def get_bc_parts(mesh, lst):
"""
Build a size_t function with boundary condition parts.
Returns all Robin and Steklov conditions that need to be applied,
the shift needed to get a nonnegative function,
and the function itself.
"""
if len(lst) > 0:
shift = max(0, -min(e.value for e in lst))
else:
return [], [], 0, FacetFunction("size_t", mesh, 0)
# values must be shifted by smallest Steklov value since size_t is unsigned
fun = FacetFunction("size_t", mesh, shift)
for bc in lst:
sub = OnBoundary()
# overwrite inside function with the one from bc
sub.inside = bc.getTest()
sub.mark(fun, bc.value + shift)
# some conditions may cancel eachother
exist = set(np.unique(fun.array()))
lst = [e for e in lst if e.value + shift in exist]
# separate Robin and Steklov, Dirichlet and Neumann are irrelevant
Robin = [e for e in lst if e.value > 1 and e.parValue != 0]
Steklov = [e for e in lst if e.value < 0 and e.parValue != 0]
return Robin, Steklov, shift, fun
def get_bc_parts(mesh, lst):
"""
Build a size_t function with boundary condition parts.
Returns all Robin and Steklov conditions that need to be applied,
the shift needed to get a nonnegative function,
and the function itself.
"""
if len(lst) > 0:
shift = max(0, -min(e.value for e in lst))
else:
return [], [], 0, FacetFunction("size_t", mesh, 0)
# values must be shifted by smallest Steklov value since size_t is unsigned
fun = FacetFunction("size_t", mesh, shift)
for bc in lst:
sub = OnBoundary()
# overwrite inside function with the one from bc
sub.inside = bc.getTest()
sub.mark(fun, bc.value + shift)
# some conditions may cancel eachother
exist = set(np.unique(fun.array()))
lst = [e for e in lst if e.value+shift in exist]
# separate Robin and Steklov, Dirichlet and Neumann are irrelevant
Robin = [e for e in lst if e.value > 1 and e.parValue != 0]
Steklov = [e for e in lst if e.value < 0 and e.parValue != 0]
return Robin, Steklov, shift, fun
def mark_conditions(mesh, lst):
""" Mark all boundary conditions from the list. """
fun = FacetFunction("int", mesh, 0)
for bc in lst:
sub = OnBoundary()
# overwrite inside function with the one from bc
sub.inside = bc.getTest()
sub.mark(fun, bc.value)
return fun.array()
def mesh_generator(n):
mesh = RectangleMesh(1.0, 0.0, 2.0, 1.0, n, n, 'left/right')
domains = CellFunction('uint', mesh)
domains.set_all(0)
dx = Measure('dx')[domains]
boundaries = FacetFunction('uint', mesh)
boundaries.set_all(0)
ds = Measure('ds')[boundaries]
return mesh, dx, ds
def mark_conditions(mesh, lst):
""" Mark all boundary conditions from the list. """
fun = FacetFunction("int", mesh, 0)
for bc in lst:
sub = OnBoundary()
# overwrite inside function with the one from bc
sub.inside = bc.getTest()
sub.mark(fun, bc.value)
return fun.array()
def square_with_obstacle():
# Create classes for defining parts of the boundaries and the interior
# of the domain
class Left(SubDomain):
def inside(self, x, on_boundary):
return near(x[0], 0.0)
class Right(SubDomain):
def inside(self, x, on_boundary):
return near(x[0], 1.0)
class Bottom(SubDomain):
def inside(self, x, on_boundary):
return near(x[1], 0.0)
class Top(SubDomain):
def inside(self, x, on_boundary):
return near(x[1], 1.0)
class Obstacle(SubDomain):
def inside(self, x, on_boundary):
return (between(x[1], (0.5, 0.7)) and between(x[0], (0.2, 1.0)))
# Initialize sub-domain instances
left = Left()
top = Top()
right = Right()
bottom = Bottom()
obstacle = Obstacle()
# Define mesh
mesh = UnitSquareMesh(100, 100, 'crossed')
# Initialize mesh function for interior domains
domains = CellFunction('size_t', mesh)
domains.set_all(0)
obstacle.mark(domains, 1)
# Initialize mesh function for boundary domains
boundaries = FacetFunction('size_t', mesh)
boundaries.set_all(0)
left.mark(boundaries, 1)
top.mark(boundaries, 2)
right.mark(boundaries, 3)
bottom.mark(boundaries, 4)
boundary_indices = {'left': 1,
'top': 2,
'right': 3,
'bottom': 4}
f = Constant(0.0)
theta0 = Constant(293.0)
return mesh, f, boundaries, boundary_indices, theta0
def test_store_mesh(casedir):
pp = PostProcessor(dict(casedir=casedir))
from dolfin import (UnitSquareMesh, CellFunction, FacetFunction,
AutoSubDomain, Mesh, HDF5File, assemble, Expression,
ds, dx)
# Store mesh
mesh = UnitSquareMesh(6, 6)
celldomains = CellFunction("size_t", mesh)
celldomains.set_all(0)
AutoSubDomain(lambda x: x[0] < 0.5).mark(celldomains, 1)
facetdomains = FacetFunction("size_t", mesh)
AutoSubDomain(lambda x, on_boundary: x[0] < 0.5 and on_boundary).mark(
facetdomains, 1)
pp.store_mesh(mesh, celldomains, facetdomains)
# Read mesh back
mesh2 = Mesh()
f = HDF5File(mpi_comm_world(), os.path.join(pp.get_casedir(), "mesh.hdf5"),
'r')
f.read(mesh2, "Mesh", False)
celldomains2 = CellFunction("size_t", mesh2)
f.read(celldomains2, "CellDomains")
facetdomains2 = FacetFunction("size_t", mesh2)
f.read(facetdomains2, "FacetDomains")
e = Expression("1+x[1]", degree=1)
dx1 = dx(1, domain=mesh, subdomain_data=celldomains)
dx2 = dx(1, domain=mesh2, subdomain_data=celldomains2)
C1 = assemble(e * dx1)
C2 = assemble(e * dx2)
assert abs(C1 - C2) < 1e-10
ds1 = ds(1, domain=mesh, subdomain_data=facetdomains)
ds2 = ds(1, domain=mesh2, subdomain_data=facetdomains2)
F1 = assemble(e * ds1)
F2 = assemble(e * ds2)
assert abs(F1 - F2) < 1e-10
def derived_bcs(V, original_bcs, u_):
new_bcs = []
# Check first if user has declared subdomains
subdomain = original_bcs[0].user_sub_domain()
if subdomain is None:
mesh = V.mesh()
ff = FacetFunction("size_t", mesh, 0)
for i, bc in enumerate(original_bcs):
bc.apply(u_[0].vector()) # Need to initialize bc
m = bc.markers() # Get facet indices of boundary
ff.array()[m] = i + 1
new_bcs.append(DirichletBC(V, Constant(0), ff, i + 1))
else:
for i, bc in enumerate(original_bcs):
subdomain = bc.user_sub_domain()
new_bcs.append(DirichletBC(V, Constant(0), subdomain))
return new_bcs
def derived_bcs(V, original_bcs, u_):
new_bcs = []
# Check first if user has declared subdomains
subdomain = original_bcs[0].user_sub_domain()
if subdomain is None:
mesh = V.mesh()
ff = FacetFunction("size_t", mesh, 0)
for i, bc in enumerate(original_bcs):
bc.apply(u_[0].vector()) # Need to initialize bc
m = bc.markers() # Get facet indices of boundary
ff.array()[m] = i + 1
new_bcs.append(DirichletBC(V, Constant(0), ff, i + 1))
else:
for i, bc in enumerate(original_bcs):
subdomain = bc.user_sub_domain()
new_bcs.append(DirichletBC(V, Constant(0), subdomain))
return new_bcs
def as_pvd(h5_file):
'''Store facet and cell function for pvd'''
root, ext = os.path.splitext(h5_file)
mesh = Mesh()
hdf = HDF5File(mesh.mpi_comm(), h5_file, 'r')
hdf.read(mesh, '/mesh', False)
facet_markers = FacetFunction('size_t', mesh)
hdf.read(facet_markers, '/facet_markers')
cell_markers = CellFunction('size_t', mesh)
hdf.read(cell_markers, '/cell_markers')
File(root + 'facets' + '.pvd') << facet_markers
File(root + 'volumes' + '.pvd') << cell_markers
return True
def les_setup(u_, mesh, Wale, bcs, CG1Function, nut_krylov_solver, **NS_namespace):
"""Set up for solving Wale LES model
"""
DG = FunctionSpace(mesh, "DG", 0)
CG1 = FunctionSpace(mesh, "CG", 1)
# Compute cell size and put in delta
delta = Function(DG)
delta.vector().zero()
delta.vector().axpy(1.0, assemble(TestFunction(DG)*dx))
# Set up Wale form
Gij = grad(u_)
Sij = sym(Gij)
Skk = tr(Sij)
dim = mesh.geometry().dim()
Sd = sym(Gij*Gij) - 1./3.*Identity(mesh.geometry().dim())*Skk*Skk
nut_form = Wale['Cw']**2 * pow(delta, 2./dim) * pow(inner(Sd, Sd), 1.5) / (Max(pow(inner(Sij, Sij), 2.5) + pow(inner(Sd, Sd), 1.25), 1e-6))
ff = FacetFunction("size_t", mesh, 0)
bcs_nut = derived_bcs(CG1, bcs['u0'], u_)
nut_ = CG1Function(nut_form, mesh, method=nut_krylov_solver, bcs=bcs_nut, name='nut', bounded=True)
return dict(Sij=Sij, Sd=Sd, Skk=Skk, nut_=nut_, delta=delta, bcs_nut=bcs_nut)
def marked_boundary(mesh):
""" Return array of vertex values with 1 on boundary, 0 otherwise. """
fun = FacetFunction("int", mesh, 0)
on = OnBoundary()
on.mark(fun, 1)
return fun.array()
def marked_boundary(mesh):
""" Return array of vertex values with 1 on boundary, 0 otherwise. """
fun = FacetFunction("int", mesh, 0)
on = OnBoundary()
on.mark(fun, 1)
return fun.array()
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
def les_setup(u_, mesh, assemble_matrix, CG1Function, nut_krylov_solver, bcs, **NS_namespace):
"""
Set up for solving the Germano Dynamic LES model applying
Lagrangian Averaging.
"""
# Create function spaces
CG1 = FunctionSpace(mesh, "CG", 1)
p, q = TrialFunction(CG1), TestFunction(CG1)
dim = mesh.geometry().dim()
# Define delta and project delta**2 to CG1
delta = pow(CellVolume(mesh), 1./dim)
delta_CG1_sq = project(delta, CG1)
delta_CG1_sq.vector().set_local(delta_CG1_sq.vector().array()**2)
delta_CG1_sq.vector().apply("insert")
# Define nut_
Sij = sym(grad(u_))
magS = sqrt(2*inner(Sij,Sij))
Cs = Function(CG1)
nut_form = Cs**2 * delta**2 * magS
# Create nut_ BCs
ff = FacetFunction("size_t", mesh, 0)
bcs_nut = []
for i, bc in enumerate(bcs['u0']):
bc.apply(u_[0].vector()) # Need to initialize bc
m = bc.markers() # Get facet indices of boundary
ff.array()[m] = i+1
bcs_nut.append(DirichletBC(CG1, Constant(0), ff, i+1))
nut_ = CG1Function(nut_form, mesh, method=nut_krylov_solver, bcs=bcs_nut, bounded=True, name="nut")
# Create functions for holding the different velocities
u_CG1 = as_vector([Function(CG1) for i in range(dim)])
u_filtered = as_vector([Function(CG1) for i in range(dim)])
dummy = Function(CG1)
ll = LagrangeInterpolator()
# Assemble required filter matrices and functions
G_under = Function(CG1, assemble(TestFunction(CG1)*dx))
G_under.vector().set_local(1./G_under.vector().array())
G_under.vector().apply("insert")
G_matr = assemble(inner(p,q)*dx)
# Set up functions for Lij and Mij
Lij = [Function(CG1) for i in range(dim*dim)]
Mij = [Function(CG1) for i in range(dim*dim)]
# Check if case is 2D or 3D and set up uiuj product pairs and
# Sij forms, assemble required matrices
Sijcomps = [Function(CG1) for i in range(dim*dim)]
Sijfcomps = [Function(CG1) for i in range(dim*dim)]
# Assemble some required matrices for solving for rate of strain terms
Sijmats = [assemble_matrix(p.dx(i)*q*dx) for i in range(dim)]
if dim == 3:
tensdim = 6
uiuj_pairs = ((0,0),(0,1),(0,2),(1,1),(1,2),(2,2))
else:
tensdim = 3
uiuj_pairs = ((0,0),(0,1),(1,1))
# Set up Lagrange functions
JLM = Function(CG1)
JLM.vector()[:] += 1E-32
JMM = Function(CG1)
JMM.vector()[:] += 1
return dict(Sij=Sij, nut_form=nut_form, nut_=nut_, delta=delta, bcs_nut=bcs_nut,
delta_CG1_sq=delta_CG1_sq, CG1=CG1, Cs=Cs, u_CG1=u_CG1,
u_filtered=u_filtered, ll=ll, Lij=Lij, Mij=Mij, Sijcomps=Sijcomps,
Sijfcomps=Sijfcomps, Sijmats=Sijmats, JLM=JLM, JMM=JMM, dim=dim,
tensdim=tensdim, G_matr=G_matr, G_under=G_under, dummy=dummy,
uiuj_pairs=uiuj_pairs)
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)
wBottom = Expression(self.wBottom)
#
# 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
class InflowBoundary(SubDomain):
def inside(self, x, on_boundary):
return on_boundary and near(x[0], x_min)
class NoslipBoundary(SubDomain):
def inside(self, x, on_boundary):
dx = x[0] - c_x
dy = x[1] - c_y
dr = sqrt(dx**2 + dy**2)
return on_boundary and (near(x[1] *
(y_max - x[1]), 0) or dr < r + 1E-3)
f_f = FacetFunction('size_t', mesh, 0)
InflowBoundary().mark(f_f, 13)
NoslipBoundary().mark(f_f, 12)
# Width of the L domain
def compute_width_L_cylinder(unit):
return 4 * unit + 4 * unit * cos(pi / 4)
# Width of the O domain
def compute_width_O_cylinder(unit):
return 4 * unit
class InflowProfileConstant(Expression):
def peter():
base = '../meshes/2d/peter'
#base = '../meshes/2d/peter-fine'
mesh = Mesh(base + '.xml')
subdomains = MeshFunction('size_t', mesh, base+'_physical_region.xml')
workpiece_index = 3
subdomain_materials = {1: 'SiC',
2: 'carbon steel',
3: 'GaAs (liquid)'}
submesh_workpiece = SubMesh(mesh, subdomains, workpiece_index)
W = VectorFunctionSpace(submesh_workpiece, 'CG', 2)
Q = FunctionSpace(submesh_workpiece, 'CG', 2)
# Define melt boundaries.
class LeftBoundary(SubDomain):
def inside(self, x, on_boundary):
# Be especially careful in the corners when defining the r=0 axis:
# For the PPE to be consistent, we need to have n.u=0 *everywhere*
# on the non-(r=0) boundaries.
return on_boundary \
and x[0] < GMSH_EPS \
and 0.005+GMSH_EPS < x[1] and x[1] < 0.050-GMSH_EPS
class SurfaceBoundary(SubDomain):
def inside(self, x, on_boundary):
return on_boundary \
and 0.055-GMSH_EPS < x[1] \
and 0.030-GMSH_EPS < x[0] and x[0] < 0.075+GMSH_EPS
class StampBoundary(SubDomain):
def inside(self, x, on_boundary):
# Well well. If we don't include the endpoints here, the PPE turns
# out inconsistent. This is weird since the endpoints should be
# picked up by RightBoundary and StampBoundary.
return on_boundary \
and 0.050-GMSH_EPS < x[1] and x[1] < 0.055+GMSH_EPS \
and x[0] < 0.030+GMSH_EPS
class LowerBoundary(SubDomain):
def inside(self, x, on_boundary):
# Danger, danger.
# If the rightmost point (0.075, 0.010) is excluded, the PPE will
# end up inconsistent.
# This is actually weird since it should be picked up by
# RightBoundary.
return on_boundary \
and (x[1] < 0.005+GMSH_EPS
or (x[0] > 0.070-GMSH_EPS and x[1] < 0.010+GMSH_EPS)
)
class RightBoundary(SubDomain):
def inside(self, x, on_boundary):
return on_boundary \
and x[0] > 0.075-GMSH_EPS
left_boundary = LeftBoundary()
lower_boundary = LowerBoundary()
right_boundary = RightBoundary()
surface_boundary = SurfaceBoundary()
stamp_boundary = StampBoundary()
# Define workpiece boundaries.
wp_boundaries = FacetFunction('size_t', submesh_workpiece)
wp_boundaries.set_all(0)
left_boundary.mark(wp_boundaries, 1)
lower_boundary.mark(wp_boundaries, 2)
right_boundary.mark(wp_boundaries, 3)
surface_boundary.mark(wp_boundaries, 4)
stamp_boundary.mark(wp_boundaries, 5)
# For local use only:
wp_boundary_indices = {'left': 1,
'lower': 2,
'right': 3,
'surface': 4,
'stamp': 5}
# Boundary conditions for the velocity.
u_bcs = [DirichletBC(W, (0.0, 0.0), stamp_boundary),
DirichletBC(W, (0.0, 0.0), right_boundary),
DirichletBC(W, (0.0, 0.0), lower_boundary),
DirichletBC(W.sub(0), 0.0, left_boundary),
DirichletBC(W.sub(1), 0.0, surface_boundary),
]
p_bcs = []
# Boundary conditions for the heat equation.
# Dirichlet
theta_bcs_d = []
# Neumann
theta_bcs_n = {}
# Robin, i.e.,
#
# -dtheta/dn = alpha (theta - theta0)
#
# (with alpha>0 to preserve coercivity of the scheme).
#
theta_bcs_r = {
wp_boundary_indices['stamp']: (100.0, 1500.0),
wp_boundary_indices['surface']: (100.0, 1550.0),
wp_boundary_indices['right']: (300.0, Expression('200*x[0] + 1600', degree=1)),
wp_boundary_indices['lower']: (300.0, Expression('-1200*x[1] + 1614', degree=1)),
}
return mesh, subdomains, subdomain_materials, workpiece_index, \
wp_boundaries, W, u_bcs, p_bcs, \
Q, theta_bcs_d, theta_bcs_n, theta_bcs_r
def coil_in_box():
mesh = Mesh('../meshes/2d/coil-in-box.xml')
f = Constant(0.0)
# 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] > 2.5 - 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] > 0.4-GMSH_EPS
upper_boundary = UpperBoundary()
class CoilBoundary(SubDomain):
def inside(self, x, on_boundary):
return on_boundary \
and x[0] > GMSH_EPS and x[0] < 2.5-GMSH_EPS \
and x[1] > GMSH_EPS and x[1] < 0.4-GMSH_EPS
coil_boundary = CoilBoundary()
#heater_temp = 380.0
#room_temp = 293.0
#bcs = [(coil_boundary, heater_temp),
# (left_boundary, room_temp),
# (right_boundary, room_temp),
# (upper_boundary, room_temp),
# (lower_boundary, room_temp)
# ]
boundaries = {}
boundaries['left'] = left_boundary
boundaries['right'] = right_boundary
boundaries['upper'] = upper_boundary
boundaries['lower'] = lower_boundary
boundaries['coil'] = coil_boundary
boundaries = FacetFunction('size_t', mesh)
boundaries.set_all(0)
left_boundary.mark(boundaries, 1)
right_boundary.mark(boundaries, 2)
upper_boundary.mark(boundaries, 3)
lower_boundary.mark(boundaries, 4)
coil_boundary.mark(boundaries, 5)
boundary_indices = {'left': 1,
'right': 2,
'top': 3,
'bottom': 4,
'coil': 5}
theta0 = Constant(293.0)
return mesh, f, boundaries, boundary_indices, theta0
if mpirank == 0: print 'Start assembling KV'
MPI.barrier(mpicomm)
t0 = time()
KV = assemble(weak_V)
MPI.barrier(mpicomm)
t1 = time()
if mpirank == 0: print 'Time to assemble KV = {}'.format(t1 - t0)
elif myrun == 2:
class LeftRight(SubDomain):
def inside(self, x, on_boundary):
return (x[0] < 1e-16 or x[0] > 1.0 - 1e-16) \
and on_boundary
class_bc_abc = LeftRight()
abc_boundaryparts = FacetFunction("size_t", mesh)
class_bc_abc.mark(abc_boundaryparts, 1)
ds = Measure("ds")[abc_boundaryparts]
weak_1 = inner(sqrt(lam1 * rho1) * nabla_grad(trial),
nabla_grad(test)) * ds(1)
weak_2 = inner(sqrt(lam2 * rho2) * nabla_grad(trial),
nabla_grad(test)) * ds(1)
lam1.vector()[:] = 1.0
rho1.vector()[:] = 1.0
print 'Start assembling K2'
t0 = time()
K2 = assemble(weak_2)
t1 = time()
print 'Time to assemble K2 = {}'.format(t1 - t0)
def construct_sleeve_geometry(
t_wall=None,
t_gap=None,
t_sleeve=None,
L_wall=None,
L_sleeve=None,
refinement_parameter=16,
):
#
# Define the domain as a polygon
mesh = Mesh()
domain = Polygon([
dolfin.Point(0.0, 0.0),
dolfin.Point(L_wall, 0.0),
dolfin.Point(L_wall, t_wall),
dolfin.Point((L_wall - L_sleeve), t_wall),
dolfin.Point((L_wall - L_sleeve), (t_wall + t_gap)),
dolfin.Point(L_wall, (t_wall + t_gap)),
dolfin.Point(L_wall, (t_sleeve + t_wall + t_gap)),
dolfin.Point((L_wall - L_sleeve), (t_sleeve + t_wall + t_gap)),
dolfin.Point((L_wall - L_sleeve - t_sleeve - t_gap), t_wall),
dolfin.Point(0.0, t_wall),
], )
#
# Define weld region
weld_subdomain = Polygon([
dolfin.Point((L_wall - L_sleeve - t_sleeve - t_gap), t_wall),
dolfin.Point((L_wall - L_sleeve), t_wall),
dolfin.Point((L_wall - L_sleeve), (t_wall + t_sleeve + t_gap)),
])
domain.set_subdomain(1, weld_subdomain)
#
# Mesh
mesh = generate_mesh(domain, refinement_parameter)
#
# Refine in the weld
cell_markers = CellFunction("bool", mesh)
cell_markers.set_all(False)
c = is_in_weld_region(
t_wall=t_wall,
t_gap=t_gap,
t_sleeve=t_sleeve,
L_wall=L_wall,
L_sleeve=L_sleeve,
)
class MyDomain(SubDomain):
def inside(self, x, on_boundary):
return c(x)
my_domain = MyDomain()
my_domain.mark(cell_markers, True)
mesh = refine(mesh, cell_markers)
#
# Define the upper and lower boundaries
class Upper(SubDomain):
def inside(self, x, on_boundary):
#
# Define relevant points
xb1 = (L_wall - L_sleeve - t_sleeve - t_gap)
xb2 = (L_wall - L_sleeve)
yb1 = t_wall
yb2 = (t_wall + t_sleeve + t_gap)
#
# Define params for assessing if on a line between points
dx_line = xb2 - xb1
dy_line = yb2 - yb1
dx = x[0] - xb1
dy = x[1] - yb1
zero = dx * dy_line - dx_line * dy
#
is_upper_region_one = x[0] <= xb1 and near(x[1], yb1)
is_upper_region_two = x[0] >= xb1 and x[0] <= xb2 and near(zero, 0)
is_upper_region_three = x[0] >= xb2 and near(x[1], yb2)
#
return is_upper_region_one or is_upper_region_two or is_upper_region_three
class Lower(SubDomain):
def inside(self, x, on_boundary):
return near(x[1], 0)
#
# Set boundaries
upper = Upper()
lower = Lower()
boundaries = FacetFunction("size_t", mesh)
boundaries.set_all(0)
upper.mark(boundaries, 1)
lower.mark(boundaries, 2)
#
return (mesh, boundaries)
def les_setup(u_, mesh, assemble_matrix, CG1Function, nut_krylov_solver, bcs,
**NS_namespace):
"""
Set up for solving the Germano Dynamic LES model applying
Lagrangian Averaging.
"""
# Create function spaces
CG1 = FunctionSpace(mesh, "CG", 1)
p, q = TrialFunction(CG1), TestFunction(CG1)
dim = mesh.geometry().dim()
# Define delta and project delta**2 to CG1
delta = pow(CellVolume(mesh), 1. / dim)
delta_CG1_sq = project(delta, CG1)
delta_CG1_sq.vector().set_local(delta_CG1_sq.vector().array()**2)
delta_CG1_sq.vector().apply("insert")
# Define nut_
Sij = sym(grad(u_))
magS = sqrt(2 * inner(Sij, Sij))
Cs = Function(CG1)
nut_form = Cs**2 * delta**2 * magS
# Create nut_ BCs
ff = FacetFunction("size_t", mesh, 0)
bcs_nut = []
for i, bc in enumerate(bcs['u0']):
bc.apply(u_[0].vector()) # Need to initialize bc
m = bc.markers() # Get facet indices of boundary
ff.array()[m] = i + 1
bcs_nut.append(DirichletBC(CG1, Constant(0), ff, i + 1))
nut_ = CG1Function(nut_form,
mesh,
method=nut_krylov_solver,
bcs=bcs_nut,
bounded=True,
name="nut")
# Create functions for holding the different velocities
u_CG1 = as_vector([Function(CG1) for i in range(dim)])
u_filtered = as_vector([Function(CG1) for i in range(dim)])
dummy = Function(CG1)
ll = LagrangeInterpolator()
# Assemble required filter matrices and functions
G_under = Function(CG1, assemble(TestFunction(CG1) * dx))
G_under.vector().set_local(1. / G_under.vector().array())
G_under.vector().apply("insert")
G_matr = assemble(inner(p, q) * dx)
# Set up functions for Lij and Mij
Lij = [Function(CG1) for i in range(dim * dim)]
Mij = [Function(CG1) for i in range(dim * dim)]
# Check if case is 2D or 3D and set up uiuj product pairs and
# Sij forms, assemble required matrices
Sijcomps = [Function(CG1) for i in range(dim * dim)]
Sijfcomps = [Function(CG1) for i in range(dim * dim)]
# Assemble some required matrices for solving for rate of strain terms
Sijmats = [assemble_matrix(p.dx(i) * q * dx) for i in range(dim)]
if dim == 3:
tensdim = 6
uiuj_pairs = ((0, 0), (0, 1), (0, 2), (1, 1), (1, 2), (2, 2))
else:
tensdim = 3
uiuj_pairs = ((0, 0), (0, 1), (1, 1))
# Set up Lagrange functions
JLM = Function(CG1)
JLM.vector()[:] += 1E-32
JMM = Function(CG1)
JMM.vector()[:] += 1
return dict(Sij=Sij,
nut_form=nut_form,
nut_=nut_,
delta=delta,
bcs_nut=bcs_nut,
delta_CG1_sq=delta_CG1_sq,
CG1=CG1,
Cs=Cs,
u_CG1=u_CG1,
u_filtered=u_filtered,
ll=ll,
Lij=Lij,
Mij=Mij,
Sijcomps=Sijcomps,
Sijfcomps=Sijfcomps,
Sijmats=Sijmats,
JLM=JLM,
JMM=JMM,
dim=dim,
tensdim=tensdim,
G_matr=G_matr,
G_under=G_under,
dummy=dummy,
uiuj_pairs=uiuj_pairs)
def __init__(self):
import os
from dolfin import Mesh, MeshFunction, SubMesh, SubDomain, \
FacetFunction, DirichletBC, dot, grad, FunctionSpace, \
MixedFunctionSpace, Expression, FacetNormal, pi, Function, \
Constant, TestFunction, MPI, mpi_comm_world, File
import numpy
import warnings
from maelstrom import heat_cylindrical as cyl_heat
from maelstrom import materials_database as md
GMSH_EPS = 1.0e-15
current_path = os.path.dirname(os.path.realpath(__file__))
base = os.path.join(
current_path,
'../../meshes/2d/crucible-with-coils'
)
self.mesh = Mesh(base + '.xml')
self.subdomains = MeshFunction('size_t',
self.mesh,
base + '_physical_region.xml'
)
self.subdomain_materials = {
1: md.get_material('porcelain'),
2: md.get_material('argon'),
3: md.get_material('GaAs (solid)'),
4: md.get_material('GaAs (liquid)'),
27: md.get_material('air')
}
# coils
for k in range(5, 27):
self.subdomain_materials[k] = md.get_material('graphite EK90')
# Define the subdomains which together form a single coil.
self.coil_domains = [
[5, 6, 7, 8, 9],
[10, 11, 12, 13, 14],
[15, 16, 17, 18, 19],
[20, 21, 22, 23],
[24, 25, 26]
]
self.wpi = 4
# http://fenicsproject.org/qa/2026/submesh-workaround-for-parallel-computation
submesh_parallel_bug_fixed = False
if submesh_parallel_bug_fixed:
submesh_workpiece = SubMesh(self.mesh, self.subdomains, self.wpi)
else:
# To get the mesh in parallel, we need to read it in from a file.
# Writing out can only happen in serial mode, though. :/
base = os.path.join(current_path,
'../../meshes/2d/crucible-with-coils-submesh'
)
filename = base + '.xml'
if not os.path.isfile(filename):
warnings.warn(
'Submesh file \'%s\' does not exist. Creating... '
% filename
)
if MPI.size(mpi_comm_world()) > 1:
raise RuntimeError(
'Can only write submesh in serial mode.'
)
submesh_workpiece = \
SubMesh(self.mesh, self.subdomains, self.wpi)
output_stream = File(filename)
output_stream << submesh_workpiece
# Read the mesh
submesh_workpiece = Mesh(base + '.xml')
coords = submesh_workpiece.coordinates()
ymin = min(coords[:, 1])
ymax = max(coords[:, 1])
# Find the top right point.
k = numpy.argmax(numpy.sum(coords, 1))
topright = coords[k, :]
# Initialize mesh function for boundary domains
class Left(SubDomain):
def inside(self, x, on_boundary):
# Explicitly exclude the lowest and the highest point of the
# symmetry axis.
# It is necessary for the consistency of the pressure-Poisson
# system in the Navier-Stokes solver that the velocity is
# exactly 0 at the boundary r>0. Hence, at the corner points
# (r=0, melt-crucible, melt-crystal) we must enforce u=0
# already and cannot have a component in z-direction.
return on_boundary \
and x[0] < GMSH_EPS \
and x[1] < ymax - GMSH_EPS \
and x[1] > ymin + GMSH_EPS
class Crucible(SubDomain):
def inside(self, x, on_boundary):
return on_boundary \
and ((x[0] > GMSH_EPS and x[1] < ymax - GMSH_EPS)
or (x[0] > topright[0] - GMSH_EPS
and x[1] > topright[1] - GMSH_EPS)
or (x[0] < GMSH_EPS and x[1] < ymin + GMSH_EPS)
)
# At the top right part (boundary melt--gas), slip is allowed, so only
# n.u=0 is enforced. Very weirdly, the PPE is consistent if and only if
# the end points of UpperRight are in UpperRight. This contrasts
# Left(), where the end points must NOT belong to Left(). Judging from
# the experiments, these settings do the right thing.
# TODO try to better understand the PPE system/dolfin's boundary
# settings
class Upper(SubDomain):
def inside(self, x, on_boundary):
return on_boundary \
and x[1] > ymax - GMSH_EPS
class UpperRight(SubDomain):
def inside(self, x, on_boundary):
return on_boundary \
and x[1] > ymax - GMSH_EPS \
and x[0] > 0.038 - GMSH_EPS
# The crystal boundary is taken to reach up to 0.038 where the
# Dirichlet boundary data is about the melting point of the crystal,
# 1511K. This setting gives pretty acceptable results when there is no
# convection except the one induced by buoyancy. Is there is any more
# stirring going on, though, the end point of the crystal with its
# fixed temperature of 1511K might be the hottest point globally. This
# looks rather unphysical.
# TODO check out alternatives
class UpperLeft(SubDomain):
def inside(self, x, on_boundary):
return on_boundary \
and x[1] > ymax - GMSH_EPS \
and x[0] < 0.038 + GMSH_EPS
left = Left()
crucible = Crucible()
upper_left = UpperLeft()
upper_right = UpperRight()
self.wp_boundaries = FacetFunction('size_t', submesh_workpiece)
self.wp_boundaries.set_all(0)
left.mark(self.wp_boundaries, 1)
crucible.mark(self.wp_boundaries, 2)
upper_right.mark(self.wp_boundaries, 3)
upper_left.mark(self.wp_boundaries, 4)
if DEBUG:
from dolfin import plot, interactive
plot(self.wp_boundaries, title='Boundaries')
interactive()
submesh_boundary_indices = {
'left': 1,
'crucible': 2,
'upper right': 3,
'upper left': 4
}
# Boundary conditions for the velocity.
#
# [1] Incompressible flow and the finite element method; volume two;
# Isothermal Laminar Flow;
# P.M. Gresho, R.L. Sani;
#
# For the choice of function space, [1] says:
# "In 2D, the triangular elements P_2^+P_1 and P_2^+P_{-1} are very
# good [...]. [...] If you wish to avoid bubble functions on
# triangular elements, P_2P_1 is not bad, and P_2(P_1+P_0) is even
# better [...]."
#
# It turns out that adding the bubble space significantly hampers the
# convergence of the Stokes solver and also considerably increases the
# time it takes to construct the Jacobian matrix of the Navier--Stokes
# problem if no optimization is applied.
V = FunctionSpace(submesh_workpiece, 'CG', 2)
with_bubbles = False
if with_bubbles:
V += FunctionSpace(submesh_workpiece, 'B', 3)
self.W = MixedFunctionSpace([V, V, V])
self.u_bcs = [
DirichletBC(self.W,
Expression(
('0.0', '0.0', '-2*pi*x[0] * 5.0/60.0'),
degree=1
),
#(0.0, 0.0, 0.0),
crucible),
DirichletBC(self.W.sub(0), 0.0, left),
DirichletBC(self.W.sub(2), 0.0, left),
# Make sure that u[2] is 0 at r=0.
DirichletBC(self.W,
Expression(
('0.0', '0.0', '2*pi*x[0] * 5.0/60.0'),
degree=1
),
upper_left),
DirichletBC(self.W.sub(1), 0.0, upper_right),
]
self.p_bcs = []
self.P = FunctionSpace(submesh_workpiece, 'CG', 1)
# Boundary conditions for heat equation.
self.Q = FunctionSpace(submesh_workpiece, 'CG', 2)
# Dirichlet.
# This is a bit of a tough call since the boundary conditions need to
# be read from a Tecplot file here.
import tecplot_reader
filename = os.path.join(
os.path.dirname(os.path.realpath(__file__)),
'data/crucible-boundary.dat'
)
data = tecplot_reader.read(filename)
RZ = numpy.c_[data['ZONE T']['node data']['r'],
data['ZONE T']['node data']['z']
]
T_vals = data['ZONE T']['node data']['temp. [K]']
class TecplotDirichletBC(Expression):
# TODO specify degree
def eval(self, value, x):
# Find on which edge x sits, and raise exception if it doesn't.
edge_found = False
for edge in data['ZONE T']['element data']:
# Given a point X and an edge X0--X1,
#
# (1 - theta) X0 + theta X1,
#
# the minimum distance is assumed for
#
# argmin_theta ||(1-theta) X0 + theta X1 - X||^2
# = <X1 - X0, X - X0> / ||X1 - X0||^2.
#
# If the distance is 0 and 0<=theta<=1, we found the edge.
#
# Note that edges are 1-based in Tecplot.
X0 = RZ[edge[0] - 1]
X1 = RZ[edge[1] - 1]
theta = numpy.dot(X1-X0, x-X0) / numpy.dot(X1-X0, X1-X0)
diff = (1.0-theta)*X0 + theta*X1 - x
if numpy.dot(diff, diff) < 1.0e-10 and \
0.0 <= theta and theta <= 1.0:
# Linear interpolation of the temperature value.
value[0] = (1.0-theta) * T_vals[edge[0]-1] \
+ theta * T_vals[edge[1]-1]
edge_found = True
break
# This class is supposed to be used for Dirichlet boundary
# conditions. For some reason, FEniCS also evaluates
# DirichletBC objects at coordinates which do not sit on the
# boundary, see
# <http://fenicsproject.org/qa/1033/dirichletbc-expressions-evaluated-away-from-the-boundary>.
# The assigned values have no meaning though, so not assigning
# values[0] here is okay.
#
#from matplotlib import pyplot as pp
#pp.plot(x[0], x[1], 'xg')
if not edge_found:
value[0] = 0.0
warnings.warn('Coordinate (%e, %e) doesn\'t sit on edge.'
% (x[0], x[1]))
#pp.plot(RZ[:, 0], RZ[:, 1], '.k')
#pp.plot(x[0], x[1], 'xr')
#pp.show()
#raise RuntimeError('Input coordinate '
# '%r is not on boundary.' % x)
return
tecplot_dbc = TecplotDirichletBC()
self.theta_bcs_d = [
DirichletBC(self.Q, tecplot_dbc, upper_left)
]
theta_bcs_d_strict = [
DirichletBC(self.Q, tecplot_dbc, upper_right),
DirichletBC(self.Q, tecplot_dbc, crucible),
DirichletBC(self.Q, tecplot_dbc, upper_left)
]
# Neumann
dTdr_vals = data['ZONE T']['node data']['dTempdx [K/m]']
dTdz_vals = data['ZONE T']['node data']['dTempdz [K/m]']
class TecplotNeumannBC(Expression):
# TODO specify degree
def eval(self, value, x):
# Same problem as above: This expression is not only evaluated
# at boundaries.
for edge in data['ZONE T']['element data']:
X0 = RZ[edge[0] - 1]
X1 = RZ[edge[1] - 1]
theta = numpy.dot(X1-X0, x-X0) / numpy.dot(X1-X0, X1-X0)
dist = numpy.linalg.norm((1-theta)*X0 + theta*X1 - x)
if dist < 1.0e-5 and 0.0 <= theta and theta <= 1.0:
value[0] = (1-theta) * dTdr_vals[edge[0]-1] \
+ theta * dTdr_vals[edge[1]-1]
value[1] = (1-theta) * dTdz_vals[edge[0]-1] \
+ theta * dTdz_vals[edge[1]-1]
break
return
def value_shape(self):
return (2,)
tecplot_nbc = TecplotNeumannBC()
n = FacetNormal(self.Q.mesh())
self.theta_bcs_n = {
submesh_boundary_indices['upper right']: dot(n, tecplot_nbc),
submesh_boundary_indices['crucible']: dot(n, tecplot_nbc)
}
self.theta_bcs_r = {}
# It seems that the boundary conditions from above are inconsistent in
# that solving with Dirichlet overall and mixed Dirichlet-Neumann give
# different results; the value *cannot* correspond to one solution.
# From looking at the solutions, the pure Dirichlet setting appears
# correct, so extract the Neumann values directly from that solution.
zeta = TestFunction(self.Q)
theta_reference = Function(self.Q, name='temperature (Dirichlet)')
theta_reference.vector()[:] = 0.0
# Solve the *quasilinear* PDE (coefficients may depend on theta).
# This is to avoid setting a fixed temperature for the coefficients.
# Get material parameters
wp_material = self.subdomain_materials[self.wpi]
if isinstance(wp_material.specific_heat_capacity, float):
cp = wp_material.specific_heat_capacity
else:
cp = wp_material.specific_heat_capacity(theta_reference)
if isinstance(wp_material.density, float):
rho = wp_material.density
else:
rho = wp_material.density(theta_reference)
if isinstance(wp_material.thermal_conductivity, float):
k = wp_material.thermal_conductivity
else:
k = wp_material.thermal_conductivity(theta_reference)
reference_problem = cyl_heat.HeatCylindrical(
self.Q, theta_reference,
zeta,
b=Constant((0.0, 0.0, 0.0)),
kappa=k,
rho=rho,
cp=cp,
source=Constant(0.0),
dirichlet_bcs=theta_bcs_d_strict
)
from dolfin import solve
solve(reference_problem.F0 == 0,
theta_reference,
bcs=theta_bcs_d_strict
)
# Create equivalent boundary conditions from theta_reference. This
# makes sure that the potentially expensive Expression evaluation in
# theta_bcs_* is replaced by something reasonably cheap.
for k, bc in enumerate(self.theta_bcs_d):
self.theta_bcs_d[k] = DirichletBC(bc.function_space(),
theta_reference,
bc.domain_args[0]
)
# Adapt Neumann conditions.
n = FacetNormal(self.Q.mesh())
for k in self.theta_bcs_n:
self.theta_bcs_n[k] = dot(n, grad(theta_reference))
if DEBUG:
# Solve the heat equation with the mixed Dirichlet-Neumann
# boundary conditions and compare it to the Dirichlet-only
# solution.
theta_new = Function(
self.Q,
name='temperature (Neumann + Dirichlet)'
)
from dolfin import Measure
ds_workpiece = Measure('ds')[self.wp_boundaries]
problem_new = cyl_heat.HeatCylindrical(
self.Q, theta_new,
zeta,
b=Constant((0.0, 0.0, 0.0)),
kappa=k,
rho=rho,
cp=cp,
source=Constant(0.0),
dirichlet_bcs=self.theta_bcs_d,
neumann_bcs=self.theta_bcs_n,
ds=ds_workpiece
)
from dolfin import solve
solve(problem_new.F0 == 0,
theta_new,
bcs=problem_new.dirichlet_bcs
)
from dolfin import plot, interactive, errornorm
print('||theta_new - theta_ref|| = %e'
% errornorm(theta_new, theta_reference)
)
plot(theta_reference)
plot(theta_new)
plot(
theta_reference - theta_new,
title='theta_ref - theta_new'
)
interactive()
#omega = 2 * pi * 10.0e3
self.omega = 2 * pi * 300.0
return
