jorgensd / jorgensd/MultiMeshShapeOpt_code
MultiMesh in solving eigenvalue problem of Stokes operator
- Langage dominant
- Python
- Étoiles
- 3
- Forks
- 1
- Métriques de merge des PR
- Aucune PR mergée en 30 j
Description
I am following your code to use multimesh to solve eigenvalue problem of the Stokes operator.
By selecting test function from a rawer mesh, I want to weaken the divergence-free condition.
When ``mesh_u`` and ``mesh_div_free`` are the same mesh, the eigenfunction should be completely divergence-free.
But the code below failed to apply the divergence-free condition to solution ``u``.
Could you give me any hint where the code is wrong?
```
from fenics import *
mesh_u=UnitSquareMesh(32, 32, diagonal="right")
mesh_div_free=UnitSquareMesh(16, 16, diagonal="right")
mesh_R=UnitSquareMesh(1, 1, diagonal="right")
multimesh = MultiMesh()
multimesh.add(mesh_u)
multimesh.add(mesh_div_free)
multimesh.add(mesh_R)
multimesh.build()
degree=3
CG = VectorElement("CG", triangle, degree,2)
DG = FiniteElement("DG", triangle, degree-1)
Real = FiniteElement("Real", triangle, 0)
MixedV = MultiMeshFunctionSpace(multimesh, MixedElement([CG, DG, Real]))
V = MultiMeshSubSpace(MixedV, 0)
(u, p, alpha) = TrialFunctions(MixedV)
(v, q, beta) = TestFunctions(MixedV)
a = inner(grad(u), grad(v))*dx + div(v)*p*dx + q*div(u)*dx + alpha*q*dx + beta*p*dx
b = inner(u,v)*dx
f = Constant((0.0, 0.0))
L = inner(f,v)*dx
mvc = MeshValueCollection("size_t", mesh_u, 1)
mf = cpp.mesh.MeshFunctionSizet(mesh_u, mvc)
noslip = Constant((0.0, 0.0))
marker=100
bc0=MultiMeshDirichletBC(V, noslip, mf, marker, 0)
A = assemble_multimesh(a)
B = assemble_multimesh(b)
bc0.apply(A)
bc0.zero(B)
# downcast to PETSc matrices
MatA = as_backend_type(A)
MatB = as_backend_type(B)
import scipy.io as myio
import scipy.sparse as sp
row_, col_, val_ = MatA.mat().getValuesCSR()
mat_A = sp.csr_matrix((val_,col_,row_))
row_,col_,val_ = MatB.mat().getValuesCSR()
mat_B = sp.csr_matrix((val_,col_,row_))
#Another approach to remove boundary value DOF
bd_int = inner(u,v)*ds
bd_int = assemble_multimesh(bd_int)
Mat_bd_int = as_backend_type(bd_int)
row_,col_,val_ = Mat_bd_int.mat().getValuesCSR()
Mat_bd_int = sp.csr_matrix((val_,col_,row_))
myio.savemat("./matrix/matrix.mat",{'A':mat_A,'B':mat_B,'BD_Int':Mat_bd_int})
```
(I exported the matrix to mat file and then solve it in Octave or MATLAB.)
Guide de contribution
Aucun guide de contribution indexé pour ce dépôt
Évaluation
Cette issue n'a pas encore été évaluée.