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using Gridap, LevelSetTopOpt | ||
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# 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 | ||
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# 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 | ||
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evaluate!(pcfs,φh); | ||
uh = get_state(state_map) | ||
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GC.gc() | ||
Sys.free_memory() / 2^20 | ||
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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; | ||
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Sys.free_memory() / 2^20 | ||
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GC.gc() | ||
Sys.free_memory() / 2^20 | ||
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for i = 1:10 | ||
begin | ||
# u = LevelSetTopOpt.forward_solve!(state_map,φh); | ||
# uh = FEFunction(LevelSetTopOpt.get_trial_space(state_map),u); | ||
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LevelSetTopOpt.update_adjoint_caches!(state_map,uh,φh); | ||
end; | ||
end; | ||
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Sys.free_memory() / 2^20 | ||
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GC.gc() | ||
Sys.free_memory() / 2^20 | ||
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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; | ||
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Sys.free_memory() / 2^20 |