_coeff = 2 - α_coeff = 4 - vf = 0.5 - path = dirname(dirname(@__DIR__))*"/results/MPI_main_3d_PZ_inverse_homenisation_ALM" - - ## FE Setup - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true,true)) - el_Δ = get_el_Δ(model) - f_Γ_D(x) = iszero(x) - update_labels!(1,model,f_Γ_D,"origin") - - ## Triangulations and measures - Ω = Triangulation(model) - dΩ = Measure(Ω,2*order) - vol_D = sum(∫(1)dΩ) - - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["origin"]) - U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) - Q = TestFESpace(model,reffe_scalar;conformity=:H1,dirichlet_tags=["origin"]) - P = TrialFESpace(Q,0) - - mfs = BlockMultiFieldStyle() - UP = MultiFieldFESpace([U,P];style=mfs) - VQ = MultiFieldFESpace([V,Q];style=mfs) - - ## Create FE functions - lsf_fn(x) cos(2π*x[1]) + cos(2π*x[2]) + cos(2π*x[3]) - φh = interpolate(lsf_fn,V_φ) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - ## Material tensors - C, e, κ = PZT5A(3); - k0 = norm(C.data,Inf); - α0 = norm(e.data,Inf); - β0 = norm(κ.data,Inf); - γ = β0*k0/α0^2; - - ## Weak forms - εᴹ = (TensorValue(1.,0.,0.,0.,0.,0.,0.,0.,0.), # ϵᵢⱼ⁽¹¹⁾≡ϵᵢⱼ⁽¹⁾ - TensorValue(0.,0.,0.,0.,1.,0.,0.,0.,0.), # ϵᵢⱼ⁽²²⁾≡ϵᵢⱼ⁽²⁾ - TensorValue(0.,0.,0.,0.,0.,0.,0.,0.,1.), # ϵᵢⱼ⁽³³⁾≡ϵᵢⱼ⁽³⁾ - TensorValue(0.,0.,0.,0.,0.,1/2,0.,1/2,0.), # ϵᵢⱼ⁽²³⁾≡ϵᵢⱼ⁽⁴⁾ - TensorValue(0.,0.,1/2,0.,0.,0.,1/2,0.,0.), # ϵᵢⱼ⁽¹³⁾≡ϵᵢⱼ⁽⁵⁾ - TensorValue(0.,1/2,0.,1/2,0.,0.,0.,0.,0.)) # ϵᵢⱼ⁽¹²⁾≡ϵᵢⱼ⁽⁶⁾ - Eⁱ = (VectorValue(1.,0.,0.), - VectorValue(0.,1.,0), - VectorValue(0.,0.,1.)) - - a((u, ϕ),(v, q),φ,dΩ) = ∫((I ∘ φ) * (1/k0*((C ⊙ ε(u)) ⊙ ε(v)) - - 1/α0*((-∇(ϕ) ⋅ e) ⊙ ε(v)) + - -1/α0*((e ⋅² ε(u)) ⋅ -∇(q)) + - -γ/β0*((κ ⋅ -∇(ϕ)) ⋅ -∇(q))) )dΩ; - - l_ε = [(v, q) -> ∫((I ∘ φ) * (-C ⊙ εᴹ[i] ⊙ ε(v) + k0/α0*(e ⋅² εᴹ[i]) ⋅ -∇(q)))dΩ for i = 1:6]; - l_E = [(v, q) -> ∫(I ∘ φ) * ((Eⁱ[i] ⋅ e ⊙ ε(v) + k0/α0*(κ ⋅ Eⁱ[i]) ⋅ -∇(q)))dΩ for i = 1:3]; - l = [l_ε; l_E] - - ## Optimisation functionals - J(u,φ,dΩ) = @notimplemented # ∫(-(I ∘ φ)*_K(C,u,εᴹ))dΩ - dJ(q,u,φ,dΩ) = @notimplemented # ∫(-_v_K(C,u,εᴹ)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - Vol(u,φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; - dVol(q,u,φ,dΩ) = ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - - ## Finite difference solver and level set function - ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,tol,max_steps) - reinit!(stencil,φh,γ_reinit) - - ## Setup solver and FE operators - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - solver_u = ElasticitySolver(V) - solver_ϕ = PETScLinearSolver() - P = BlockDiagonalPreconditioner([solver_u,solver_ϕ]) - solver = GridapSolvers.LinearSolvers.GMRESSolver(100;Pr=P,rtol=1.e-8,verbose=i_am_main(ranks)) - - - state_map = RepeatingAffineFEStateMap( - 9,a,l,UP,VQ,V_φ,U_reg,φh,dΩ; - assem_U = SparseMatrixAssembler(Tm,Tv,UP,VQ), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,VQ,UP), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver, adjoint_ls = solver - ) - pcfs = PDEConstrainedFunctionals(J,[Vol],state_map;analytic_dJ=dJ,analytic_dC=[dVol]) - - J, C, dJ, dC = Gridap.evaluate!(pcfs,φh) - - # ## Hilbertian extension-regularisation problems - # α = α_coeff*maximum(el_Δ) - # a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; - # vel_ext = VelocityExtension( - # a_hilb,U_reg,V_reg, - # assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - # ls = PETScLinearSolver() - # ) - - # ## Optimiser - # make_dir(path;ranks=ranks) - # optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=i_am_main(ranks)) - # for (it, uh, φh) in optimiser - # write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) - # write_history(path*"/history.txt",optimiser.history;ranks=ranks) - # end - # it = optimiser.history.niter; uh = get_state(optimiser.problem) - # write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) -end; - -with_mpi() do distribute - main((2,2,2),distribute,(25,25,25)) -end; - -function dh(stuff) - C(M,N) = @notimplemented - e(i,M) = @notimplemented - dh = (C23^2*e31 - C22*C33*e31 + C13^2*e32 + C11*C23*e32 - C11*C33*e32 + - C12*C33*(e31 + e32) + C12^2*e33 + C11*(-C22 + C23)*e33 - C12*C23*(e31 + e33) + - C13*(-(C23*(e31 + e32)) + C22*(e31 + e33) - C12*(e32 + e33)))/( - C13^2*C22 - 2*C12*C13*C23 + C12^2*C33 + C11*(C23^2 - C22*C33)) -end - -## TESTING -model = CartesianDiscreteModel((0,1,0,1),(10,10)); -Ω = Triangulation(model) -dΩ = Measure(Ω,2) -V = TestFESpace(model,ReferenceFE(lagrangian,Float64,1)) -uh = interpolate(x->x[1]^2*x[2]^2,V); -Cmock = [i*j*∫(uh)dΩ for i = 1:3, j =1:3] - -## Piezo helpers -function PZT5A(D::Int) - ε_0 = 8.854e-12; - if D == 3 - C_Voigt = [12.0400e10 7.52000e10 7.51000e10 0.0 0.0 0.0 - 7.52000e10 12.0400e10 7.51000e10 0.0 0.0 0.0 - 7.51000e10 7.51000e10 11.0900e10 0.0 0.0 0.0 - 0.0 0.0 0.0 2.1000e10 0.0 0.0 - 0.0 0.0 0.0 0.0 2.1000e10 0.0 - 0.0 0.0 0.0 0.0 0.0 2.30e10] - e_Voigt = [0.0 0.0 0.0 0.0 12.30000 0.0 - 0.0 0.0 0.0 12.30000 0.0 0.0 - -5.40000 -5.40000 15.80000 0.0 0.0 0.0] - K_Voigt = [540*ε_0 0 0 - 0 540*ε_0 0 - 0 0 830*ε_0] - elseif D == 2 - C_Voigt = [12.0400e10 7.51000e10 0.0 - 7.51000e10 11.0900e10 0.0 - 0.0 0.0 2.1000e10] - e_Voigt = [0.0 0.0 12.30000 - -5.40000 15.80000 0.0] - K_Voigt = [540*ε_0 0 - 0 830*ε_0] - else - @notimplemented - end - C = voigt2tensor4(C_Voigt) - e = voigt2tensor3(e_Voigt) - κ = voigt2tensor2(K_Voigt) - C,e,κ -end - -""" - Given a material constant given in Voigt notation, - return a SymFourthOrderTensorValue using ordering from Gridap -""" -function voigt2tensor4(A::Array{M,2}) where M - if isequal(size(A),(3,3)) - return SymFourthOrderTensorValue(A[1,1], A[3,1], A[2,1], - A[1,3], A[3,3], A[2,3], - A[1,2], A[3,2], A[2,2]) - elseif isequal(size(A),(6,6)) - return SymFourthOrderTensorValue(A[1,1], A[6,1], A[5,1], A[2,1], A[4,1], A[3,1], - A[1,6], A[6,6], A[5,6], A[2,6], A[4,6], A[3,6], - A[1,5], A[6,5], A[5,5], A[2,5], A[4,5], A[3,5], - A[1,2], A[6,2], A[5,2], A[2,2], A[4,2], A[3,2], - A[1,4], A[6,4], A[5,4], A[2,4], A[4,4], A[3,4], - A[1,3], A[6,3], A[5,3], A[2,3], A[4,3], A[3,3]) - else - @notimplemented - end -end - -""" - Given a material constant given in Voigt notation, - return a ThirdOrderTensorValue using ordering from Gridap -""" -function voigt2tensor3(A::Array{M,2}) where M - if isequal(size(A),(2,3)) - return ThirdOrderTensorValue(A[1,1], A[2,1], A[1,3], A[2,3], A[1,3], A[2,3], A[1,2], A[2,2]) - elseif isequal(size(A),(3,6)) - return ThirdOrderTensorValue( - A[1,1], A[2,1], A[3,1], A[1,6], A[2,6], A[3,6], A[1,5], A[2,5], A[3,5], - A[1,6], A[2,6], A[3,6], A[1,2], A[2,2], A[3,2], A[1,4], A[2,4], A[3,4], - A[1,5], A[2,5], A[3,5], A[1,4], A[2,4], A[3,4], A[1,3], A[2,3], A[3,3]) - else - @notimplemented - end -end - -""" - Given a material constant given in Voigt notation, - return a SymTensorValue using ordering from Gridap -""" -function voigt2tensor2(A::Array{M,2}) where M - return TensorValue(A) -end \ No newline at end of file diff --git a/scripts/_dev/full_piezo_script_2d.jl b/scripts/_dev/full_piezo_script_2d.jl deleted file mode 100644 index f56e65fa..00000000 --- a/scripts/_dev/full_piezo_script_2d.jl +++ /dev/null @@ -1,246 +0,0 @@ -using LevelSetTopOpt, Gridap - -using Gridap, Gridap.TensorValues, Gridap.Geometry, Gridap.FESpaces, Gridap.Helpers, Gridap.Algebra -using GridapDistributed -using GridapPETSc -using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code -using PartitionedArrays -using SparseMatricesCSR -using ChainRulesCore - -using GridapSolvers -using Gridap.MultiField - -## Piezo helpers -function PZT5A(D::Int) - ε_0 = 8.854e-12; - if D == 3 - C_Voigt = [12.0400e10 7.52000e10 7.51000e10 0.0 0.0 0.0 - 7.52000e10 12.0400e10 7.51000e10 0.0 0.0 0.0 - 7.51000e10 7.51000e10 11.0900e10 0.0 0.0 0.0 - 0.0 0.0 0.0 2.1000e10 0.0 0.0 - 0.0 0.0 0.0 0.0 2.1000e10 0.0 - 0.0 0.0 0.0 0.0 0.0 2.30e10] - e_Voigt = [0.0 0.0 0.0 0.0 12.30000 0.0 - 0.0 0.0 0.0 12.30000 0.0 0.0 - -5.40000 -5.40000 15.80000 0.0 0.0 0.0] - K_Voigt = [540*ε_0 0 0 - 0 540*ε_0 0 - 0 0 830*ε_0] - elseif D == 2 - C_Voigt = [12.0400e10 7.51000e10 0.0 - 7.51000e10 11.0900e10 0.0 - 0.0 0.0 2.1000e10] - e_Voigt = [0.0 0.0 12.30000 - -5.40000 15.80000 0.0] - K_Voigt = [540*ε_0 0 - 0 830*ε_0] - else - @notimplemented - end - C = voigt2tensor4(C_Voigt) - e = voigt2tensor3(e_Voigt) - κ = voigt2tensor2(K_Voigt) - C,e,κ -end - -""" - Given a material constant given in Voigt notation, - return a SymFourthOrderTensorValue using ordering from Gridap -""" -function voigt2tensor4(A::Array{M,2}) where M - if isequal(size(A),(3,3)) - return SymFourthOrderTensorValue(A[1,1], A[3,1], A[2,1], - A[1,3], A[3,3], A[2,3], - A[1,2], A[3,2], A[2,2]) - elseif isequal(size(A),(6,6)) - return SymFourthOrderTensorValue(A[1,1], A[6,1], A[5,1], A[2,1], A[4,1], A[3,1], - A[1,6], A[6,6], A[5,6], A[2,6], A[4,6], A[3,6], - A[1,5], A[6,5], A[5,5], A[2,5], A[4,5], A[3,5], - A[1,2], A[6,2], A[5,2], A[2,2], A[4,2], A[3,2], - A[1,4], A[6,4], A[5,4], A[2,4], A[4,4], A[3,4], - A[1,3], A[6,3], A[5,3], A[2,3], A[4,3], A[3,3]) - else - @notimplemented - end -end - -""" - Given a material constant given in Voigt notation, - return a ThirdOrderTensorValue using ordering from Gridap -""" -function voigt2tensor3(A::Array{M,2}) where M - if isequal(size(A),(2,3)) - return ThirdOrderTensorValue(A[1,1], A[2,1], A[1,3], A[2,3], A[1,3], A[2,3], A[1,2], A[2,2]) - elseif isequal(size(A),(3,6)) - return ThirdOrderTensorValue( - A[1,1], A[2,1], A[3,1], A[1,6], A[2,6], A[3,6], A[1,5], A[2,5], A[3,5], - A[1,6], A[2,6], A[3,6], A[1,2], A[2,2], A[3,2], A[1,4], A[2,4], A[3,4], - A[1,5], A[2,5], A[3,5], A[1,4], A[2,4], A[3,4], A[1,3], A[2,3], A[3,3]) - else - @notimplemented - end -end - -""" - Given a material constant given in Voigt notation, - return a SymTensorValue using ordering from Gridap -""" -function voigt2tensor2(A::Array{M,2}) where M - return TensorValue(A) -end - -## Parameters -el_size = (100,100) -order = 1 -xmax,ymax=(1.0,1.0) -dom = (0,xmax,0,ymax) -γ = 0.1 -γ_reinit = 0.5 -max_steps = floor(Int,order*minimum(el_size)/10) -tol = 1/(5order^2)/minimum(el_size) -η_coeff = 2 -α_coeff = 4*max_steps*γ -vf = 0.5 -path = dirname(dirname(@__DIR__))*"/results/2d_PZ_inverse_homenisation_ALM" - -## FE Setup -model = CartesianDiscreteModel(dom,el_size,isperiodic=(true,true)) -el_Δ = get_el_Δ(model) -f_Γ_D(x) = iszero(x) -update_labels!(1,model,f_Γ_D,"origin") - -## Triangulations and measures -Ω = Triangulation(model) -dΩ = Measure(Ω,2*order) -vol_D = sum(∫(1)dΩ) - -## Spaces -reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) -reffe_scalar = ReferenceFE(lagrangian,Float64,order) -V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["origin"]) -U = TrialFESpace(V,VectorValue(0.0,0.0)) -Q = TestFESpace(model,reffe_scalar;conformity=:H1,dirichlet_tags=["origin"]) -P = TrialFESpace(Q,0) -# mfs = BlockMultiFieldStyle() -UP = MultiFieldFESpace([U,P])#;style=mfs) -VQ = MultiFieldFESpace([V,Q])#;style=mfs) - -V_φ = TestFESpace(model,reffe_scalar) -V_reg = TestFESpace(model,reffe_scalar) -U_reg = TrialFESpace(V_reg) - -## Create FE functions -φh = interpolate(initial_lsf(4,0.2),V_φ) - -## Interpolation and weak form -interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ))#,ϵ=10^-9) -I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - -## Material tensors -C, e, κ = PZT5A(2); -k0 = norm(C.data,Inf); -α0 = norm(e.data,Inf); -β0 = norm(κ.data,Inf); -γ = β0*k0/α0^2; - -## Weak forms -εᴹ = (SymTensorValue(1.0,0.0,0.0), - SymTensorValue(0.0,0.0,1.0), - SymTensorValue(0.0,1/2,0)) -Eⁱ = (VectorValue(1.0,0.0,), - VectorValue(0.0,1.0)) - -a((u,ϕ),(v,q),φ,dΩ) = ∫((I ∘ φ) * (1/k0*((C ⊙ ε(u)) ⊙ ε(v)) - - 1/α0*((-∇(ϕ) ⋅ e) ⊙ ε(v)) + - -1/α0*((e ⋅² ε(u)) ⋅ -∇(q)) + - -γ/β0*((κ ⋅ -∇(ϕ)) ⋅ -∇(q))) )dΩ; - -l_ε = [((v,q),φ,dΩ) -> ∫(((I ∘ φ) * (-C ⊙ εᴹ[i] ⊙ ε(v) + k0/α0*(e ⋅² εᴹ[i]) ⋅ -∇(q))))dΩ for i = 1:3]; -l_E = [((v,q),φ,dΩ) -> ∫((I ∘ φ) * ((Eⁱ[i] ⋅ e ⊙ ε(v) + k0/α0*(κ ⋅ Eⁱ[i]) ⋅ -∇(q))))dΩ for i = 1:2]; -l = [l_ε; l_E] - -state_map = RepeatingAffineFEStateMap(5,a,l,UP,VQ,V_φ,U_reg,φh,dΩ) - -x = state_map(φh) -U = LevelSetTopOpt.get_trial_space(state_map) -xh = FEFunction(U,x) -# u1,ϕ1,u2,ϕ2,u3,ϕ3,u4,ϕ4,u5,ϕ5 = xh - - -function Cᴴ(r,s,uϕ,φ,dΩ) # (normalised by 1/k0) - u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] - ∫(1/k0 * (I ∘ φ) * (((C ⊙ (1/k0*ε(u_s) + εᴹ[s])) ⊙ εᴹ[r]) + ((1/α0*∇(ϕ_s) ⋅ e) ⊙ εᴹ[r])))dΩ; -end - -function eᴴ(i,s,uϕ,φ,dΩ) # (normalised by 1/α0) - u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] - ∫(1/α0 * (I ∘ φ) * (((e ⋅² (1/k0*ε(u_s) + εᴹ[s])) ⋅ Eⁱ[i]) + ((κ ⋅ (-1/α0*∇(ϕ_s))) ⋅ Eⁱ[i])))dΩ; -end - -function κᴴ(i,j,uϕ,φ,dΩ) # (normalised by 1/β0) - u_j = uϕ[6+2j-1]; ϕ_j = uϕ[6+2j] - ∫(1/β0 * (I ∘ φ) * (((e ⋅² (1/k0*ε(u_j)) ⋅ Eⁱ[i]) + ((κ ⋅ (-1/α0*∇(ϕ_j) + Eⁱ[j])) ⋅ Eⁱ[i]))))dΩ; -end - -function dᴴ(uϕ,φ,dΩ) - _Cᴴ(r,s) = sum(Cᴴ(r,s,uϕ,φ,dΩ)) - _eᴴ(i,s) = sum(eᴴ(i,s,uϕ,φ,dΩ)) - (_Cᴴ(2,2)*_eᴴ(2,1) + _Cᴴ(1,1)*_eᴴ(2,2) - _Cᴴ(2,1)*(_eᴴ(2,1) + _eᴴ(2,2)))/ - (_Cᴴ(1,1)*_Cᴴ(2,2) - _Cᴴ(2,1)^2) -end - -# map(rs->sum(Cᴴ(rs[1],rs[2],xh,φh,dΩ)), CartesianIndices((1:3, 1:3))) -# map(is->sum(eᴴ(is[1],is[2],xh,φh,dΩ)), CartesianIndices((1:2, 1:3))) -# map(ij->sum(κᴴ(ij[1],ij[2],xh,φh,dΩ)), CartesianIndices((1:2, 1:2))) -dᴴ(xh,φh,dΩ)#*α0/k0 - -C_mat = map(rs->sum(Cᴴ(rs[1],rs[2],xh,φh,dΩ)), CartesianIndices((1:3, 1:3))) -e_mat = map(is->sum(eᴴ(is[1],is[2],xh,φh,dΩ)), CartesianIndices((1:2, 1:3))) -d_mat = e_mat*inv(C_mat); -dh = d_mat[2,1] + d_mat[2,2] - -nothing -# ## Optimisation functionals -# J((u, p),φ,dΩ) = ∫(0)dΩ -# dJ(q,(u, p),φ,dΩ) = ∫(0q)dΩ -# Vol((u, p),φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; -# dVol(q,(u, p),φ,dΩ) = ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - -# ## Finite difference solver and level set function -# stencil = AdvectionStencil(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) - -# ## Setup solver and FE operators -# state_map = RepeatingAffineFEStateMap(5,a,l,UP,VQ,V_φ,U_reg,φh,dΩ) -# pcfs = PDEConstrainedFunctionals(J,[Vol],state_map;analytic_dJ=dJ,analytic_dC=[dVol]) - -# evaluate!(pcfs,φh) - -# ## Hilbertian extension-regularisation problems -# α = α_coeff*maximum(el_Δ) -# a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; -# vel_ext = VelocityExtension( -# a_hilb,U_reg,V_reg, -# assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), -# ls = PETScLinearSolver() -# ) - -# ## Optimiser -# make_dir(path;ranks=ranks) -# optimiser = AugmentedLagrangian(pcfs,stencil,vel_ext,φh;γ,γ_reinit,verbose=i_am_main(ranks)) -# for (it, uh, φh) in optimiser -# write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -# write_history(path*"/history.txt",optimiser.history;ranks=ranks) -# end -# it = optimiser.history.niter; uh = get_state(optimiser.problem) -# write_vtk(Ω,path*"/struc_$it",it,["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh];iter_mod=1) - - -function dh(stuff) - C(M,N) = @notimplemented - e(i,M) = @notimplemented - dh = (C23^2*e31 - C22*C33*e31 + C13^2*e32 + C11*C23*e32 - C11*C33*e32 + - C12*C33*(e31 + e32) + C12^2*e33 + C11*(-C22 + C23)*e33 - C12*C23*(e31 + e33) + - C13*(-(C23*(e31 + e32)) + C22*(e31 + e33) - C12*(e32 + e33)))/( - C13^2*C22 - 2*C12*C13*C23 + C12^2*C33 + C11*(C23^2 - C22*C33)) -end diff --git a/scripts/_dev/inv_hom_block_assem_testing.jl b/scripts/_dev/inv_hom_block_assem_testing.jl deleted file mode 100644 index 14d2b24a..00000000 --- a/scripts/_dev/inv_hom_block_assem_testing.jl +++ /dev/null @@ -1,132 +0,0 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR - -nothing - -np = (2,3); - -ranks = with_debug() do distribute - distribute(LinearIndices((prod(np),))) -end; - -## Parameters -order = 1; -xmax,ymax=(1.0,1.0) -dom = (0,xmax,0,ymax); -el_size = (10,10); -γ = 0.05; -γ_reinit = 0.5; -max_steps = floor(Int,minimum(el_size)/10) -tol = 1/(order^2*10)/minimum(el_size) -C = isotropic_elast_tensor(2,1.,0.3); -η_coeff = 2; -α_coeff = 4; -path = dirname(dirname(@__DIR__))*"/results/block_testing" - -## FE Setup -model = CartesianDiscreteModel(ranks,(2,3),dom,el_size,isperiodic=(true,true)); -# model = CartesianDiscreteModel(dom,el_size,isperiodic=(true,true)); -el_Δ = get_el_Δ(model) -f_Γ_D(x) = iszero(x) -update_labels!(1,model,f_Γ_D,"origin") - -## Triangulations and measures -Ω = Triangulation(model) -dΩ = Measure(Ω,2order) -vol_D = sum(∫(1)dΩ) - -## Spaces -reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) -reffe_scalar = ReferenceFE(lagrangian,Float64,order) -_V = TestFESpace(model,reffe;dirichlet_tags=["origin"]) -_U = TrialFESpace(_V,VectorValue(0.0,0.0)) -mfs = BlockMultiFieldStyle() -U = MultiFieldFESpace([_U,_U,_U];style=mfs); -V = MultiFieldFESpace([_V,_V,_V];style=mfs); -V_reg = V_φ = TestFESpace(model,reffe_scalar) -U_reg = TrialFESpace(V_reg) - -## Create FE functions -lsf_fn = x->max(initial_lsf(2,0.4)(x),initial_lsf(2,0.4;b=VectorValue(0,0.5))(x)); -φh = interpolate(-1,V_φ); -φ = get_free_dof_values(φh) - -## Interpolation and weak form -interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) -I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - -εᴹ = (TensorValue(1.,0.,0.,0.), # ϵᵢⱼ⁽¹¹⁾≡ϵᵢⱼ⁽¹⁾ - TensorValue(0.,0.,0.,1.), # ϵᵢⱼ⁽²²⁾≡ϵᵢⱼ⁽²⁾ - TensorValue(0.,1/2,1/2,0.)) # ϵᵢⱼ⁽¹²⁾≡ϵᵢⱼ⁽³⁾ - -a(u,v,φ,dΩ) = ∫((I ∘ φ)*sum(C ⊙ ε(u[i]) ⊙ ε(v[i]) for i = 1:length(u)))dΩ -l(v,φ,dΩ) = ∫(-(I ∘ φ)*sum(C ⊙ εᴹ[i] ⊙ ε(v[i]) for i ∈ 1:length(v)))dΩ; -res(u,v,φ,dΩ) = a(u,v,φ,dΩ) - l(v,φ,dΩ) - -## Optimisation functionals -_C(C,ε_p,ε_q) = C ⊙ ε_p ⊙ ε_q; -_K(C,(u1,u2,u3),εᴹ) = (_C(C,ε(u1)+εᴹ[1],εᴹ[1]) + _C(C,ε(u2)+εᴹ[2],εᴹ[2]) + 2*_C(C,ε(u1)+εᴹ[1],εᴹ[2]))/4 -_v_K(C,(u1,u2,u3),εᴹ) = (_C(C,ε(u1)+εᴹ[1],ε(u1)+εᴹ[1]) + _C(C,ε(u2)+εᴹ[2],ε(u2)+εᴹ[2]) + 2*_C(C,ε(u1)+εᴹ[1],ε(u2)+εᴹ[2]))/4 - -J = (u,φ,dΩ) -> ∫(-(I ∘ φ)*_K(C,u,εᴹ))dΩ -dJ = (q,u,φ,dΩ) -> ∫(-_v_K(C,u,εᴹ)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; -Vol = (u,φ,dΩ) -> ∫(((ρ ∘ φ) - 0.5)/vol_D)dΩ; -dVol = (q,u,φ,dΩ) -> ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - -## Finite difference solver and level set function -ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol); -reinit!(stencil,φ,γ_reinit) - -## Initialise op -uhd = zero(U); -Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} -Tv=Vector{PetscScalar} -assem = DiagonalBlockMatrixAssembler(SparseMatrixAssembler(Tm,Tv,U,V)); -@time op = AffineFEOperator((u,v) -> a(u,v,φh,dΩ),v -> l(v,φh,dΩ),U,V,assem); -K = get_matrix(op); b = get_vector(op); -x = GridapDistributed.allocate_in_domain(K) - -## Initialise adjoint -assem_adjoint = DiagonalBlockMatrixAssembler(SparseMatrixAssembler(V,U)); -adjoint_K = assemble_matrix((u,v) -> a(v,u,φh,dΩ),assem_adjoint,V,U); - -## Update mat and vec -LevelSetTopOpt._assemble_matrix_and_vector!((u,v) -> a(u,v,φh,dΩ),v -> l(v,φh,dΩ),K,b,assem,U,V,uhd) -# numerical_setup!(...) - -## Update adjoint -LevelSetTopOpt.assemble_matrix!((u,v) -> a(v,u,φh,dΩ),adjoint_K,assem_adjoint,V,U) - -### Test -@time op_test = AffineFEOperator((u,v) -> a(u,v,φh,dΩ),v -> l(v,φh,dΩ),U,V,SparseMatrixAssembler(U,V)) -K_test = get_matrix(op_test); b_test=get_vector(op_test) -x_test = GridapDistributed.allocate_in_domain(K_test) -@show Base.summarysize(K) -@show Base.summarysize(K_test) - -using BlockArrays -if typeof(K_test) <: BlockArray - @assert K_test == K -else - for I ∈ CartesianIndices(K.blocks) - @assert K.blocks[I].matrix_partition.items[:] ≈ K_test.blocks[I].matrix_partition.items[:] - end -end - -## Solver -options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky"; - -GridapPETSc.with(args=split(options)) do - P = BlockDiagonalPreconditioner(map(Vi -> ElasticitySolver(Vi),V)) - solver = GridapSolvers.LinearSolvers.CGSolver(P;rtol=1.e-8,verbose=i_am_main(ranks)) - P2 = BlockDiagonalPreconditioner(map(Vi -> ElasticitySolver(Vi),V)) - solver2 = GridapSolvers.LinearSolvers.CGSolver(P2;rtol=1.e-8,verbose=i_am_main(ranks)) - - @time ns = numerical_setup(symbolic_setup(solver,K),K) - @time ns_test = numerical_setup(symbolic_setup(solver2,K_test),K_test) - - @time numerical_setup!(ns,K) - @time numerical_setup!(ns_test,K_test) -end \ No newline at end of file diff --git a/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl b/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl deleted file mode 100644 index 3c7e57a6..00000000 --- a/scripts/_dev/inv_hom_block_assem_testing_3D_MPI.jl +++ /dev/null @@ -1,172 +0,0 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR -using Gridap.MultiField: BlockMultiFieldStyle - -""" - (MPI) Maximum bulk modulus inverse homogenisation with augmented Lagrangian method in 3D. - - Optimisation problem: - Min J(Ω) = -κ(Ω) - Ω - s.t., Vol(Ω) = Vf, - ⎡For unique εᴹᵢ, find uᵢ∈V=H¹ₚₑᵣ(Ω)ᵈ, - ⎣∫ ∑ᵢ C ⊙ ε(uᵢ) ⊙ ε(vᵢ) dΩ = ∫ -∑ᵢ C ⊙ ε⁰ᵢ ⊙ ε(vᵢ) dΩ, ∀v∈V. -""" -function main(mesh_partition,distribute,el_size,diag_assem::Bool) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - t = PTimer(ranks) - - ## Parameters - order = 1; - xmax,ymax,zmax=(1.0,1.0,1.0) - dom = (0,xmax,0,ymax,0,zmax); - γ = 0.05; - γ_reinit = 0.5; - max_steps = floor(Int,minimum(el_size)/3) - tol = 1/(order^2*10)/minimum(el_size) - C = isotropic_elast_tensor(3,1.,0.3); - η_coeff = 2; - α_coeff = 4; - path = dirname(dirname(@__DIR__))*"/results/MPI_main_3d_inverse_homenisation_ALM" - - ## FE Setup - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true,true)); - el_Δ = get_el_Δ(model) - f_Γ_D(x) = iszero(x) - update_labels!(1,model,f_Γ_D,"origin") - - ## Triangulations and measures - Ω = Triangulation(model) - dΩ = Measure(Ω,2order) - vol_D = sum(∫(1)dΩ) - - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - _V = TestFESpace(model,reffe;dirichlet_tags=["origin"]) - _U = TrialFESpace(_V,VectorValue(0.0,0.0,0.0)) - mfs = BlockMultiFieldStyle() - U = MultiFieldFESpace([_U,_U,_U,_U,_U,_U];style=mfs); - V = MultiFieldFESpace([_V,_V,_V,_V,_V,_V];style=mfs); - V_reg = V_φ = TestFESpace(model,reffe_scalar) - U_reg = TrialFESpace(V_reg) - - ## Create FE functions - lsf_fn = x -> cos(2π*x[1]) + cos(2π*x[2]) + cos(2π*x[3]) - φh = interpolate(lsf_fn,V_φ); - φ = get_free_dof_values(φh) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - εᴹ = (TensorValue(1.,0.,0.,0.,0.,0.,0.,0.,0.), # ϵᵢⱼ⁽¹¹⁾≡ϵᵢⱼ⁽¹⁾ - TensorValue(0.,0.,0.,0.,1.,0.,0.,0.,0.), # ϵᵢⱼ⁽²²⁾≡ϵᵢⱼ⁽²⁾ - TensorValue(0.,0.,0.,0.,0.,0.,0.,0.,1.), # ϵᵢⱼ⁽³³⁾≡ϵᵢⱼ⁽³⁾ - TensorValue(0.,0.,0.,0.,0.,1/2,0.,1/2,0.), # ϵᵢⱼ⁽²³⁾≡ϵᵢⱼ⁽⁴⁾ - TensorValue(0.,0.,1/2,0.,0.,0.,1/2,0.,0.), # ϵᵢⱼ⁽¹³⁾≡ϵᵢⱼ⁽⁵⁾ - TensorValue(0.,1/2,0.,1/2,0.,0.,0.,0.,0.)) # ϵᵢⱼ⁽¹²⁾≡ϵᵢⱼ⁽⁶⁾ - - a(u,v,φ,dΩ) = ∫((I ∘ φ)*sum(C ⊙ ε(u[i]) ⊙ ε(v[i]) for i = 1:length(u)))dΩ - l(v,φ,dΩ) = ∫(-(I ∘ φ)*sum(C ⊙ εᴹ[i] ⊙ ε(v[i]) for i = 1:length(v)))dΩ; - res(u,v,φ,dΩ) = a(u,v,φ,dΩ) - l(v,φ,dΩ) - - ## Optimisation functionals - _C(C,ε_p,ε_q) = C ⊙ ε_p ⊙ ε_q; - - _K(C,u,εᴹ) = (_C(C,ε(u[1])+εᴹ[1],εᴹ[1]) + _C(C,ε(u[2])+εᴹ[2],εᴹ[2]) + _C(C,ε(u[3])+εᴹ[3],εᴹ[3]) + - 2(_C(C,ε(u[1])+εᴹ[1],εᴹ[2]) + _C(C,ε(u[1])+εᴹ[1],εᴹ[3]) + _C(C,ε(u[2])+εᴹ[2],εᴹ[3])))/9 - - _v_K(C,u,εᴹ) = (_C(C,ε(u[1])+εᴹ[1],ε(u[1])+εᴹ[1]) + _C(C,ε(u[2])+εᴹ[2],ε(u[2])+εᴹ[2]) + _C(C,ε(u[3])+εᴹ[3],ε(u[3])+εᴹ[3]) + - 2(_C(C,ε(u[1])+εᴹ[1],ε(u[2])+εᴹ[2]) + _C(C,ε(u[1])+εᴹ[1],ε(u[3])+εᴹ[3]) + _C(C,ε(u[2])+εᴹ[2],ε(u[3])+εᴹ[3])))/9 - - J = (u,φ,dΩ) -> ∫(-(I ∘ φ)*_K(C,u,εᴹ))dΩ - dJ = (q,u,φ,dΩ) -> ∫(-_v_K(C,u,εᴹ)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; - Vol = (u,φ,dΩ) -> ∫(((ρ ∘ φ) - 0.5)/vol_D)dΩ; - dVol = (q,u,φ,dΩ) -> ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - - ## Finite difference solver and level set function - ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(3,Float64),model,V_φ,el_size./order,max_steps,tol) - reinit!(stencil,φ,γ_reinit) - - ## Setup solver and FE operators - Tm=SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv=Vector{PetscScalar} - P = BlockDiagonalPreconditioner(map(Vi -> ElasticitySolver(Vi),V)) - solver = GridapSolvers.LinearSolvers.CGSolver(P;rtol=1.e-8,verbose=i_am_main(ranks)) - - assem_U,assem_adjoint = if diag_assem - DiagonalBlockMatrixAssembler(SparseMatrixAssembler(Tm,Tv,U,V)), - DiagonalBlockMatrixAssembler(SparseMatrixAssembler(Tm,Tv,V,U)) - else - SparseMatrixAssembler(Tm,Tv,U,V), - SparseMatrixAssembler(Tm,Tv,V,U) - end - - state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ; - assem_U = assem_U, - assem_adjoint = assem_adjoint, - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls=solver, - adjoint_ls=solver) - - tic!(t) - state_map(φ) - toc!(t,"Assembly and solve") - - pcfs = PDEConstrainedFunctionals(J,[Vol],state_map;analytic_dJ=dJ,analytic_dC=[dVol]) - - J_init,C_init,dJ,dC = Gridap.evaluate!(pcfs,φ) - u_vec = pcfs.state_map.fwd_caches[4] - - return [J_init,C_init,dJ,dC],u_vec,t - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(el_Δ) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; - vel_ext = VelocityExtension(a_hilb,U_reg,V_reg, - assem=SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls=PETScLinearSolver()) - - ## Optimiser - make_dir(path;ranks=ranks) - optimiser = AugmentedLagrangian(φ,pcfs,ls_evo,vel_ext,interp,el_size,γ,γ_reinit); - for history in optimiser - it,Ji,Ci,Li = last(history) - λi = optimiser.λ; Λi = optimiser.Λ - print_history(it,["J"=>Ji,"C"=>Ci,"L"=>Li,"λ"=>λi,"Λ"=>Λi];ranks=ranks) - write_history(history,path*"/history.csv";ranks=ranks) - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))] - iszero(it % 10) && writevtk(Ω,path*"out$it",cellfields=data) - end - it,Ji,Ci,Li = last(optimiser.history) - λi = optimiser.λ; Λi = optimiser.Λ - print_history(it,["J"=>Ji,"C"=>Ci,"L"=>Li,"λ"=>λi,"Λ"=>Λi];ranks=ranks) - write_history(optimiser.history,path*"/history.csv";ranks=ranks) - writevtk(Ω,path*"/out$it",cellfields=["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))]) -end - -# RUN: mpiexecjl --project=. -n 8 julia ./scripts/inv_hom_block_assem_testing_3D_MPI.jl -with_mpi() do distribute - mesh_partition = (2,2,2) - el_size = (20,20,20) - hilb_solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12 -mat_block_size 3 - -mg_levels_ksp_type chebyshev -mg_levels_esteig_ksp_type cg -mg_coarse_sub_pc_type cholesky" - - GridapPETSc.with(args=split(hilb_solver_options)) do - main(mesh_partition,distribute,el_size,false) - main(mesh_partition,distribute,el_size,true) - - _OBJ_VALS,_U,T = main(mesh_partition,distribute,el_size,false) - _OBJ_VALS_diag,_U_diag,T_diag = main(mesh_partition,distribute,el_size,true) - - @show _OBJ_VALS[1] - _OBJ_VALS_diag[1] - @show _OBJ_VALS[2] - _OBJ_VALS_diag[2] - @show maximum(abs,_OBJ_VALS[3] - _OBJ_VALS_diag[3]) - @show maximum(maximum.(abs,_U.blocks - _U_diag.blocks)) - - display(T) - display(T_diag) - end -end; \ No newline at end of file diff --git a/scripts/_dev/inv_hom_block_assem_testing_full_script.jl b/scripts/_dev/inv_hom_block_assem_testing_full_script.jl deleted file mode 100644 index 46d9baf3..00000000 --- a/scripts/_dev/inv_hom_block_assem_testing_full_script.jl +++ /dev/null @@ -1,151 +0,0 @@ -using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, LevelSetTopOpt -using GridapSolvers: LinearSolvers -using Gridap.MultiField: BlockMultiFieldStyle - -""" - (Serial) Maximum bulk modulus inverse homogenisation with augmented Lagrangian method in 2D. - - Optimisation problem: - Min J(Ω) = -κ(Ω) - Ω - s.t., Vol(Ω) = Vf, - ⎡For unique εᴹᵢ, find uᵢ∈V=H¹ₚₑᵣ(Ω)ᵈ, - ⎣∫ ∑ᵢ C ⊙ ε(uᵢ) ⊙ ε(vᵢ) dΩ = ∫ -∑ᵢ C ⊙ ε⁰ᵢ ⊙ ε(vᵢ) dΩ, ∀v∈V. -""" -function main(diag_block) - ## Parameters - order = 2; - xmax,ymax=(1.0,1.0) - dom = (0,xmax,0,ymax); - el_size = (200,200); - γ = 0.05; - γ_reinit = 0.5; - max_steps = floor(Int,minimum(el_size)/10) - tol = 1/(order^2*10)/minimum(el_size) - C = isotropic_elast_tensor(2,1.,0.3); - η_coeff = 2; - α_coeff = 4; - path = dirname(dirname(@__DIR__))*"/results/main_inverse_homogenisation_ALM" - - ## FE Setup - model = CartesianDiscreteModel(dom,el_size,isperiodic=(true,true)); - el_Δ = get_el_Δ(model) - f_Γ_D(x) = iszero(x) - update_labels!(1,model,f_Γ_D,"origin") - - ## Triangulations and measures - Ω = Triangulation(model) - dΩ = Measure(Ω,2order) - vol_D = sum(∫(1)dΩ) - - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - _V = TestFESpace(model,reffe;dirichlet_tags=["origin"]) - _U = TrialFESpace(_V,VectorValue(0.0,0.0)) - mfs = BlockMultiFieldStyle() - U = MultiFieldFESpace([_U,_U,_U];style=mfs); - V = MultiFieldFESpace([_V,_V,_V];style=mfs); - V_reg = V_φ = TestFESpace(model,reffe_scalar) - U_reg = TrialFESpace(V_reg) - - ## Create FE functions - lsf_fn = x->max(initial_lsf(2,0.4)(x),initial_lsf(2,0.4;b=VectorValue(0,0.5))(x)); - φh = interpolate(lsf_fn,V_φ); - φ = get_free_dof_values(φh) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - εᴹ = (TensorValue(1.,0.,0.,0.), # ϵᵢⱼ⁽¹¹⁾≡ϵᵢⱼ⁽¹⁾ - TensorValue(0.,0.,0.,1.), # ϵᵢⱼ⁽²²⁾≡ϵᵢⱼ⁽²⁾ - TensorValue(0.,1/2,1/2,0.)) # ϵᵢⱼ⁽¹²⁾≡ϵᵢⱼ⁽³⁾ - - a(u,v,φ,dΩ) = ∫((I ∘ φ)*sum(C ⊙ ε(u[i]) ⊙ ε(v[i]) for i = 1:length(u)))dΩ - l(v,φ,dΩ) = ∫(-(I ∘ φ)*sum(C ⊙ εᴹ[i] ⊙ ε(v[i]) for i = 1:length(v)))dΩ; - res(u,v,φ,dΩ) = a(u,v,φ,dΩ) - l(v,φ,dΩ) - - ## Optimisation functionals - _C(C,ε_p,ε_q) = C ⊙ ε_p ⊙ ε_q; - _K(C,(u1,u2,u3),εᴹ) = (_C(C,ε(u1)+εᴹ[1],εᴹ[1]) + _C(C,ε(u2)+εᴹ[2],εᴹ[2]) + 2*_C(C,ε(u1)+εᴹ[1],εᴹ[2]))/4 - _v_K(C,(u1,u2,u3),εᴹ) = (_C(C,ε(u1)+εᴹ[1],ε(u1)+εᴹ[1]) + _C(C,ε(u2)+εᴹ[2],ε(u2)+εᴹ[2]) + 2*_C(C,ε(u1)+εᴹ[1],ε(u2)+εᴹ[2]))/4 - - J = (u,φ,dΩ) -> ∫(-(I ∘ φ)*_K(C,u,εᴹ))dΩ - dJ = (q,u,φ,dΩ) -> ∫(-_v_K(C,u,εᴹ)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; - Vol = (u,φ,dΩ) -> ∫(((ρ ∘ φ) - 0.5)/vol_D)dΩ; - dVol = (q,u,φ,dΩ) -> ∫(1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - - ## Finite difference solver and level set function - ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol) - reinit!(stencil,φ,γ_reinit) - - ## Setup solver and FE operators - P = LinearSolvers.JacobiLinearSolver() - pcg = LinearSolvers.CGSolver(P;rtol=10e-12,verbose=true) - - assem = if diag_block - DiagonalBlockMatrixAssembler(SparseMatrixAssembler(U,V)) - else - SparseMatrixAssembler(U,V) - end - - state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ; - ls = pcg, - adjoint_ls = pcg, - assem_U=assem, - assem_adjoint=assem) - pcfs = PDEConstrainedFunctionals(J,[Vol],state_map;analytic_dJ=dJ,analytic_dC=[dVol]) - - J_init,C_init,dJ,dC = Gridap.evaluate!(pcfs,φ) - u_vec = pcfs.state_map.fwd_caches[4] - - return pcfs,[J_init,C_init,dJ,dC],u_vec - - ## Hilbertian extension-regularisation problems - α = α_coeff*maximum(el_Δ) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; - vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - - ## Optimiser - make_dir(path) - optimiser = AugmentedLagrangian(φ,pcfs,ls_evo,vel_ext,interp,el_size,γ,γ_reinit); - for history in optimiser - it,Ji,Ci,Li = last(history) - λi = optimiser.λ; Λi = optimiser.Λ - print_history(it,["J"=>Ji,"C"=>Ci,"L"=>Li,"λ"=>λi,"Λ"=>Λi]) - write_history(history,path*"/history.csv") - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh))] - iszero(it % 10) && writevtk(Ω,path*"out$it",cellfields=data) - end - it,Ji,Ci,Li = last(optimiser.history) - λi = optimiser.λ; Λi = optimiser.Λ - print_history(it,["J"=>Ji,"C"=>Ci,"L"=>Li,"λ"=>λi,"Λ"=>Λi]) - write_history(optimiser.history,path*"/history.csv") - writevtk(Ω,path*"/out$it",cellfields=["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))]) -end - -using LinearAlgebra -using BlockArrays -function LinearAlgebra.diag(A::BlockArray) - @assert ndims(A) == 2 "diag only supports matrices currently" - _blk_axes = blockaxes(A); - blkrng = (_blk_axes[1]<_blk_axes[2]) ? _blk_axes[1] : _blk_axes[2] - - mortar(map(I->diag(A[I,I]),blkrng)) -end -function Gridap.Algebra.numerical_setup!(ns::LinearSolvers.JacobiNumericalSetup, A::AbstractMatrix) - ns.inv_diag .= 1.0 ./ diag(A) -end - -# The above is a crappy solver for this problem, use AMG instead (see MPI version) - -_PSFs,_OBJ_VALS,_U = main(false); -_PSFs_diag,_OBJ_VALS_diag,_U_diag = main(true); - - - -_without = Base.summarysize(_PSFs.state_map.fwd_caches[2]) -_with = Base.summarysize(_PSFs_diag.state_map.fwd_caches[2]) - -_with/_without \ No newline at end of file diff --git a/scripts/_dev/mem_leak.jl b/scripts/_dev/mem_leak.jl deleted file mode 100644 index 278ec667..00000000 --- a/scripts/_dev/mem_leak.jl +++ /dev/null @@ -1,114 +0,0 @@ -using Gridap, LevelSetTopOpt - -# FE parameters -order = 1 # Finite element order -xmax=ymax=zmax=1.0 # Domain size -dom = (0,xmax,0,ymax,0,zmax) # Bounding domain -el_size = (10,10,10) # Mesh partition size -prop_Γ_N = 0.4 # Γ_N size parameter -prop_Γ_D = 0.2 # Γ_D size parameter -f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function - (ymax/2-ymax*prop_Γ_N/4 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/4 + eps()) && - (zmax/2-zmax*prop_Γ_N/4 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/4 + eps()) -f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps()) && - (x[3] <= zmax*prop_Γ_D + eps() || x[3] >= zmax-zmax*prop_Γ_D - eps()) -# FD parameters -γ = 0.1 # HJ equation time step coefficient -γ_reinit = 0.5 # Reinit. equation time step coefficient -max_steps = floor(Int,minimum(el_size)/3) # Max steps for advection -tol = 1/(2*order^2)*prod(inv,minimum(el_size)) # Advection tolerance -# Problem parameters -κ = 1 # Diffusivity -g = 1 # Heat flow in -vf = 0.4 # Volume fraction constraint -lsf_func = initial_lsf(4,0.2) # Initial level set function -iter_mod = 10 # Output VTK files every 10th iteration - -# Model -model = CartesianDiscreteModel(dom,el_size); -update_labels!(1,model,f_Γ_D,"Gamma_D") -update_labels!(2,model,f_Γ_N,"Gamma_N") -# Triangulation and measures -Ω = Triangulation(model) -Γ_N = BoundaryTriangulation(model,tags="Gamma_N") -dΩ = Measure(Ω,2*order) -dΓ_N = Measure(Γ_N,2*order) -# Spaces -reffe = ReferenceFE(lagrangian,Float64,order) -V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) -U = TrialFESpace(V,0.0) -V_φ = TestFESpace(model,reffe) -V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) -U_reg = TrialFESpace(V_reg,0) -# Level set and interpolator -φh = interpolate(lsf_func,V_φ) -interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) -I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ -# Weak formulation -a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ -l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N -state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) -# Objective and constraints -J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ -dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ -vol_D = sum(∫(1)dΩ) -C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ -dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ -pcfs = PDEConstrainedFunctionals(J,[C],state_map,analytic_dJ=dJ,analytic_dC=[dC]) -# Velocity extension -α = 4*maximum(get_el_Δ(model)) -a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ -vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) -# Finite difference scheme -scheme = FirstOrderStencil(length(el_size),Float64) -ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) -# Optimiser -optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) -# Solve -for i = 1:10 - LevelSetTopOpt.rrule(state_map,φh) -end - -evaluate!(pcfs,φh); -uh = get_state(state_map) - -GC.gc() -Sys.free_memory() / 2^20 - -for i = 1:10 - begin - u = LevelSetTopOpt.forward_solve!(state_map,φh); - uh = FEFunction(LevelSetTopOpt.get_trial_space(state_map),u); - # LevelSetTopOpt.update_adjoint_caches!(state_map,uh,φh); - end; -end; - -Sys.free_memory() / 2^20 - -GC.gc() -Sys.free_memory() / 2^20 - -for i = 1:10 - begin - # u = LevelSetTopOpt.forward_solve!(state_map,φh); - # uh = FEFunction(LevelSetTopOpt.get_trial_space(state_map),u); - - LevelSetTopOpt.update_adjoint_caches!(state_map,uh,φh); - end; -end; - -Sys.free_memory() / 2^20 - -GC.gc() -Sys.free_memory() / 2^20 - -for i = 1:10 - begin - u = LevelSetTopOpt.forward_solve!(state_map,φh); - uh = FEFunction(LevelSetTopOpt.get_trial_space(state_map),u); - LevelSetTopOpt.update_adjoint_caches!(state_map,uh,φh); - end; -end; - -Sys.free_memory() / 2^20 diff --git a/scripts/_dev/nonlinear_adjoint_MWE.jl b/scripts/_dev/nonlinear_adjoint_MWE.jl deleted file mode 100644 index df5fe18a..00000000 --- a/scripts/_dev/nonlinear_adjoint_MWE.jl +++ /dev/null @@ -1,83 +0,0 @@ -using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, LevelSetTopOpt - -""" - (Serial) Minimum thermal compliance with Lagrangian method in 2D with nonlinear diffusivity. - - Optimisation problem: - Min J(Ω) = ∫ D(u)*∇(u)⋅∇(u) + ξ dΩ - Ω - s.t., ⎡u∈V=H¹(Ω;u(Γ_D)=0), - ⎣∫ D(u)*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. - - In this example D(u) = D0*(exp(ξ*u)) -""" -function main() - ## Parameters - order = 1; - xmax=ymax=1.0 - prop_Γ_N = 0.2; - prop_Γ_D = 0.2 - dom = (0,xmax,0,ymax); - el_size = (200,200); - γ = 0.1; - γ_reinit = 0.5; - max_steps = floor(Int,minimum(el_size)/10) - tol = 1/(order^2*10)/minimum(el_size) # <- We can do better than this I think - η_coeff = 2; - α_coeff = 4; - path = dirname(dirname(@__DIR__))*"/results/main_nonlinear" - - ## FE Setup - model = CartesianDiscreteModel(dom,el_size); - el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || - x[2] >= ymax-ymax*prop_Γ_D - eps())) ? true : false; - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= - ymax/2+ymax*prop_Γ_N/2 + eps()) ? true : false; - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - - ## Triangulations and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2order) - dΓ_N = Measure(Γ_N,2order) - - ## Spaces - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe_scalar) - V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - - ## Create FE functions - φh = interpolate(initial_lsf(4,0.2),V_φ); - φ = get_free_dof_values(φh) - - ## Interpolation and weak form - interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - - D0 = 1; - ξ = -1; - D(u) = D0*(exp(ξ*u)); - - res(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(D ∘ u)*∇(u)⋅∇(v))dΩ - ∫(v)dΓ_N - - ## Optimisation functionals - ξ = 0.2; - J = (u,φ,dΩ,dΓ_N) -> ∫((I ∘ φ)*(D ∘ u)*∇(u)⋅∇(u) + ξ*(ρ ∘ φ))dΩ - - ## Finite difference solver and level set function - ls_evo = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,el_size./order,max_steps,tol) - reinit!(stencil,φ,γ_reinit) - - ## Setup solver and FE operators - state_map = NonlinearFEStateMap(res,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) - pcfs = PDEConstrainedFunctionals(J,state_map) - - J,C,dJ,dC = Gridap.evaluate!(pcfs,φ) -end - -main(); diff --git a/scripts/_dev/nonlinear_adjoint_testing.jl b/scripts/_dev/nonlinear_adjoint_testing.jl deleted file mode 100644 index 52c96044..00000000 --- a/scripts/_dev/nonlinear_adjoint_testing.jl +++ /dev/null @@ -1,41 +0,0 @@ - -using LinearAlgebra -using Gridap, Gridap.FESpaces, Gridap.CellData - -function transpose_contributions(b::DomainContribution) - c = DomainContribution() - for (trian,array_old) in b.dict - array_new = lazy_map(transpose,array_old) - add_contribution!(c,trian,array_new) - end - return c -end - -function assemble_adjoint_matrix!(f::Function,A::AbstractMatrix,a::Assembler,U::FESpace,V::FESpace) - v = get_fe_basis(V) - u = get_trial_fe_basis(U) - contr = transpose_contributions(f(u,v)) - assemble_matrix!(A,a,collect_cell_matrix(V,U,contr)) -end - -model = CartesianDiscreteModel((0,1,0,1),(4,4)) - -reffe = ReferenceFE(lagrangian,Float64,1) -V = FESpace(model,reffe) -U = TrialFESpace(V) - -Ω = Triangulation(model) -dΩ = Measure(Ω,4) - -e = VectorValue(1.0,-1.0) -a(u,v) = ∫((∇(u)⋅e)⋅v)*dΩ - -A = assemble_matrix(a,U,V) -At = assemble_matrix((u,v) -> a(v,u), V, U) - -A ≈ transpose(At) # true - -assem = SparseMatrixAssembler(V,U) -Ad = copy(At); LinearAlgebra.fillstored!(Ad,0.0) -Ad = assemble_adjoint_matrix!(a,Ad,assem,U,V) -Ad ≈ transpose(A) # true diff --git a/scripts/_dev/operations/ops_testing.jl b/scripts/_dev/operations/ops_testing.jl deleted file mode 100644 index fe4a38b3..00000000 --- a/scripts/_dev/operations/ops_testing.jl +++ /dev/null @@ -1,85 +0,0 @@ -using LevelSetTopOpt -using Gridap -using Gridap.CellData: DomainContribution -using Gridap.FESpaces: _gradient -using GridapDistributed: DistributedDomainContribution -import Base.*, Base./ - -ContributionTypes = Union{DomainContribution,DistributedDomainContribution} - -struct DomainContributionOperation{A} - a - b - op :: A -end - -(F::DomainContributionOperation)(args...) = F.op(sum(F.a),sum(F.b)) - -function (*)(a::ContributionTypes,b::ContributionTypes) - DomainContributionOperation(a,b,*) -end - -function (*)(a::ContributionTypes,b::DomainContributionOperation) - DomainContributionOperation(a,b,*) -end - -(*)(a::DomainContributionOperation,b::ContributionTypes) = b*a - -Gridap.gradient(F::DomainContributionOperation{typeof(*)},xh) = gradient(F.a,xh)*sum(F.b(xh)) + gradient(F.b,xh)*sum(F.a(xh)) - -# function Gridap.FESpaces._gradient(f,xh,fuh::DomainContributionOperation) -# @show typeof(fuh.a) -# _gradient(f,xh,fuh.a)#*sum(fuh.b(xh)) + _gradient(f,xh,fuh.b)*sum(fuh.a(xh)) -# end - -## TESTING -model = CartesianDiscreteModel((0,1,0,1),(10,10)); -Ω = Triangulation(model) -dΩ = Measure(Ω,2) -V = TestFESpace(model,ReferenceFE(lagrangian,Float64,1)) -uh = interpolate(x->x[1]^2*x[2]^2,V); -F(u) = ∫(u)dΩ; -G(u) = ∫(u*u)dΩ; -# H(u) = ∫(cos ∘ u)dΩ; - -struct FunctionOperation - a - b - op -end - -function (*)(a::Function,b::Function) - FunctionOperation(a,b,*) -end - -function (*)(a::Function,b::FunctionOperation) - IntegrandWithMeasureOperation(a,b,*) -end - -(*)(a::FunctionOperation,b::Function) = b*a - -(F*G) - -# d/du F*F -dF = gradient(F,uh); -dFxF = 2dF*sum(F(uh)); -dFxF_new = gradient(FG,uh); -@assert get_array(dFxF_new) == get_array(dFxF) - -# # d/du F*G -# dF_iwf = gradient(F_iwf,uh); -# dG_iwf = gradient(G_iwf,uh); -# dFxG = dF_iwf*sum(G_iwf(uh)) + dG_iwf*sum(F_iwf(uh)); -# dFxG_new = gradient(F_iwf*G_iwf,uh); -# @assert get_array(dFxG) == get_array(dFxG_new) -# # d/du (F*G)*H -# dF_iwf = gradient(F_iwf,uh); -# dG_iwf = gradient(G_iwf,uh); -# dH_iwf = gradient(H_iwf,uh); -# # dFxGxH = dF_iwf*sum(G_iwf(uh)) + dG_iwf*sum(F_iwf(uh)); -# dFxGxH_new = gradient(F_iwf*G_iwf*H_iwf,uh); - -# sum(F_iwf(uh))*sum(G_iwf(uh)) -# (F_iwf*G_iwf)(uh) - -# # get_array(dFxG) == get_array(dFxG_new) \ No newline at end of file diff --git a/scripts/_dev/operations/ops_testing_fn_version.jl b/scripts/_dev/operations/ops_testing_fn_version.jl deleted file mode 100644 index d710c66b..00000000 --- a/scripts/_dev/operations/ops_testing_fn_version.jl +++ /dev/null @@ -1,96 +0,0 @@ -using LevelSetTopOpt -using Gridap -using Gridap.CellData: DomainContribution -using Gridap.FESpaces: _gradient -using GridapDistributed: DistributedDomainContribution -import Base.*, Base./ - -struct FunctionOperation{A} <: Function - a - b - op :: A -end - -(F::FunctionOperation)(args...) = F.op(sum(F.a(args...)),sum(F.b(args...))) - -function (*)(a::Function,b::Function) - FunctionOperation(a,b,*) -end - -function (*)(a::Function,b::FunctionOperation) - FunctionOperation(a,b,*) -end - -(*)(a::FunctionOperation,b::Function) = b*a - -Gridap.gradient(F::FunctionOperation{typeof(*)},xh) = gradient(F.a,xh)*sum(F.b(xh)) + gradient(F.b,xh)*sum(F.a(xh)) - -## Testing with ChainRules.jl -D = 1 -model = CartesianDiscreteModel((0,1,0,1),(10,10)); -Ω = Triangulation(model) -Γ_N = BoundaryTriangulation(model,tags=[6,]) -dΩ = Measure(Ω,2) -dΓ_N = Measure(Γ_N,2) -reffe_scalar = ReferenceFE(lagrangian,Float64,1) -V = TestFESpace(model,reffe_scalar;dirichlet_tags=[1]) -U = TrialFESpace(V,0.0) -V_φ = TestFESpace(model,reffe_scalar) -V_reg = TestFESpace(model,reffe_scalar;dirichlet_tags=[6,]) -U_reg = TrialFESpace(V_reg,0) - -## Create FE functions -φh = interpolate(x->-1,V_φ) -interp = SmoothErsatzMaterialInterpolation(η = 2maximum(get_el_size(model))); -I,_H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - -a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*D*∇(u)⋅∇(v))dΩ -l(v,φ,dΩ,dΓ_N) = ∫(v)dΓ_N - -## Optimisation functionals -J1(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*D*∇(u)⋅∇(u))dΩ -J2(u,φ,dΩ,dΓ_N) = ∫(ρ ∘ φ)dΩ - -J = J1*J2 - -J_iwm = LevelSetTopOpt.IntegrandWithMeasure(J,(dΩ,dΓ_N)); -uh = interpolate(x->x[1]^2*x[2]^2,V); -gradient(J_iwm,[uh,φh],1) - -function Gridap.gradient(F::LevelSetTopOpt.IntegrandWithMeasure{<:FunctionOperation},uh::Vector{<:FEFunction},K::Int) - _f(uk) = F.F(uh[1:K-1]...,uk,uh[K+1:end]...,F.dΩ...) - return gradient(_f,uh[K]) -end - -# state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) -# pcfs = PDEConstrainedFunctionals(J,state_map) - -## TESTING -model = CartesianDiscreteModel((0,1,0,1),(10,10)); -Ω = Triangulation(model) -dΩ = Measure(Ω,2) -V = TestFESpace(model,ReferenceFE(lagrangian,Float64,1)) -uh = interpolate(x->x[1]^2*x[2]^2,V); -F(u) = ∫(u)dΩ; -G(u) = ∫(u*u)dΩ; -H(u) = ∫(cos ∘ u)dΩ; - -# d/du F*F -dF = gradient(F,uh); -dFxF = 2dF*sum(F(uh)); -dFxF_new = gradient(F*F,uh); -@assert get_array(dFxF_new) == get_array(dFxF) - -# d/du F*G -dF = gradient(F,uh); -dG = gradient(G,uh); -dFxG = dF*sum(G(uh)) + dG*sum(F(uh)); -dFxG_new = gradient(F*G,uh); -@assert get_array(dFxG) == get_array(dFxG_new) -# d/du F*G*H -dF = gradient(F,uh); -dG = gradient(G,uh); -dH = gradient(H,uh); -dFxGxH = dF*sum(G(uh))*sum(H(uh)) + dG*sum(F(uh))*sum(H(uh)) + dH*sum(F(uh))*sum(G(uh)); -dFxGxH_new = gradient(F*G*H,uh); -get_array(dFxG) == get_array(dFxG_new) \ No newline at end of file diff --git a/scripts/_dev/operations/ops_testing_iwm.jl b/scripts/_dev/operations/ops_testing_iwm.jl deleted file mode 100644 index 1f50bd63..00000000 --- a/scripts/_dev/operations/ops_testing_iwm.jl +++ /dev/null @@ -1,72 +0,0 @@ -using LevelSetTopOpt -using Gridap -using LevelSetTopOpt: IntegrandWithMeasure -import Base.*, Base./ - -struct IntegrandWithMeasureOperation{A<:Function} - a - b - op :: A -end - -(F::IntegrandWithMeasureOperation)(args...) = F.op(sum(F.a(args...)),sum(F.b(args...))) - -function (*)(a::IntegrandWithMeasure,b::IntegrandWithMeasure) - IntegrandWithMeasureOperation(a,b,*) -end - -function (*)(a::IntegrandWithMeasure,b::IntegrandWithMeasureOperation) - IntegrandWithMeasureOperation(a,b,*) -end - -(*)(a::IntegrandWithMeasureOperation,b::IntegrandWithMeasure) = b*a - -Gridap.gradient(F::IntegrandWithMeasureOperation{typeof(*)},xh) = gradient(F.a,xh)*sum(F.b(xh)) + gradient(F.b,xh)*sum(F.a(xh)) - -# function (/)(a::Number,b::DomainContribution) -# DomainContributionOperation(a,b,/) -# end - -# function (/)(a::DomainContribution,b::DomainContribution) -# DomainContributionOperation(a,b,/) -# end - -# function (/)(a::DomainContribution,b::DomainContributionOperation) -# DomainContributionOperation(a,b,/) -# end - -# function (/)(a::DomainContributionOperation,b::DomainContribution) -# DomainContributionOperation(a,b,/) -# end - -## TESTING -model = CartesianDiscreteModel((0,1,0,1),(10,10)); -Ω = Triangulation(model) -dΩ = Measure(Ω,2) -V = TestFESpace(model,ReferenceFE(lagrangian,Float64,1)) -uh = interpolate(x->x[1]^2*x[2]^2,V); -F_iwf = IntegrandWithMeasure((u,dΩ)->∫(u)dΩ,(dΩ,)); -G_iwf = IntegrandWithMeasure((u,dΩ)->∫(u*u)dΩ,(dΩ,)); -H_iwf = IntegrandWithMeasure((u,dΩ)->∫(cos ∘ u)dΩ,(dΩ,)); -# d/du F*F -dF_iwf = gradient(F_iwf,uh); -dFxF = 2dF_iwf*sum(F_iwf(uh)); -dFxF_new = gradient(F_iwf*F_iwf,uh); -@assert get_array(dFxF_new) == get_array(dFxF) -# d/du F*G -dF_iwf = gradient(F_iwf,uh); -dG_iwf = gradient(G_iwf,uh); -dFxG = dF_iwf*sum(G_iwf(uh)) + dG_iwf*sum(F_iwf(uh)); -dFxG_new = gradient(F_iwf*G_iwf,uh); -@assert get_array(dFxG) == get_array(dFxG_new) -# d/du (F*G)*H -dF_iwf = gradient(F_iwf,uh); -dG_iwf = gradient(G_iwf,uh); -dH_iwf = gradient(H_iwf,uh); -# dFxGxH = dF_iwf*sum(G_iwf(uh)) + dG_iwf*sum(F_iwf(uh)); -dFxGxH_new = gradient(F_iwf*G_iwf*H_iwf,uh); - -sum(F_iwf(uh))*sum(G_iwf(uh)) -(F_iwf*G_iwf)(uh) - -# get_array(dFxG) == get_array(dFxG_new) \ No newline at end of file diff --git a/scripts/_dev/piezo_repeating.jl b/scripts/_dev/piezo_repeating.jl deleted file mode 100644 index 4c069651..00000000 --- a/scripts/_dev/piezo_repeating.jl +++ /dev/null @@ -1,354 +0,0 @@ -using Gridap, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR -using Gridap.TensorValues, Gridap.Helpers, Gridap.MultiField -using GridapSolvers.BlockSolvers - -function PZT5A(D::Int) - ε_0 = 8.854e-12; - if D == 3 - C_Voigt = [12.0400e10 7.52000e10 7.51000e10 0.0 0.0 0.0 - 7.52000e10 12.0400e10 7.51000e10 0.0 0.0 0.0 - 7.51000e10 7.51000e10 11.0900e10 0.0 0.0 0.0 - 0.0 0.0 0.0 2.1000e10 0.0 0.0 - 0.0 0.0 0.0 0.0 2.1000e10 0.0 - 0.0 0.0 0.0 0.0 0.0 2.30e10] - e_Voigt = [0.0 0.0 0.0 0.0 12.30000 0.0 - 0.0 0.0 0.0 12.30000 0.0 0.0 - -5.40000 -5.40000 15.80000 0.0 0.0 0.0] - K_Voigt = [540*ε_0 0 0 - 0 540*ε_0 0 - 0 0 830*ε_0] - elseif D == 2 - C_Voigt = [12.0400e10 7.51000e10 0.0 - 7.51000e10 11.0900e10 0.0 - 0.0 0.0 2.1000e10] - e_Voigt = [0.0 0.0 12.30000 - -5.40000 15.80000 0.0] - K_Voigt = [540*ε_0 0 - 0 830*ε_0] - else - @notimplemented - end - C = voigt2tensor4(C_Voigt) - e = voigt2tensor3(e_Voigt) - κ = voigt2tensor2(K_Voigt) - C,e,κ -end - -""" - Given a material constant given in Voigt notation, - return a SymFourthOrderTensorValue using ordering from Gridap -""" -function voigt2tensor4(A::Array{M,2}) where M - if isequal(size(A),(3,3)) - return SymFourthOrderTensorValue(A[1,1], A[3,1], A[2,1], - A[1,3], A[3,3], A[2,3], - A[1,2], A[3,2], A[2,2]) - elseif isequal(size(A),(6,6)) - return SymFourthOrderTensorValue(A[1,1], A[6,1], A[5,1], A[2,1], A[4,1], A[3,1], - A[1,6], A[6,6], A[5,6], A[2,6], A[4,6], A[3,6], - A[1,5], A[6,5], A[5,5], A[2,5], A[4,5], A[3,5], - A[1,2], A[6,2], A[5,2], A[2,2], A[4,2], A[3,2], - A[1,4], A[6,4], A[5,4], A[2,4], A[4,4], A[3,4], - A[1,3], A[6,3], A[5,3], A[2,3], A[4,3], A[3,3]) - else - @notimplemented - end -end - -""" - Given a material constant given in Voigt notation, - return a ThirdOrderTensorValue using ordering from Gridap -""" -function voigt2tensor3(A::Array{M,2}) where M - if isequal(size(A),(2,3)) - return ThirdOrderTensorValue(A[1,1], A[2,1], A[1,3], A[2,3], A[1,3], A[2,3], A[1,2], A[2,2]) - elseif isequal(size(A),(3,6)) - return ThirdOrderTensorValue( - A[1,1], A[2,1], A[3,1], A[1,6], A[2,6], A[3,6], A[1,5], A[2,5], A[3,5], - A[1,6], A[2,6], A[3,6], A[1,2], A[2,2], A[3,2], A[1,4], A[2,4], A[3,4], - A[1,5], A[2,5], A[3,5], A[1,4], A[2,4], A[3,4], A[1,3], A[2,3], A[3,3]) - else - @notimplemented - end -end - -""" - Given a material constant given in Voigt notation, - return a SymTensorValue using ordering from Gridap -""" -function voigt2tensor2(A::Array{M,2}) where M - return TensorValue(A) -end - -## Parameters -#function main(mesh_partition,distribute) - #ranks = distribute(LinearIndices((prod(mesh_partition),))) - -mesh_partition = (1,1) -ranks = with_mpi() do distribute - distribute(LinearIndices((prod(mesh_partition),))) -end - -el_size = (100,100) -order = 1 -xmax,ymax=(1.0,1.0) -dom = (0,xmax,0,ymax) -γ = 0.1 -γ_reinit = 0.5 -max_steps = floor(Int,order*minimum(el_size)/10) -tol = 1/(5order^2)/minimum(el_size) -η_coeff = 2 -α_coeff = 4*max_steps*γ -vf = 0.5 -path = dirname(@__DIR__)*"/results/2d_PZ_inverse_homenisation_MPI_Nx$(mesh_partition[1])Ny$(mesh_partition[2])/" -#i_am_main(ranks) && mkpath(path) - -## FE Setup -model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true)) -el_Δ = get_el_Δ(model) -f_Γ_D(x) = iszero(x) -update_labels!(1,model,f_Γ_D,"origin") - -## Triangulations and measures -Ω = Triangulation(model) -dΩ = Measure(Ω,2*order) -vol_D = sum(∫(1)dΩ) - -## Spaces -reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) -reffe_scalar = ReferenceFE(lagrangian,Float64,order) -V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["origin"]) -U = TrialFESpace(V,VectorValue(0.0,0.0)) -Q = TestFESpace(model,reffe_scalar;conformity=:H1,dirichlet_tags=["origin"]) -P = TrialFESpace(Q,0) -mfs = BlockMultiFieldStyle() -UP = MultiFieldFESpace([U,P];style=mfs) -VQ = MultiFieldFESpace([V,Q];style=mfs) - -V_φ = TestFESpace(model,reffe_scalar) -V_reg = TestFESpace(model,reffe_scalar) -U_reg = TrialFESpace(V_reg) - -## Create FE functions -lsf_fn = initial_lsf(2,0.2) -φh = interpolate(lsf_fn,V_φ) - -## Interpolation and weak form -interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ),ϵ=10^-9) -I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - -## Material tensors -C, e, κ = PZT5A(2); -k0 = norm(C.data,Inf); -α0 = norm(e.data,Inf); -β0 = norm(κ.data,Inf); -γ0 = β0*k0/α0^2; - -## Weak forms -εᴹ = (SymTensorValue(1.0,0.0,0.0), - SymTensorValue(0.0,0.0,1.0), - SymTensorValue(0.0,1/2,0)) -Eⁱ = (VectorValue(1.0,0.0,), - VectorValue(0.0,1.0)) - -a((u,ϕ),(v,q),φ,dΩ) = ∫((I ∘ φ) * (1/k0*((C ⊙ ε(u)) ⊙ ε(v)) - - 1/α0*((-∇(ϕ) ⋅ e) ⊙ ε(v)) + - -1/α0*((e ⋅² ε(u)) ⋅ -∇(q)) + - -γ0/β0*((κ ⋅ -∇(ϕ)) ⋅ -∇(q))) )dΩ; - -l_ε = [((v,q),φ,dΩ) -> ∫(((I ∘ φ) * (-C ⊙ εᴹ[i] ⊙ ε(v) + k0/α0*(e ⋅² εᴹ[i]) ⋅ -∇(q))))dΩ for i = 1:3]; -l_E = [((v,q),φ,dΩ) -> ∫((I ∘ φ) * ((Eⁱ[i] ⋅ e ⊙ ε(v) + k0/α0*(κ ⋅ Eⁱ[i]) ⋅ -∇(q))))dΩ for i = 1:2]; -l = [l_ε; l_E] - -## Optimisation functionals -# Note, uϕ unpacks as -> uϕ = u1,ϕ1,u2,ϕ2,u3,ϕ3,u4,ϕ4,u5,ϕ5 -# where entries 1,2,3 correspond to εᴹ[1],εᴹ[2],εᴹ[3] and -# 4,5 correspond to Eⁱ[1],Eⁱ[2]. - -function Cᴴ(r,s,uϕ,φ,dΩ) # (normalised by 1/k0) - u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] - ∫(1/k0 * (I ∘ φ) * (((C ⊙ (1/k0*ε(u_s) + εᴹ[s])) ⊙ εᴹ[r]) - ((-1/α0*∇(ϕ_s) ⋅ e) ⊙ εᴹ[r])))dΩ; -end - -function DCᴴ(r,s,q,uϕ,φ,dΩ) # (normalised by 1/k0) - u_r = uϕ[2r-1]; ϕ_r = uϕ[2r] - u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] - ∫(- 1/k0 * q * ( - (C ⊙ (1/k0*ε(u_s) + εᴹ[s])) ⊙ (1/k0*ε(u_r) + εᴹ[r]) - - (-1/α0*∇(ϕ_s) ⋅ e) ⊙ (1/k0*ε(u_r) + εᴹ[r]) - - (e ⋅² (1/k0*ε(u_s) + εᴹ[s])) ⋅ (-1/α0*∇(ϕ_r)) - - (κ ⋅ (-1/α0*∇(ϕ_s))) ⋅ (-1/α0*∇(ϕ_r)) - ) * (DH ∘ φ) * (norm ∘ ∇(φ)) - )dΩ; -end - -function eᴴ(i,s,uϕ,φ,dΩ) # (normalised by 1/α0) - u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] - ∫(1/α0 * (I ∘ φ) * (((e ⋅² (1/k0*ε(u_s) + εᴹ[s])) ⋅ Eⁱ[i]) + ((κ ⋅ (-1/α0*∇(ϕ_s))) ⋅ Eⁱ[i])))dΩ; -end - -function Deᴴ(i,s,q,uϕ,φ,dΩ) # (normalised by 1/α0) - u_i = uϕ[6+2i-1]; ϕ_i = uϕ[6+2i] - u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] - ∫(- 1/α0 * q * ( - - (C ⊙ (1/k0*ε(u_s) + εᴹ[s])) ⊙ (1/k0*ε(u_i)) + - (-1/α0*∇(ϕ_s) ⋅ e) ⊙ (1/k0*ε(u_i)) + - (e ⋅² (1/k0*ε(u_s) + εᴹ[s])) ⋅ (-1/α0*∇(ϕ_i) + Eⁱ[i]) + - (κ ⋅ (-1/α0*∇(ϕ_s))) ⋅ (-1/α0*∇(ϕ_i) + Eⁱ[i]) - ) * (DH ∘ φ) * (norm ∘ ∇(φ)) - )dΩ; -end - -function κᴴ(i,j,uϕ,φ,dΩ) # (normalised by 1/β0) - u_j = uϕ[6+2j-1]; ϕ_j = uϕ[6+2j] - ∫(1/β0 * (I ∘ φ) * (((e ⋅² (1/k0*ε(u_j)) ⋅ Eⁱ[i]) + ((κ ⋅ (-1/α0*∇(ϕ_j) + Eⁱ[j])) ⋅ Eⁱ[i]))))dΩ; -end - -function Dκᴴ(i,j,q,uϕ,φ,dΩ) # (normalised by 1/β0) - u_i = uϕ[6+2i-1]; ϕ_i = uϕ[6+2i] - u_j = uϕ[6+2j-1]; ϕ_j = uϕ[6+2j] - ∫(- 1/β0 * q * ( - - (C ⊙ (1/k0*ε(u_j))) ⊙ (1/k0*ε(u_i)) + - ((-1/α0*∇(ϕ_j) + Eⁱ[j]) ⋅ e) ⊙ (1/k0*ε(u_i)) + - (e ⋅² (1/k0*ε(u_j))) ⋅ (-1/α0*∇(ϕ_i) + Eⁱ[i]) + - (κ ⋅ (-1/α0*∇(ϕ_j) + Eⁱ[j])) ⋅ (-1/α0*∇(ϕ_i) + Eⁱ[i]) - ) * (DH ∘ φ) * (norm ∘ ∇(φ)) - )dΩ; -end - -# Equiv to -# C_mat = map(rs->sum(Cᴴ(rs[1],rs[2],xh,φh,dΩ)), CartesianIndices((1:3, 1:3))) -# e_mat = map(is->sum(eᴴ(is[1],is[2],xh,φh,dΩ)), CartesianIndices((1:2, 1:3))) -# d_mat = e_mat*inv(C_mat); -# dh = d_mat[2,1] + d_mat[2,2] -function dᴴ(uϕ,φ,dΩ) - # We leave eᴴ_21 and eᴴ_22 as DomainContribution so that result is a DomainContribution. - # Note that this means AD applied to this functional would be incorrect. - Cᴴ_11 = sum(Cᴴ(1,1,uϕ,φ,dΩ)); - Cᴴ_22 = sum(Cᴴ(2,2,uϕ,φ,dΩ)); - Cᴴ_21 = sum(Cᴴ(2,1,uϕ,φ,dΩ)); - eᴴ_21 = eᴴ(2,1,uϕ,φ,dΩ); - eᴴ_22 = eᴴ(2,2,uϕ,φ,dΩ); - (Cᴴ_22*eᴴ_21 + Cᴴ_11*eᴴ_22 - Cᴴ_21*(eᴴ_21 + eᴴ_22))*(1/(Cᴴ_11*Cᴴ_22 - Cᴴ_21^2)) -end - -function Ddᴴ(q,uϕ,φ,dΩ) - Cᴴ_11 = sum(Cᴴ(1,1,uϕ,φ,dΩ)); DCᴴ_11 = DCᴴ(1,1,q,uϕ,φ,dΩ) - Cᴴ_22 = sum(Cᴴ(2,2,uϕ,φ,dΩ)); DCᴴ_22 = DCᴴ(2,2,q,uϕ,φ,dΩ) - Cᴴ_21 = sum(Cᴴ(2,1,uϕ,φ,dΩ)); DCᴴ_21 = DCᴴ(2,1,q,uϕ,φ,dΩ) - eᴴ_21 = sum(eᴴ(2,1,uϕ,φ,dΩ)); Deᴴ_21 = DCᴴ(2,1,q,uϕ,φ,dΩ) - eᴴ_22 = sum(eᴴ(2,2,uϕ,φ,dΩ)); Deᴴ_22 = DCᴴ(2,2,q,uϕ,φ,dΩ) - (-1*Cᴴ_11^2*eᴴ_22*(DCᴴ_22)+Cᴴ_22^2*(-eᴴ_21*(DCᴴ_11)+Cᴴ_11*(Deᴴ_21))+ - Cᴴ_21^3*((Deᴴ_21)+(Deᴴ_22))+Cᴴ_11*Cᴴ_22*(-1*((eᴴ_21+eᴴ_22)*(DCᴴ_21))+ - Cᴴ_11*(Deᴴ_22))-Cᴴ_21^2*(eᴴ_22*((DCᴴ_11)+(DCᴴ_21))+eᴴ_21*((DCᴴ_21)+(DCᴴ_22))+ - Cᴴ_22*(Deᴴ_21)+Cᴴ_11*(Deᴴ_22))+Cᴴ_21*(Cᴴ_11*(2*eᴴ_22*(DCᴴ_21)+(eᴴ_21+eᴴ_22)*(DCᴴ_22))+ - Cᴴ_22*((eᴴ_21+eᴴ_22)*(DCᴴ_11)+2*eᴴ_21*(DCᴴ_21)-Cᴴ_11*((Deᴴ_21)+(Deᴴ_22)))))*(1/(Cᴴ_21^2-Cᴴ_11*Cᴴ_22)^2) -end - -Bᴴ(uϕ,φ,dΩ) = 1/4*(Cᴴ(1,1,uϕ,φ,dΩ)+Cᴴ(2,2,uϕ,φ,dΩ)+2*Cᴴ(1,2,uϕ,φ,dΩ)) -DBᴴ(q,uϕ,φ,dΩ) = 1/4*(DCᴴ(1,1,q,uϕ,φ,dΩ)+DCᴴ(2,2,q,uϕ,φ,dΩ)+2*DCᴴ(1,2,q,uϕ,φ,dΩ)) - - -J(uϕ,φ,dΩ) = -1*dᴴ(uϕ,φ,dΩ) -DJ(q,uϕ,φ,dΩ) = -1*Ddᴴ(q,uϕ,φ,dΩ) -C1(uϕ,φ,dΩ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; -DC1(q,uϕ,φ,dΩ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ -C2(uϕ,φ,dΩ) = Cᴴ(2,2,uϕ,φ,dΩ) - ∫(0.05/vol_D)dΩ -DC2(q,uϕ,φ,dΩ) = DCᴴ(2,2,q,uϕ,φ,dΩ) - -# ## Finite difference solver and level set function -stencil = HamiltonJacobiEvolution(FirstOrderStencil(2,Float64),model,V_φ,tol,max_steps) - -# ## Setup solver and FE operators -Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} -Tv = Vector{PetscScalar} -solver_u = LUSolver() #ElasticitySolver(V) #GridapSolvers.LinearSolvers.ElasticitySolver(V) -solver_ϕ = LUSolver() #PETScLinearSolver() - -# P = GridapSolvers.BlockDiagonalSolver([solver_u,solver_ϕ]) -# solver = GridapSolvers.LinearSolvers.GMRESSolver(100;Pr=P,rtol=1.e-8,verbose=i_am_main(ranks)) -solver = BlockTriangularSolver([solver_u,solver_ϕ]) - -state_map = RepeatingAffineFEStateMap(5,a,l,UP,VQ,V_φ,U_reg,φh,dΩ; - assem_U = SparseMatrixAssembler(Tm,Tv,UP,VQ), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,VQ,UP), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = solver,adjoint_ls = solver -) -pcfs = PDEConstrainedFunctionals(J,[C1,C2],state_map;analytic_dJ=DJ,analytic_dC=[DC1,DC2]) - -# ## Hilbertian extension-regularisation problems -α = α_coeff*maximum(el_Δ) -a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; -vel_ext = VelocityExtension( - a_hilb,U_reg,V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = PETScLinearSolver() -) - -# ## Optimiser -has_oscillations(m,os_it) = LevelSetTopOpt.default_has_oscillations(m,os_it;itlength=25) -optimiser = HilbertianProjection(pcfs,stencil,vel_ext,φh;γ,γ_reinit,has_oscillations, - verbose=i_am_main(ranks),ls_enabled=true) -for (it, uh, φh) in optimiser - u1,ϕ1,u2,ϕ2,u3,ϕ3,u4,ϕ4,u5,ϕ5 = uh - data = ["φ"=>φh,"H(φ)"=>(H ∘ φh),"|∇(φ)|"=>(norm ∘ ∇(φh)), - "u1"=>1/k0*u1,"ϕ1"=>1/α0*ϕ1,"u2"=>1/k0*u2,"ϕ2"=>1/α0*ϕ2,"u3"=>1/k0*u3,"ϕ3"=>1/α0*ϕ3, - "u4"=>1/k0*u4,"ϕ4"=>1/α0*ϕ4,"u5"=>1/k0*u5,"ϕ5"=>1/α0*ϕ5] - writevtk(Ω,path*"out$it",cellfields=data) - write_history(path*"/history.txt",optimiser.history) -end -#end - -#with_debug() do distribute -# mesh_partition = (2,2) -# solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -# -ksp_converged_reason -ksp_rtol 1.0e-12" -# GridapPETSc.with(args=split(solver_options)) do -# main(mesh_partition,distribute) -# end -#end - -# mesh_partition = (2,2) -# ranks = with_debug() do distribute -# distribute(LinearIndices((prod(mesh_partition),))) -# end - -# el_size = (200,200) -# order = 1 -# xmax,ymax=(1.0,1.0) -# dom = (0,xmax,0,ymax) -# γ = 0.1 -# γ_reinit = 0.5 -# max_steps = floor(Int,order*minimum(el_size)/10) -# tol = 1/(5order^2)/minimum(el_size) -# η_coeff = 2 -# α_coeff = 4*max_steps*γ -# vf = 0.5 - -# ## FE Setup -# model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true)) -# el_Δ = get_el_Δ(model) -# f_Γ_D(x) = iszero(x) -# update_labels!(1,model,f_Γ_D,"origin") - -# ## Triangulations and measures -# Ω = Triangulation(model) -# dΩ = Measure(Ω,2*order) -# vol_D = sum(∫(1)dΩ) - -# ## Spaces -# reffe = ReferenceFE(lagrangian,VectorValue{2,Float64},order) -# reffe_scalar = ReferenceFE(lagrangian,Float64,order) -# V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["origin"]) -# U = TrialFESpace(V,VectorValue(0.0,0.0)) -# Q = TestFESpace(model,reffe_scalar;conformity=:H1,dirichlet_tags=["origin"]) -# P = TrialFESpace(Q,0) -# mfs = BlockMultiFieldStyle() -# UP = MultiFieldFESpace([U,P];style=mfs) -# VQ = MultiFieldFESpace([V,Q];style=mfs) - -# Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} -# Tv = Vector{PetscScalar} -# assem = SparseMatrixAssembler(Tm,Tv,UP,VQ) diff --git a/scripts/_dev/piezo_script.jl b/scripts/_dev/piezo_script.jl deleted file mode 100644 index f4e7faae..00000000 --- a/scripts/_dev/piezo_script.jl +++ /dev/null @@ -1,154 +0,0 @@ -using Gridap, Gridap.TensorValues, Gridap.Geometry, Gridap.FESpaces, Gridap.Helpers, Gridap.Algebra -using GridapDistributed -using GridapPETSc -using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code -using PartitionedArrays -using SparseMatricesCSR -using ChainRulesCore -using LevelSetTopOpt - -using GridapSolvers -using Gridap.MultiField - -function PZT5A(D::Int) - ε_0 = 8.854e-12; - if D == 3 - C_Voigt = [12.0400e10 7.52000e10 7.51000e10 0.0 0.0 0.0 - 7.52000e10 12.0400e10 7.51000e10 0.0 0.0 0.0 - 7.51000e10 7.51000e10 11.0900e10 0.0 0.0 0.0 - 0.0 0.0 0.0 2.1000e10 0.0 0.0 - 0.0 0.0 0.0 0.0 2.1000e10 0.0 - 0.0 0.0 0.0 0.0 0.0 2.30e10] - e_Voigt = [0.0 0.0 0.0 0.0 12.30000 0.0 - 0.0 0.0 0.0 12.30000 0.0 0.0 - -5.40000 -5.40000 15.80000 0.0 0.0 0.0] - K_Voigt = [540*ε_0 0 0 - 0 540*ε_0 0 - 0 0 830*ε_0] - elseif D == 2 - C_Voigt = [12.0400e10 7.51000e10 0.0 - 7.51000e10 11.0900e10 0.0 - 0.0 0.0 2.1000e10] - e_Voigt = [0.0 0.0 12.30000 - -5.40000 15.80000 0.0] - K_Voigt = [540*ε_0 0 - 0 830*ε_0] - else - @notimplemented - end - C = voigt2tensor4(C_Voigt) - e = voigt2tensor3(e_Voigt) - κ = voigt2tensor2(K_Voigt) - C,e,κ -end - -""" - Given a material constant given in Voigt notation, - return a SymFourthOrderTensorValue using ordering from Gridap -""" -function voigt2tensor4(A::Array{M,2}) where M - if isequal(size(A),(3,3)) - return SymFourthOrderTensorValue(A[1,1], A[3,1], A[2,1], - A[1,3], A[3,3], A[2,3], - A[1,2], A[3,2], A[2,2]) - elseif isequal(size(A),(6,6)) - return SymFourthOrderTensorValue(A[1,1], A[6,1], A[5,1], A[2,1], A[4,1], A[3,1], - A[1,6], A[6,6], A[5,6], A[2,6], A[4,6], A[3,6], - A[1,5], A[6,5], A[5,5], A[2,5], A[4,5], A[3,5], - A[1,2], A[6,2], A[5,2], A[2,2], A[4,2], A[3,2], - A[1,4], A[6,4], A[5,4], A[2,4], A[4,4], A[3,4], - A[1,3], A[6,3], A[5,3], A[2,3], A[4,3], A[3,3]) - else - @notimplemented - end -end - -""" - Given a material constant given in Voigt notation, - return a ThirdOrderTensorValue using ordering from Gridap -""" -function voigt2tensor3(A::Array{M,2}) where M - if isequal(size(A),(2,3)) - return ThirdOrderTensorValue(A[1,1], A[2,1], A[1,3], A[2,3], A[1,3], A[2,3], A[1,2], A[2,2]) - elseif isequal(size(A),(3,6)) - return ThirdOrderTensorValue( - A[1,1], A[2,1], A[3,1], A[1,6], A[2,6], A[3,6], A[1,5], A[2,5], A[3,5], - A[1,6], A[2,6], A[3,6], A[1,2], A[2,2], A[3,2], A[1,4], A[2,4], A[3,4], - A[1,5], A[2,5], A[3,5], A[1,4], A[2,4], A[3,4], A[1,3], A[2,3], A[3,3]) - else - @notimplemented - end -end - -""" - Given a material constant given in Voigt notation, - return a SymTensorValue using ordering from Gridap -""" -function voigt2tensor2(A::Array{M,2}) where M - return TensorValue(A) -end - -function main(mesh_partition,distribute) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - - order = 1; - el_size = (30,30,30); - dom = (0.,1.,0.,1.,0.,1.); - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size,isperiodic=(true,true,true)); - ## Define Γ_N and Γ_D - f_Γ_D(x) = iszero(x) - update_labels!(1,model,f_Γ_D,"origin") - ## Triangulations and measures - Ω = Triangulation(model) - dΩ = Measure(Ω,2order) - ## Spaces - reffe = ReferenceFE(lagrangian,VectorValue{3,Float64},order) - reffe_scalar = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;conformity=:H1,dirichlet_tags=["origin"]) - U = TrialFESpace(V,VectorValue(0.0,0.0,0.0)) - Q = TestFESpace(model,reffe_scalar;conformity=:H1,dirichlet_tags=["origin"]) - P = TrialFESpace(Q,0) - - mfs = BlockMultiFieldStyle() - UP = MultiFieldFESpace([U,P];style=mfs) - VQ = MultiFieldFESpace([V,Q];style=mfs) - - C, e, κ = PZT5A(3); - k0 = norm(C.data,Inf); - α0 = norm(e.data,Inf); - β0 = norm(κ.data,Inf); - γ = β0*k0/α0^2; - - ϵ⁰ = TensorValue(1.,0.,0.,0.,0.,0.,0.,0.,0.); - - a((u, ϕ),(v, q)) = ∫(1/k0*C ⊙ ε(u) ⊙ ε(v) - - 1/α0*((-∇(ϕ) ⋅ e) ⊙ ε(v)) + - -1/α0*((e ⋅² ε(u)) ⋅ -∇(q)) + - -γ/β0*((κ ⋅ -∇(ϕ)) ⋅ -∇(q)) )dΩ; - - l((v, q)) = ∫(-C ⊙ ϵ⁰ ⊙ ε(v) + k0/α0*((e ⋅² ϵ⁰) ⋅ -∇(q)))dΩ; - - assem = SparseMatrixAssembler(SparseMatrixCSR{0,PetscScalar,PetscInt},Vector{PetscScalar},UP,VQ) - op = AffineFEOperator(a,l,UP,VQ,assem) - ## Solve - #options = "-pc_type bjacobi -ksp_type gmres -ksp_error_if_not_converged true - # -ksp_converged_reason -ksp_rtol 1.0e-10 -ksp_monitor_short" - options = "-ksp_converged_reason -pc_type gamg -ksp_type cg " - GridapPETSc.with(args=split(options)) do - # ls = PETScLinearSolver() - # xh = solve(ls,op) - solver_u = ElasticitySolver(V) - solver_ϕ = PETScLinearSolver() - P = BlockDiagonalPreconditioner([solver_u,solver_ϕ]) - solver = GridapSolvers.LinearSolvers.GMRESSolver(100;Pr=P,rtol=1.e-8,verbose=i_am_main(ranks)) - A = get_matrix(op) - b = get_vector(op) - ns = numerical_setup(symbolic_setup(solver,A),A) - x = allocate_in_domain(A); fill!(x,0.0) - solve!(x,ns,b) - end -end; - -with_mpi() do distribute - main((2,2,1),distribute) -end; diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation.jl deleted file mode 100644 index 91dbabaa..00000000 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation.jl +++ /dev/null @@ -1,76 +0,0 @@ -using Gridap, LevelSetTopOpt - -# FE parameters -order = 1 # Finite element order -xmax = ymax = 1.0 # Domain size -dom = (0,xmax,0,ymax) # Bounding domain -el_size = (200,200) # Mesh partition size -prop_Γ_N = 0.2 # Γ_N size parameter -prop_Γ_D = 0.2 # Γ_D size parameter -f_Γ_N(x) = (x[1] ≈ xmax && # Γ_N indicator function - ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) -f_Γ_D(x) = (x[1] ≈ 0.0 && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) -# FD parameters -γ = 0.1 # HJ equation time step coefficient -γ_reinit = 0.5 # Reinit. equation time step coefficient -max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection -tol = 1/(5order^2)/minimum(el_size) # Advection tolerance -# Problem parameters -κ = 1 # Diffusivity -g = 1 # Heat flow in -vf = 0.4 # Volume fraction constraint -lsf_func = initial_lsf(4,0.2) # Initial level set function -iter_mod = 10 # Output VTK files every 10th iteration -path = "./results/tut1/" # Output path -mkpath(path) # Create path -# Model -model = CartesianDiscreteModel(dom,el_size); -update_labels!(1,model,f_Γ_D,"Gamma_D") -update_labels!(2,model,f_Γ_N,"Gamma_N") -# Triangulation and measures -Ω = Triangulation(model) -Γ_N = BoundaryTriangulation(model,tags="Gamma_N") -dΩ = Measure(Ω,2*order) -dΓ_N = Measure(Γ_N,2*order) -# Spaces -reffe = ReferenceFE(lagrangian,Float64,order) -V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) -U = TrialFESpace(V,0.0) -V_φ = TestFESpace(model,reffe) -V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) -U_reg = TrialFESpace(V_reg,0) -# Level set and interpolator -φh = interpolate(lsf_func,V_φ) -interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) -I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ -# Weak formulation -a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ -l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N -state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) -# Objective and constraints -J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ -dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ -vol_D = sum(∫(1)dΩ) -C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ -dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ -pcfs = PDEConstrainedFunctionals(J,[C],state_map,analytic_dJ=dJ,analytic_dC=[dC]) -# Velocity extension -α = 4*maximum(get_el_Δ(model)) -a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ -vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) -# Finite difference scheme -scheme = FirstOrderStencil(length(el_size),Float64) -ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) -# Optimiser -optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) -# Solve -for (it,uh,φh) in optimiser - data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && (writevtk(Ω,path*"struc_$it",cellfields=data);GC.gc()) - write_history(path*"/history.txt",get_history(optimiser)) -end -# Final structure -it = get_history(optimiser).niter; uh = get_state(pcfs) -writevtk(Ω,path*"struc_$it",cellfields=["phi"=>φh, - "H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) \ No newline at end of file diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d.jl deleted file mode 100644 index 8218dabf..00000000 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d.jl +++ /dev/null @@ -1,78 +0,0 @@ -using Gridap, LevelSetTopOpt - -# FE parameters -order = 1 # Finite element order -xmax=ymax=zmax=1.0 # Domain size -dom = (0,xmax,0,ymax,0,zmax) # Bounding domain -el_size = (40,40,40) # Mesh partition size -prop_Γ_N = 0.2 # Γ_N size parameter -prop_Γ_D = 0.2 # Γ_D size parameter -f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function - (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) && - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) -f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps()) && - (x[3] <= zmax*prop_Γ_D + eps() || x[3] >= zmax-zmax*prop_Γ_D - eps()) -# FD parameters -γ = 0.1 # HJ equation time step coefficient -γ_reinit = 0.5 # Reinit. equation time step coefficient -max_steps = floor(Int,minimum(el_size)/3) # Max steps for advection -tol = 1/(2order^2)/minimum(el_size) # Advection tolerance -# Problem parameters -κ = 1 # Diffusivity -g = 1 # Heat flow in -vf = 0.4 # Volume fraction constraint -lsf_func = initial_lsf(4,0.2) # Initial level set function -iter_mod = 10 # Output VTK files every 10th iteration -path = "./results/tut1_3d/" # Output path -mkpath(path) # Create path -# Model -model = CartesianDiscreteModel(dom,el_size); -update_labels!(1,model,f_Γ_D,"Gamma_D") -update_labels!(2,model,f_Γ_N,"Gamma_N") -# Triangulation and measures -Ω = Triangulation(model) -Γ_N = BoundaryTriangulation(model,tags="Gamma_N") -dΩ = Measure(Ω,2*order) -dΓ_N = Measure(Γ_N,2*order) -# Spaces -reffe = ReferenceFE(lagrangian,Float64,order) -V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) -U = TrialFESpace(V,0.0) -V_φ = TestFESpace(model,reffe) -V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) -U_reg = TrialFESpace(V_reg,0) -# Level set and interpolator -φh = interpolate(lsf_func,V_φ) -interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) -I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ -# Weak formulation -a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ -l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N -state_map = AffineFEStateMap(a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) -# Objective and constraints -J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ -dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ -vol_D = sum(∫(1)dΩ) -C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ -dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ -pcfs = PDEConstrainedFunctionals(J,[C],state_map,analytic_dJ=dJ,analytic_dC=[dC]) -# Velocity extension -α = 4*maximum(get_el_Δ(model)) -a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ -vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) -# Finite difference scheme -scheme = FirstOrderStencil(length(el_size),Float64) -ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) -# Optimiser -optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) -# Solve -for (it,uh,φh) in optimiser - data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && (writevtk(Ω,path*"struc_$it",cellfields=data);GC.gc()) - write_history(path*"/history.txt",get_history(optimiser)) -end -# Final structure -it = get_history(optimiser).niter; uh = get_state(pcfs) -writevtk(Ω,path*"struc_$it",cellfields=["phi"=>φh, - "H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) \ No newline at end of file diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc.jl deleted file mode 100644 index 10c1dacf..00000000 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc.jl +++ /dev/null @@ -1,99 +0,0 @@ -using Gridap, GridapPETSc, SparseMatricesCSR, LevelSetTopOpt - -function main() - # FE parameters - order = 1 # Finite element order - xmax=ymax=zmax=1.0 # Domain size - dom = (0,xmax,0,ymax,0,zmax) # Bounding domain - el_size = (100,100,100) # Mesh partition size - prop_Γ_N = 0.2 # Γ_N size parameter - prop_Γ_D = 0.2 # Γ_D size parameter - f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function - (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) && - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps()) && - (x[3] <= zmax*prop_Γ_D + eps() || x[3] >= zmax-zmax*prop_Γ_D - eps()) - # FD parameters - γ = 0.1 # HJ equation time step coefficient - γ_reinit = 0.5 # Reinit. equation time step coefficient - max_steps = floor(Int,minimum(el_size)/3) # Max steps for advection - tol = 1/(2order^2)/minimum(el_size) # Advection tolerance - # Problem parameters - κ = 1 # Diffusivity - g = 1 # Heat flow in - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - iter_mod = 10 # Output VTK files every 10th iteration - path = "./results/tut1_3d_petsc/" # Output path - mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe) - V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N - # State map - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - state_map = AffineFEStateMap( - a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = PETScLinearSolver(),adjoint_ls = PETScLinearSolver() - ) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - vol_D = sum(∫(1)dΩ) - C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C],state_map,analytic_dJ=dJ,analytic_dC=[dC]) - # Velocity extension - α = 4*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = PETScLinearSolver() - ) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) - # Solve - for (it,uh,φh) in optimiser - data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && (writevtk(Ω,path*"struc_$it",cellfields=data);GC.gc()) - write_history(path*"/history.txt",get_history(optimiser)) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"struc_$it",cellfields=["phi"=>φh, - "H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" -GridapPETSc.with(args=split(solver_options)) do - main() -end \ No newline at end of file diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc_mpi.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc_mpi.jl deleted file mode 100644 index 1b88fd91..00000000 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_3d_petsc_mpi.jl +++ /dev/null @@ -1,104 +0,0 @@ -using Gridap, GridapPETSc, GridapDistributed, PartitionedArrays, SparseMatricesCSR, LevelSetTopOpt - -function main(mesh_partition,distribute) - ranks = distribute(LinearIndices((prod(mesh_partition),))) - # FE parameters - order = 1 # Finite element order - xmax=ymax=zmax=1.0 # Domain size - dom = (0,xmax,0,ymax,0,zmax) # Bounding domain - el_size = (100,100,100) # Mesh partition size - prop_Γ_N = 0.2 # Γ_N size parameter - prop_Γ_D = 0.2 # Γ_D size parameter - f_Γ_N(x) = (x[1] ≈ xmax) && # Γ_N indicator function - (ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) && - (zmax/2-zmax*prop_Γ_N/2 - eps() <= x[3] <= zmax/2+zmax*prop_Γ_N/2 + eps()) - f_Γ_D(x) = (x[1] ≈ 0.0) && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps()) && - (x[3] <= zmax*prop_Γ_D + eps() || x[3] >= zmax-zmax*prop_Γ_D - eps()) - # FD parameters - γ = 0.1 # HJ equation time step coefficient - γ_reinit = 0.5 # Reinit. equation time step coefficient - max_steps = floor(Int,minimum(el_size)/3) # Max steps for advection - tol = 1/(2order^2)/minimum(el_size) # Advection tolerance - # Problem parameters - κ = 1 # Diffusivity - g = 1 # Heat flow in - vf = 0.4 # Volume fraction constraint - lsf_func = initial_lsf(4,0.2) # Initial level set function - iter_mod = 10 # Output VTK files every 10th iteration - path = "./results/tut1_3d_petsc_mpi/" # Output path - i_am_main(ranks) && mkpath(path) # Create path - # Model - model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); - update_labels!(1,model,f_Γ_D,"Gamma_D") - update_labels!(2,model,f_Γ_N,"Gamma_N") - # Triangulation and measures - Ω = Triangulation(model) - Γ_N = BoundaryTriangulation(model,tags="Gamma_N") - dΩ = Measure(Ω,2*order) - dΓ_N = Measure(Γ_N,2*order) - # Spaces - reffe = ReferenceFE(lagrangian,Float64,order) - V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) - U = TrialFESpace(V,0.0) - V_φ = TestFESpace(model,reffe) - V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) - U_reg = TrialFESpace(V_reg,0) - # Level set and interpolator - φh = interpolate(lsf_func,V_φ) - interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) - I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ - # Weak formulation - a(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ - l(v,φ,dΩ,dΓ_N) = ∫(g*v)dΓ_N - # State map - Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} - Tv = Vector{PetscScalar} - state_map = AffineFEStateMap( - a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_N; - assem_U = SparseMatrixAssembler(Tm,Tv,U,V), - assem_adjoint = SparseMatrixAssembler(Tm,Tv,V,U), - assem_deriv = SparseMatrixAssembler(Tm,Tv,U_reg,U_reg), - ls = PETScLinearSolver(),adjoint_ls = PETScLinearSolver() - ) - # Objective and constraints - J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ - dJ(q,u,φ,dΩ,dΓ_N) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - vol_D = sum(∫(1)dΩ) - C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ - dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ - pcfs = PDEConstrainedFunctionals(J,[C],state_map,analytic_dJ=dJ,analytic_dC=[dC]) - # Velocity extension - α = 4*maximum(get_el_Δ(model)) - a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ - vel_ext = VelocityExtension( - a_hilb, U_reg, V_reg; - assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), - ls = PETScLinearSolver() - ) - # Finite difference scheme - scheme = FirstOrderStencil(length(el_size),Float64) - ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) - # Optimiser - optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; - γ,γ_reinit,verbose=i_am_main(ranks),constraint_names=[:Vol]) - # Solve - for (it,uh,φh) in optimiser - data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && (writevtk(Ω,path*"struc_$it",cellfields=data);GC.gc()) - write_history(path*"/history.txt",get_history(optimiser)) - end - # Final structure - it = get_history(optimiser).niter; uh = get_state(pcfs) - writevtk(Ω,path*"struc_$it",cellfields=["phi"=>φh, - "H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) -end - -with_mpi() do distribute - mesh_partition = (2,2,2) - solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true - -ksp_converged_reason -ksp_rtol 1.0e-12" - GridapPETSc.with(args=split(solver_options)) do - main(mesh_partition,distribute) - end -end \ No newline at end of file diff --git a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_nonlinear.jl b/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_nonlinear.jl deleted file mode 100644 index 3642fb95..00000000 --- a/scripts/_dev/tutorial_test/minimum_thermal_compliance_implementation_nonlinear.jl +++ /dev/null @@ -1,74 +0,0 @@ -using Gridap, LevelSetTopOpt - -# FE parameters -order = 1 # Finite element order -xmax = ymax = 1.0 # Domain size -dom = (0,xmax,0,ymax) # Bounding domain -el_size = (200,200) # Mesh partition size -prop_Γ_N = 0.2 # Γ_N size parameter -prop_Γ_D = 0.2 # Γ_D size parameter -f_Γ_N(x) = (x[1] ≈ xmax && # Γ_N indicator function - ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) -f_Γ_D(x) = (x[1] ≈ 0.0 && # Γ_D indicator function - (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) -# FD parameters -γ = 0.1 # HJ equation time step coefficient -γ_reinit = 0.5 # Reinit. equation time step coefficient -max_steps = floor(Int,minimum(el_size)/10) # Max steps for advection -tol = 1/(5order^2)/minimum(el_size) # Advection tolerance -# Problem parameters -κ(u) = exp(-u) # Diffusivity -g = 1 # Heat flow in -vf = 0.4 # Volume fraction constraint -lsf_func = initial_lsf(4,0.2) # Initial level set function -iter_mod = 10 # Output VTK files every 10th iteration -path = "./results/tut1_nonlinear/" # Output path -mkpath(path) # Create path -# Model -model = CartesianDiscreteModel(dom,el_size); -update_labels!(1,model,f_Γ_D,"Gamma_D") -update_labels!(2,model,f_Γ_N,"Gamma_N") -# Triangulation and measures -Ω = Triangulation(model) -Γ_N = BoundaryTriangulation(model,tags="Gamma_N") -dΩ = Measure(Ω,2*order) -dΓ_N = Measure(Γ_N,2*order) -# Spaces -reffe = ReferenceFE(lagrangian,Float64,order) -V = TestFESpace(model,reffe;dirichlet_tags=["Gamma_D"]) -U = TrialFESpace(V,0.0) -V_φ = TestFESpace(model,reffe) -V_reg = TestFESpace(model,reffe;dirichlet_tags=["Gamma_N"]) -U_reg = TrialFESpace(V_reg,0) -# Level set and interpolator -φh = interpolate(lsf_func,V_φ) -interp = SmoothErsatzMaterialInterpolation(η = 2*maximum(get_el_Δ(model))) -I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ -# Weak formulation -R(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(κ ∘ u)*∇(u)⋅∇(v))dΩ - ∫(g*v)dΓ_N -state_map = NonlinearFEStateMap(R,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) -# Objective and constraints -J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(κ ∘ u)*∇(u)⋅∇(u))dΩ -vol_D = sum(∫(1)dΩ) -C(u,φ,dΩ,dΓ_N) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ -dC(q,u,φ,dΩ,dΓ_N) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ -pcfs = PDEConstrainedFunctionals(J,[C],state_map,analytic_dC=[dC]) -# Velocity extension -α = 4*maximum(get_el_Δ(model)) -a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ -vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) -# Finite difference scheme -scheme = FirstOrderStencil(length(el_size),Float64) -ls_evo = HamiltonJacobiEvolution(scheme,model,V_φ,tol,max_steps) -# Optimiser -optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) -# Solve -for (it,uh,φh) in optimiser - data = ["phi"=>φh,"H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh] - iszero(it % iter_mod) && (writevtk(Ω,path*"struc_$it",cellfields=data);GC.gc()) - write_history(path*"/history.txt",get_history(optimiser)) -end -# Final structure -it = get_history(optimiser).niter; uh = get_state(pcfs) -writevtk(Ω,path*"struc_$it",cellfields=["phi"=>φh, - "H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) \ No newline at end of file From ed2c63921ab585bbdddaad6bd5a52a26d30993b0 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Tue, 7 May 2024 11:29:24 +1000 Subject: [PATCH 85/90] Rename package --- .gitignore | 2 +- Project.toml | 2 +- README.md | 8 +- compile/compile.jl | 4 +- compile/warmup.jl | 4 +- docs/make.jl | 6 +- docs/src/dev/shape_der.md | 12 +- docs/src/getting-started.md | 18 +-- docs/src/index.md | 10 +- docs/src/reference/benchmarking.md | 16 +-- docs/src/reference/chainrules.md | 66 +++++------ docs/src/reference/io.md | 16 +-- docs/src/reference/levelsetevolution.md | 32 +++--- docs/src/reference/optimisers.md | 26 ++--- docs/src/reference/utilities.md | 10 +- docs/src/reference/velext.md | 2 +- .../tutorials/minimum_thermal_compliance.md | 84 +++++++------- scripts/Benchmarks/benchmark.jl | 32 +++--- .../Benchmarks/generate_benchmark_scripts.jl | 12 +- scripts/MPI/3d_elastic_compliance_ALM.jl | 2 +- scripts/MPI/3d_hyperelastic_compliance_ALM.jl | 2 +- .../3d_hyperelastic_compliance_neohook_ALM.jl | 2 +- scripts/MPI/3d_inverse_homenisation_ALM.jl | 2 +- scripts/MPI/3d_inverter_ALM.jl | 2 +- scripts/MPI/3d_inverter_HPM.jl | 2 +- .../3d_nonlinear_thermal_compliance_ALM.jl | 2 +- scripts/MPI/3d_thermal_compliance_ALM.jl | 2 +- scripts/MPI/elastic_compliance_ALM.jl | 2 +- scripts/MPI/inverse_homenisation_ALM.jl | 2 +- .../MPI/nonlinear_thermal_compliance_ALM.jl | 2 +- scripts/MPI/thermal_compliance_ALM.jl | 2 +- scripts/MPI/thermal_compliance_ALM_PETSc.jl | 2 +- scripts/Serial/elastic_compliance_ALM.jl | 2 +- scripts/Serial/elastic_compliance_HPM.jl | 2 +- scripts/Serial/elastic_compliance_LM.jl | 2 +- scripts/Serial/hyperelastic_compliance_ALM.jl | 2 +- .../hyperelastic_compliance_neohook_ALM.jl | 2 +- scripts/Serial/inverse_homenisation_ALM.jl | 2 +- scripts/Serial/inverter_ALM.jl | 2 +- scripts/Serial/inverter_HPM.jl | 2 +- .../nonlinear_thermal_compliance_ALM.jl | 2 +- scripts/Serial/thermal_compliance_ALM.jl | 2 +- .../thermal_compliance_ALM_higherorderlsf.jl | 2 +- src/ChainRules.jl | 104 +++++++++--------- src/{LevelSetTopOpt.jl => GridapTopOpt.jl} | 4 +- src/Optimisers/Optimisers.jl | 14 +-- test/seq/InverseHomogenisationALMTests.jl | 8 +- test/seq/InverterHPMTests.jl | 14 +-- .../seq/NonlinearThermalComplianceALMTests.jl | 12 +- test/seq/PZMultiFieldRepeatingStateTests.jl | 16 +-- test/seq/ThermalComplianceALMTests.jl | 14 +-- 51 files changed, 298 insertions(+), 298 deletions(-) rename src/{LevelSetTopOpt.jl => GridapTopOpt.jl} (94%) diff --git a/.gitignore b/.gitignore index d43b6663..ddd3c8e5 100644 --- a/.gitignore +++ b/.gitignore @@ -26,4 +26,4 @@ docs/site/ # environment. Manifest.toml LocalPreferences.toml -LevelSetTopOpt.so +GridapTopOpt.so diff --git a/Project.toml b/Project.toml index 8f014570..1ad4f421 100755 --- a/Project.toml +++ b/Project.toml @@ -1,4 +1,4 @@ -name = "LevelSetTopOpt" +name = "GridapTopOpt" uuid = "27dd0110-1916-4fd6-8b4b-1bc109db1170" authors = ["Zach Wegert ", "JordiManyer "] version = "0.1.0" diff --git a/README.md b/README.md index f49144ea..d75a3ce5 100755 --- a/README.md +++ b/README.md @@ -1,10 +1,10 @@ -# LevelSetTopOpt +# GridapTopOpt | **badges** | -LevelSetTopOpt is computational toolbox for level set-based topology optimisation implemented in Julia and the [Gridap](https://github.com/gridap/Gridap.jl) package ecosystem. See the documentation and following publication for further details: +GridapTopOpt is computational toolbox for level set-based topology optimisation implemented in Julia and the [Gridap](https://github.com/gridap/Gridap.jl) package ecosystem. See the documentation and following publication for further details: -> Zachary J. Wegert, Jordi Manyer, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable Julia toolbox for level set-based topology optimisation". In preparation. +> Zachary J. Wegert, Jordi Manyer, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "GridapTopOpt.jl: A scalable Julia toolbox for level set-based topology optimisation". In preparation. ## Documentation @@ -12,4 +12,4 @@ LevelSetTopOpt is computational toolbox for level set-based topology optimisatio - [**LATEST**](...) — *Documentation for the in-development version.* ## Citation -In order to give credit to the `LevelSetTopOpt` contributors, we ask that you please reference the above paper along with the required citations for [Gridap](https://github.com/gridap/Gridap.jl?tab=readme-ov-file#how-to-cite-gridap). \ No newline at end of file +In order to give credit to the `GridapTopOpt` contributors, we ask that you please reference the above paper along with the required citations for [Gridap](https://github.com/gridap/Gridap.jl?tab=readme-ov-file#how-to-cite-gridap). \ No newline at end of file diff --git a/compile/compile.jl b/compile/compile.jl index 60943604..f3fc72d6 100644 --- a/compile/compile.jl +++ b/compile/compile.jl @@ -1,5 +1,5 @@ using PackageCompiler -create_sysimage([:LevelSetTopOpt], - sysimage_path=joinpath(@__DIR__,"..","LevelSetTopOpt.so"), +create_sysimage([:GridapTopOpt], + sysimage_path=joinpath(@__DIR__,"..","GridapTopOpt.so"), precompile_execution_file=joinpath(@__DIR__,"warmup.jl")) diff --git a/compile/warmup.jl b/compile/warmup.jl index c2b6e5e3..feed08f6 100644 --- a/compile/warmup.jl +++ b/compile/warmup.jl @@ -1,4 +1,4 @@ -using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, LevelSetTopOpt +using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, GridapTopOpt """ (MPI) Minimum thermal compliance with Lagrangian method in 2D. @@ -83,7 +83,7 @@ function main(mesh_partition,distribute) vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) ## Optimiser - _conv_cond = t->LevelSetTopOpt.conv_cond(t;coef=1/50); + _conv_cond = t->GridapTopOpt.conv_cond(t;coef=1/50); optimiser = AugmentedLagrangian(φ,pcfs,ls_evo,vel_ext,interp,el_size,γ,γ_reinit,conv_criterion=_conv_cond); for history in optimiser it,Ji,_,_ = last(history) diff --git a/docs/make.jl b/docs/make.jl index 6edb2324..7755b4c2 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -3,15 +3,15 @@ # using Pkg; Pkg.activate(".") using Documenter -using LevelSetTopOpt +using GridapTopOpt makedocs( - sitename = "LevelSetTopOpt.jl", + sitename = "GridapTopOpt.jl", format = Documenter.HTML( prettyurls = false, # collapselevel = 1, ), - modules = [LevelSetTopOpt], + modules = [GridapTopOpt], pages = [ "Home" => "index.md", "Getting Started" => "getting-started.md", diff --git a/docs/src/dev/shape_der.md b/docs/src/dev/shape_der.md index 8d4ddb8d..f0477089 100644 --- a/docs/src/dev/shape_der.md +++ b/docs/src/dev/shape_der.md @@ -32,7 +32,7 @@ The final result of course does not yet match ``(\star)``. Over a fixed computat J_1^\prime(\Omega)(-v\boldsymbol{n})=-\int_{D}vf(\boldsymbol{x})H'(\varphi)\lvert\nabla\varphi\rvert~\mathrm{d}s. ``` -As ``\varphi`` is a signed distance function we have ``\lvert\nabla\varphi\rvert=1`` for ``D\setminus\Sigma`` where ``\Sigma`` is the skeleton of ``\Omega`` and ``\Omega^\complement``. Furthermore, ``H'(\varphi)`` provides support only within a band of ``\partial\Omega``. +As ``\varphi`` is a signed distance function we have ``\lvert\nabla\varphi\rvert=1`` for ``D\setminus\Sigma`` where ``\Sigma`` is the skeleton of ``\Omega`` and ``\Omega^\complement``. Furthermore, ``H'(\varphi)`` provides support only within a band of ``\partial\Omega``. !!! tip "Result I" Therefore, we have that almost everywhere @@ -71,9 +71,9 @@ Consider ``\Omega\subset D`` with ``J(\Omega)=\int_\Omega j(\boldsymbol{u})~\mat In the above ``\boldsymbol{\varepsilon}`` is the strain tensor, ``\boldsymbol{C}`` is the stiffness tensor, ``\Gamma_0 = \partial\Omega\setminus(\Gamma_D\cup\Gamma_N\cup\Gamma_R)``, and ``\Gamma_D``, ``\Gamma_N``, ``\Gamma_R`` are required to be fixed. ### Shape derivative -Let us first consider the shape derivative of ``J``. Disregarding embedding inside the computational domain ``D``, the above strong form can be written in weak form as: +Let us first consider the shape derivative of ``J``. Disregarding embedding inside the computational domain ``D``, the above strong form can be written in weak form as: -``\quad`` *Find* ``\boldsymbol{u}\in H^1_{\Gamma_D}(\Omega)^d`` *such that* +``\quad`` *Find* ``\boldsymbol{u}\in H^1_{\Gamma_D}(\Omega)^d`` *such that* ```math \int_{\Omega} \boldsymbol{C\varepsilon}(\boldsymbol{u})\boldsymbol{\varepsilon}(\boldsymbol{v})~\mathrm{d}\boldsymbol{x}+\int_{\Gamma_R}\boldsymbol{w}(\boldsymbol{u})\cdot\boldsymbol{v}~\mathrm{d}s=\int_\Omega \boldsymbol{f}\cdot\boldsymbol{v}~\mathrm{d}\boldsymbol{x}+\int_{\Gamma_N}\boldsymbol{g}\cdot\boldsymbol{v}~\mathrm{d}s,~\forall \boldsymbol{v}\in H^1_{\Gamma_D}(\Omega)^d. @@ -137,7 +137,7 @@ As required. Note that in the above, we have used that ``\boldsymbol{\theta}\cdo ### Gâteaux derivative in ``\varphi`` -Let us now return to derivatives of ``J`` with respect to ``\varphi`` over the whole computational domain. As previously, suppose that we rewrite ``J`` as +Let us now return to derivatives of ``J`` with respect to ``\varphi`` over the whole computational domain. As previously, suppose that we rewrite ``J`` as ```math \hat{\mathcal{J}}(\varphi)=\int_D (1-H(\varphi))j(\boldsymbol{u})~\mathrm{d}\boldsymbol{x}+\int_{\Gamma_N} l_1(\boldsymbol{u})~\mathrm{d}s+\int_{\Gamma_R} l_2(\boldsymbol{u})~\mathrm{d}s @@ -212,7 +212,7 @@ This exactly as previously up to relaxation over ``D``. Finally, The derivative \end{aligned} ``` -where we have used that ``v=0`` on ``\Gamma_D`` as previously. As previously taking ``\boldsymbol{\theta}=v\boldsymbol{n}`` and relaxing the shape derivative of ``J`` over ``D`` with a signed distance function ``\varphi`` yields: +where we have used that ``v=0`` on ``\Gamma_D`` as previously. As previously taking ``\boldsymbol{\theta}=v\boldsymbol{n}`` and relaxing the shape derivative of ``J`` over ``D`` with a signed distance function ``\varphi`` yields: !!! tip "Result II" ```math @@ -227,7 +227,7 @@ Owing to a fixed computational regime we do not capture a variation of the domai In addition, functionals of the signed distance function posed over the whole bounding domain ``D`` admit a special structure under shape differentiation ([Paper](https://doi.org/10.1051/m2an/2019056)). Such cases are not captured by a Gâteaux derivative at ``\varphi`` under relaxation. !!! note - In future, we plan to implement CellFEM via GridapEmbedded in LevelSetTopOpt. This will enable Gâteaux derivative of the mapping + In future, we plan to implement CellFEM via GridapEmbedded in GridapTopOpt. This will enable Gâteaux derivative of the mapping ```math \varphi \mapsto \int_{\Omega(\varphi)}f(\varphi)~\mathrm{d}\boldsymbol{x} + \int_{\Omega(\varphi)^\complement}f(\varphi)~\mathrm{d}\boldsymbol{x}. diff --git a/docs/src/getting-started.md b/docs/src/getting-started.md index 80775cda..841ad21c 100644 --- a/docs/src/getting-started.md +++ b/docs/src/getting-started.md @@ -2,11 +2,11 @@ ## Installation -`LevelSetTopOpt.jl` and additional dependencies can be installed in an existing Julia environment using the package manager. This can be accessed in the Julia REPL (read-eval–print loop) by pressing `]`. We then add the required packages via: +`GridapTopOpt.jl` and additional dependencies can be installed in an existing Julia environment using the package manager. This can be accessed in the Julia REPL (read-eval–print loop) by pressing `]`. We then add the required packages via: ``` -pkg> add LevelSetTopOpt, Gridap, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, SparseMatricesCSR +pkg> add GridapTopOpt, Gridap, GridapDistributed, GridapPETSc, GridapSolvers, PartitionedArrays, SparseMatricesCSR ``` -Once installed, serial driver scripts can be run immediately, whereas parallel problems also require an MPI installation. +Once installed, serial driver scripts can be run immediately, whereas parallel problems also require an MPI installation. ### MPI For basic users, [`MPI.jl`](https://github.com/JuliaParallel/MPI.jl) provides such an implementation and a Julia wrapper for `mpiexec` - the MPI executor. This is installed via: @@ -19,18 +19,18 @@ Once the `mpiexecjl` wrapper has been added to the system `PATH`, MPI scripts ca ``` mpiexecjl -n P julia main.jl ``` -where `main` is a driver script, `P` denotes the number of processors. +where `main` is a driver script, `P` denotes the number of processors. ### PETSc -In `LevelSetTopOpt.jl` we rely on the [`GridapPETSc.jl`](https://github.com/gridap/GridapPETSc.jl) satellite package to interface with the linear and nonlinear solvers provided by the PETSc (Portable, Extensible Toolkit for Scientific Computation) library. For basic users these solvers are provided by `GridapPETSc.jl` with no additional work. +In `GridapTopOpt.jl` we rely on the [`GridapPETSc.jl`](https://github.com/gridap/GridapPETSc.jl) satellite package to interface with the linear and nonlinear solvers provided by the PETSc (Portable, Extensible Toolkit for Scientific Computation) library. For basic users these solvers are provided by `GridapPETSc.jl` with no additional work. ### Advanced installation For more advanced installations, such as use of a custom MPI/PETSc installation on a HPC cluster, we refer the reader to the [discussion](https://github.com/gridap/GridapPETSc.jl) for `GridapPETSc.jl` and the [configuration page](https://juliaparallel.org/MPI.jl/stable/configuration/) for `MPI.jl`. ## Usage and tutorials -In order to get familiar with the library we recommend following the numerical examples described in: +In order to get familiar with the library we recommend following the numerical examples described in: -> Zachary J. Wegert, Jordi Manyer, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. +> Zachary J. Wegert, Jordi Manyer, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "GridapTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. In addition, there are several driver scripts available in `/scripts/..` @@ -38,5 +38,5 @@ More general tutorials for familiarising ones self with Gridap are available via ## Known issues - PETSc's GAMG preconditioner breaks for split Dirichlet DoFs (e.g., x constrained while y free for a single node). There is no simple fix for this. We recommend instead using MUMPS or another preconditioner for this case. -- Currently, our implementation of automatic differentiation does not support multiplication and division of optimisation functionals. We plan to add this in a future release of `LevelSetTopOpt.jl` -- Issue [#38](https://github.com/zjwegert/LSTO_Distributed/issues/38). -- Analytic gradient breaks in parallel for integrals of certain measures -- Issue [#46](https://github.com/zjwegert/LSTO_Distributed/issues/46) \ No newline at end of file +- Currently, our implementation of automatic differentiation does not support multiplication and division of optimisation functionals. We plan to add this in a future release of `GridapTopOpt.jl` -- Issue [#38](https://github.com/zjwegert/GridapTopOpt/issues/38). +- Analytic gradient breaks in parallel for integrals of certain measures -- Issue [#46](https://github.com/zjwegert/GridapTopOpt/issues/46) \ No newline at end of file diff --git a/docs/src/index.md b/docs/src/index.md index e3b8ed44..c8239bcd 100644 --- a/docs/src/index.md +++ b/docs/src/index.md @@ -1,10 +1,10 @@ -# LevelSetTopOpt.jl -Welcome to the documentation for `LevelSetTopOpt.jl`! +# GridapTopOpt.jl +Welcome to the documentation for `GridapTopOpt.jl`! ## Introduction -`LevelSetTopOpt.jl` is computational toolbox for level set-based topology optimisation implemented in Julia and the Gridap package ecosystem. The core design principle of `LevelSetTopOpt.jl` is to provide an extendable framework for solving optimisation problems in serial or parallel with a high-level programming interface and automatic differentiation. See the following publication for further details: +`GridapTopOpt.jl` is computational toolbox for level set-based topology optimisation implemented in Julia and the Gridap package ecosystem. The core design principle of `GridapTopOpt.jl` is to provide an extendable framework for solving optimisation problems in serial or parallel with a high-level programming interface and automatic differentiation. See the following publication for further details: -> Zachary J. Wegert, Jordi Manyer, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "LevelSetTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. +> Zachary J. Wegert, Jordi Manyer, Connor Mallon, Santiago Badia, and Vivien J. Challis (2024). "GridapTopOpt.jl: A scalable computational toolbox for level set-based topology optimisation". In preparation. ## How to use this documentation @@ -16,7 +16,7 @@ Welcome to the documentation for `LevelSetTopOpt.jl`! ## Julia educational resources -A basic knowledge of the Julia programming language is needed to use the `LevelSetTopOpt.jl` package. +A basic knowledge of the Julia programming language is needed to use the `GridapTopOpt.jl` package. Here, one can find a list of resources to get started with this programming language. * First steps to learn Julia form the [Gridap wiki](https://github.com/gridap/Gridap.jl/wiki/Start-learning-Julia) page. diff --git a/docs/src/reference/benchmarking.md b/docs/src/reference/benchmarking.md index 617ee276..59594ae3 100644 --- a/docs/src/reference/benchmarking.md +++ b/docs/src/reference/benchmarking.md @@ -1,16 +1,16 @@ # Benchmarking ```@docs -LevelSetTopOpt.benchmark +GridapTopOpt.benchmark ``` ## Existing benchmark methods ```@docs -LevelSetTopOpt.benchmark_optimizer -LevelSetTopOpt.benchmark_single_iteration -LevelSetTopOpt.benchmark_forward_problem -LevelSetTopOpt.benchmark_advection -LevelSetTopOpt.benchmark_reinitialisation -LevelSetTopOpt.benchmark_velocity_extension -LevelSetTopOpt.benchmark_hilbertian_projection_map +GridapTopOpt.benchmark_optimizer +GridapTopOpt.benchmark_single_iteration +GridapTopOpt.benchmark_forward_problem +GridapTopOpt.benchmark_advection +GridapTopOpt.benchmark_reinitialisation +GridapTopOpt.benchmark_velocity_extension +GridapTopOpt.benchmark_hilbertian_projection_map ``` \ No newline at end of file diff --git a/docs/src/reference/chainrules.md b/docs/src/reference/chainrules.md index 36559333..00d6f058 100644 --- a/docs/src/reference/chainrules.md +++ b/docs/src/reference/chainrules.md @@ -3,42 +3,42 @@ ## `PDEConstrainedFunctionals` ```@docs -LevelSetTopOpt.PDEConstrainedFunctionals -LevelSetTopOpt.evaluate! -LevelSetTopOpt.evaluate_functionals! -LevelSetTopOpt.evaluate_derivatives! -LevelSetTopOpt.get_state +GridapTopOpt.PDEConstrainedFunctionals +GridapTopOpt.evaluate! +GridapTopOpt.evaluate_functionals! +GridapTopOpt.evaluate_derivatives! +GridapTopOpt.get_state ``` ## `StateParamIntegrandWithMeasure` ```@docs -LevelSetTopOpt.StateParamIntegrandWithMeasure -LevelSetTopOpt.rrule(u_to_j::LevelSetTopOpt.StateParamIntegrandWithMeasure,uh,φh) +GridapTopOpt.StateParamIntegrandWithMeasure +GridapTopOpt.rrule(u_to_j::GridapTopOpt.StateParamIntegrandWithMeasure,uh,φh) ``` ## Implemented types of `AbstractFEStateMap` ```@docs -LevelSetTopOpt.AbstractFEStateMap +GridapTopOpt.AbstractFEStateMap ``` ### `AffineFEStateMap` ```@docs -LevelSetTopOpt.AffineFEStateMap -LevelSetTopOpt.AffineFEStateMap(a::Function,l::Function,U,V,V_φ,U_reg,φh,dΩ...;assem_U = SparseMatrixAssembler(U,V),assem_adjoint = SparseMatrixAssembler(V,U),assem_deriv = SparseMatrixAssembler(U_reg,U_reg),ls::LinearSolver = LUSolver(),adjoint_ls::LinearSolver = LUSolver()) +GridapTopOpt.AffineFEStateMap +GridapTopOpt.AffineFEStateMap(a::Function,l::Function,U,V,V_φ,U_reg,φh,dΩ...;assem_U = SparseMatrixAssembler(U,V),assem_adjoint = SparseMatrixAssembler(V,U),assem_deriv = SparseMatrixAssembler(U_reg,U_reg),ls::LinearSolver = LUSolver(),adjoint_ls::LinearSolver = LUSolver()) ``` ### `NonlinearFEStateMap` ```@docs -LevelSetTopOpt.NonlinearFEStateMap -LevelSetTopOpt.NonlinearFEStateMap(res::Function,U,V,V_φ,U_reg,φh,dΩ...;assem_U = SparseMatrixAssembler(U,V),assem_adjoint = SparseMatrixAssembler(V,U),assem_deriv = SparseMatrixAssembler(U_reg,U_reg),nls::NonlinearSolver = NewtonSolver(LUSolver();maxiter=50,rtol=1.e-8,verbose=true),adjoint_ls::LinearSolver = LUSolver()) +GridapTopOpt.NonlinearFEStateMap +GridapTopOpt.NonlinearFEStateMap(res::Function,U,V,V_φ,U_reg,φh,dΩ...;assem_U = SparseMatrixAssembler(U,V),assem_adjoint = SparseMatrixAssembler(V,U),assem_deriv = SparseMatrixAssembler(U_reg,U_reg),nls::NonlinearSolver = NewtonSolver(LUSolver();maxiter=50,rtol=1.e-8,verbose=true),adjoint_ls::LinearSolver = LUSolver()) ``` ### `RepeatingAffineFEStateMap` ```@docs -LevelSetTopOpt.RepeatingAffineFEStateMap -LevelSetTopOpt.RepeatingAffineFEStateMap(nblocks::Int,a::Function,l::Vector{<:Function},U0,V0,V_φ,U_reg,φh,dΩ...;assem_U = SparseMatrixAssembler(U0,V0),assem_adjoint = SparseMatrixAssembler(V0,U0),assem_deriv = SparseMatrixAssembler(U_reg,U_reg),ls::LinearSolver = LUSolver(),adjoint_ls::LinearSolver = LUSolver()) +GridapTopOpt.RepeatingAffineFEStateMap +GridapTopOpt.RepeatingAffineFEStateMap(nblocks::Int,a::Function,l::Vector{<:Function},U0,V0,V_φ,U_reg,φh,dΩ...;assem_U = SparseMatrixAssembler(U0,V0),assem_adjoint = SparseMatrixAssembler(V0,U0),assem_deriv = SparseMatrixAssembler(U_reg,U_reg),ls::LinearSolver = LUSolver(),adjoint_ls::LinearSolver = LUSolver()) ``` ## Advanced @@ -47,32 +47,32 @@ LevelSetTopOpt.RepeatingAffineFEStateMap(nblocks::Int,a::Function,l::Vector{<:Fu #### Existing methods ```@docs -LevelSetTopOpt.rrule(φ_to_u::LevelSetTopOpt.AbstractFEStateMap,φh) -LevelSetTopOpt.pullback +GridapTopOpt.rrule(φ_to_u::GridapTopOpt.AbstractFEStateMap,φh) +GridapTopOpt.pullback ``` #### Required to implement ```@docs -LevelSetTopOpt.forward_solve! -LevelSetTopOpt.adjoint_solve! -LevelSetTopOpt.update_adjoint_caches! -LevelSetTopOpt.dRdφ -LevelSetTopOpt.get_state(::LevelSetTopOpt.AbstractFEStateMap) -LevelSetTopOpt.get_measure -LevelSetTopOpt.get_spaces -LevelSetTopOpt.get_assemblers -LevelSetTopOpt.get_trial_space -LevelSetTopOpt.get_test_space -LevelSetTopOpt.get_aux_space -LevelSetTopOpt.get_deriv_space -LevelSetTopOpt.get_pde_assembler -LevelSetTopOpt.get_deriv_assembler +GridapTopOpt.forward_solve! +GridapTopOpt.adjoint_solve! +GridapTopOpt.update_adjoint_caches! +GridapTopOpt.dRdφ +GridapTopOpt.get_state(::GridapTopOpt.AbstractFEStateMap) +GridapTopOpt.get_measure +GridapTopOpt.get_spaces +GridapTopOpt.get_assemblers +GridapTopOpt.get_trial_space +GridapTopOpt.get_test_space +GridapTopOpt.get_aux_space +GridapTopOpt.get_deriv_space +GridapTopOpt.get_pde_assembler +GridapTopOpt.get_deriv_assembler ``` ### `IntegrandWithMeasure` ```@docs -LevelSetTopOpt.IntegrandWithMeasure -LevelSetTopOpt.gradient -LevelSetTopOpt.jacobian +GridapTopOpt.IntegrandWithMeasure +GridapTopOpt.gradient +GridapTopOpt.jacobian ``` \ No newline at end of file diff --git a/docs/src/reference/io.md b/docs/src/reference/io.md index e4c4ff89..ce7a6127 100644 --- a/docs/src/reference/io.md +++ b/docs/src/reference/io.md @@ -1,21 +1,21 @@ # IO -In LevelSetTopOpt, the usual IO from [Gridap](https://github.com/gridap/Gridap.jl/) is available. In addition, we also implement the below IO for convenience. +In GridapTopOpt, the usual IO from [Gridap](https://github.com/gridap/Gridap.jl/) is available. In addition, we also implement the below IO for convenience. ## Optimiser history ```@docs -LevelSetTopOpt.write_history +GridapTopOpt.write_history ``` ## Object IO in serial ```@docs -LevelSetTopOpt.save -LevelSetTopOpt.load -LevelSetTopOpt.load! +GridapTopOpt.save +GridapTopOpt.load +GridapTopOpt.load! ``` ## Object IO in parallel ```@docs -LevelSetTopOpt.psave -LevelSetTopOpt.pload -LevelSetTopOpt.pload! +GridapTopOpt.psave +GridapTopOpt.pload +GridapTopOpt.pload! ``` \ No newline at end of file diff --git a/docs/src/reference/levelsetevolution.md b/docs/src/reference/levelsetevolution.md index 3f41a926..0ddcc12f 100644 --- a/docs/src/reference/levelsetevolution.md +++ b/docs/src/reference/levelsetevolution.md @@ -1,39 +1,39 @@ # LevelSetEvolution -In LevelSetTopOpt, the level set is evolved and reinitialised using a `LevelSetEvolution` method. The most standard of these is the Hamilton-Jacobi evolution equation solved using a first order upwind finite difference scheme. A forward Euler in time method is provided below via `HamiltonJacobiEvolution <: LevelSetEvolution` along with an upwind finite difference stencil for the spatial discretisation via `FirstOrderStencil`. +In GridapTopOpt, the level set is evolved and reinitialised using a `LevelSetEvolution` method. The most standard of these is the Hamilton-Jacobi evolution equation solved using a first order upwind finite difference scheme. A forward Euler in time method is provided below via `HamiltonJacobiEvolution <: LevelSetEvolution` along with an upwind finite difference stencil for the spatial discretisation via `FirstOrderStencil`. This can be extended in several ways. For example, higher order spatial stencils can be implemented by extending the `Stencil` interface below. In addition, more advanced ODE solvers could be implemented (e.g., Runge–Kutta methods) or entirely different level set evolution methods by extending the `LevelSetEvolution` interface below. ## `HamiltonJacobiEvolution` ```@docs -LevelSetTopOpt.HamiltonJacobiEvolution -LevelSetTopOpt.HamiltonJacobiEvolution(stencil::LevelSetTopOpt.Stencil,model,space,tol=1.e-3,max_steps=100,max_steps_reinit=2000) -LevelSetTopOpt.evolve! -LevelSetTopOpt.reinit! -LevelSetTopOpt.get_dof_Δ(m::HamiltonJacobiEvolution) +GridapTopOpt.HamiltonJacobiEvolution +GridapTopOpt.HamiltonJacobiEvolution(stencil::GridapTopOpt.Stencil,model,space,tol=1.e-3,max_steps=100,max_steps_reinit=2000) +GridapTopOpt.evolve! +GridapTopOpt.reinit! +GridapTopOpt.get_dof_Δ(m::HamiltonJacobiEvolution) ``` ## Spatial stencils for `HamiltonJacobiEvolution` ```@docs -LevelSetTopOpt.FirstOrderStencil +GridapTopOpt.FirstOrderStencil ``` ## Custom `Stencil` ```@docs -LevelSetTopOpt.Stencil -LevelSetTopOpt.evolve!(::LevelSetTopOpt.Stencil,φ,vel,Δt,Δx,isperiodic,caches) -LevelSetTopOpt.reinit!(::LevelSetTopOpt.Stencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) -LevelSetTopOpt.allocate_caches(::LevelSetTopOpt.Stencil,φ,vel) -LevelSetTopOpt.check_order +GridapTopOpt.Stencil +GridapTopOpt.evolve!(::GridapTopOpt.Stencil,φ,vel,Δt,Δx,isperiodic,caches) +GridapTopOpt.reinit!(::GridapTopOpt.Stencil,φ_new,φ,vel,Δt,Δx,isperiodic,caches) +GridapTopOpt.allocate_caches(::GridapTopOpt.Stencil,φ,vel) +GridapTopOpt.check_order ``` ## Custom `LevelSetEvolution` To implement a custom level set evolution method, we can extend the methods below. For example, one could consider Reaction-Diffusion-based evolution of the level set function. This can be solved with a finite element method and so we can implement a new type that inherits from `LevelSetEvolution` independently of the `Stencil` types. ```@docs -LevelSetTopOpt.LevelSetEvolution -LevelSetTopOpt.evolve!(::LevelSetTopOpt.LevelSetEvolution,φ,args...) -LevelSetTopOpt.reinit!(::LevelSetTopOpt.LevelSetEvolution,φ,args...) -LevelSetTopOpt.get_dof_Δ(::LevelSetTopOpt.LevelSetEvolution) +GridapTopOpt.LevelSetEvolution +GridapTopOpt.evolve!(::GridapTopOpt.LevelSetEvolution,φ,args...) +GridapTopOpt.reinit!(::GridapTopOpt.LevelSetEvolution,φ,args...) +GridapTopOpt.get_dof_Δ(::GridapTopOpt.LevelSetEvolution) ``` \ No newline at end of file diff --git a/docs/src/reference/optimisers.md b/docs/src/reference/optimisers.md index fbbe278e..78b8287c 100644 --- a/docs/src/reference/optimisers.md +++ b/docs/src/reference/optimisers.md @@ -1,37 +1,37 @@ # Optimisers -In LevelSetTopOpt we implement optimisation algorithms as [iterators](https://docs.julialang.org/en/v1/manual/interfaces/) that inherit from an abstract type `Optimiser`. A concrete `Optimiser` implementation, say `OptEg`, then implements `iterate(m::OptEg) ↦ (var,state)` and `iterate(m::OptEg,state) ↦ (var,state)`, where `var` and `state` are the available items in the outer loop and internal state of the iterator, respectively. As a result we can iterate over the object `m=OptEg(...)` using `for var in m`. The benefit of this implementation is that the internals of the optimisation method can be hidden in the source code while the explicit `for` loop is still visible to the user. The body of the loop can then be used for auxiliary operations such as writing the optimiser history and other files. +In GridapTopOpt we implement optimisation algorithms as [iterators](https://docs.julialang.org/en/v1/manual/interfaces/) that inherit from an abstract type `Optimiser`. A concrete `Optimiser` implementation, say `OptEg`, then implements `iterate(m::OptEg) ↦ (var,state)` and `iterate(m::OptEg,state) ↦ (var,state)`, where `var` and `state` are the available items in the outer loop and internal state of the iterator, respectively. As a result we can iterate over the object `m=OptEg(...)` using `for var in m`. The benefit of this implementation is that the internals of the optimisation method can be hidden in the source code while the explicit `for` loop is still visible to the user. The body of the loop can then be used for auxiliary operations such as writing the optimiser history and other files. -The below describes the implemented optimisers along with the `OptimiserHistory` type. Custom optimisers can be implemented by creating types that inherit from `Optimiser` and extending the interfaces in [Custom optimiser](@ref). +The below describes the implemented optimisers along with the `OptimiserHistory` type. Custom optimisers can be implemented by creating types that inherit from `Optimiser` and extending the interfaces in [Custom optimiser](@ref). -## Lagrangian & Augmented Lagrangian method +## Lagrangian & Augmented Lagrangian method ```@autodocs -Modules = [LevelSetTopOpt] +Modules = [GridapTopOpt] Pages = ["Optimisers/AugmentedLagrangian.jl"] ``` ## Hilbertian projection method ```@autodocs -Modules = [LevelSetTopOpt] +Modules = [GridapTopOpt] Pages = ["Optimisers/HilbertianProjection.jl"] ``` ```@autodocs -Modules = [LevelSetTopOpt] +Modules = [GridapTopOpt] Pages = ["Optimisers/OrthogonalisationMaps.jl"] ``` ## Optimiser history ```@docs -LevelSetTopOpt.OptimiserHistory -LevelSetTopOpt.OptimiserHistorySlice +GridapTopOpt.OptimiserHistory +GridapTopOpt.OptimiserHistorySlice ``` ## Custom `Optimiser` ```@docs -LevelSetTopOpt.Optimiser -LevelSetTopOpt.iterate(::LevelSetTopOpt.Optimiser) -LevelSetTopOpt.iterate(::LevelSetTopOpt.Optimiser,state) -LevelSetTopOpt.get_history(::LevelSetTopOpt.Optimiser) -LevelSetTopOpt.converged(::LevelSetTopOpt.Optimiser) +GridapTopOpt.Optimiser +GridapTopOpt.iterate(::GridapTopOpt.Optimiser) +GridapTopOpt.iterate(::GridapTopOpt.Optimiser,state) +GridapTopOpt.get_history(::GridapTopOpt.Optimiser) +GridapTopOpt.converged(::GridapTopOpt.Optimiser) ``` \ No newline at end of file diff --git a/docs/src/reference/utilities.md b/docs/src/reference/utilities.md index 02bc4ba7..6fc92a5f 100644 --- a/docs/src/reference/utilities.md +++ b/docs/src/reference/utilities.md @@ -2,18 +2,18 @@ ## Ersatz material interpolation ```@docs -LevelSetTopOpt.SmoothErsatzMaterialInterpolation +GridapTopOpt.SmoothErsatzMaterialInterpolation ``` ## Mesh labelling ```@docs -LevelSetTopOpt.update_labels! +GridapTopOpt.update_labels! ``` ## Helpers ```@docs -LevelSetTopOpt.initial_lsf -LevelSetTopOpt.isotropic_elast_tensor -LevelSetTopOpt.get_el_Δ +GridapTopOpt.initial_lsf +GridapTopOpt.isotropic_elast_tensor +GridapTopOpt.get_el_Δ ``` \ No newline at end of file diff --git a/docs/src/reference/velext.md b/docs/src/reference/velext.md index 7e94e680..4179b745 100644 --- a/docs/src/reference/velext.md +++ b/docs/src/reference/velext.md @@ -1,6 +1,6 @@ # Velocity extension ```@autodocs -Modules = [LevelSetTopOpt] +Modules = [GridapTopOpt] Pages = ["VelocityExtension.jl"] ``` \ No newline at end of file diff --git a/docs/src/tutorials/minimum_thermal_compliance.md b/docs/src/tutorials/minimum_thermal_compliance.md index 3d52db3c..966a71f3 100644 --- a/docs/src/tutorials/minimum_thermal_compliance.md +++ b/docs/src/tutorials/minimum_thermal_compliance.md @@ -3,7 +3,7 @@ The goal of this tutorial is to learn - How to formulate a topology optimisation problem - How to describe the problem over a fixed computational domain ``D`` via the level-set method. -- How to setup and solve the problem in LevelSetTopOpt +- How to setup and solve the problem in GridapTopOpt We consider the following extensions at the end of the tutorial: - How to extend problems to 3D and utilise PETSc solvers @@ -63,7 +63,7 @@ For this tutorial, we consider minimising the thermal compliance (or dissipated \right. \end{aligned} ``` -where ``\operatorname{Vol}(\Omega)=\int_\Omega1~\mathrm{d}\boldsymbol{x}``. This objective is equivalent to equivalent to maximising the heat transfer efficiency through ``\Omega``. +where ``\operatorname{Vol}(\Omega)=\int_\Omega1~\mathrm{d}\boldsymbol{x}``. This objective is equivalent to equivalent to maximising the heat transfer efficiency through ``\Omega``. ## Shape differentiation @@ -74,7 +74,7 @@ Suppose that we consider smooth variations of the domain ``\Omega`` of the form !!! note "Definition [3]" The shape derivative of ``J(\Omega)`` at ``\Omega`` is defined as the Fréchet derivative in ``W^{1, \infty}(\mathbb{R}^d, \mathbb{R}^d)`` at ``\boldsymbol{\theta}`` of the application ``\boldsymbol{\theta} \rightarrow J(\Omega_{\boldsymbol{\theta}})``, i.e., ```math - J(\Omega_{\boldsymbol{\theta}})(\Omega)=J(\Omega)+J^{\prime}(\Omega)(\boldsymbol{\theta})+\mathrm{o}(\boldsymbol{\theta}) + J(\Omega_{\boldsymbol{\theta}})(\Omega)=J(\Omega)+J^{\prime}(\Omega)(\boldsymbol{\theta})+\mathrm{o}(\boldsymbol{\theta}) ``` with ``\lim _{\boldsymbol{\theta} \rightarrow 0} \frac{\lvert\mathrm{o}(\boldsymbol{\theta})\rvert}{\|\boldsymbol{\theta}\|}=0,`` where the shape derivative ``J^{\prime}(\Omega)`` is a continuous linear form on ``W^{1, \infty}(\mathbb{R}^d, \mathbb{R}^d)`` @@ -97,7 +97,7 @@ and \operatorname{Vol}'(\Omega)(-q\boldsymbol{n}) = -\int_{\Gamma}q~\mathrm{d}s. ``` -## Discretisation via a level set +## Discretisation via a level set Suppose that we attribute a level set function ``\varphi:D\rightarrow\mathbb{R}`` to our domain ``\Omega\subset D`` with ``\bar{\Omega}=\lbrace \boldsymbol{x}:\varphi(\boldsymbol{x})\leq0\rbrace`` and ``\Omega^\complement=\lbrace \boldsymbol{x}:\varphi(\boldsymbol{x})>0\rbrace``. We can then define a smooth characteristic function ``I:\mathbb{R}\rightarrow[\epsilon,1]`` as ``I(\varphi)=(1-H(\varphi))+\epsilon H(\varphi)`` where ``H`` is a smoothed Heaviside function with smoothing radius ``\eta``, and ``\epsilon\ll1`` allows for an ersatz material approximation. Of course, ``\epsilon`` can be taken as zero depending on the computational regime. Over the fixed computational domain we may relax integrals to be over all of ``D`` via ``\mathrm{d}\boldsymbol{x}= H(\varphi)~\mathrm{d}\boldsymbol{x}`` and ``\mathrm{d}s = H'(\varphi)\lvert\nabla\varphi\rvert~\mathrm{d}\boldsymbol{x}``. The above optimisation problem then rewrites in terms of ``\varphi`` as @@ -122,14 +122,14 @@ C(\varphi)&=\int_D (\rho(\varphi) - V_f)/\operatorname{Vol}(D)~\mathrm{d}\boldsy &=\int_D \rho(\varphi)~\mathrm{d}\boldsymbol{x}/\operatorname{Vol}(D) - V_f\\ &=\int_\Omega~\mathrm{d}\boldsymbol{x}/\operatorname{Vol}(D)-V_f = \operatorname{Vol}(\Omega)/\operatorname{Vol}(D)-V_f \end{aligned} -``` +``` where ``\rho(\varphi)=1-H(\varphi)`` is the smoothed volume density function. !!! note - In LevelSetTopOpt we assume constraints are of the integral form above. + In GridapTopOpt we assume constraints are of the integral form above. -The shape derivatives from the previous section can be relaxed over the computational domain as +The shape derivatives from the previous section can be relaxed over the computational domain as ```math J'(\varphi)(-q\boldsymbol{n}) = \int_{D}q\kappa\boldsymbol{\nabla}(u)\cdot\boldsymbol{\nabla}(u)H'(\varphi)\lvert\nabla\varphi\rvert~\mathrm{d}\boldsymbol{x} @@ -141,16 +141,16 @@ C'(\varphi)(-q\boldsymbol{n}) = -\int_{D}qH'(\varphi)\lvert\nabla\varphi\rvert~\ ## Computational method -In the following, we discuss the implementation of the above optimisation problem in LevelSetTopOpt. For the purpose of this tutorial we break the computational formulation into chunks. +In the following, we discuss the implementation of the above optimisation problem in GridapTopOpt. For the purpose of this tutorial we break the computational formulation into chunks. The first step in creating our script is to load any packages required: ```julia -using LevelSetTopOpt, Gridap +using GridapTopOpt, Gridap ``` ### Parameters -The following are user defined parameters for the problem. -These parameters will be discussed over the course of this tutorial. +The following are user defined parameters for the problem. +These parameters will be discussed over the course of this tutorial. ```julia # FE parameters @@ -199,7 +199,7 @@ dΓ_N = Measure(Γ_N,2*order) ``` where `2*order` indicates the quadrature degree for numerical integration. -The final stage of the finite element setup is the approximation of the finite element spaces. This is given as follows: +The final stage of the finite element setup is the approximation of the finite element spaces. This is given as follows: ```julia # Spaces reffe = ReferenceFE(lagrangian,Float64,order) @@ -223,7 +223,7 @@ For this problem we set `lsf_func` using the function [`initial_lsf`](@ref) in t ```math \varphi_{\xi,a}(\boldsymbol{x})=-\frac{1}{4} \prod_i^D(\cos(\xi\pi x_i)) - a/4 ``` -with ``\xi,a=(4,0.2)`` and ``D=2`` in two dimensions. +with ``\xi,a=(4,0.2)`` and ``D=2`` in two dimensions. We also generate a smooth characteristic function of radius ``\eta`` using: @@ -238,7 +238,7 @@ This the [`SmoothErsatzMaterialInterpolation`](@ref) structure defines the chara |:--:| |Figure 2: A visualisation of the initial level set function and the interpolated density function ``\rho`` for ``\Omega``.| -Optional: we can generate a VTK file for visualisation in Paraview via +Optional: we can generate a VTK file for visualisation in Paraview via ```julia writevtk(Ω,"initial_lsf",cellfields=["phi"=>φh, "ρ(phi)"=>(ρ ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh))]) @@ -292,17 +292,17 @@ In this case, the analytic shape derivatives are passed as optional arguments. W ### Velocity extension-regularisation method -The Hilbertian extension-regularisation [4] method involves solving an -identification problem over a Hilbert space ``H`` on ``D`` with -inner product ``\langle\cdot,\cdot\rangle_H``: +The Hilbertian extension-regularisation [4] method involves solving an +identification problem over a Hilbert space ``H`` on ``D`` with +inner product ``\langle\cdot,\cdot\rangle_H``: *Find* ``g_\Omega\in H`` *such that* ``\langle g_\Omega,q\rangle_H =-J^{\prime}(\Omega)(q\boldsymbol{n})~ \forall q\in H.`` -This provides two benefits: - 1) It naturally extends the shape sensitivity from ``\partial\Omega`` +This provides two benefits: + 1) It naturally extends the shape sensitivity from ``\partial\Omega`` onto the bounding domain ``D``; and - 2) ensures a descent direction for ``J(\Omega)`` with additional regularity + 2) ensures a descent direction for ``J(\Omega)`` with additional regularity (i.e., ``H`` as opposed to ``L^2(\partial\Omega)``). For our problem above we take the inner product @@ -317,7 +317,7 @@ where ``\alpha`` is the smoothing length scale. Equivalently in our script we ha a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ ``` -We then build an object [`VelocityExtension`](@ref). This object provides a method [`project!`](@ref) that applies the Hilbertian velocity-extension method to a given shape derivative. +We then build an object [`VelocityExtension`](@ref). This object provides a method [`project!`](@ref) that applies the Hilbertian velocity-extension method to a given shape derivative. ```julia vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) @@ -360,7 +360,7 @@ We may now create the optimiser object. This structure holds all information reg optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=true,constraint_names=[:Vol]) ``` -As optimisers inheriting from [`LevelSetTopOpt.Optimiser`](@ref) implement Julia's iterator functionality, we can solve the optimisation problem to convergence by iterating over the optimiser: +As optimisers inheriting from [`GridapTopOpt.Optimiser`](@ref) implement Julia's iterator functionality, we can solve the optimisation problem to convergence by iterating over the optimiser: ```julia # Solve @@ -379,7 +379,7 @@ end ``` !!! warning - Due to a possible memory leak in Julia 1.9.* IO, we include a call to the garbage collector using `GC.gc()`. + Due to a possible memory leak in Julia 1.9.* IO, we include a call to the garbage collector using `GC.gc()`. Depending on whether we use `iszero(it % iter_mod)`, the VTK file for the final structure may need to be saved using @@ -398,7 +398,7 @@ writevtk(Ω,path*"_$it",cellfields=["phi"=>φh, ``` ```julia -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt # FE parameters order = 1 # Finite element order @@ -504,7 +504,7 @@ The first and most straightforward in terms of programmatic changes is extending |:--:| |Figure 4: The setup for the three-dimensional minimum thermal compliance problem.| -We use a unit cube for the bounding domain ``D`` with ``50^3`` elements. This corresponds to changing lines 5-7 in the above script to +We use a unit cube for the bounding domain ``D`` with ``50^3`` elements. This corresponds to changing lines 5-7 in the above script to ```julia xmax=ymax=zmax=1.0 # Domain size @@ -539,7 +539,7 @@ tol = 1/(2order^2)/minimum(el_size) # Advection tolerance ``` ```julia -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt # FE parameters order = 1 # Finite element order @@ -623,10 +623,10 @@ writevtk(Ω,path*"struc_$it",cellfields=["phi"=>φh, ``` -At this stage the problem will not be possible to run as we're using a standard LU solver. For this reason we now consider adjusting Script 2 to use an iterative solver provided by PETSc. We rely on the GridapPETSc satellite package to utilise PETSc. This provides the necessary structures to efficiently interface with the linear and nonlinear solvers provided by the PETSc library. To call GridapPETSc we change line 1 of Script 2 to +At this stage the problem will not be possible to run as we're using a standard LU solver. For this reason we now consider adjusting Script 2 to use an iterative solver provided by PETSc. We rely on the GridapPETSc satellite package to utilise PETSc. This provides the necessary structures to efficiently interface with the linear and nonlinear solvers provided by the PETSc library. To call GridapPETSc we change line 1 of Script 2 to ```julia -using Gridap, GridapPETSc, SparseMatricesCSR, LevelSetTopOpt +using Gridap, GridapPETSc, SparseMatricesCSR, GridapTopOpt ``` We also use `SparseMatricesCSR` as PETSc is based on the `SparseMatrixCSR` datatype. We then replace line 52 and 63 with @@ -655,13 +655,13 @@ respectively. Here we specify that the `SparseMatrixAssembler` should be based o Finally, we wrap the entire script in a function and call it inside a `GridapPETSc.with` block. This ensures that PETSc is safely initialised. This should take the form ```Julia -using Gridap, GridapPETSc, SparseMatricesCSR, LevelSetTopOpt +using Gridap, GridapPETSc, SparseMatricesCSR, GridapTopOpt function main() ... end -solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true +solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do main() @@ -675,7 +675,7 @@ We utilise a conjugate gradient method with geometric algebraic multigrid precon ``` ```julia -using Gridap, GridapPETSc, SparseMatricesCSR, LevelSetTopOpt +using Gridap, GridapPETSc, SparseMatricesCSR, GridapTopOpt function main() # FE parameters @@ -769,7 +769,7 @@ function main() "H(phi)"=>(H ∘ φh),"|nabla(phi)|"=>(norm ∘ ∇(φh)),"uh"=>uh]) end -solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true +solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do main() @@ -788,10 +788,10 @@ We can run this script and visualise the initial and final structures using Para ### Serial to MPI -Script 3 contains no parallelism to enable further speedup or scalability. To enable MPI-based computing we rely on the tools implemented in PartitionedArrays and GridapDistributed. Further information regarding these packages and how they interface with LevelSetTopOpt can be found [here](../usage/mpi-mode.md). To add these packages we adjust the first line of our script: +Script 3 contains no parallelism to enable further speedup or scalability. To enable MPI-based computing we rely on the tools implemented in PartitionedArrays and GridapDistributed. Further information regarding these packages and how they interface with GridapTopOpt can be found [here](../usage/mpi-mode.md). To add these packages we adjust the first line of our script: ```julia -using Gridap, GridapPETSc, GridapDistributed, PartitionedArrays, SparseMatricesCSR, LevelSetTopOpt +using Gridap, GridapPETSc, GridapDistributed, PartitionedArrays, SparseMatricesCSR, GridapTopOpt ``` Before we change any parts of the function `main`, we adjust the end of the script to safely launch MPI inside a Julia `do` block. We replace lines 95-99 in Script 3 with @@ -799,7 +799,7 @@ Before we change any parts of the function `main`, we adjust the end of the scri ```julia with_mpi() do distribute mesh_partition = (2,2,2) - solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do main(mesh_partition,distribute) @@ -838,7 +838,7 @@ That's it! These are the only changes that are necessary to run your application ``` ```julia -using Gridap, GridapPETSc, GridapDistributed, PartitionedArrays, SparseMatricesCSR, LevelSetTopOpt +using Gridap, GridapPETSc, GridapDistributed, PartitionedArrays, SparseMatricesCSR, GridapTopOpt function main(mesh_partition,distribute) ranks = distribute(LinearIndices((prod(mesh_partition),))) @@ -936,7 +936,7 @@ end with_mpi() do distribute mesh_partition = (2,2,2) - solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + solver_options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" GridapPETSc.with(args=split(solver_options)) do main(mesh_partition,distribute) @@ -980,7 +980,7 @@ As we're considering a 2D problem, we consider modifications of Script 1 as foll κ(u) = exp(-u) # Diffusivity ``` -We then replace the `a` and `l` on line 48 and 49 by the residual `R` given by +We then replace the `a` and `l` on line 48 and 49 by the residual `R` given by ```julia R(u,v,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(κ ∘ u)*∇(u)⋅∇(v))dΩ - ∫(g*v)dΓ_N ``` @@ -991,7 +991,7 @@ state_map = NonlinearFEStateMap(R,U,V,V_φ,U_reg,φh,dΩ,dΓ_N) ``` This by default implements a standard `NewtonSolver` from GridapSolvers while utilising an LU solver for intermediate linear solves involving the Jacobian. As with other `FEStateMap` types, this constructor can optionally take assemblers and different solvers (e.g., PETSc solvers). -Next, we replace the objective functional on line 52 with +Next, we replace the objective functional on line 52 with ```julia J(u,φ,dΩ,dΓ_N) = ∫((I ∘ φ)*(κ ∘ u)*∇(u)⋅∇(u))dΩ @@ -1009,7 +1009,7 @@ Notice that the argument `analytic_dJ=...` has been removed, this enables the AD ``` ```julia -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt # FE parameters order = 1 # Finite element order @@ -1103,11 +1103,11 @@ A 3D example of a nonlinear thermal conductivity problem can be found under `scr ## References > 1. *Z. Guo, X. Cheng, and Z. Xia. Least dissipation principle of heat transport potential capacity and its application in heat conduction optimization. Chinese Science Bulletin, 48(4):406–410, Feb 2003. ISSN 1861-9541. doi: 10.1007/BF03183239.* -> +> > 2. *C. Zhuang, Z. Xiong, and H. Ding. A level set method for topology optimization of heat conduction problem under multiple load cases. Computer Methods in Applied Mechanics and Engineering, 196(4–6):1074–1084, Jan 2007. ISSN 00457825. doi: 10.1016/j.cma.2006.08.005.* > > 3. *Allaire G, Jouve F, Toader AM (2004) Structural optimization using sensitivity analysis and a level-set method. Journal of Computational Physics 194(1):363–393. doi: 10.1016/j.jcp.2003.09.032* -> +> > 4. *Allaire G, Dapogny C, Jouve F (2021) Shape and topology optimization, vol 22, Elsevier, p 1–132. doi: 10.1016/bs.hna.2020.10.004* > > 5. *Osher S, Fedkiw R (2006) Level Set Methods and Dynamic Implicit Surfaces, 1st edn. Applied Mathematical Sciences, Springer Science & Business Media. doi: 10.1007/b98879* diff --git a/scripts/Benchmarks/benchmark.jl b/scripts/Benchmarks/benchmark.jl index c3dc701c..c31d395c 100644 --- a/scripts/Benchmarks/benchmark.jl +++ b/scripts/Benchmarks/benchmark.jl @@ -1,7 +1,7 @@ -using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR +using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, + PartitionedArrays, GridapTopOpt, SparseMatricesCSR -using LevelSetTopOpt: get_deriv_space, get_aux_space,benchmark_optimizer, +using GridapTopOpt: get_deriv_space, get_aux_space,benchmark_optimizer, benchmark_forward_problem,benchmark_advection,benchmark_reinitialisation, benchmark_velocity_extension,benchmark_hilbertian_projection_map,benchmark_single_iteration @@ -75,7 +75,7 @@ function nl_elast(mesh_partition,ranks,el_size,order,verbose) F(∇u) = one(∇u) + ∇u' ## Volume change J(F) = sqrt(det(C(F))) - ## Residual + ## Residual res(u,v,φ,dΩ,dΓ_N) = ∫( (I ∘ φ)*((dE ∘ (∇(v),∇(u))) ⊙ (S ∘ ∇(u))) )*dΩ - ∫(g⋅v)dΓ_N Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} Tv = Vector{PetscScalar} @@ -281,11 +281,11 @@ function inverter_HPM(mesh_partition,ranks,el_size,order,verbose) ## FE Setup model = CartesianDiscreteModel(ranks,mesh_partition,dom,el_size); el_Δ = get_el_Δ(model) - f_Γ_in(x) = (x[1] ≈ 0.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && + f_Γ_in(x) = (x[1] ≈ 0.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) - f_Γ_out(x) = (x[1] ≈ 1.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && + f_Γ_out(x) = (x[1] ≈ 1.0) && (0.4 - eps() <= x[2] <= 0.6 + eps()) && (0.4 - eps() <= x[3] <= 0.6 + eps()) - f_Γ_out_ext(x) = ~f_Γ_out(x) && (0.9 <= x[1] <= 1.0) && (0.3 - eps() <= x[2] <= 0.7 + eps()) && + f_Γ_out_ext(x) = ~f_Γ_out(x) && (0.9 <= x[1] <= 1.0) && (0.3 - eps() <= x[2] <= 0.7 + eps()) && (0.3 - eps() <= x[3] <= 0.7 + eps()) f_Γ_D(x) = (x[1] ≈ 0.0) && (x[2] <= 0.1 || x[2] >= 0.9) && (x[3] <= 0.1 || x[3] >= 0.9) update_labels!(1,model,f_Γ_in,"Gamma_in") @@ -337,7 +337,7 @@ function inverter_HPM(mesh_partition,ranks,el_size,order,verbose) Tm = SparseMatrixCSR{0,PetscScalar,PetscInt} Tv = Vector{PetscScalar} solver = ElasticitySolver(V) - + state_map = AffineFEStateMap( a,l,U,V,V_φ,U_reg,φh,dΩ,dΓ_in,dΓ_out; assem_U = SparseMatrixAssembler(Tm,Tv,U,V), @@ -355,7 +355,7 @@ function inverter_HPM(mesh_partition,ranks,el_size,order,verbose) assem = SparseMatrixAssembler(Tm,Tv,U_reg,V_reg), ls = PETScLinearSolver() ) - + ## Optimiser return HilbertianProjection(pcfs,ls_evo,vel_ext,φh;γ,γ_reinit,verbose=verbose) end @@ -365,21 +365,21 @@ with_mpi() do distribute mesh_partition = (Nx,Ny,Nz) ranks = distribute(LinearIndices((prod(mesh_partition),))) el_size = (N_EL,N_EL,N_EL) - verbose = Bool(VERBOSE) ? i_am_main(ranks) : false; + verbose = Bool(VERBOSE) ? i_am_main(ranks) : false; if PROB_TYPE == "NLELAST" - options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" opt = nl_elast - elseif PROB_TYPE == "THERM" - options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + elseif PROB_TYPE == "THERM" + options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" opt = therm elseif PROB_TYPE == "ELAST" - options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" opt = elast elseif PROB_TYPE == "INVERTER_HPM" - options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true + options = "-pc_type gamg -ksp_type cg -ksp_error_if_not_converged true -ksp_converged_reason -ksp_rtol 1.0e-12" opt = inverter_HPM else @@ -439,7 +439,7 @@ with_mpi() do distribute end ## HPM if occursin("bhpm",BMARK_TYPE) - @assert typeof(optim) <: HilbertianProjection + @assert typeof(optim) <: HilbertianProjection J, C, dJ, dC = Gridap.evaluate!(optim.problem,optim.φ0) optim.projector,dJ,C,dC,optim.vel_ext.K bhpm = benchmark_hilbertian_projection_map(optim.projector,dJ,C,dC,optim.vel_ext.K,ranks) diff --git a/scripts/Benchmarks/generate_benchmark_scripts.jl b/scripts/Benchmarks/generate_benchmark_scripts.jl index f142b86b..071177a4 100644 --- a/scripts/Benchmarks/generate_benchmark_scripts.jl +++ b/scripts/Benchmarks/generate_benchmark_scripts.jl @@ -34,11 +34,11 @@ function generate( ) ncpus = prod(mesh_partition) - wallhr = occursin("STRONG",name) && ncpus == 1 ? 100 : - occursin("STRONG",name) && ncpus == 8 ? 24 : + wallhr = occursin("STRONG",name) && ncpus == 1 ? 100 : + occursin("STRONG",name) && ncpus == 8 ? 24 : occursin("STRONG",name) && ncpus == 27 ? 10 : wallhr - mem = occursin("STRONG",name) && ncpus == 1 ? 100 : - occursin("STRONG",name) && ncpus == 8 ? 128 : + mem = occursin("STRONG",name) && ncpus == 1 ? 100 : + occursin("STRONG",name) && ncpus == 8 ? 128 : occursin("STRONG",name) && ncpus == 27 ? 192 : Int(gb_per_node*ncpus/cps_per_node); Nx_partition, Ny_partition, Nz_partition = mesh_partition @@ -68,7 +68,7 @@ function generate_jobs(template,phys_type,ndof_per_node,bmark_types) strong_jobs,weak_jobs,dof_sanity_check end -dir_name= "LevelSetTopOpt"; +dir_name= "GridapTopOpt"; job_output_path = "$(ENV["SCRATCH"])/$dir_name/scripts/Benchmarks/jobs-gadi/"; mkpath(job_output_path); @@ -103,7 +103,7 @@ jobs_by_phys = map(x->(x[1],generate_jobs(template,x[1],x[2],x[3])),phys_types); for jobs in jobs_by_phys strong_jobs,weak_jobs,dof_sanity_check = jobs[2] - + println("$(jobs[1]): Weak dofs = $(dof_sanity_check[1])\n Error = $(dof_sanity_check[2])\n") for job in vcat(strong_jobs,weak_jobs) name = job[1] diff --git a/scripts/MPI/3d_elastic_compliance_ALM.jl b/scripts/MPI/3d_elastic_compliance_ALM.jl index cb221837..a5ff5c02 100644 --- a/scripts/MPI/3d_elastic_compliance_ALM.jl +++ b/scripts/MPI/3d_elastic_compliance_ALM.jl @@ -1,5 +1,5 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + PartitionedArrays, GridapTopOpt, SparseMatricesCSR global elx = parse(Int,ARGS[1]) global ely = parse(Int,ARGS[2]) diff --git a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl index fe6d8f61..35836c01 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_ALM.jl @@ -1,5 +1,5 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + PartitionedArrays, GridapTopOpt, SparseMatricesCSR using GridapSolvers: NewtonSolver diff --git a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl index 7d781947..a8c8b110 100644 --- a/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/MPI/3d_hyperelastic_compliance_neohook_ALM.jl @@ -1,5 +1,5 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + PartitionedArrays, GridapTopOpt, SparseMatricesCSR using GridapSolvers: NewtonSolver diff --git a/scripts/MPI/3d_inverse_homenisation_ALM.jl b/scripts/MPI/3d_inverse_homenisation_ALM.jl index 087372b4..359a1cf2 100644 --- a/scripts/MPI/3d_inverse_homenisation_ALM.jl +++ b/scripts/MPI/3d_inverse_homenisation_ALM.jl @@ -1,5 +1,5 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + PartitionedArrays, GridapTopOpt, SparseMatricesCSR global elx = parse(Int,ARGS[1]) global ely = parse(Int,ARGS[2]) diff --git a/scripts/MPI/3d_inverter_ALM.jl b/scripts/MPI/3d_inverter_ALM.jl index aa7fb6fd..93b4a36b 100644 --- a/scripts/MPI/3d_inverter_ALM.jl +++ b/scripts/MPI/3d_inverter_ALM.jl @@ -1,5 +1,5 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + PartitionedArrays, GridapTopOpt, SparseMatricesCSR global elx = parse(Int,ARGS[1]) global ely = parse(Int,ARGS[2]) diff --git a/scripts/MPI/3d_inverter_HPM.jl b/scripts/MPI/3d_inverter_HPM.jl index 681450d0..ccaf8dcd 100644 --- a/scripts/MPI/3d_inverter_HPM.jl +++ b/scripts/MPI/3d_inverter_HPM.jl @@ -1,5 +1,5 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + PartitionedArrays, GridapTopOpt, SparseMatricesCSR global elx = parse(Int,ARGS[1]) global ely = parse(Int,ARGS[2]) diff --git a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl index 08bcb6f2..dd6a0503 100644 --- a/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_nonlinear_thermal_compliance_ALM.jl @@ -1,5 +1,5 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + PartitionedArrays, GridapTopOpt, SparseMatricesCSR using GridapSolvers: NewtonSolver diff --git a/scripts/MPI/3d_thermal_compliance_ALM.jl b/scripts/MPI/3d_thermal_compliance_ALM.jl index 4bf81ede..2b238351 100644 --- a/scripts/MPI/3d_thermal_compliance_ALM.jl +++ b/scripts/MPI/3d_thermal_compliance_ALM.jl @@ -1,5 +1,5 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + PartitionedArrays, GridapTopOpt, SparseMatricesCSR global elx = parse(Int,ARGS[1]) global ely = parse(Int,ARGS[2]) diff --git a/scripts/MPI/elastic_compliance_ALM.jl b/scripts/MPI/elastic_compliance_ALM.jl index 2c434df7..2cdafccf 100644 --- a/scripts/MPI/elastic_compliance_ALM.jl +++ b/scripts/MPI/elastic_compliance_ALM.jl @@ -1,5 +1,5 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + PartitionedArrays, GridapTopOpt, SparseMatricesCSR global write_dir = ARGS[1] diff --git a/scripts/MPI/inverse_homenisation_ALM.jl b/scripts/MPI/inverse_homenisation_ALM.jl index 032e93c8..5946f589 100644 --- a/scripts/MPI/inverse_homenisation_ALM.jl +++ b/scripts/MPI/inverse_homenisation_ALM.jl @@ -1,5 +1,5 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + PartitionedArrays, GridapTopOpt, SparseMatricesCSR global write_dir = ARGS[1] diff --git a/scripts/MPI/nonlinear_thermal_compliance_ALM.jl b/scripts/MPI/nonlinear_thermal_compliance_ALM.jl index ceb760da..beccd0e9 100644 --- a/scripts/MPI/nonlinear_thermal_compliance_ALM.jl +++ b/scripts/MPI/nonlinear_thermal_compliance_ALM.jl @@ -1,5 +1,5 @@ using Gridap, Gridap.MultiField, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + PartitionedArrays, GridapTopOpt, SparseMatricesCSR global write_dir = ARGS[1] diff --git a/scripts/MPI/thermal_compliance_ALM.jl b/scripts/MPI/thermal_compliance_ALM.jl index a90225d5..9c78fbb1 100644 --- a/scripts/MPI/thermal_compliance_ALM.jl +++ b/scripts/MPI/thermal_compliance_ALM.jl @@ -1,4 +1,4 @@ -using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, LevelSetTopOpt +using Gridap, GridapDistributed, GridapPETSc, PartitionedArrays, GridapTopOpt global write_dir = ARGS[1] diff --git a/scripts/MPI/thermal_compliance_ALM_PETSc.jl b/scripts/MPI/thermal_compliance_ALM_PETSc.jl index 0344f063..9248276f 100644 --- a/scripts/MPI/thermal_compliance_ALM_PETSc.jl +++ b/scripts/MPI/thermal_compliance_ALM_PETSc.jl @@ -1,5 +1,5 @@ using Gridap, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR + PartitionedArrays, GridapTopOpt, SparseMatricesCSR global write_dir = ARGS[1] diff --git a/scripts/Serial/elastic_compliance_ALM.jl b/scripts/Serial/elastic_compliance_ALM.jl index 25c7aeb7..9f0b7024 100644 --- a/scripts/Serial/elastic_compliance_ALM.jl +++ b/scripts/Serial/elastic_compliance_ALM.jl @@ -1,4 +1,4 @@ -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Minimum elastic compliance with augmented Lagrangian method in 2D. diff --git a/scripts/Serial/elastic_compliance_HPM.jl b/scripts/Serial/elastic_compliance_HPM.jl index 14e734fe..9f787c30 100644 --- a/scripts/Serial/elastic_compliance_HPM.jl +++ b/scripts/Serial/elastic_compliance_HPM.jl @@ -1,4 +1,4 @@ -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Minimum elastic compliance with Hilbertian projection method in 2D. diff --git a/scripts/Serial/elastic_compliance_LM.jl b/scripts/Serial/elastic_compliance_LM.jl index 135cccd8..b09e501c 100644 --- a/scripts/Serial/elastic_compliance_LM.jl +++ b/scripts/Serial/elastic_compliance_LM.jl @@ -1,4 +1,4 @@ -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Minimum elastic compliance with Lagrangian method in 2D. diff --git a/scripts/Serial/hyperelastic_compliance_ALM.jl b/scripts/Serial/hyperelastic_compliance_ALM.jl index e3f15cfd..dce96bd5 100644 --- a/scripts/Serial/hyperelastic_compliance_ALM.jl +++ b/scripts/Serial/hyperelastic_compliance_ALM.jl @@ -1,4 +1,4 @@ -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Minimum hyperelastic compliance with augmented Lagrangian method in 2D. diff --git a/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl b/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl index d6ae9163..eca9d1ce 100644 --- a/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl +++ b/scripts/Serial/hyperelastic_compliance_neohook_ALM.jl @@ -1,4 +1,4 @@ -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Minimum hyperelastic (neohookean) compliance with augmented Lagrangian method in 2D. diff --git a/scripts/Serial/inverse_homenisation_ALM.jl b/scripts/Serial/inverse_homenisation_ALM.jl index d06b2d47..972d4328 100644 --- a/scripts/Serial/inverse_homenisation_ALM.jl +++ b/scripts/Serial/inverse_homenisation_ALM.jl @@ -1,4 +1,4 @@ -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Maximum bulk modulus inverse homogenisation with augmented Lagrangian method in 2D. diff --git a/scripts/Serial/inverter_ALM.jl b/scripts/Serial/inverter_ALM.jl index f9a8e3be..ad2d8786 100644 --- a/scripts/Serial/inverter_ALM.jl +++ b/scripts/Serial/inverter_ALM.jl @@ -1,4 +1,4 @@ -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Inverter mechanism with Hilbertian projection method in 2D. diff --git a/scripts/Serial/inverter_HPM.jl b/scripts/Serial/inverter_HPM.jl index 2274a2f4..fbe13122 100644 --- a/scripts/Serial/inverter_HPM.jl +++ b/scripts/Serial/inverter_HPM.jl @@ -1,4 +1,4 @@ -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Inverter mechanism with Hilbertian projection method in 2D. diff --git a/scripts/Serial/nonlinear_thermal_compliance_ALM.jl b/scripts/Serial/nonlinear_thermal_compliance_ALM.jl index 16ffa9b4..2bf32486 100644 --- a/scripts/Serial/nonlinear_thermal_compliance_ALM.jl +++ b/scripts/Serial/nonlinear_thermal_compliance_ALM.jl @@ -1,4 +1,4 @@ -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Minimum thermal compliance with augmented Lagrangian method in 2D with nonlinear diffusivity. diff --git a/scripts/Serial/thermal_compliance_ALM.jl b/scripts/Serial/thermal_compliance_ALM.jl index 1201db0d..aaf45b24 100644 --- a/scripts/Serial/thermal_compliance_ALM.jl +++ b/scripts/Serial/thermal_compliance_ALM.jl @@ -1,4 +1,4 @@ -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Minimum thermal compliance with augmented Lagrangian method in 2D. diff --git a/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl b/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl index 3db4ea46..51f8e1a1 100644 --- a/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl +++ b/scripts/Serial/thermal_compliance_ALM_higherorderlsf.jl @@ -1,4 +1,4 @@ -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Minimum thermal compliance with augmented Lagrangian method in 2D. diff --git a/src/ChainRules.jl b/src/ChainRules.jl index 501c4f7b..361f8daa 100644 --- a/src/ChainRules.jl +++ b/src/ChainRules.jl @@ -1,8 +1,8 @@ """ struct IntegrandWithMeasure{A,B<:Tuple} -A wrapper to enable serial or parallel partial differentation of an -integral `F` using `Gridap.gradient`. This is required to allow automatic +A wrapper to enable serial or parallel partial differentation of an +integral `F` using `Gridap.gradient`. This is required to allow automatic differentation with `DistributedMeasure`. # Properties @@ -30,13 +30,13 @@ evaluate the partial derivative of `F.F` with respect to `uh[K]`. # Example Suppose `uh` and `φh` are FEFunctions with measures `dΩ` and `dΓ_N`. -Then the partial derivative of a function `J` wrt to `φh` is computed via +Then the partial derivative of a function `J` wrt to `φh` is computed via ```` J(u,φ,dΩ,dΓ_N) = ∫(f(u,φ))dΩ + ∫(g(u,φ))dΓ_N J_iwm = IntegrandWithMeasure(J,(dΩ,dΓ_N)) ∂J∂φh = ∇(J_iwm,[uh,φh],2) ```` -where `f` and `g` are user defined. +where `f` and `g` are user defined. """ function Gridap.gradient(F::IntegrandWithMeasure,uh::Vector{<:FEFunction},K::Int) @check 0 < K <= length(uh) @@ -49,8 +49,8 @@ function Gridap.gradient(F::IntegrandWithMeasure,uh::Vector,K::Int) local_fields = map(local_views,uh) |> to_parray_of_arrays local_measures = map(local_views,F.dΩ) |> to_parray_of_arrays contribs = map(local_measures,local_fields) do dΩ,lf - # TODO: Remove second term below, this is a fix for the problem discussed in - # https://github.com/zjwegert/LSTO_Distributed/issues/46 + # TODO: Remove second term below, this is a fix for the problem discussed in + # https://github.com/zjwegert/GridapTopOpt/issues/46 _f = u -> F.F(lf[1:K-1]...,u,lf[K+1:end]...,dΩ...) #+ ∑(∫(0)dΩ[i] for i = 1:length(dΩ)) return Gridap.Fields.gradient(_f,lf[K]) end @@ -62,7 +62,7 @@ Gridap.gradient(F::IntegrandWithMeasure,uh) = Gridap.gradient(F,[uh],1) """ Gridap.jacobian(F::IntegrandWithMeasure,uh::Vector,K::Int) -Given an an `IntegrandWithMeasure` `F` and a vector of `FEFunctions` or `CellField` `uh` +Given an an `IntegrandWithMeasure` `F` and a vector of `FEFunctions` or `CellField` `uh` (excluding measures) evaluate the Jacobian `F.F` with respect to `uh[K]`. """ function Gridap.jacobian(F::IntegrandWithMeasure,uh::Vector{<:Union{FEFunction,CellField}},K::Int) @@ -93,7 +93,7 @@ function GridapDistributed.to_parray_of_arrays(a::NTuple{N,T}) where {N,T<:Debug aj.items[i] end end -end +end function GridapDistributed.to_parray_of_arrays(a::NTuple{N,T}) where {N,T<:MPIArray} indices = linear_indices(first(a)) @@ -130,7 +130,7 @@ end StateParamIntegrandWithMeasure(F::IntegrandWithMeasure,U::FESpace,V_φ::FESpace, U_reg::FESpace,assem_U::Assembler,assem_deriv::Assembler) -Create an instance of `StateParamIntegrandWithMeasure`. +Create an instance of `StateParamIntegrandWithMeasure`. """ function StateParamIntegrandWithMeasure( F::IntegrandWithMeasure, @@ -151,7 +151,7 @@ end """ (u_to_j::StateParamIntegrandWithMeasure)(uh,φh) -Evaluate the `StateParamIntegrandWithMeasure` at parameters `uh` and `φh`. +Evaluate the `StateParamIntegrandWithMeasure` at parameters `uh` and `φh`. """ (u_to_j::StateParamIntegrandWithMeasure)(uh,φh) = sum(u_to_j.F(uh,φh)) @@ -165,7 +165,7 @@ end """ ChainRulesCore.rrule(u_to_j::StateParamIntegrandWithMeasure,uh,φh) -Return the evaluation of a `StateParamIntegrandWithMeasure` and a +Return the evaluation of a `StateParamIntegrandWithMeasure` and a a function for evaluating the pullback of `u_to_j`. This enables compatiblity with `ChainRules.jl` """ @@ -200,7 +200,7 @@ end """ abstract type AbstractFEStateMap -Types inheriting from this abstract type should enable the evaluation and differentiation of +Types inheriting from this abstract type should enable the evaluation and differentiation of the solution to an FE problem `u` that implicitly depends on an auxiliary parameter `φ`. """ abstract type AbstractFEStateMap end @@ -208,7 +208,7 @@ abstract type AbstractFEStateMap end """ get_state(m::AbstractFEStateMap) -Return the solution/state `u` to the FE problem. +Return the solution/state `u` to the FE problem. """ get_state(::AbstractFEStateMap) = @abstractmethod @@ -222,7 +222,7 @@ get_measure(::AbstractFEStateMap) = @abstractmethod """ get_spaces(m::AbstractFEStateMap) -Return a collection of FE spaces. The first four entires should correspond to +Return a collection of FE spaces. The first four entires should correspond to [`get_trial_space`](@ref), [`get_test_space`](@ref), [`get_aux_space`](@ref), and [`get_deriv_space`](@ref) unless these are overloaded for a particular implementation. """ @@ -231,8 +231,8 @@ get_spaces(::AbstractFEStateMap) = @abstractmethod """ get_assemblers(m::AbstractFEStateMap) -Return a collection of assemblers. The first two entires should correspond to -[`get_pde_assembler`](@ref) and [`get_deriv_assembler`](@ref) unless these are +Return a collection of assemblers. The first two entires should correspond to +[`get_pde_assembler`](@ref) and [`get_deriv_assembler`](@ref) unless these are overloaded for a particular implementation. """ get_assemblers(::AbstractFEStateMap) = @abstractmethod @@ -326,7 +326,7 @@ This should solve the linear problem `dRduᵀ*λ = ∂F∂uᵀ`. """ function adjoint_solve!(φ_to_u::AbstractFEStateMap,du::AbstractVector) @abstractmethod -end +end """ dRdφ(φ_to_u::AbstractFEStateMap,uh,vh,φh) @@ -347,7 +347,7 @@ end """ pullback(φ_to_u::AbstractFEStateMap,uh,φh,du;updated) -Compute `∂F∂u*dudφ` at `φh` and `uh` using the adjoint method. I.e., let +Compute `∂F∂u*dudφ` at `φh` and `uh` using the adjoint method. I.e., let `∂F∂u*dudφ = -λᵀ*dRdφ` @@ -365,10 +365,10 @@ function pullback(φ_to_u::AbstractFEStateMap,uh,φh,du;updated=false) λh = FEFunction(get_test_space(φ_to_u),λ) ## Compute grad - dudφ_vecdata = collect_cell_vector(U_reg,dRdφ(φ_to_u,uh,λh,φh)) + dudφ_vecdata = collect_cell_vector(U_reg,dRdφ(φ_to_u,uh,λh,φh)) assemble_vector!(dudφ_vec,assem_deriv,dudφ_vecdata) rmul!(dudφ_vec, -1) - + return (NoTangent(),dudφ_vec) end @@ -381,7 +381,7 @@ end """ rrule(φ_to_u::AbstractFEStateMap,φh) -Return the evaluation of a `AbstractFEStateMap` and a +Return the evaluation of a `AbstractFEStateMap` and a a function for evaluating the pullback of `φ_to_u`. This enables compatiblity with `ChainRules.jl` """ @@ -452,7 +452,7 @@ struct AffineFEStateMap{A,B,C,D,E,F} <: AbstractFEStateMap Create an instance of `AffineFEStateMap` given the bilinear form `a` and linear form `l` as `Function` types, trial and test spaces `U` and `V`, the FE space `V_φ` - for `φh`, the FE space `U_reg` for derivatives, and the measures as additional arguments. + for `φh`, the FE space `U_reg` for derivatives, and the measures as additional arguments. Optional arguments enable specification of assemblers and linear solvers. """ @@ -567,9 +567,9 @@ struct NonlinearFEStateMap{A,B,C,D,E,F} <: AbstractFEStateMap adjoint_ls::LinearSolver = LUSolver() ) - Create an instance of `NonlinearFEStateMap` given the residual `res` as a `Function` type, - trial and test spaces `U` and `V`, the FE space `V_φ` for `φh`, the FE space `U_reg` - for derivatives, and the measures as additional arguments. + Create an instance of `NonlinearFEStateMap` given the residual `res` as a `Function` type, + trial and test spaces `U` and `V`, the FE space `V_φ` for `φh`, the FE space `U_reg` + for derivatives, and the measures as additional arguments. Optional arguments enable specification of assemblers, nonlinear solver, and adjoint (linear) solver. """ @@ -605,7 +605,7 @@ struct NonlinearFEStateMap{A,B,C,D,E,F} <: AbstractFEStateMap adjoint_x = allocate_in_domain(adjoint_K); fill!(adjoint_x,zero(eltype(adjoint_x))) adjoint_ns = numerical_setup(symbolic_setup(adjoint_ls,adjoint_K),adjoint_K) adj_caches = (adjoint_ns,adjoint_K,adjoint_x,assem_adjoint) - + A, B, C = typeof(res), typeof(jac), typeof(spaces) D, E, F = typeof(plb_caches), typeof(fwd_caches), typeof(adj_caches) return new{A,B,C,D,E,F}(res,jac,spaces,plb_caches,fwd_caches,adj_caches) @@ -685,16 +685,16 @@ struct RepeatingAffineFEStateMap{A,B,C,D,E,F,G} <: AbstractFEStateMap adjoint_ls::LinearSolver = LUSolver() ) - Create an instance of `RepeatingAffineFEStateMap` given the number of blocks `nblocks`, - a bilinear form `a`, a vector of linear form `l` as `Function` types, the trial and test - spaces `U` and `V`, the FE space `V_φ` for `φh`, the FE space `U_reg` for derivatives, - and the measures as additional arguments. + Create an instance of `RepeatingAffineFEStateMap` given the number of blocks `nblocks`, + a bilinear form `a`, a vector of linear form `l` as `Function` types, the trial and test + spaces `U` and `V`, the FE space `V_φ` for `φh`, the FE space `U_reg` for derivatives, + and the measures as additional arguments. Optional arguments enable specification of assemblers and linear solvers. # Note - - The resulting `FEFunction` will be a `MultiFieldFEFunction` (or GridapDistributed equivalent) + - The resulting `FEFunction` will be a `MultiFieldFEFunction` (or GridapDistributed equivalent) where each field corresponds to an entry in the vector of linear forms """ function RepeatingAffineFEStateMap( @@ -790,7 +790,7 @@ repeated_blocks(::ConsecutiveMultiFieldStyle,V0,x::AbstractBlockVector) = blocks function repeated_blocks(::BlockMultiFieldStyle{NB},V0::MultiFieldSpaceTypes,x::AbstractBlockVector) where NB xb = blocks(x) @assert length(xb) % NB == 0 - + nblocks = length(xb) ÷ NB rep_blocks = map(1:nblocks) do iB mortar(xb[(iB-1)*NB+1:iB*NB]) @@ -875,37 +875,37 @@ end """ struct PDEConstrainedFunctionals{N,A} -An object that computes the objective, constraints, and their derivatives. +An object that computes the objective, constraints, and their derivatives. # Implementation -This implementation computes derivatives of a integral quantity +This implementation computes derivatives of a integral quantity -``F(u(\\varphi),\\varphi,\\mathrm{d}\\Omega_1,\\mathrm{d}\\Omega_2,...) = -\\Sigma_{i}\\int_{\\Omega_i} f_i(\\varphi)~\\mathrm{d}\\Omega`` +``F(u(\\varphi),\\varphi,\\mathrm{d}\\Omega_1,\\mathrm{d}\\Omega_2,...) = +\\Sigma_{i}\\int_{\\Omega_i} f_i(\\varphi)~\\mathrm{d}\\Omega`` with respect to an auxiliary parameter ``\\varphi`` where ``u`` -is the solution to a PDE and implicitly depends on ``\\varphi``. +is the solution to a PDE and implicitly depends on ``\\varphi``. This requires two pieces of information: - 1) Computation of ``\\frac{\\partial F}{\\partial u}`` and + 1) Computation of ``\\frac{\\partial F}{\\partial u}`` and ``\\frac{\\partial F}{\\partial \\varphi}`` (handled by [`StateParamIntegrandWithMeasure `](@ref)). 2) Computation of ``\\frac{\\partial F}{\\partial u} - \\frac{\\partial u}{\\partial \\varphi}`` at ``\\varphi`` and ``u`` - using the adjoint method (handled by [`AbstractFEStateMap`](@ref)). I.e., let - + \\frac{\\partial u}{\\partial \\varphi}`` at ``\\varphi`` and ``u`` + using the adjoint method (handled by [`AbstractFEStateMap`](@ref)). I.e., let + ``\\frac{\\partial F}{\\partial u} - \\frac{\\partial u}{\\partial \\varphi} = -\\lambda^\\intercal + \\frac{\\partial u}{\\partial \\varphi} = -\\lambda^\\intercal \\frac{\\partial \\mathcal{R}}{\\partial \\varphi}`` - where ``\\mathcal{R}`` is the residual and solve the (linear) adjoint + where ``\\mathcal{R}`` is the residual and solve the (linear) adjoint problem: - - ``\\frac{\\partial \\mathcal{R}}{\\partial u}^\\intercal\\lambda = + + ``\\frac{\\partial \\mathcal{R}}{\\partial u}^\\intercal\\lambda = \\frac{\\partial F}{\\partial u}^\\intercal.`` -The gradient is then ``\\frac{\\partial F}{\\partial \\varphi} = -\\frac{\\partial F}{\\partial \\varphi} - +The gradient is then ``\\frac{\\partial F}{\\partial \\varphi} = +\\frac{\\partial F}{\\partial \\varphi} - \\frac{\\partial F}{\\partial u}\\frac{\\partial u}{\\partial \\varphi}``. # Parameters @@ -938,7 +938,7 @@ struct PDEConstrainedFunctionals{N,A} Create an instance of `PDEConstrainedFunctionals`. The arguments for the objective and constraints must follow the specification in [`StateParamIntegrandWithMeasure`](@ref). - By default we use automatic differentation for the objective and all constraints. This + By default we use automatic differentation for the objective and all constraints. This can be disabled by passing the shape derivative as a type `Function` to `analytic_dJ` and/or entires in `analytic_dC`. """ @@ -952,7 +952,7 @@ struct PDEConstrainedFunctionals{N,A} # Create StateParamIntegrandWithMeasures J = StateParamIntegrandWithMeasure(objective,state_map) C = map(Ci -> StateParamIntegrandWithMeasure(Ci,state_map),constraints) - + # Preallocate dJ = similar(J.caches[2]) dC = map(Ci->similar(Ci.caches[2]),C) @@ -968,7 +968,7 @@ end Create an instance of `PDEConstrainedFunctionals` when the problem has no constraints. """ -PDEConstrainedFunctionals(J::Function,state_map::AbstractFEStateMap;analytic_dJ=nothing) = +PDEConstrainedFunctionals(J::Function,state_map::AbstractFEStateMap;analytic_dJ=nothing) = PDEConstrainedFunctionals(J,Function[],state_map;analytic_dJ = analytic_dJ,analytic_dC = Nothing[]) get_state(m::PDEConstrainedFunctionals) = get_state(m.state_map) @@ -1011,7 +1011,7 @@ end Fields.evaluate!(pcf::PDEConstrainedFunctionals,φh) Evaluate the objective and constraints, and their derivatives at -`φh`. +`φh`. """ function Fields.evaluate!(pcf::PDEConstrainedFunctionals,φh) J, C, dJ, dC = pcf.J,pcf.C,pcf.dJ,pcf.dC @@ -1031,7 +1031,7 @@ function Fields.evaluate!(pcf::PDEConstrainedFunctionals,φh) # Automatic differentation j_val, j_pullback = rrule(F,uh,φh) # Compute functional and pull back _, dFdu, dFdφ = j_pullback(1) # Compute dFdu, dFdφ - _, dφ_adj = u_pullback(dFdu) # Compute -dFdu*dudφ via adjoint + _, dφ_adj = u_pullback(dFdu) # Compute -dFdu*dudφ via adjoint copy!(dF,dφ_adj) dF .+= dFdφ return j_val diff --git a/src/LevelSetTopOpt.jl b/src/GridapTopOpt.jl similarity index 94% rename from src/LevelSetTopOpt.jl rename to src/GridapTopOpt.jl index 43f948f7..c0c0dbea 100644 --- a/src/LevelSetTopOpt.jl +++ b/src/GridapTopOpt.jl @@ -1,4 +1,4 @@ -module LevelSetTopOpt +module GridapTopOpt using GridapPETSc, GridapPETSc.PETSC using GridapPETSc: PetscScalar, PetscInt, PETSC, @check_error_code @@ -19,7 +19,7 @@ using Gridap.FESpaces: get_assembly_strategy using Gridap: writevtk using GridapDistributed -using GridapDistributed: DistributedDiscreteModel, DistributedTriangulation, +using GridapDistributed: DistributedDiscreteModel, DistributedTriangulation, DistributedFESpace, DistributedDomainContribution, to_parray_of_arrays, allocate_in_domain, DistributedCellField, DistributedMultiFieldCellField, DistributedMultiFieldFEBasis, BlockPMatrix, BlockPVector, change_ghost diff --git a/src/Optimisers/Optimisers.jl b/src/Optimisers/Optimisers.jl index c95aa097..e5e31537 100644 --- a/src/Optimisers/Optimisers.jl +++ b/src/Optimisers/Optimisers.jl @@ -1,8 +1,8 @@ """ abstract type Optimiser -Optimisers in LevelSetTopOpt.jl are implemented as iterators. -Your own optimiser can be implemented by implementing +Optimisers in GridapTopOpt.jl are implemented as iterators. +Your own optimiser can be implemented by implementing concrete functionality of the below. """ abstract type Optimiser end @@ -43,7 +43,7 @@ get_history(::Optimiser) :: OptimiserHistory = @abstractmethod """ converged(::Optimiser) -Return a `Bool` that is true if the `Optimiser` has +Return a `Bool` that is true if the `Optimiser` has converged, otherwise false. """ function converged(::Optimiser) :: Bool @@ -59,7 +59,7 @@ function finished(m::Optimiser) :: Bool return A || B end -function print_msg(opt::Optimiser,msg::String;kwargs...) +function print_msg(opt::Optimiser,msg::String;kwargs...) print_msg(get_history(opt),msg;kwargs...) end @@ -203,7 +203,7 @@ end """ write_history(path::String,h::OptimiserHistory;ranks=nothing) - + Write the contents of an `OptimiserHistory` object to a `path`. Provide MPI `ranks` when running in parallel. """ @@ -211,7 +211,7 @@ function write_history(path::String,h::OptimiserHistory;ranks=nothing) if i_am_main(ranks) open(path,"w") do f write(f,h) - end + end end end @@ -224,7 +224,7 @@ end """ struct OptimiserHistorySlice{T} end -A read-only wrapper of OptimiserHistory for IO display +A read-only wrapper of OptimiserHistory for IO display of iteration history at a specific iteration. """ struct OptimiserHistorySlice{T} diff --git a/test/seq/InverseHomogenisationALMTests.jl b/test/seq/InverseHomogenisationALMTests.jl index 82929b7d..b0b79d4a 100644 --- a/test/seq/InverseHomogenisationALMTests.jl +++ b/test/seq/InverseHomogenisationALMTests.jl @@ -1,7 +1,7 @@ module InverseHomogenisationALMTests using Test -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Maximum bulk modulus inverse homogenisation with augmented Lagrangian method in 2D. @@ -10,9 +10,9 @@ using Gridap, LevelSetTopOpt Min J(Ω) = -κ(Ω) Ω s.t., Vol(Ω) = vf, - ⎡For unique εᴹᵢ, find uᵢ∈V=H¹ₚₑᵣ(Ω)ᵈ, + ⎡For unique εᴹᵢ, find uᵢ∈V=H¹ₚₑᵣ(Ω)ᵈ, ⎣∫ ∑ᵢ C ⊙ ε(uᵢ) ⊙ ε(vᵢ) dΩ = ∫ -∑ᵢ C ⊙ ε⁰ᵢ ⊙ ε(vᵢ) dΩ, ∀v∈V. -""" +""" function main(;AD) ## Parameters order = 1 @@ -85,7 +85,7 @@ function main(;AD) α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) diff --git a/test/seq/InverterHPMTests.jl b/test/seq/InverterHPMTests.jl index ce94a389..06fffac5 100644 --- a/test/seq/InverterHPMTests.jl +++ b/test/seq/InverterHPMTests.jl @@ -1,7 +1,7 @@ module InverterHPMTests using Test -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Inverter mechanism with Hilbertian projection method in 2D. @@ -10,13 +10,13 @@ using Gridap, LevelSetTopOpt Min J(Ω) = ηᵢₙ*∫ u⋅e₁ dΓᵢₙ/Vol(Γᵢₙ) Ω s.t., Vol(Ω) = vf, - C(Ω) = 0, - ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, + C(Ω) = 0, + ⎡u∈V=H¹(Ω;u(Γ_D)=0)ᵈ, ⎣∫ C ⊙ ε(u) ⊙ ε(v) dΩ + ∫ kₛv⋅u dΓₒᵤₜ = ∫ v⋅g dΓᵢₙ , ∀v∈V. - + where C(Ω) = ∫ -u⋅e₁-δₓ dΓₒᵤₜ/Vol(Γₒᵤₜ). We assume symmetry in the problem to aid convergence. -""" +""" function main() ## Parameters order = 1 @@ -33,7 +33,7 @@ function main() δₓ = 0.2 ks = 0.1 g = VectorValue(0.5,0) - + ## FE Setup model = CartesianDiscreteModel(dom,el_size) el_Δ = get_el_Δ(model) @@ -97,7 +97,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) = ∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = HilbertianProjection(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,debug=true,constraint_names=[:Vol,:UΓ_out]) diff --git a/test/seq/NonlinearThermalComplianceALMTests.jl b/test/seq/NonlinearThermalComplianceALMTests.jl index c624d997..c4808705 100644 --- a/test/seq/NonlinearThermalComplianceALMTests.jl +++ b/test/seq/NonlinearThermalComplianceALMTests.jl @@ -1,7 +1,7 @@ module NonlinearThermalComplianceALMTests using Test -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Minimum thermal compliance with augmented Lagrangian method in 2D with nonlinear diffusivity. @@ -12,9 +12,9 @@ using Gridap, LevelSetTopOpt s.t., Vol(Ω) = vf, ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ(u)*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. - + In this example κ(u) = κ0*(exp(ξ*u)) -""" +""" function main() ## Parameters order = 1 @@ -34,9 +34,9 @@ function main() ## FE Setup model = CartesianDiscreteModel(dom,el_size); el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || + f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())); - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= + f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()); update_labels!(1,model,f_Γ_D,"Gamma_D") update_labels!(2,model,f_Γ_N,"Gamma_N") @@ -84,7 +84,7 @@ function main() α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) diff --git a/test/seq/PZMultiFieldRepeatingStateTests.jl b/test/seq/PZMultiFieldRepeatingStateTests.jl index 827f9c91..06db9bb2 100644 --- a/test/seq/PZMultiFieldRepeatingStateTests.jl +++ b/test/seq/PZMultiFieldRepeatingStateTests.jl @@ -1,8 +1,8 @@ module PZMultiFieldRepeatingStateTests using Test -using Gridap, GridapDistributed, GridapPETSc, GridapSolvers, - PartitionedArrays, LevelSetTopOpt, SparseMatricesCSR +using Gridap, GridapDistributed, GridapPETSc, GridapSolvers, + PartitionedArrays, GridapTopOpt, SparseMatricesCSR using Gridap.TensorValues, Gridap.Helpers @@ -54,8 +54,8 @@ function main(;AD) ## Material tensors C, e, κ = PZT5A_2D(); - k0 = norm(C.data,Inf); - α0 = norm(e.data,Inf); + k0 = norm(C.data,Inf); + α0 = norm(e.data,Inf); β0 = norm(κ.data,Inf); γ0 = β0*k0/α0^2; @@ -66,9 +66,9 @@ function main(;AD) Eⁱ = (VectorValue(1.0,0.0,), VectorValue(0.0,1.0)) - a((u,ϕ),(v,q),φ,dΩ) = ∫((I ∘ φ) * (1/k0*((C ⊙ ε(u)) ⊙ ε(v)) - + a((u,ϕ),(v,q),φ,dΩ) = ∫((I ∘ φ) * (1/k0*((C ⊙ ε(u)) ⊙ ε(v)) - 1/α0*((-∇(ϕ) ⋅ e) ⊙ ε(v)) + - -1/α0*((e ⋅² ε(u)) ⋅ -∇(q)) + + -1/α0*((e ⋅² ε(u)) ⋅ -∇(q)) + -γ0/β0*((κ ⋅ -∇(ϕ)) ⋅ -∇(q))) )dΩ; l_ε = [((v,q),φ,dΩ) -> ∫(((I ∘ φ) * (-C ⊙ εᴹ[i] ⊙ ε(v) + k0/α0*(e ⋅² εᴹ[i]) ⋅ -∇(q))))dΩ for i = 1:3]; @@ -84,9 +84,9 @@ function main(;AD) u_r = uϕ[2r-1]; ϕ_r = uϕ[2r] u_s = uϕ[2s-1]; ϕ_s = uϕ[2s] ∫(- 1/k0 * q * ( - (C ⊙ (1/k0*ε(u_s) + εᴹ[s])) ⊙ (1/k0*ε(u_r) + εᴹ[r]) - + (C ⊙ (1/k0*ε(u_s) + εᴹ[s])) ⊙ (1/k0*ε(u_r) + εᴹ[r]) - (-1/α0*∇(ϕ_s) ⋅ e) ⊙ (1/k0*ε(u_r) + εᴹ[r]) - - (e ⋅² (1/k0*ε(u_s) + εᴹ[s])) ⋅ (-1/α0*∇(ϕ_r)) - + (e ⋅² (1/k0*ε(u_s) + εᴹ[s])) ⋅ (-1/α0*∇(ϕ_r)) - (κ ⋅ (-1/α0*∇(ϕ_s))) ⋅ (-1/α0*∇(ϕ_r)) ) * (DH ∘ φ) * (norm ∘ ∇(φ)) )dΩ; diff --git a/test/seq/ThermalComplianceALMTests.jl b/test/seq/ThermalComplianceALMTests.jl index c96225f8..fcf3704d 100644 --- a/test/seq/ThermalComplianceALMTests.jl +++ b/test/seq/ThermalComplianceALMTests.jl @@ -1,7 +1,7 @@ module ThermalComplianceALMTests using Test -using Gridap, LevelSetTopOpt +using Gridap, GridapTopOpt """ (Serial) Minimum thermal compliance with augmented Lagrangian method in 2D. @@ -12,7 +12,7 @@ using Gridap, LevelSetTopOpt s.t., Vol(Ω) = vf, ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. -""" +""" function main(;order,AD) ## Parameters xmax = ymax = 1.0 @@ -32,9 +32,9 @@ function main(;order,AD) ## FE Setup model = CartesianDiscreteModel(dom,el_size); el_Δ = get_el_Δ(model) - f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || + f_Γ_D(x) = (x[1] ≈ 0.0 && (x[2] <= ymax*prop_Γ_D + eps() || x[2] >= ymax-ymax*prop_Γ_D - eps())) - f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= + f_Γ_N(x) = (x[1] ≈ xmax && ymax/2-ymax*prop_Γ_N/2 - eps() <= x[2] <= ymax/2+ymax*prop_Γ_N/2 + eps()) update_labels!(1,model,f_Γ_D,"Gamma_D") update_labels!(2,model,f_Γ_N,"Gamma_N") @@ -85,7 +85,7 @@ function main(;order,AD) α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) @@ -105,7 +105,7 @@ end s.t., Vol(Ω) = vf, ⎡u∈V=H¹(Ω;u(Γ_D)=0), ⎣∫ κ*∇(u)⋅∇(v) dΩ = ∫ v dΓ_N, ∀v∈V. -""" +""" function main_3d(;order) ## Parameters xmax = ymax = zmax = 1.0 @@ -174,7 +174,7 @@ function main_3d(;order) α = α_coeff*maximum(el_Δ) a_hilb(p,q) =∫(α^2*∇(p)⋅∇(q) + p*q)dΩ; vel_ext = VelocityExtension(a_hilb,U_reg,V_reg) - + ## Optimiser optimiser = AugmentedLagrangian(pcfs,ls_evo,vel_ext,φh; γ,γ_reinit,verbose=true,constraint_names=[:Vol]) From 03407de48819567ebab3e4bdb4baa51cd690b769 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Tue, 7 May 2024 12:06:57 +1000 Subject: [PATCH 86/90] Add folder ignore --- .gitignore | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.gitignore b/.gitignore index ddd3c8e5..1a774d3b 100644 --- a/.gitignore +++ b/.gitignore @@ -27,3 +27,6 @@ docs/site/ Manifest.toml LocalPreferences.toml GridapTopOpt.so + +# Ensure never to write results to git +results/* \ No newline at end of file From c26a526c4a2dea0289c8fb625efd5e29e4018043 Mon Sep 17 00:00:00 2001 From: Z J Wegert <60646897+zjwegert@users.noreply.github.com> Date: Wed, 8 May 2024 14:51:04 +1000 Subject: [PATCH 87/90] Update LICENSE.md From 93a553e74ecc21e3f37cdca0a8b6eeff79f50c47 Mon Sep 17 00:00:00 2001 From: Z J Wegert <60646897+zjwegert@users.noreply.github.com> Date: Wed, 8 May 2024 14:51:25 +1000 Subject: [PATCH 88/90] Update LICENSE.md --- LICENSE.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/LICENSE.md b/LICENSE.md index 1dbccfec..fab81e84 100644 --- a/LICENSE.md +++ b/LICENSE.md @@ -18,4 +18,4 @@ FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE -SOFTWARE. +SOFTWARE. From 63bda7ce16e029246afaad0c1744866ac6da3455 Mon Sep 17 00:00:00 2001 From: "Z J Wegert (Workstation)" Date: Thu, 9 May 2024 16:21:25 +1000 Subject: [PATCH 89/90] update readme --- README.md | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index d75a3ce5..bd628f68 100755 --- a/README.md +++ b/README.md @@ -12,4 +12,7 @@ GridapTopOpt is computational toolbox for level set-based topology optimisation - [**LATEST**](...) — *Documentation for the in-development version.* ## Citation -In order to give credit to the `GridapTopOpt` contributors, we ask that you please reference the above paper along with the required citations for [Gridap](https://github.com/gridap/Gridap.jl?tab=readme-ov-file#how-to-cite-gridap). \ No newline at end of file +In order to give credit to the `GridapTopOpt` contributors, we ask that you please reference the above paper along with the required citations for [Gridap](https://github.com/gridap/Gridap.jl?tab=readme-ov-file#how-to-cite-gridap). + +## Known issues +- We currently require the `develop` branch of `GridapSolvers` for `GridapTopOpt`. Ensure that this is correctly loaded via `pkg> add GridapSolvers#develop`. \ No newline at end of file From 9b1d0ffee2c8347aad7dd8f555123d7579c568cf Mon Sep 17 00:00:00 2001 From: zjwegert <60646897+zjwegert@users.noreply.github.com> Date: Fri, 10 May 2024 07:12:57 +1000 Subject: [PATCH 90/90] Cleanup docs --- docs/make.jl | 15 --------------- docs/src/{ => deprecated}/dev/shape_der.md | 0 .../2d_min_thermal_comp_final_struc.png | Bin .../2d_min_thermal_comp_initial_lsf_combined.png | Bin .../tutorials/2d_min_thermal_comp_setup.png | Bin .../tutorials/2d_min_thermal_nl_final_struc.png | Bin .../tutorials/3d_min_thermal_combined.png | Bin .../tutorials/3d_min_thermal_comp.png | Bin .../tutorials/inverse_homogenisation.md | 0 .../tutorials/inverter_mechanism.md | 0 .../tutorials/minimum_elastic_compliance.md | 0 .../tutorials/minimum_thermal_compliance.md | 0 docs/src/{ => deprecated}/usage/ad.md | 0 .../{ => deprecated}/usage/getting-started.md | 0 docs/src/{ => deprecated}/usage/mpi-mode.md | 0 docs/src/{ => deprecated}/usage/petsc.md | 0 16 files changed, 15 deletions(-) rename docs/src/{ => deprecated}/dev/shape_der.md (100%) rename docs/src/{ => deprecated}/tutorials/2d_min_thermal_comp_final_struc.png (100%) rename docs/src/{ => deprecated}/tutorials/2d_min_thermal_comp_initial_lsf_combined.png (100%) rename docs/src/{ => deprecated}/tutorials/2d_min_thermal_comp_setup.png (100%) rename docs/src/{ => deprecated}/tutorials/2d_min_thermal_nl_final_struc.png (100%) rename docs/src/{ => deprecated}/tutorials/3d_min_thermal_combined.png (100%) rename docs/src/{ => deprecated}/tutorials/3d_min_thermal_comp.png (100%) rename docs/src/{ => deprecated}/tutorials/inverse_homogenisation.md (100%) rename docs/src/{ => deprecated}/tutorials/inverter_mechanism.md (100%) rename docs/src/{ => deprecated}/tutorials/minimum_elastic_compliance.md (100%) rename docs/src/{ => deprecated}/tutorials/minimum_thermal_compliance.md (100%) rename docs/src/{ => deprecated}/usage/ad.md (100%) rename docs/src/{ => deprecated}/usage/getting-started.md (100%) rename docs/src/{ => deprecated}/usage/mpi-mode.md (100%) rename docs/src/{ => deprecated}/usage/petsc.md (100%) diff --git a/docs/make.jl b/docs/make.jl index 7755b4c2..edd81efb 100644 --- a/docs/make.jl +++ b/docs/make.jl @@ -15,18 +15,6 @@ makedocs( pages = [ "Home" => "index.md", "Getting Started" => "getting-started.md", - # "Usage" => [ - # "usage/getting-started.md", - # "usage/ad.md", - # "usage/petsc.md", - # "usage/mpi-mode.md", - # ], - # "Tutorials" => [ - # "tutorials/minimum_thermal_compliance.md", - # "tutorials/minimum_elastic_compliance.md", - # "tutorials/inverter_mechanism.md", - # "tutorials/inverse_homogenisation.md", - # ], "Reference" => [ "reference/optimisers.md", "reference/chainrules.md", @@ -36,9 +24,6 @@ makedocs( "reference/utilities.md", "reference/benchmarking.md" ], - # "Developer Notes" => [ - # "dev/shape_der.md", - # ] ], ) diff --git a/docs/src/dev/shape_der.md b/docs/src/deprecated/dev/shape_der.md similarity index 100% rename from docs/src/dev/shape_der.md rename to docs/src/deprecated/dev/shape_der.md diff --git a/docs/src/tutorials/2d_min_thermal_comp_final_struc.png b/docs/src/deprecated/tutorials/2d_min_thermal_comp_final_struc.png similarity index 100% rename from docs/src/tutorials/2d_min_thermal_comp_final_struc.png rename to docs/src/deprecated/tutorials/2d_min_thermal_comp_final_struc.png diff --git a/docs/src/tutorials/2d_min_thermal_comp_initial_lsf_combined.png b/docs/src/deprecated/tutorials/2d_min_thermal_comp_initial_lsf_combined.png similarity index 100% rename from docs/src/tutorials/2d_min_thermal_comp_initial_lsf_combined.png rename to docs/src/deprecated/tutorials/2d_min_thermal_comp_initial_lsf_combined.png diff --git a/docs/src/tutorials/2d_min_thermal_comp_setup.png b/docs/src/deprecated/tutorials/2d_min_thermal_comp_setup.png similarity index 100% rename from docs/src/tutorials/2d_min_thermal_comp_setup.png rename to docs/src/deprecated/tutorials/2d_min_thermal_comp_setup.png diff --git a/docs/src/tutorials/2d_min_thermal_nl_final_struc.png b/docs/src/deprecated/tutorials/2d_min_thermal_nl_final_struc.png similarity index 100% rename from docs/src/tutorials/2d_min_thermal_nl_final_struc.png rename to docs/src/deprecated/tutorials/2d_min_thermal_nl_final_struc.png diff --git a/docs/src/tutorials/3d_min_thermal_combined.png b/docs/src/deprecated/tutorials/3d_min_thermal_combined.png similarity index 100% rename from docs/src/tutorials/3d_min_thermal_combined.png rename to docs/src/deprecated/tutorials/3d_min_thermal_combined.png diff --git a/docs/src/tutorials/3d_min_thermal_comp.png b/docs/src/deprecated/tutorials/3d_min_thermal_comp.png similarity index 100% rename from docs/src/tutorials/3d_min_thermal_comp.png rename to docs/src/deprecated/tutorials/3d_min_thermal_comp.png diff --git a/docs/src/tutorials/inverse_homogenisation.md b/docs/src/deprecated/tutorials/inverse_homogenisation.md similarity index 100% rename from docs/src/tutorials/inverse_homogenisation.md rename to docs/src/deprecated/tutorials/inverse_homogenisation.md diff --git a/docs/src/tutorials/inverter_mechanism.md b/docs/src/deprecated/tutorials/inverter_mechanism.md similarity index 100% rename from docs/src/tutorials/inverter_mechanism.md rename to docs/src/deprecated/tutorials/inverter_mechanism.md diff --git a/docs/src/tutorials/minimum_elastic_compliance.md b/docs/src/deprecated/tutorials/minimum_elastic_compliance.md similarity index 100% rename from docs/src/tutorials/minimum_elastic_compliance.md rename to docs/src/deprecated/tutorials/minimum_elastic_compliance.md diff --git a/docs/src/tutorials/minimum_thermal_compliance.md b/docs/src/deprecated/tutorials/minimum_thermal_compliance.md similarity index 100% rename from docs/src/tutorials/minimum_thermal_compliance.md rename to docs/src/deprecated/tutorials/minimum_thermal_compliance.md diff --git a/docs/src/usage/ad.md b/docs/src/deprecated/usage/ad.md similarity index 100% rename from docs/src/usage/ad.md rename to docs/src/deprecated/usage/ad.md diff --git a/docs/src/usage/getting-started.md b/docs/src/deprecated/usage/getting-started.md similarity index 100% rename from docs/src/usage/getting-started.md rename to docs/src/deprecated/usage/getting-started.md diff --git a/docs/src/usage/mpi-mode.md b/docs/src/deprecated/usage/mpi-mode.md similarity index 100% rename from docs/src/usage/mpi-mode.md rename to docs/src/deprecated/usage/mpi-mode.md diff --git a/docs/src/usage/petsc.md b/docs/src/deprecated/usage/petsc.md similarity index 100% rename from docs/src/usage/petsc.md rename to docs/src/deprecated/usage/petsc.md

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