1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244
|
# ---
# jupyter:
# jupytext:
# text_representation:
# extension: .py
# format_name: light
# format_version: '1.5'
# jupytext_version: 1.13.6
# ---
# # Solve the Poisson and linearised elasticity equations using pyamg
#
# The demo illustrates solving the Poisson and linearised elasticity
# equations with using algebraic multigrid from
# [pyamg](https://github.com/pyamg/pyamg). It is implemented in
# {download}`demo_pyamg.py`.
#
# pyamg is not MPI-parallel, therefore this demo runs in serial only.
# +
import sys
from mpi4py import MPI
import numpy as np
import numpy.typing as npt
if MPI.COMM_WORLD.size > 1:
print("This demo works only in serial.")
exit(0)
try:
import pyamg
except (ImportError, AttributeError):
print('This demo requires pyamg, install using "pip install pyamg"')
exit(0)
import ufl
from dolfinx import fem, io
from dolfinx.fem import (
apply_lifting,
assemble_matrix,
assemble_vector,
dirichletbc,
form,
functionspace,
locate_dofs_topological,
)
from dolfinx.mesh import CellType, create_box, locate_entities_boundary
from ufl import ds, dx, grad, inner
# -
# +
def poisson_problem(dtype: npt.DTypeLike, solver_type: str):
"""Solve a 3D Poisson problem using Ruge-Stuben algebraic multigrid.
Args:
dtype: Scalar type to use.
solver_type: pyamg solver type, either "ruge_stuben" or "smoothed_aggregation"
"""
real_type = np.real(dtype(0)).dtype
mesh = create_box(
comm=MPI.COMM_WORLD,
points=[(0.0, 0.0, 0.0), (3.0, 2.0, 1.0)],
n=[30, 20, 10],
cell_type=CellType.tetrahedron,
dtype=real_type,
)
V = functionspace(mesh, ("Lagrange", 1))
facets = locate_entities_boundary(
mesh,
dim=(mesh.topology.dim - 1),
marker=lambda x: np.isclose(x[0], 0.0) | np.isclose(x[0], 3.0),
)
tdim = mesh.topology.dim
dofs = locate_dofs_topological(V=V, entity_dim=tdim - 1, entities=facets)
bc = dirichletbc(value=dtype(0), dofs=dofs, V=V)
u, v = ufl.TrialFunction(V), ufl.TestFunction(V)
x = ufl.SpatialCoordinate(mesh)
f = 10 * ufl.exp(-((x[0] - 0.5) ** 2 + (x[1] - 0.5) ** 2) / 0.02)
g = ufl.sin(5 * x[0])
a = form(inner(grad(u), grad(v)) * dx, dtype=dtype)
L = form(inner(f, v) * dx + inner(g, v) * ds, dtype=dtype)
A = assemble_matrix(a, [bc]).to_scipy()
b = assemble_vector(L)
apply_lifting(b.array, [a], bcs=[[bc]])
bc.set(b.array)
# Create solution function and create AMG solver
uh = fem.Function(V, dtype=dtype)
if solver_type == "ruge_stuben":
ml = pyamg.ruge_stuben_solver(A)
elif solver_type == "smoothed_aggregation":
ml = pyamg.smoothed_aggregation_solver(A)
else:
raise ValueError(f"Invalid multigrid type: {solver_type}")
print(ml)
# Solve linear systems
print(f"\nSolve Poisson equation: {dtype.__name__}")
res: list[float] = []
tol = 1e-10 if real_type == np.float64 else 1e-6
uh.x.array[:] = ml.solve(b.array, tol=tol, residuals=res, accel="cg")
for i, q in enumerate(res):
print(f"Convergence history: iteration {i}, residual= {q}")
with io.XDMFFile(mesh.comm, f"out_pyamg/poisson_{dtype.__name__}.xdmf", "w") as file:
file.write_mesh(mesh)
file.write_function(uh)
# -
# +
def nullspace_elasticty(Q: fem.FunctionSpace) -> list[np.ndarray]:
"""Create the elasticity (near)nulspace.
Args:
Q: Displacement field function space.
Returns:
Nullspace for the unconstrained problem.
"""
B = np.zeros((Q.dofmap.index_map.size_local * Q.dofmap.bs, 6))
# Get dof indices for each subspace (x, y and z dofs)
dofs = [Q.sub(i).dofmap.list.flatten() for i in range(3)]
# Set the three translational rigid body modes
for i in range(3):
B[dofs[i], i] = 1.0
# Set the three rotational rigid body modes
x = Q.tabulate_dof_coordinates()
dofs_block = Q.dofmap.list.flatten()
x0, x1, x2 = x[dofs_block, 0], x[dofs_block, 1], x[dofs_block, 2]
B[dofs[0], 3] = -x1
B[dofs[1], 3] = x0
B[dofs[0], 4] = x2
B[dofs[2], 4] = -x0
B[dofs[2], 5] = x1
B[dofs[1], 5] = -x2
return B
# -
# +
def elasticity_problem(dtype):
"""Solve a 3D linearised elasticity problem using a smoothed
aggregation algebraic multigrid method.
Args:
dtype: Scalar type to use.
"""
mesh = create_box(
comm=MPI.COMM_WORLD,
points=[(0.0, 0.0, 0.0), (3.0, 2.0, 1.0)],
n=[30, 20, 10],
cell_type=CellType.tetrahedron,
dtype=dtype,
)
facets = locate_entities_boundary(
mesh,
dim=(mesh.topology.dim - 1),
marker=lambda x: np.isclose(x[0], 0.0) | np.isclose(x[0], 3.0),
)
ω, ρ = 300.0, 10.0
x = ufl.SpatialCoordinate(mesh)
f = ufl.as_vector((ρ * ω**2 * x[0], ρ * ω**2 * x[1], 0.0))
# Define the elasticity parameters and create a function that
# computes an expression for the stress given a displacement field.
E = 1.0e9
ν = 0.3
μ = E / (2.0 * (1.0 + ν))
λ = E * ν / ((1.0 + ν) * (1.0 - 2.0 * ν))
def σ(v):
"""Return an expression for the stress σ given a displacement field"""
return 2.0 * μ * ufl.sym(grad(v)) + λ * ufl.tr(ufl.sym(grad(v))) * ufl.Identity(len(v))
V = functionspace(mesh, ("Lagrange", 1, (mesh.geometry.dim,)))
u, v = ufl.TrialFunction(V), ufl.TestFunction(V)
a = form(inner(σ(u), grad(v)) * dx, dtype=dtype)
L = form(inner(f, v) * dx, dtype=dtype)
tdim = mesh.topology.dim
dofs = locate_dofs_topological(V=V, entity_dim=tdim - 1, entities=facets)
bc = dirichletbc(np.zeros(3, dtype=dtype), dofs, V=V)
A = assemble_matrix(a, bcs=[bc]).to_scipy()
b = assemble_vector(L)
apply_lifting(b.array, [a], bcs=[[bc]])
bc.set(b.array)
uh = fem.Function(V, dtype=dtype)
B = nullspace_elasticty(V)
ml = pyamg.smoothed_aggregation_solver(A, B=B)
print(ml)
print(f"\nLinearised elasticity: {dtype.__name__}")
res_e: list[float] = []
tol = 1e-10 if dtype == np.float64 else 1e-6
uh.x.array[:] = ml.solve(b.array, tol=tol, residuals=res_e, accel="cg")
for i, q in enumerate(res_e):
print(f"Convergence history: iteration {i}, residual= {q}")
with io.XDMFFile(mesh.comm, f"out_pyamg/elasticity_{dtype.__name__}.xdmf", "w") as file:
file.write_mesh(mesh)
file.write_function(uh)
# -
# Solve Poission problem with different scalar types
poisson_problem(np.float32, "ruge_stuben")
poisson_problem(np.float64, "ruge_stuben")
# For complex, pyamg requires smoothed aggregation multigrid
if not sys.platform.startswith("win32"):
poisson_problem(np.complex64, "smoothed_aggregation")
poisson_problem(np.complex128, "smoothed_aggregation")
# Solve elasticity problem with different scalar types
elasticity_problem(np.float32)
elasticity_problem(np.float64)
# -
|