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scripts/Embedded/MWEs/zygote/thermal_compliance_ALM copy.jl
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using Gridap, GridapTopOpt | ||
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path="./results/TEST_thermal_compliance_ALM/" | ||
## 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,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 | ||
iter_mod = 10 | ||
mkpath(path) | ||
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## 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") | ||
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## 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) | ||
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## 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) | ||
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## Create FE functions | ||
φh = interpolate(initial_lsf(4,0.2),V_φ) | ||
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## Interpolation and weak form | ||
interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) | ||
I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ | ||
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a(u,v,φ) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ | ||
l(v,φ) = ∫(v)dΓ_N | ||
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## Optimisation functionals | ||
J(u,φ) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ | ||
dJ(q,u,φ) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; | ||
Vol(u,φ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; | ||
dVol(q,u,φ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ | ||
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state_map = AffineFEStateMap(a,l,U,V,V_φ,V_φ,φh) | ||
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# Create StateParamIntegrandWithMeasures | ||
_J = GridapTopOpt.StateParamIntegrandWithMeasure(J,state_map) | ||
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function φ_to_j(φ) | ||
u = state_map(φ) | ||
_J(u,φ) | ||
end | ||
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using Zygote | ||
_data = Zygote.gradient(φ_to_j,get_free_dof_values(φh)) | ||
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sum(_data[1]) |
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scripts/Embedded/MWEs/zygote/thermal_compliance_ALM copy_2.jl
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using Gridap, GridapTopOpt, GridapDistributed, PartitionedArrays | ||
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parts = (3,3); | ||
ranks = with_debug() do distribute | ||
distribute(LinearIndices((prod(parts),))) | ||
end | ||
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path="./results/TEST_thermal_compliance_ALM2/" | ||
## 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,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 | ||
iter_mod = 10 | ||
mkpath(path) | ||
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## FE Setup | ||
model = CartesianDiscreteModel(ranks,parts,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") | ||
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## 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) | ||
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## 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) | ||
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## Create FE functions | ||
φh = interpolate(initial_lsf(4,0.2),V_φ) | ||
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## Interpolation and weak form | ||
interp = SmoothErsatzMaterialInterpolation(η = η_coeff*maximum(el_Δ)) | ||
I,H,DH,ρ = interp.I,interp.H,interp.DH,interp.ρ | ||
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a(u,v,φ) = ∫((I ∘ φ)*κ*∇(u)⋅∇(v))dΩ | ||
l(v,φ) = ∫(v)dΓ_N | ||
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## Optimisation functionals | ||
J(u,φ) = ∫((I ∘ φ)*κ*∇(u)⋅∇(u))dΩ | ||
dJ(q,u,φ) = ∫(κ*∇(u)⋅∇(u)*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ; | ||
Vol(u,φ) = ∫(((ρ ∘ φ) - vf)/vol_D)dΩ; | ||
dVol(q,u,φ) = ∫(-1/vol_D*q*(DH ∘ φ)*(norm ∘ ∇(φ)))dΩ | ||
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state_map = AffineFEStateMap(a,l,U,V,V_φ,V_φ,φh) | ||
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# Create StateParamIntegrandWithMeasures | ||
_J = GridapTopOpt.StateParamIntegrandWithMeasure(J,state_map) | ||
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function φ_to_j(φ) | ||
u = state_map(φ) | ||
_J(u,φ) | ||
end | ||
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using Zygote | ||
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state_map(get_free_dof_values(φh)) | ||
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φ_to_j(get_free_dof_values(φh)) | ||
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_data = Zygote.gradient(φ_to_j,get_free_dof_values(φh)) | ||
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sum(_data[1]) |