def get_poisson_steps(pts, cells, tol):
# Still can't initialize a mesh from points, cells
filename = "mesh.xdmf"
if cells.shape[1] == 3:
meshio.write_points_cells(filename, pts, {"triangle": cells})
else:
assert cells.shape[1] == 4
meshio.write_points_cells(filename, pts, {"tetra": cells})
mesh = Mesh()
with XDMFFile(filename) as f:
f.read(mesh)
os.remove(filename)
os.remove("mesh.h5")
# build Laplace matrix with Dirichlet boundary using dolfin
V = FunctionSpace(mesh, "Lagrange", 1)
u = TrialFunction(V)
v = TestFunction(V)
a = inner(grad(u), grad(v)) * dx
u0 = Constant(0.0)
bc = DirichletBC(V, u0, "on_boundary")
f = Constant(1.0)
L = f * v * dx
A = assemble(a)
b = assemble(L)
bc.apply(A, b)
# solve(A, x, b, "cg")
solver = KrylovSolver("cg", "none")
solver.parameters["absolute_tolerance"] = 0.0
solver.parameters["relative_tolerance"] = tol
x = Function(V)
x_vec = x.vector()
num_steps = solver.solve(A, x_vec, b)
# # convert to scipy matrix
# A = as_backend_type(A).mat()
# ai, aj, av = A.getValuesCSR()
# A = scipy.sparse.csr_matrix(
# (av, aj, ai), shape=(A.getLocalSize()[0], A.getSize()[1])
# )
# # ev = eigvals(A.todense())
# ev_max = scipy.sparse.linalg.eigs(A, k=1, which="LM")[0][0]
# assert numpy.abs(ev_max.imag) < 1.0e-15
# ev_max = ev_max.real
# ev_min = scipy.sparse.linalg.eigs(A, k=1, which="SM")[0][0]
# assert numpy.abs(ev_min.imag) < 1.0e-15
# ev_min = ev_min.real
# cond = ev_max / ev_min
# solve poisson system, count num steps
# b = numpy.ones(A.shape[0])
# out = pykry.gmres(A, b)
# num_steps = len(out.resnorms)
return num_steps
def cyclic3D(u):
""" Symmetrize with respect to (xyz) cycle. """
try:
nrm = np.linalg.norm(u.vector())
V = u.function_space()
assert V.mesh().topology().dim() == 3
mesh1 = Mesh(V.mesh())
mesh1.coordinates()[:, :] = mesh1.coordinates()[:, [1, 2, 0]]
W1 = FunctionSpace(mesh1, 'CG', 1)
# testing if symmetric
bc = DirichletBC(V, 1, DomainBoundary())
test = Function(V)
bc.apply(test.vector())
test = interpolate(Function(W1, test.vector()), V)
assert max(test.vector()) - min(test.vector()) < 1.1
v1 = interpolate(Function(W1, u.vector()), V)
mesh2 = Mesh(mesh1)
mesh2.coordinates()[:, :] = mesh2.coordinates()[:, [1, 2, 0]]
W2 = FunctionSpace(mesh2, 'CG', 1)
v2 = interpolate(Function(W2, u.vector()), V)
pr = project(u+v1+v2)
assert np.linalg.norm(pr.vector())/nrm > 0.01
return pr
except:
print "Cyclic symmetrization failed!"
return u
class StreamFunction(Field):
def before_first_compute(self, get):
u = get("Velocity")
assert len(u) == 2, "Can only compute stream function for 2D problems"
V = u.function_space()
spaces = SpacePool(V.mesh())
degree = V.ufl_element().degree()
V = spaces.get_space(degree, 0)
psi = TrialFunction(V)
self.q = TestFunction(V)
a = dot(grad(psi), grad(self.q)) * dx()
self.bc = DirichletBC(V, Constant(0), DomainBoundary())
self.A = assemble(a)
self.L = Vector()
self.bc.apply(self.A)
self.solver = KrylovSolver(self.A, "cg")
self.psi = Function(V)
def compute(self, get):
u = get("Velocity")
assemble(dot(u[1].dx(0) - u[0].dx(1), self.q) * dx(), tensor=self.L)
self.bc.apply(self.L)
self.solver.solve(self.psi.vector(), self.L)
#solve(self.A, self.psi.vector(), self.L)
return self.psi
def assert_solves(
mesh: Mesh,
diffusion: Coefficient,
convection: Optional[Coefficient],
reaction: Optional[Coefficient],
source: Coefficient,
exact: Coefficient,
l2_tol: Optional[float] = 1.0e-8,
h1_tol: Optional[float] = 1.0e-6,
):
eafe_matrix = eafe_assemble(mesh, diffusion, convection, reaction)
pw_linears = FunctionSpace(mesh, "Lagrange", 1)
test_function = TestFunction(pw_linears)
rhs_vector = assemble(source * test_function * dx)
bc = DirichletBC(pw_linears, exact, lambda _, on_bndry: on_bndry)
bc.apply(eafe_matrix, rhs_vector)
solution = Function(pw_linears)
solver = LUSolver(eafe_matrix, "default")
solver.parameters["symmetric"] = False
solver.solve(solution.vector(), rhs_vector)
l2_err: float = errornorm(exact, solution, "l2", 3)
assert l2_err <= l2_tol, f"L2 error too large: {l2_err} > {l2_tol}"
h1_err: float = errornorm(exact, solution, "H1", 3)
assert h1_err <= h1_tol, f"H1 error too large: {h1_err} > {h1_tol}"
def compute_error(problem, mesh_size):
mesh = problem.mesh_generator(mesh_size)
u = problem.solution['u']
u_sol = Expression((ccode(u['value'][0]), ccode(u['value'][1])),
degree=u['degree'])
p = problem.solution['p']
p_sol = Expression(ccode(p['value']), degree=p['degree'])
f = Expression(
(ccode(problem.f['value'][0]), ccode(problem.f['value'][1])),
degree=problem.f['degree'])
W = VectorElement('Lagrange', mesh.ufl_cell(), 2)
P = FiniteElement('Lagrange', mesh.ufl_cell(), 1)
WP = FunctionSpace(mesh, W * P)
# Get Dirichlet boundary conditions
u_bcs = DirichletBC(WP.sub(0), u_sol, 'on_boundary')
p_bcs = DirichletBC(WP.sub(1), p_sol, 'on_boundary')
u_approx, p_approx = flow.stokes.solve(WP,
bcs=[u_bcs, p_bcs],
mu=problem.mu,
f=f,
verbose=True,
tol=1.0e-12)
# compute errors
u_error = errornorm(u_sol, u_approx)
p_error = errornorm(p_sol, p_approx)
return mesh.hmax(), u_error, p_error
def transfer(self, V):
fenics_bcs = list()
for bc in self._bcs:
if bc.component is not None:
if not bc.pointwise:
fenics_bcs.append(
DirichletBC(V.sub(bc.component), bc.expression,
bc.domain))
else:
fenics_bcs.append(
DirichletBC(V.sub(bc.component),
bc.expression,
bc.domain,
method='pointwise'))
else:
if not bc.pointwise:
fenics_bcs.append(DirichletBC(V, bc.expression, bc.domain))
else:
fenics_bcs.append(
DirichletBC(V,
bc.expression,
bc.domain,
method='pointwise'))
return fenics_bcs
def homogenize(bcs):
b = []
for bc in bcs:
b0 = DirichletBC(bc)
b0.homogenize()
b.append(b0)
return b
def __init__(self, coarse_mesh, nref, p_coarse, p_fine):
super(LaplaceEigenvalueProblem, self).__init__(coarse_mesh, nref, p_coarse, p_fine)
print0("Assembling fine-mesh problem")
self.dirichlet_bdry = lambda x,on_boundary: on_boundary
bc = DirichletBC(self.V_fine, 0.0, self.dirichlet_bdry)
u = TrialFunction(self.V_fine)
v = TestFunction(self.V_fine)
a = inner(grad(u), grad(v))*dx
m = u*v*dx
# Assemble the stiffness matrix and the mass matrix.
b = v*dx # just need this to feed an argument to assemble_system
assemble_system(a, b, bc, A_tensor=self.A_fine)
assemble_system(m, b, bc, A_tensor=self.B_fine)
# set the diagonal elements of M corresponding to boundary nodes to zero to
# remove spurious eigenvalues.
bc.zero(self.B_fine)
print0("Assembling coarse-mesh problem")
self.bc_coarse = DirichletBC(self.V_coarse, 0.0, self.dirichlet_bdry)
u = TrialFunction(self.V_coarse)
v = TestFunction(self.V_coarse)
a = inner(grad(u), grad(v))*dx
m = u*v*dx
# Assemble the stiffness matrix and the mass matrix, without Dirichlet BCs. Dirichlet DOFs will be removed later.
assemble(a, tensor=self.A_coarse)
assemble(m, tensor=self.B_coarse)
def stokes(self):
P2 = VectorElement("CG", self.mesh.ufl_cell(), 2)
P1 = FiniteElement("CG", self.mesh.ufl_cell(), 1)
TH = P2 * P1
VQ = FunctionSpace(self.mesh, TH)
mf = self.mf
self.no_slip = Constant((0., 0))
self.topflow = Expression(("-x[0] * (x[0] - 1.0) * 6.0 * m", "0.0"),
m=self.U_m,
degree=2)
bc0 = DirichletBC(VQ.sub(0), self.topflow, mf, self.bc_dict["top"])
bc1 = DirichletBC(VQ.sub(0), self.no_slip, mf, self.bc_dict["left"])
bc2 = DirichletBC(VQ.sub(0), self.no_slip, mf, self.bc_dict["bottom"])
bc3 = DirichletBC(VQ.sub(0), self.no_slip, mf, self.bc_dict["right"])
# bc4 = DirichletBC(VQ.sub(1), Constant(0), mf, self.bc_dict["top"])
bcs = [bc0, bc1, bc2, bc3]
vup = TestFunction(VQ)
up = TrialFunction(VQ)
# the solution will be in here:
up_ = Function(VQ)
u, p = split(up) # Trial
vu, vp = split(vup) # Test
u_, p_ = split(up_) # Function holding the solution
F = self.mu*inner(grad(vu), grad(u))*dx - inner(div(vu), p)*dx \
- inner(vp, div(u))*dx + dot(self.g*self.rho, vu)*dx
solve(lhs(F) == rhs(F), up_, bcs=bcs)
self.u_.assign(project(u_, self.V))
self.p_.assign(project(p_, self.Q))
return
def homogenize(bcs):
b = []
for bc in bcs:
b0 = DirichletBC(bc)
b0.homogenize()
b.append(b0)
return b
def __init__(self, U_m, mesh):
"""Function spaces and BCs"""
V = VectorFunctionSpace(mesh, 'P', 2)
Q = FunctionSpace(mesh, 'P', 1)
self.mesh = mesh
self.vu, self.vp = TestFunction(V), TestFunction(Q) # for integration
self.u_, self.p_ = Function(V), Function(Q) # for the solution
self.u_1, self.p_1 = Function(V), Function(Q) # for the prev. solution
self.u_k, self.p_k = Function(V), Function(Q) # for the prev. solution
self.u, self.p = TrialFunction(V), TrialFunction(Q) # unknown!
U0_str = "4.*U_m*x[1]*(.41-x[1])/(.41*.41)"
x = [0,
.41 / 2] # evaluate the Expression at the center of the channel
self.U_mean = np.mean(2 / 3 * eval(U0_str))
U0 = Expression((U0_str, "0"), U_m=U_m, degree=2)
bc0 = DirichletBC(V, Constant((0, 0)), cylinderwall)
bc1 = DirichletBC(V, Constant((0, 0)), topandbottom)
bc2 = DirichletBC(V, U0, inlet)
bc3 = DirichletBC(Q, Constant(0), outlet)
self.bcu = [bc0, bc1, bc2]
self.bcp = [bc3]
# ds is needed to compute drag and lift.
ASD1 = AutoSubDomain(topandbottom)
ASD2 = AutoSubDomain(cylinderwall)
mf = MeshFunction("size_t", mesh, 1)
mf.set_all(0)
ASD1.mark(mf, 1)
ASD2.mark(mf, 2)
self.ds_ = ds(subdomain_data=mf, domain=mesh)
return
def cyclic3D(u):
""" Symmetrize with respect to (xyz) cycle. """
try:
nrm = np.linalg.norm(u.vector())
V = u.function_space()
assert V.mesh().topology().dim() == 3
mesh1 = Mesh(V.mesh())
mesh1.coordinates()[:, :] = mesh1.coordinates()[:, [1, 2, 0]]
W1 = FunctionSpace(mesh1, 'CG', 1)
# testing if symmetric
bc = DirichletBC(V, 1, DomainBoundary())
test = Function(V)
bc.apply(test.vector())
test = interpolate(Function(W1, test.vector()), V)
assert max(test.vector()) - min(test.vector()) < 1.1
v1 = interpolate(Function(W1, u.vector()), V)
mesh2 = Mesh(mesh1)
mesh2.coordinates()[:, :] = mesh2.coordinates()[:, [1, 2, 0]]
W2 = FunctionSpace(mesh2, 'CG', 1)
v2 = interpolate(Function(W2, u.vector()), V)
pr = project(u + v1 + v2)
assert np.linalg.norm(pr.vector()) / nrm > 0.01
return pr
except:
print "Cyclic symmetrization failed!"
return u
class StreamFunction(Field):
def before_first_compute(self, get):
u = get("Velocity")
assert len(u) == 2, "Can only compute stream function for 2D problems"
V = u.function_space()
spaces = SpacePool(V.mesh())
degree = V.ufl_element().degree()
V = spaces.get_space(degree, 0)
psi = TrialFunction(V)
self.q = TestFunction(V)
a = dot(grad(psi), grad(self.q))*dx()
self.bc = DirichletBC(V, Constant(0), DomainBoundary())
self.A = assemble(a)
self.L = Vector()
self.bc.apply(self.A)
self.solver = KrylovSolver(self.A, "cg")
self.psi = Function(V)
def compute(self, get):
u = get("Velocity")
assemble(dot(u[1].dx(0)-u[0].dx(1), self.q)*dx(), tensor=self.L)
self.bc.apply(self.L)
self.solver.solve(self.psi.vector(), self.L)
#solve(self.A, self.psi.vector(), self.L)
return self.psi
class Heat(object):
'''
u' = \\Delta u + f
'''
def __init__(self, V):
self.sol = Expression(sympy.printing.ccode(solution),
degree=MAX_DEGREE,
t=0.0,
cell=triangle)
self.V = V
u = TrialFunction(V)
v = TestFunction(V)
self.M = assemble(u * v * dx)
n = FacetNormal(self.V.mesh())
self.A = assemble(-inner(kappa * grad(u), grad(v /
(rho * cp))) * dx +
inner(kappa * grad(u), n) * v / (rho * cp) * ds)
self.bcs = DirichletBC(self.V, self.sol, 'on_boundary')
return
def eval_alpha_M_beta_F(self, alpha, beta, u, t):
# Evaluate alpha * M * u + beta * F(u, t).
uvec = u.vector()
v = TestFunction(self.V)
f.t = t
b = assemble(f * v / (rho * cp) * dx)
out = Function(self.V)
out.vector()[:] = \
alpha * (self.M * uvec) + beta * (self.A * uvec + b)
return out
def solve_alpha_M_beta_F(self, alpha, beta, b, t):
# Solve alpha * M * u + beta * F(u, t) = b for u.
A = alpha * self.M + beta * self.A
f.t = t
v = TestFunction(self.V)
b2 = f / (rho * cp)
rhs = assemble((b - beta * b2) * v * dx)
self.bcs.apply(A, rhs)
solver = \
KrylovSolver('gmres', 'ilu') if alpha < 0.0 or beta > 0.0 \
else KrylovSolver('cg', 'amg')
solver.parameters['relative_tolerance'] = 1.0e-13
solver.parameters['absolute_tolerance'] = 0.0
solver.parameters['maximum_iterations'] = 100
solver.parameters['monitor_convergence'] = False
solver.set_operator(A)
u = Function(self.V)
solver.solve(u.vector(), rhs)
return u
def __init__(self):
self.mesh = UnitSquareMesh(40, 40, "left/right")
self.V = FunctionSpace(self.mesh, "Lagrange", 1)
self.bc = DirichletBC(self.V, 0.0, "on_boundary")
u = TrialFunction(self.V)
v = TestFunction(self.V)
self.a = assemble(dot(grad(u), grad(v)) * dx)
self.m = assemble(u * v * dx)
def __init__(self, V):
self.V = V
u = TrialFunction(V)
v = TestFunction(V)
self.M = assemble(u * v * dx)
self.A = assemble(-dot(grad(u), grad(v)) * dx)
self.b = assemble(1.0 * v * dx)
self.bcs = DirichletBC(self.V, 0.0, 'on_boundary')
return
def ball_in_tube():
mesh = Mesh("../meshes/2d/ball-in-tube-cylindrical-coarse4.xml")
V0 = FunctionSpace(mesh, "CG", 2)
V1 = FunctionSpace(mesh, "B", 3)
V = V0 + V1
W = MixedFunctionSpace([V, V])
P = FunctionSpace(mesh, "CG", 1)
# Define mesh and boundaries.
class LeftBoundary(SubDomain):
def inside(self, x, on_boundary):
return on_boundary and x[0] < GMSH_EPS
left_boundary = LeftBoundary()
class RightBoundary(SubDomain):
def inside(self, x, on_boundary):
return on_boundary and x[0] > 1.0 - GMSH_EPS
right_boundary = RightBoundary()
class LowerBoundary(SubDomain):
def inside(self, x, on_boundary):
return on_boundary and x[1] < GMSH_EPS
lower_boundary = LowerBoundary()
class UpperBoundary(SubDomain):
def inside(self, x, on_boundary):
return on_boundary and x[1] > 5.0 - GMSH_EPS
class CoilBoundary(SubDomain):
def inside(self, x, on_boundary):
# One has to pay a little bit of attention when defining the
# coil boundary; it's easy to miss the edges closest to x[0]=0.
return (
on_boundary
and x[1] > 1.0 - GMSH_EPS
and x[1] < 2.0 + GMSH_EPS
and x[0] < 1.0 - GMSH_EPS
)
coil_boundary = CoilBoundary()
u_bcs = [
DirichletBC(W, (0.0, 0.0), right_boundary),
DirichletBC(W.sub(0), 0.0, left_boundary),
DirichletBC(W, (0.0, 0.0), lower_boundary),
DirichletBC(W, (0.0, 0.0), coil_boundary),
]
p_bcs = []
# p_bcs = [DirichletBC(Q, 0.0, upper_boundary)]
return mesh, W, P, u_bcs, p_bcs
def pinBC(membrane):
bc = []
if membrane.nsd==2:
bc.append(DirichletBC(membrane.V, Constant((0,0)), bd_all_1D))
elif membrane.nsd==3:
# This constrains the thickness at the support but is not plane strain
bc.append(DirichletBC(membrane.V.sub(1), Constant(0), bd_all))
bc.append(DirichletBC(membrane.V, Constant((0, 0, 0)), bd_x))
return bc
def get_boundary_conditions(self, use_pressure_BC, v_space, p_space):
# boundary parts: 1 walls, 2 inflow, 3 outflow
bc0 = DirichletBC(v_space, (0.0, 0.0, 0.0), self.facet_function,
1) # no-slip
inflow = DirichletBC(v_space, self.v_in, self.facet_function, 2)
bcu = [inflow, bc0]
bcp = []
if use_pressure_BC:
outflow = DirichletBC(p_space, 0.0, self.facet_function, 3)
bcp = [outflow]
return bcu, bcp
def create_dirichlet_conditions(values, boundaries, function_spaces):
"""Create Dirichlet boundary conditions for given boundary values,
boundaries and function space."""
# Check that the size matches
if len(values) != len(boundaries):
error(
"The number of Dirichlet values does not match the number of Dirichlet boundaries."
)
if len(values) != len(function_spaces):
error(
"The number of Dirichlet values does not match the number of function spaces."
)
if len(boundaries) != len(function_spaces):
error(
"The number of Dirichlet boundaries does not match the number of function spaces."
)
info("Creating %d Dirichlet boundary condition(s)." % len(values))
# Create Dirichlet conditions
bcs = []
for (i, value) in enumerate(values):
# Get current boundary
boundary = boundaries[i]
function_space = function_spaces[i]
# Case 0: boundary is a string
if isinstance(boundary, str):
boundary = CompiledSubDomain(boundary)
bc = DirichletBC(function_space, value, boundary)
# Case 1: boundary is a SubDomain
elif isinstance(boundary, SubDomain):
bc = DirichletBC(function_space, value, boundary)
# Case 2: boundary is defined by a MeshFunction
elif isinstance(boundary, tuple):
mesh_function, index = boundary
bc = DirichletBC(function_space, value, mesh_function, index)
# Unhandled case
else:
error(
"Unhandled boundary specification for boundary condition. "
"Expecting a string, a SubDomain or a (MeshFunction, int) tuple."
)
bcs.append(bc)
return bcs
def get_boundary_conditions(self, use_pressure_BC, v_space, p_space):
# boundary parts: 1 walls, 2, 4 inflow, 3, 5 outflow
# Boundary conditions
bc_wall = DirichletBC(v_space, (0.0, 0.0, 0.0), self.facet_function, 1)
bc_cyl = DirichletBC(v_space, (0.0, 0.0, 0.0), self.facet_function, 5)
inflow = DirichletBC(v_space, self.v_in, self.facet_function, 2)
bcu = [inflow, bc_cyl, bc_wall]
bcp = []
if use_pressure_BC:
outflow = DirichletBC(p_space, 0.0, self.facet_function, 3)
bcp = [outflow]
return bcu, bcp
def navier_stokes_IPCS(mesh, dt, parameter):
"""
fenics code: weak form of the problem.
"""
mu, rho, nu = parameter
V = VectorFunctionSpace(mesh, 'P', 2)
Q = FunctionSpace(mesh, 'P', 1)
bc0 = DirichletBC(V, Constant((0, 0)), cylinderwall)
bc1 = DirichletBC(V, Constant((0, 0)), topandbottom)
bc2 = DirichletBC(V, U0, inlet)
bc3 = DirichletBC(Q, Constant(1), outlet)
bcs = [bc0, bc1, bc2, bc3]
# ds is needed to compute drag and lift. Not used here.
ASD1 = AutoSubDomain(topandbottom)
ASD2 = AutoSubDomain(cylinderwall)
mf = MeshFunction("size_t", mesh, 1)
mf.set_all(0)
ASD1.mark(mf, 1)
ASD2.mark(mf, 2)
ds_ = ds(subdomain_data=mf, domain=mesh)
vu, vp = TestFunction(V), TestFunction(Q) # for integration
u_, p_ = Function(V), Function(Q) # for the solution
u_1, p_1 = Function(V), Function(Q) # for the prev. solution
u, p = TrialFunction(V), TrialFunction(Q) # unknown!
bcu = [bcs[0], bcs[1], bcs[2]]
bcp = [bcs[3]]
n = FacetNormal(mesh)
u_mid = (u + u_1) / 2.0
F1 = rho*dot((u - u_1) / dt, vu)*dx \
+ rho*dot(dot(u_1, nabla_grad(u_1)), vu)*dx \
+ inner(sigma(u_mid, p_1, mu), epsilon(vu))*dx \
+ dot(p_1*n, vu)*ds - dot(mu*nabla_grad(u_mid)*n, vu)*ds
a1 = lhs(F1)
L1 = rhs(F1)
# Define variational problem for step 2
a2 = dot(nabla_grad(p), nabla_grad(vp)) * dx
L2 = dot(nabla_grad(p_1), nabla_grad(vp)) * dx - (
rho / dt) * div(u_) * vp * dx # rho missing in FEniCS tutorial
# Define variational problem for step 3
a3 = dot(u, vu) * dx
L3 = dot(u_, vu) * dx - dt * dot(nabla_grad(p_ - p_1), vu) * dx
# Assemble matrices
A1 = assemble(a1)
A2 = assemble(a2)
A3 = assemble(a3)
# Apply boundary conditions to matrices
[bc.apply(A1) for bc in bcu]
[bc.apply(A2) for bc in bcp]
return u_, p_, u_1, p_1, L1, A1, L2, A2, L3, A3, bcu, bcp
def __init__(self, V):
self.sol = Expression(sympy.printing.ccode(theta),
degree=MAX_DEGREE,
t=0.0,
cell=triangle)
self.V = V
u = TrialFunction(V)
v = TestFunction(V)
self.M = assemble(u * v * dx)
self.A = assemble(-inner(grad(u), grad(v)) * dx)
self.bcs = DirichletBC(self.V, self.sol, 'on_boundary')
return
def rollerBC(membrane):
bc =[]
if membrane.nsd==2:
#
bc.append(DirichletBC(membrane.V.sub(1), Constant(0), bd_all_1D))
bc.append(DirichletBC(membrane.V.sub(0), Constant(0), bd_x_mid_1D))
elif membrane.nsd==3:
# This constrains the thickness at the support but is not plane strain
bc.append(DirichletBC(membrane.V.sub(1), Constant(0), bd_all))
bc.append(DirichletBC(membrane.V.sub(0), Constant(0), bd_x_mid))
bc.append(DirichletBC(membrane.V.sub(2), Constant(0), bd_x))
return bc
def define_boundary_conditions(self):
V = self.z.function_space()
bc_clamped = [
DirichletBC(V.sub(1), Constant([0., 0.]), 'on_boundary'),
DirichletBC(V.sub(2), Constant(0.), 'on_boundary')
]
bc_free = []
bc_vert = [DirichletBC(V.sub(2), Constant(0.), 'on_boundary')]
bc_horiz = [DirichletBC(V.sub(1), Constant([0., 0.]), 'on_boundary')]
bcs = [bc_clamped, bc_free, bc_vert, bc_horiz]
return bcs[self.bc_no]
class Bratu(object):
def __init__(self):
self.mesh = UnitSquareMesh(40, 40, "left/right")
self.V = FunctionSpace(self.mesh, "Lagrange", 1)
self.bc = DirichletBC(self.V, 0.0, "on_boundary")
u = TrialFunction(self.V)
v = TestFunction(self.V)
self.a = assemble(dot(grad(u), grad(v)) * dx)
self.m = assemble(u * v * dx)
def inner(self, a, b):
return a.inner(self.m * b)
def norm2_r(self, a):
return a.inner(a)
def f(self, u, lmbda):
v = TestFunction(self.V)
ufun = Function(self.V)
ufun.vector()[:] = u
out = self.a * u - lmbda * assemble(exp(ufun) * v * dx)
DirichletBC(self.V, ufun, "on_boundary").apply(out)
return out
def df_dlmbda(self, u, lmbda):
v = TestFunction(self.V)
ufun = Function(self.V)
ufun.vector()[:] = u
out = -assemble(exp(ufun) * v * dx)
self.bc.apply(out)
return out
def jacobian_solver(self, u, lmbda, rhs):
t = TrialFunction(self.V)
v = TestFunction(self.V)
# from dolfin import Constant
# a = assemble(
# dot(grad(t), grad(v)) * dx - Constant(lmbda) * exp(u) * t * v * dx
# )
ufun = Function(self.V)
ufun.vector()[:] = u
a = self.a - lmbda * assemble(exp(ufun) * t * v * dx)
self.bc.apply(a)
x = Function(self.V)
# solve(a, x.vector(), rhs, "gmres", "ilu")
solve(a, x.vector(), rhs)
return x.vector()
def symmetrize(u, d, sym):
""" Symmetrize function u. """
if len(d) == 3:
# three dimensions -> cycle XYZ
return cyclic3D(u)
elif len(d) >= 4:
# four dimensions -> rotations in 2D
return rotational(u, d[-1])
nrm = np.linalg.norm(u.vector())
V = u.function_space()
mesh = Mesh(V.mesh())
# test if domain is symmetric using function equal 0 inside, 1 on boundary
# extrapolation will force large values if not symmetric since the flipped
# domain is different
bc = DirichletBC(V, 1, DomainBoundary())
test = Function(V)
bc.apply(test.vector())
if len(d) == 2:
# two dimensions given: swap dimensions
mesh.coordinates()[:, d] = mesh.coordinates()[:, d[::-1]]
else:
# one dimension given: reflect
mesh.coordinates()[:, d[0]] *= -1
# FIXME functionspace takes a long time to construct, maybe copy?
W = FunctionSpace(mesh, 'CG', 1)
try:
# testing
test = interpolate(Function(W, test.vector()), V)
# max-min should be around 1 if domain was symmetric
# may be slightly above due to boundary approximation
assert max(test.vector()) - min(test.vector()) < 1.1
v = interpolate(Function(W, u.vector()), V)
if sym:
# symmetric
pr = project(u+v)
else:
# antisymmetric
pr = project(u-v)
# small solution norm most likely means that symmetrization gives
# trivial function
assert np.linalg.norm(pr.vector())/nrm > 0.01
return pr
except:
# symmetrization failed for some reason
print "Symmetrization " + str(d) + " failed!"
return u
def symmetrize(u, d, sym):
""" Symmetrize function u. """
if len(d) == 3:
# three dimensions -> cycle XYZ
return cyclic3D(u)
elif len(d) >= 4:
# four dimensions -> rotations in 2D
return rotational(u, d[-1])
nrm = np.linalg.norm(u.vector())
V = u.function_space()
mesh = Mesh(V.mesh())
# test if domain is symmetric using function equal 0 inside, 1 on boundary
# extrapolation will force large values if not symmetric since the flipped
# domain is different
bc = DirichletBC(V, 1, DomainBoundary())
test = Function(V)
bc.apply(test.vector())
if len(d) == 2:
# two dimensions given: swap dimensions
mesh.coordinates()[:, d] = mesh.coordinates()[:, d[::-1]]
else:
# one dimension given: reflect
mesh.coordinates()[:, d[0]] *= -1
# FIXME functionspace takes a long time to construct, maybe copy?
W = FunctionSpace(mesh, 'CG', 1)
try:
# testing
test = interpolate(Function(W, test.vector()), V)
# max-min should be around 1 if domain was symmetric
# may be slightly above due to boundary approximation
assert max(test.vector()) - min(test.vector()) < 1.1
v = interpolate(Function(W, u.vector()), V)
if sym:
# symmetric
pr = project(u + v)
else:
# antisymmetric
pr = project(u - v)
# small solution norm most likely means that symmetrization gives
# trivial function
assert np.linalg.norm(pr.vector()) / nrm > 0.01
return pr
except:
# symmetrization failed for some reason
print "Symmetrization " + str(d) + " failed!"
return u
def dbcs_to_productspace(W, bcs_list):
new_bcs = []
for k, bcs in enumerate(bcs_list):
for bc in bcs:
C = bc.function_space().component()
# pylint: disable=len-as-condition
if len(C) == 0:
new_bcs.append(DirichletBC(W.sub(k), bc.value(), bc.domain_args[0]))
else:
assert len(C) == 1, "Illegal number of subspace components."
new_bcs.append(
DirichletBC(W.sub(k).sub(int(C[0])), bc.value(), bc.domain_args[0])
)
return new_bcs
def solve(self, L, a, plate_potential):
A = assemble(a)
b = assemble(L)
# print(' assembled')
dirichlet_bc = DirichletBC(self.V, plate_potential,
(lambda x, on_boundary: on_boundary and x[2]
< self.GROUNDED_PLATE_AT))
dirichlet_bc.apply(A, b)
# print(' modified')
f = self.function()
self.solver.solve(A, f.vector(), b)
# print(' solved')
return f
def cavity():
# Define mesh and boundaries.
mesh = UnitSquareMesh(32, 32, "left/right")
V = VectorFunctionSpace(mesh, "CG", 2)
Q = FunctionSpace(mesh, "CG", 1)
class LeftBoundary(SubDomain):
def inside(self, x, on_boundary):
return on_boundary and x[0] < GMSH_EPS
left_boundary = LeftBoundary()
class RightBoundary(SubDomain):
def inside(self, x, on_boundary):
return on_boundary and x[0] > 1.0 - GMSH_EPS
right_boundary = RightBoundary()
class LowerBoundary(SubDomain):
def inside(self, x, on_boundary):
return on_boundary and x[1] < GMSH_EPS
lower_boundary = LowerBoundary()
class UpperBoundary(SubDomain):
def inside(self, x, on_boundary):
return on_boundary and x[1] > 1.0 - GMSH_EPS
upper_boundary = UpperBoundary()
# Boundary conditions for the velocity.
u_bcs = [
DirichletBC(V, (0.0, 0.0), lower_boundary),
DirichletBC(V, (0.0, 0.0), upper_boundary),
DirichletBC(V, (0.0, 0.0), right_boundary),
DirichletBC(V, (0.0, 0.0), left_boundary),
]
p_bcs = []
return (
mesh,
V,
Q,
u_bcs,
p_bcs,
[right_boundary],
[upper_boundary, left_boundary, lower_boundary],
)
def les_setup(u_, mesh, KineticEnergySGS, assemble_matrix, CG1Function,
nut_krylov_solver, bcs, **NS_namespace):
"""
Set up for solving the Kinetic Energy SGS-model.
"""
DG = FunctionSpace(mesh, "DG", 0)
CG1 = FunctionSpace(mesh, "CG", 1)
dim = mesh.geometry().dim()
delta = Function(DG)
delta.vector().zero()
delta.vector().axpy(1.0, assemble(TestFunction(DG) * dx))
delta.vector().set_local(delta.vector().array()**(1. / dim))
delta.vector().apply('insert')
Ck = KineticEnergySGS["Ck"]
ksgs = interpolate(Constant(1E-7), CG1)
bc_ksgs = DirichletBC(CG1, 0, "on_boundary")
A_mass = assemble_matrix(TrialFunction(CG1) * TestFunction(CG1) * dx)
nut_form = Ck * delta * sqrt(ksgs)
bcs_nut = derived_bcs(CG1, bcs['u0'], u_)
nut_ = CG1Function(nut_form,
mesh,
method=nut_krylov_solver,
bcs=bcs_nut,
bounded=True,
name="nut")
At = Matrix()
bt = Vector(nut_.vector())
ksgs_sol = KrylovSolver("bicgstab", "additive_schwarz")
#ksgs_sol.parameters["preconditioner"]["structure"] = "same_nonzero_pattern"
ksgs_sol.parameters["error_on_nonconvergence"] = False
ksgs_sol.parameters["monitor_convergence"] = False
ksgs_sol.parameters["report"] = False
del NS_namespace
return locals()
def f(self, u, lmbda):
v = TestFunction(self.V)
ufun = Function(self.V)
ufun.vector()[:] = u
out = self.a * u - lmbda * assemble(exp(ufun) * v * dx)
DirichletBC(self.V, ufun, "on_boundary").apply(out)
return out
def test_cmscr1d_weak_solution_zero_Dirichlet(self):
print("Running test 'test_cmscr1d_weak_solution_zero_Dirichlet'")
# Define temporal and spatial sample points.
m, n = 10, 20
# Define mesh and function space.
mesh = UnitSquareMesh(m - 1, n - 1)
V = dh.create_function_space(mesh, 'default')
W = dh.create_vector_function_space(mesh, 'default')
# Define boundary conditions for velocity.
bc = DirichletBC(W.sub(0), Constant(0), dh.DirichletBoundary())
# Create zero function.
f = Function(V)
# Compute velocity.
v, k, res, fun, converged = cmscr1d_weak_solution(W, f,
f.dx(0), f.dx(1),
1.0, 1.0,
1.0, 1.0, 1.0,
bcs=bc)
v = v.vector().get_local()
k = k.vector().get_local()
np.testing.assert_allclose(v.shape, m * n)
np.testing.assert_allclose(v, np.zeros_like(v))
np.testing.assert_allclose(k.shape, m * n)
np.testing.assert_allclose(k, np.zeros_like(k))
def _boundary_condition(self, *args, **kwargs):
return DirichletBC(
self._V,
Constant(
self.potential_behind_dome(self.RADIUS, *args,
**kwargs)),
self._boundaries, self.EXTERNAL_SURFACE)
# this option does not appear to be working at the moment:
#parameters["num_threads"] = 6
mycomm = mpi_comm_world()
myrank = MPI.rank(mycomm)
# Domain, f-e spaces and boundary conditions:
mesh = UnitSquareMesh(500,500)
V = FunctionSpace(mesh, 'Lagrange', 2) # space for state and adjoint variables
Vm = FunctionSpace(mesh, 'Lagrange', 1) # space for medium parameter
Vme = FunctionSpace(mesh, 'Lagrange', 5) # sp for target med param
# Define zero Boundary conditions:
def u0_boundary(x, on_boundary):
return on_boundary
u0 = Constant("0.0")
bc = DirichletBC(V, u0, u0_boundary)
# Define target medium and rhs:
mtrue_exp = Expression('1 + 7*(pow(pow(x[0] - 0.5,2) +' + \
' pow(x[1] - 0.5,2),0.5) > 0.2)')
#mtrue = interpolate(mtrue_exp, Vme)
mtrue = interpolate(mtrue_exp, Vm)
f = Expression("1.0")
# Assemble weak form
trial = TrialFunction(V)
test = TestFunction(V)
a_true = inner(mtrue*nabla_grad(trial), nabla_grad(test))*dx
A_true = assemble(a_true)
bc.apply(A_true)
solver = PETScKrylovSolver('cg') # doesn't work with ilu preconditioner
def solve(self):
""" Find eigenvalues for transformed mesh. """
self.progress("Building mesh.")
# build transformed mesh
mesh = self.refineMesh()
# dim = mesh.topology().dim()
if self.bcLast:
mesh = transform_mesh(mesh, self.transformList)
Robin, Steklov, shift, bcs = get_bc_parts(mesh, self.bcList)
else:
Robin, Steklov, shift, bcs = get_bc_parts(mesh, self.bcList)
mesh = transform_mesh(mesh, self.transformList)
# boundary conditions computed on non-transformed mesh
# copy the values to transformed mesh
fun = FacetFunction("size_t", mesh, shift)
fun.array()[:] = bcs.array()[:]
bcs = fun
ds = Measure('ds', domain=mesh, subdomain_data=bcs)
V = FunctionSpace(mesh, self.method, self.deg)
u = TrialFunction(V)
v = TestFunction(V)
self.progress("Assembling matrices.")
wTop = Expression(self.wTop, degree=self.deg)
wBottom = Expression(self.wBottom, degree=self.deg)
#
# build stiffness matrix form
#
s = dot(grad(u), grad(v))*wTop*dx
# add Robin parts
for bc in Robin:
s += Constant(bc.parValue)*u*v*wTop*ds(bc.value+shift)
#
# build mass matrix form
#
if len(Steklov) > 0:
m = 0
for bc in Steklov:
m += Constant(bc.parValue)*u*v*wBottom*ds(bc.value+shift)
else:
m = u*v*wBottom*dx
# assemble
# if USE_EIGEN:
# S, M = EigenMatrix(), EigenMatrix()
# tempv = EigenVector()
# else:
S, M = PETScMatrix(), PETScMatrix()
# tempv = PETScVector()
if not np.any(bcs.array() == shift+1):
# no Dirichlet parts
assemble(s, tensor=S)
assemble(m, tensor=M)
else:
#
# with EIGEN we could
# apply Dirichlet condition symmetrically
# completely remove rows and columns
#
# Dirichlet parts are marked with shift+1
#
# temp = Constant(0)*v*dx
bc = DirichletBC(V, Constant(0.0), bcs, shift+1)
# assemble_system(s, temp, bc, A_tensor=S, b_tensor=tempv)
# assemble_system(m, temp, bc, A_tensor=M, b_tensor=tempv)
assemble(s, tensor=S)
bc.apply(S)
assemble(m, tensor=M)
# bc.zero(M)
# if USE_EIGEN:
# M = M.sparray()
# M.eliminate_zeros()
# print M.shape
# indices = M.indptr[:-1] - M.indptr[1:] < 0
# M = M[indices, :].tocsc()[:, indices]
# S = S.sparray()[indices, :].tocsc()[:, indices]
# print M.shape
#
# solve the eigenvalue problem
#
self.progress("Solving eigenvalue problem.")
eigensolver = SLEPcEigenSolver(S, M)
eigensolver.parameters["problem_type"] = "gen_hermitian"
eigensolver.parameters["solver"] = "krylov-schur"
if self.target is not None:
eigensolver.parameters["spectrum"] = "target real"
eigensolver.parameters["spectral_shift"] = self.target
else:
eigensolver.parameters["spectrum"] = "smallest magnitude"
eigensolver.parameters["spectral_shift"] = -0.01
eigensolver.parameters["spectral_transform"] = "shift-and-invert"
eigensolver.solve(self.number)
self.progress("Generating eigenfunctions.")
if eigensolver.get_number_converged() == 0:
return None
eigf = []
eigv = []
if self.deg > 1:
mesh = refine(mesh)
W = FunctionSpace(mesh, 'CG', 1)
for i in range(eigensolver.get_number_converged()):
pair = eigensolver.get_eigenpair(i)[::2]
eigv.append(pair[0])
u = Function(V)
u.vector()[:] = pair[1]
eigf.append(interpolate(u, W))
return eigv, eigf
