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Apply Diriclet boundary on the Cofunction RHS. #3754

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Apply Diriclet boundary on the Cofunction RHS. #3754

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5 changes: 5 additions & 0 deletions firedrake/variational_solver.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@
DEFAULT_SNES_PARAMETERS
)
from firedrake.function import Function
from firedrake.cofunction import Cofunction
from firedrake.functionspace import RestrictedFunctionSpace
from firedrake.ufl_expr import TrialFunction, TestFunction
from firedrake.bcs import DirichletBC, EquationBC
Expand Down Expand Up @@ -305,6 +306,10 @@ def solve(self, bounds=None):

for dbc in problem.dirichlet_bcs():
dbc.apply(problem.u_restrict)
for coeff in coefficients:
if isinstance(coeff, Cofunction):
# Apply the DirichletBC to the right hand side of the equation.
dbc.apply(coeff)
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This does not look right. The residual form might contain many cofunctions in function spaces different from the one of the solution. This should be done before calling the solver, and only on the Cofunction RHS. Also it is likely that you need dbc.zero() instead of dbc.apply(). Also see the comment I left in #3662

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This will have side effects on Cofunctions in the problem definition.

u = Function(space, name="u")
b = Cofunction(space.dual(), name="b")
...
problem = LinearVariationalProblem(
    inner(trial, test) * dx, b, u, DirichletBC(space, 1, "on_boundary"))
assert b in problem.F.coefficients()  # passes


if bounds is not None:
lower, upper = bounds
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40 changes: 40 additions & 0 deletions tests/regression/test_cofunction.py
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Expand Up @@ -60,3 +60,43 @@ def test_scalar_cofunction_zero_with_subset(V):
assert f is g
assert np.allclose(f.dat.data_ro[:2], 0.0)
assert np.allclose(f.dat.data_ro[2:], 1.0)


def test_diriclet_bc_rhs(V):
# Issue https://github.com/firedrakeproject/firedrake/issues/3498
# Apply DirichletBC to RHS (Cofunction) in LinearVariationalSolver
mesh = UnitIntervalMesh(2)
space = FunctionSpace(mesh, "Lagrange", 1)
test, trial = TestFunction(space), TrialFunction(space)

# Form RHS
u = Function(space, name="u")
problem = LinearVariationalProblem(
inner(trial, test) * dx, inner(Constant(1.0), test) * dx, u,
DirichletBC(space, 0.0, "on_boundary"))
solver = LinearVariationalSolver(problem)
solver.solve()

assert np.allclose(assemble(inner(u, u) * ds), 0.0)

# Cofunction RHS
b = assemble(inner(Constant(1.0), test) * dx)
u = Function(space, name="u")
problem = LinearVariationalProblem(
inner(trial, test) * dx, b, u,
DirichletBC(space, 0.0, "on_boundary"))
solver = LinearVariationalSolver(problem)
solver.solve()

assert np.allclose(assemble(inner(u, u) * ds), 0.0)

# FormSum RHS
b = assemble(inner(Constant(0.5), test) * dx) + inner(Constant(0.5), test) * dx
u = Function(space, name="u")
problem = LinearVariationalProblem(
inner(trial, test) * dx, b, u,
DirichletBC(space, 0.0, "on_boundary"))
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The test should have non-homogeneous bcs

solver = LinearVariationalSolver(problem)
solver.solve()

assert np.allclose(assemble(inner(u, u) * ds), 0.0)
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