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‎demo/thermomechanical_dlrbnicsx/dlrbnicsx_thermomechanical.py

Lines changed: 10 additions & 223 deletions
Original file line numberDiff line numberDiff line change
@@ -8,6 +8,7 @@
88
import rbnicsx.online
99

1010
from dlrbnicsx_thermomechanical_geometric_deformation import MeshDeformationWrapperClass
11+
from dlrbnicsx_thermal import ThermalProblemOnDeformedDomain
1112

1213
from mpi4py import MPI
1314
from petsc4py import PETSc
@@ -27,171 +28,6 @@
2728
from dlrbnicsx.train_validate_test.train_validate_test import \
2829
train_nn, validate_nn, online_nn, error_analysis
2930

30-
class ThermalProblemOnDeformedDomain(abc.ABC):
31-
def __init__(self, mesh, subdomains, boundaries):
32-
self._mesh = mesh
33-
self._subdomains = subdomains
34-
self._boundaries = boundaries
35-
dx = ufl.Measure("dx", domain=mesh, subdomain_data=subdomains)
36-
ds = ufl.Measure("ds", domain=self._mesh, subdomain_data=self._boundaries)
37-
self.dx = dx
38-
self._ds_sf = ds(11) + ds(20) + ds(21) + ds(22) + ds(23)
39-
self._ds_bottom = ds(1) + ds(31)
40-
self._ds_out = ds(30)
41-
self._ds_sym = ds(5) + ds(9) + ds(12)
42-
self._ds_top = ds(18) + ds(19) + ds(27) + ds(28) + ds(29)
43-
x = ufl.SpatialCoordinate(self._mesh)
44-
self._VT = dolfinx.fem.FunctionSpace(self._mesh, ("CG", 1))
45-
uT, vT = ufl.TrialFunction(self._VT), ufl.TestFunction(self._VT)
46-
self._trial, self._test = uT, vT
47-
self._inner_product = ufl.inner(uT, vT) * x[0] * ufl.dx + \
48-
ufl.inner(ufl.grad(uT), ufl.grad(vT)) * x[0] * ufl.dx
49-
self.inner_product_action = \
50-
rbnicsx.backends.bilinear_form_action(self._inner_product,
51-
part="real")
52-
self._T_f, self._T_out, self._T_bottom = 1773., 300., 300.
53-
self._h_cf, self._h_cout, self._h_cbottom = 2000., 200., 200.
54-
self._q_source = dolfinx.fem.Function(self._VT)
55-
self._q_source.x.array[:] = 0.
56-
self._q_top = dolfinx.fem.Function(self._VT)
57-
self._q_top.x.array[:] = 0.
58-
self.uT_func = dolfinx.fem.Function(self._VT)
59-
self.mu_ref = [0.6438, 0.4313, 1., 0.5]
60-
61-
self._max_iterations = 20
62-
self.rtol = 1.e-4
63-
self.atol = 1.e-12
64-
65-
def thermal_diffusivity_1(self, sym_T):
66-
conditions = [ufl.le(sym_T, 293.), ufl.And(ufl.ge(sym_T, 293.), ufl.le(sym_T, 673.)), ufl.And(ufl.ge(sym_T, 673.), ufl.le(sym_T, 1273.)), ufl.ge(sym_T, 1273.)]
67-
interps = [8.17484662576687e-6*sym_T**2 - 0.00926193251533741*sym_T + 18.0819438190184, 8.17484662576687e-6*sym_T**2 - 0.00926193251533741*sym_T + 18.0819438190184, 1.76073619631904e-6*sym_T**2 - 0.000628539877300632*sym_T + 15.176807196319, 1.76073619631904e-6*sym_T**2 - 0.000628539877300632*sym_T + 15.176807196319]
68-
assert len(conditions) == len(interps)
69-
d_func = ufl.conditional(conditions[0], interps[0], interps[0])
70-
for i in range(1, len(conditions)):
71-
d_func = ufl.conditional(conditions[i], interps[i], d_func)
72-
return d_func
73-
74-
def thermal_diffusivity_2(self, sym_T):
75-
conditions = [ufl.le(sym_T, 293.), ufl.And(ufl.ge(sym_T, 293.), ufl.le(sym_T, 693.)), ufl.And(ufl.ge(sym_T, 673.), ufl.le(sym_T, 1273.)), ufl.ge(sym_T, 1273.)]
76-
interps = [0.000299054192229039*sym_T**2 - 0.36574217791411*sym_T + 130.838954780164, 0.000299054192229039*sym_T**2 - 0.36574217791411*sym_T + 130.838954780164, -1.10434560327197e-5*sym_T**2 + 0.0516492566462166*sym_T - 9.61326294938646, -1.10434560327197e-5*sym_T**2 + 0.0516492566462166*sym_T - 9.61326294938646]
77-
assert len(conditions) == len(interps)
78-
d_func = ufl.conditional(conditions[0], interps[0], interps[0])
79-
for i in range(1, len(conditions)):
80-
d_func = ufl.conditional(conditions[i], interps[i], d_func)
81-
return d_func
82-
83-
def thermal_diffusivity_3(self, sym_T):
84-
conditions = [ufl.le(sym_T, 293.), ufl.And(ufl.ge(sym_T, 293.), ufl.le(sym_T, 693.)), ufl.And(ufl.ge(sym_T, 673.), ufl.le(sym_T, 1273.)), ufl.ge(sym_T, 1273.)]
85-
interps = [8.17484662576687e-6*sym_T**2 - 0.00926193251533741*sym_T + 18.0819438190184, 8.17484662576687e-6*sym_T**2 - 0.00926193251533741*sym_T + 18.0819438190184, 1.76073619631904e-6*sym_T**2 - 0.000628539877300632*sym_T + 15.176807196319, 1.76073619631904e-6*sym_T**2 - 0.000628539877300632*sym_T + 15.176807196319]
86-
assert len(conditions) == len(interps)
87-
d_func = ufl.conditional(conditions[0], interps[0], interps[0])
88-
for i in range(1, len(conditions)):
89-
d_func = ufl.conditional(conditions[i], interps[i], d_func)
90-
return d_func
91-
92-
def thermal_diffusivity_4(self, sym_T):
93-
conditions = [ufl.le(sym_T, 293.), ufl.And(ufl.ge(sym_T, 293.), ufl.le(sym_T, 693.)), ufl.And(ufl.ge(sym_T, 673.), ufl.le(sym_T, 1273.)), ufl.ge(sym_T, 1273.)]
94-
interps = [8.17484662576687e-6*sym_T**2 - 0.00926193251533741*sym_T + 18.0819438190184, 8.17484662576687e-6*sym_T**2 - 0.00926193251533741*sym_T + 18.0819438190184, 1.76073619631904e-6*sym_T**2 - 0.000628539877300632*sym_T + 15.176807196319, 1.76073619631904e-6*sym_T**2 - 0.000628539877300632*sym_T + 15.176807196319]
95-
assert len(conditions) == len(interps)
96-
d_func = ufl.conditional(conditions[0], interps[0], interps[0])
97-
for i in range(1, len(conditions)):
98-
d_func = ufl.conditional(conditions[i], interps[i], d_func)
99-
return d_func
100-
101-
def thermal_diffusivity_5(self, sym_T):
102-
conditions = [ufl.le(sym_T, 293.), ufl.And(ufl.ge(sym_T, 293.), ufl.le(sym_T, 693.)), ufl.And(ufl.ge(sym_T, 673.), ufl.le(sym_T, 1273.)), ufl.ge(sym_T, 1273.)]
103-
interps = [3.08018064076346e-5*sym_T**2 - 0.0376497392638036*sym_T + 31.7270693260054, 3.08018064076346e-5*sym_T**2 - 0.0376497392638036*sym_T + 31.7270693260054, -2.79311520109062e-6*sym_T**2 + 0.00756902522154049*sym_T + 16.5109550766871, -2.79311520109062e-6*sym_T**2 + 0.00756902522154049*sym_T + 16.5109550766871]
104-
assert len(conditions) == len(interps)
105-
d_func = ufl.conditional(conditions[0], interps[0], interps[0])
106-
for i in range(1, len(conditions)):
107-
d_func = ufl.conditional(conditions[i], interps[i], d_func)
108-
return d_func
109-
110-
def thermal_diffusivity_6(self, sym_T):
111-
conditions = [ufl.le(sym_T, 293.), ufl.And(ufl.ge(sym_T, 293.), ufl.le(sym_T, 693.)), ufl.And(ufl.ge(sym_T, 673.), ufl.le(sym_T, 1273.)), ufl.ge(sym_T, 1273.)]
112-
interps = [8.17484662576687e-6*sym_T**2 - 0.00926193251533741*sym_T + 18.0819438190184, 8.17484662576687e-6*sym_T**2 - 0.00926193251533741*sym_T + 18.0819438190184, 1.76073619631904e-6*sym_T**2 - 0.000628539877300632*sym_T + 15.176807196319, 1.76073619631904e-6*sym_T**2 - 0.000628539877300632*sym_T + 15.176807196319]
113-
assert len(conditions) == len(interps)
114-
d_func = ufl.conditional(conditions[0], interps[0], interps[0])
115-
for i in range(1, len(conditions)):
116-
d_func = ufl.conditional(conditions[i], interps[i], d_func)
117-
return d_func
118-
119-
def thermal_diffusivity_7(self, sym_T):
120-
conditions = [ufl.le(sym_T, 293.), ufl.And(ufl.ge(sym_T, 293.), ufl.le(sym_T, 693.)), ufl.And(ufl.ge(sym_T, 673.), ufl.le(sym_T, 1273.)), ufl.ge(sym_T, 1273.)]
121-
interps = [0.000299054192229039*sym_T**2 - 0.36574217791411*sym_T + 130.838954780164, 0.000299054192229039*sym_T**2 - 0.36574217791411*sym_T + 130.838954780164, -1.10434560327197e-5*sym_T**2 + 0.0516492566462166*sym_T - 9.61326294938646, -1.10434560327197e-5*sym_T**2 + 0.0516492566462166*sym_T - 9.61326294938646]
122-
assert len(conditions) == len(interps)
123-
d_func = ufl.conditional(conditions[0], interps[0], interps[0])
124-
for i in range(1, len(conditions)):
125-
d_func = ufl.conditional(conditions[i], interps[i], d_func)
126-
return d_func
127-
128-
@property
129-
def lhs_form(self):
130-
uT_func, vT = self.uT_func, self._test
131-
x = ufl.SpatialCoordinate(self._mesh)
132-
dx = self.dx
133-
a_T = \
134-
ufl.inner(self.thermal_diffusivity_1(uT_func) * ufl.grad(uT_func), ufl.grad(vT)) * x[0] * dx(1) + \
135-
ufl.inner(self.thermal_diffusivity_2(uT_func) * ufl.grad(uT_func), ufl.grad(vT)) * x[0] * dx(2) + \
136-
ufl.inner(5.3 * ufl.grad(uT_func), ufl.grad(vT)) * x[0] * dx(3) + \
137-
ufl.inner(4.75 * ufl.grad(uT_func), ufl.grad(vT)) * x[0] * dx(4) + \
138-
ufl.inner(self.thermal_diffusivity_5(uT_func) * ufl.grad(uT_func), ufl.grad(vT)) * x[0] * dx(5) + \
139-
ufl.inner(45.6 * ufl.grad(uT_func), ufl.grad(vT)) * x[0] * dx(6) + \
140-
ufl.inner(self.thermal_diffusivity_7(uT_func) * ufl.grad(uT_func), ufl.grad(vT)) * x[0] * dx(7) + \
141-
ufl.inner(self._h_cf * uT_func, vT) * x[0] * self._ds_sf + \
142-
ufl.inner(self._h_cout * uT_func, vT) * x[0] * self._ds_out + \
143-
ufl.inner(self._h_cbottom * uT_func, vT) * x[0] * self._ds_bottom
144-
return a_T
145-
146-
@property
147-
def rhs_form(self):
148-
vT = self._test
149-
x = ufl.SpatialCoordinate(self._mesh)
150-
dx = self.dx
151-
l_T = \
152-
ufl.inner(self._q_source, vT) * x[0] * dx + \
153-
self._h_cf * vT * self._T_f * x[0] * self._ds_sf + \
154-
self._h_cout * vT * self._T_out * x[0] * self._ds_out + \
155-
self._h_cbottom * vT * self._T_bottom * x[0] * self._ds_bottom - \
156-
ufl.inner(self._q_top, vT) * x[0] * self._ds_top
157-
return l_T
158-
159-
@property
160-
def set_problem(self):
161-
problemNonlinear = \
162-
NonlinearProblem(self.lhs_form - self.rhs_form,
163-
self.uT_func, bcs=[])
164-
return problemNonlinear
165-
166-
def solve(self, mu):
167-
vT = self._test
168-
self.mu = mu
169-
self.uT_func.x.array[:] = 350.
170-
self.uT_func.x.scatter_forward()
171-
problemNonlinear = self.set_problem
172-
solution = dolfinx.fem.Function(self._VT)
173-
with MeshDeformationWrapperClass(self._mesh, self._boundaries,
174-
self.mu_ref, self.mu):
175-
solver = NewtonSolver(self._mesh.comm, problemNonlinear)
176-
solver.convergence_criterion = "incremental"
177-
178-
solver.rtol = 1e-10
179-
solver.report = True
180-
ksp = solver.krylov_solver
181-
ksp.setFromOptions()
182-
# dolfinx.log.set_log_level(dolfinx.log.LogLevel.INFO)
183-
184-
n, converged = solver.solve(self.uT_func)
185-
# print(f"Computed solution array: {uT_func.x.array}")
186-
assert (converged)
187-
print(f"Number of interations: {n:d}")
188-
189-
solution.x.array[:] = self.uT_func.x.array.copy()
190-
solution.x.scatter_forward()
191-
x = ufl.SpatialCoordinate(self._mesh)
192-
print(f"Temperature field norm: {self._mesh.comm.allreduce(dolfinx.fem.assemble_scalar(dolfinx.fem.form(ufl.inner(solution, solution) * x[0] * ufl.dx + ufl.inner(ufl.grad(solution), ufl.grad(solution)) * x[0] * ufl.dx)))}")
193-
return solution
194-
19531
class MechanicalProblemOnDeformedDomain(abc.ABC):
19632
def __init__(self, mesh, subdomains, boundaries, thermalproblem):
19733
self._mesh = mesh
@@ -404,57 +240,6 @@ def solve(self, mu):
404240
print(f"Displacement field norm: {self._mesh.comm.allreduce(dolfinx.fem.assemble_scalar(dolfinx.fem.form(ufl.inner(uM_func, uM_func) * x[0] * ufl.dx + ufl.inner(self.epsilon(uM_func), self.epsilon(uM_func)) * x[0] * ufl.dx)))}")
405241
return uM_func
406242

407-
class ThermalPODANNReducedProblem(abc.ABC):
408-
def __init__(self, thermal_problem) -> None:
409-
self._basis_functions = rbnicsx.backends.FunctionsList(thermal_problem._VT)
410-
uT, vT = ufl.TrialFunction(thermal_problem._VT), ufl.TestFunction(thermal_problem._VT)
411-
x = ufl.SpatialCoordinate(thermal_problem._mesh)
412-
self._inner_product = ufl.inner(uT, vT) * x[0] * ufl.dx + \
413-
ufl.inner(ufl.grad(uT), ufl.grad(vT)) * x[0] * ufl.dx
414-
self._inner_product_action = \
415-
rbnicsx.backends.bilinear_form_action(self._inner_product,
416-
part="real")
417-
self.input_scaling_range = [-1., 1.]
418-
self.output_scaling_range = [-1., 1.]
419-
self.input_range = \
420-
np.array([[0.55, 0.35, 0.8, 0.4], [0.75, 0.55, 1.2, 0.6]])
421-
self.output_range = [-6., 3.]
422-
self.regularisation = "EarlyStopping"
423-
424-
def reconstruct_solution(self, reduced_solution):
425-
"""Reconstructed reduced solution on the high fidelity space."""
426-
return self._basis_functions[:reduced_solution.size] * \
427-
reduced_solution
428-
429-
def compute_norm(self, function):
430-
"""Compute the norm of a function inner product
431-
on the reference domain."""
432-
return np.sqrt(self._inner_product_action(function)(function))
433-
434-
def project_snapshot(self, solution, N):
435-
return self._project_snapshot(solution, N)
436-
437-
def _project_snapshot(self, solution, N):
438-
projected_snapshot = rbnicsx.online.create_vector(N)
439-
A = rbnicsx.backends.\
440-
project_matrix(self._inner_product_action,
441-
self._basis_functions[:N])
442-
F = rbnicsx.backends.\
443-
project_vector(self._inner_product_action(solution),
444-
self._basis_functions[:N])
445-
ksp = PETSc.KSP()
446-
ksp.create(projected_snapshot.comm)
447-
ksp.setOperators(A)
448-
ksp.setType("preonly")
449-
ksp.getPC().setType("lu")
450-
ksp.setFromOptions()
451-
ksp.solve(F, projected_snapshot)
452-
return projected_snapshot
453-
454-
def norm_error(self, u, v):
455-
return self.compute_norm(u-v)/self.compute_norm(u)
456-
457-
458243
class MechanicalPODANNReducedProblem(abc.ABC):
459244
def __init__(self, mechanical_problem) -> None:
460245
self._basis_functions = rbnicsx.backends.FunctionsList(mechanical_problem._VM)
@@ -525,6 +310,7 @@ def norm_error(self, u, v):
525310
thermal_problem_parametric = \
526311
ThermalProblemOnDeformedDomain(mesh, cell_tags, facet_tags)
527312

313+
'''
528314
# solution_mu = thermal_problem_parametric.solve(mu_ref)
529315
# print(f"Solution norm at mu:{mu_ref}: {thermal_problem_parametric.inner_product_action(solution_mu)(solution_mu)}")
530316
@@ -540,7 +326,7 @@ def norm_error(self, u, v):
540326
with dolfinx.io.XDMFFile(mesh.comm, computed_file, "w") as solution_file:
541327
solution_file.write_mesh(mesh)
542328
solution_file.write_function(uT_func_plot)
543-
329+
'''
544330
# Thermal POD Starts ###
545331

546332
def generate_training_set(samples=pod_samples):
@@ -554,7 +340,7 @@ def generate_training_set(samples=pod_samples):
554340
training_set_3)))
555341
return training_set
556342

557-
343+
'''
558344
thermal_training_set = rbnicsx.io.on_rank_zero(mesh.comm, generate_training_set)
559345
560346
Nmax = 30
@@ -614,7 +400,7 @@ def generate_training_set(samples=pod_samples):
614400
plt.savefig("thermal_eigenvalues.png")
615401
616402
print(f"Eigenvalues (Thermal): {thermal_positive_eigenvalues}")
617-
403+
'''
618404
# Thermal POD Ends ###
619405

620406
# 5. ANN implementation
@@ -648,7 +434,7 @@ def generate_ann_output_set(problem, reduced_problem,
648434
len(reduced_problem._basis_functions)).array.astype("f")
649435
return output_set
650436

651-
437+
'''
652438
# Training dataset
653439
thermal_ann_input_set = generate_ann_input_set(samples=ann_samples)
654440
# np.random.shuffle(thermal_ann_input_set)
@@ -753,7 +539,7 @@ def generate_ann_output_set(problem, reduced_problem,
753539
print(f"Error: {thermal_error_numpy[i]}")
754540
755541
# ### Thermal ANN ends
756-
542+
'''
757543
mechanical_problem_parametric = \
758544
MechanicalProblemOnDeformedDomain(mesh, cell_tags, facet_tags,
759545
thermal_problem_parametric)
@@ -943,6 +729,7 @@ def generate_ann_output_set(problem, reduced_problem,
943729

944730
# ### Online phase ###
945731
online_mu = np.array([0.45, 0.56, 0.9, 0.7])
732+
'''
946733
thermal_fem_solution = thermal_problem_parametric.solve(online_mu)
947734
thermal_rb_solution = \
948735
thermal_reduced_problem.reconstruct_solution(
@@ -998,7 +785,7 @@ def generate_ann_output_set(problem, reduced_problem,
998785
999786
print(thermal_reduced_problem.norm_error(thermal_fem_solution, thermal_rb_solution))
1000787
print(thermal_reduced_problem.compute_norm(thermal_error_function))
1001-
788+
'''
1002789
mechanical_fem_solution = mechanical_problem_parametric.solve(online_mu)
1003790
mechanical_rb_solution = \
1004791
mechanical_reduced_problem.reconstruct_solution(
@@ -1051,5 +838,5 @@ def generate_ann_output_set(problem, reduced_problem,
1051838
print(mechanical_reduced_problem.norm_error(mechanical_fem_solution, mechanical_rb_solution))
1052839
print(mechanical_reduced_problem.compute_norm(mechanical_error_function))
1053840

1054-
print(f"Training time (Thermal): {thermal_elapsed_time}")
841+
# print(f"Training time (Thermal): {thermal_elapsed_time}")
1055842
print(f"Training time (Mechanical): {mechanical_elapsed_time}")

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