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# Copyright (C) 2022 Jørgen S. Dokken
#
# This file is part of DOLFINX_MPC
#
# SPDX-License-Identifier: MIT
#
# This demo illustrates how to apply a slip condition on an
# interface not aligned with the coordiante axis.
# The demos solves the Stokes problem
import dolfinx_mpc.utils
import gmsh
import numpy as np
import scipy.sparse.linalg
from dolfinx import fem, io
from dolfinx.common import Timer, TimingType, list_timings
from dolfinx.io import gmshio
from dolfinx_mpc import LinearProblem, MultiPointConstraint
from mpi4py import MPI
from numpy.typing import NDArray
from petsc4py import PETSc
from ufl import (FacetNormal, FiniteElement, Identity, Measure, TestFunctions,
TrialFunctions, VectorElement, div, dot, dx, grad, inner,
outer, sym)
from ufl.core.expr import Expr
def create_mesh_gmsh(L: int = 2, H: int = 1, res: float = 0.1, theta: float = np.pi / 5,
wall_marker: int = 1, outlet_marker: int = 2, inlet_marker: int = 3):
"""
Create a channel of length L, height H, rotated theta degrees
around origin, with facet markers for inlet, outlet and walls.
Parameters
----------
L
The length of the channel
H
Width of the channel
res
Mesh resolution (uniform)
theta
Rotation angle
wall_marker
Integer used to mark the walls of the channel
outlet_marker
Integer used to mark the outlet of the channel
inlet_marker
Integer used to mark the inlet of the channel
"""
gmsh.initialize()
if MPI.COMM_WORLD.rank == 0:
gmsh.model.add("Square duct")
# Create rectangular channel
channel = gmsh.model.occ.addRectangle(0, 0, 0, L, H)
gmsh.model.occ.synchronize()
# Find entity markers before rotation
surfaces = gmsh.model.occ.getEntities(dim=1)
walls = []
inlets = []
outlets = []
for surface in surfaces:
com = gmsh.model.occ.getCenterOfMass(surface[0], surface[1])
if np.allclose(com, [0, H / 2, 0]):
inlets.append(surface[1])
elif np.allclose(com, [L, H / 2, 0]):
outlets.append(surface[1])
elif np.isclose(com[1], 0) or np.isclose(com[1], H):
walls.append(surface[1])
# Rotate channel theta degrees in the xy-plane
gmsh.model.occ.rotate([(2, channel)], 0, 0, 0,
0, 0, 1, theta)
gmsh.model.occ.synchronize()
# Add physical markers
gmsh.model.addPhysicalGroup(2, [channel], 1)
gmsh.model.setPhysicalName(2, 1, "Fluid volume")
gmsh.model.addPhysicalGroup(1, walls, wall_marker)
gmsh.model.setPhysicalName(1, wall_marker, "Walls")
gmsh.model.addPhysicalGroup(1, inlets, inlet_marker)
gmsh.model.setPhysicalName(1, inlet_marker, "Fluid inlet")
gmsh.model.addPhysicalGroup(1, outlets, outlet_marker)
gmsh.model.setPhysicalName(1, outlet_marker, "Fluid outlet")
# Set number of threads used for mesh
gmsh.option.setNumber("Mesh.MaxNumThreads1D", MPI.COMM_WORLD.size)
gmsh.option.setNumber("Mesh.MaxNumThreads2D", MPI.COMM_WORLD.size)
gmsh.option.setNumber("Mesh.MaxNumThreads3D", MPI.COMM_WORLD.size)
# Set uniform mesh size
gmsh.option.setNumber("Mesh.CharacteristicLengthMin", res)
gmsh.option.setNumber("Mesh.CharacteristicLengthMax", res)
# Generate mesh
gmsh.model.mesh.generate(2)
# Convert gmsh model to DOLFINx Mesh and meshtags
mesh, _, ft = gmshio.model_to_mesh(gmsh.model, MPI.COMM_WORLD, 0, gdim=2)
gmsh.finalize()
return mesh, ft
# ------------------- Mesh and function space creation ------------------------
mesh, mt = create_mesh_gmsh(res=0.1)
fdim = mesh.topology.dim - 1
# Create the function space
P2 = VectorElement("Lagrange", mesh.ufl_cell(), 2)
P1 = FiniteElement("Lagrange", mesh.ufl_cell(), 1)
TH = P2 * P1
W = fem.FunctionSpace(mesh, TH)
V, V_to_W = W.sub(0).collapse()
Q, _ = W.sub(1).collapse()
def inlet_velocity_expression(x: NDArray[np.float64]) -> NDArray[np.bool_]:
return np.stack((np.sin(np.pi * np.sqrt(x[0]**2 + x[1]**2)),
5 * x[1] * np.sin(np.pi * np.sqrt(x[0]**2 + x[1]**2))))
# ----------------------Defining boundary conditions----------------------
# Inlet velocity Dirichlet BC
inlet_velocity = fem.Function(V)
inlet_velocity.interpolate(inlet_velocity_expression)
inlet_velocity.x.scatter_forward()
W0 = W.sub(0)
dofs = fem.locate_dofs_topological((W0, V), 1, mt.find(3))
bc1 = fem.dirichletbc(inlet_velocity, dofs, W0)
# Collect Dirichlet boundary conditions
bcs = [bc1]
# Slip conditions for walls
n = dolfinx_mpc.utils.create_normal_approximation(V, mt, 1)
with Timer("~Stokes: Create slip constraint"):
mpc = MultiPointConstraint(W)
mpc.create_slip_constraint(W.sub(0), (mt, 1), n, bcs=bcs)
mpc.finalize()
def tangential_proj(u: Expr, n: Expr):
"""
See for instance:
https://link.springer.com/content/pdf/10.1023/A:1022235512626.pdf
"""
return (Identity(u.ufl_shape[0]) - outer(n, n)) * u
def sym_grad(u: Expr):
return sym(grad(u))
def T(u: Expr, p: Expr, mu: Expr):
return 2 * mu * sym_grad(u) - p * Identity(u.ufl_shape[0])
# --------------------------Variational problem---------------------------
# Traditional terms
mu = 1
f = fem.Constant(mesh, PETSc.ScalarType((0, 0)))
(u, p) = TrialFunctions(W)
(v, q) = TestFunctions(W)
a = (2 * mu * inner(sym_grad(u), sym_grad(v))
- inner(p, div(v))
- inner(div(u), q)) * dx
L = inner(f, v) * dx
# No prescribed shear stress
n = FacetNormal(mesh)
g_tau = tangential_proj(fem.Constant(mesh, PETSc.ScalarType(((0, 0), (0, 0)))) * n, n)
ds = Measure("ds", domain=mesh, subdomain_data=mt, subdomain_id=1)
# Terms due to slip condition
# Explained in for instance: https://arxiv.org/pdf/2001.10639.pdf
a -= inner(outer(n, n) * dot(T(u, p, mu), n), v) * ds
L += inner(g_tau, v) * ds
# Solve linear problem
petsc_options = {"ksp_type": "preonly", "pc_type": "lu", "pc_factor_solver_type": "mumps"}
problem = LinearProblem(a, L, mpc, bcs=bcs, petsc_options=petsc_options)
U = problem.solve()
# ------------------------------ Output ----------------------------------
u = U.sub(0).collapse()
p = U.sub(1).collapse()
u.name = "u"
p.name = "p"
with io.VTXWriter(mesh.comm, "results/demo_stokes_u.bp", u) as vtx:
vtx.write(0.0)
with io.VTXWriter(mesh.comm, "results/demo_stokes_p.bp", p) as vtx:
vtx.write(0.0)
# -------------------- Verification --------------------------------
# Transfer data from the MPC problem to numpy arrays for comparison
with Timer("~Stokes: Verification of problem by global matrix reduction"):
# Solve the MPC problem using a global transformation matrix
# and numpy solvers to get reference values
# Generate reference matrices and unconstrained solution
bilinear_form = fem.form(a)
A_org = fem.petsc.assemble_matrix(bilinear_form, bcs)
A_org.assemble()
linear_form = fem.form(L)
L_org = fem.petsc.assemble_vector(linear_form)
fem.petsc.apply_lifting(L_org, [bilinear_form], [bcs])
L_org.ghostUpdate(addv=PETSc.InsertMode.ADD_VALUES, mode=PETSc.ScatterMode.REVERSE)
fem.petsc.set_bc(L_org, bcs)
root = 0
dolfinx_mpc.utils.compare_mpc_lhs(A_org, problem.A, mpc, root=root)
dolfinx_mpc.utils.compare_mpc_rhs(L_org, problem.b, mpc, root=root)
# Gather LHS, RHS and solution on one process
A_csr = dolfinx_mpc.utils.gather_PETScMatrix(A_org, root=root)
K = dolfinx_mpc.utils.gather_transformation_matrix(mpc, root=root)
L_np = dolfinx_mpc.utils.gather_PETScVector(L_org, root=root)
u_mpc = dolfinx_mpc.utils.gather_PETScVector(U.vector, root=root)
if MPI.COMM_WORLD.rank == root:
KTAK = K.T * A_csr * K
reduced_L = K.T @ L_np
# Solve linear system
d = scipy.sparse.linalg.spsolve(KTAK, reduced_L)
# Back substitution to full solution vector
uh_numpy = K @ d
assert np.allclose(uh_numpy, u_mpc)
# -------------------- List timings --------------------------
list_timings(MPI.COMM_WORLD, [TimingType.wall])
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