--- jupytext: main_language: python text_representation: extension: .md format_name: myst format_version: 0.13 jupytext_version: 1.16.1 --- (demo-static-condensation)= # Static condensation of linear elasticity Copyright (C) 2020 Michal Habera and Andreas Zilian This demo solves a Cook's plane stress elasticity test in a mixed space formulation. The test is a sloped cantilever under upward traction force at free end. Static condensation of internal (stress) degrees-of-freedom is demonstrated. ```python from pathlib import Path from mpi4py import MPI from petsc4py import PETSc import cffi import numba import numba.core.typing.cffi_utils as cffi_support import numpy as np import ufl from basix.ufl import element from dolfinx import geometry from dolfinx.fem import ( Form, Function, IntegralType, dirichletbc, form, form_cpp_class, functionspace, locate_dofs_topological, ) from dolfinx.fem.petsc import apply_lifting, assemble_matrix, assemble_vector, set_bc from dolfinx.io import XDMFFile from dolfinx.jit import ffcx_jit from dolfinx.mesh import locate_entities_boundary, meshtags from ffcx.codegeneration.utils import numba_ufcx_kernel_signature as ufcx_signature if np.issubdtype(PETSc.RealType, np.float32): # type: ignore print("float32 not yet supported for this demo.") exit(0) infile = XDMFFile( MPI.COMM_WORLD, Path(Path(__file__).parent, "data", "cooks_tri_mesh.xdmf"), "r", encoding=XDMFFile.Encoding.ASCII, ) msh = infile.read_mesh(name="Grid") infile.close() # Stress (Se) and displacement (Ue) elements Se = element("DG", msh.basix_cell(), 1, shape=(2, 2), symmetry=True, dtype=PETSc.RealType) # type: ignore Ue = element("Lagrange", msh.basix_cell(), 2, shape=(2,), dtype=PETSc.RealType) # type: ignore S = functionspace(msh, Se) U = functionspace(msh, Ue) sigma, tau = ufl.TrialFunction(S), ufl.TestFunction(S) u, v = ufl.TrialFunction(U), ufl.TestFunction(U) # Locate all facets at the free end and assign them value 1. Sort the # facet indices (requirement for constructing MeshTags) free_end_facets = np.sort(locate_entities_boundary(msh, 1, lambda x: np.isclose(x[0], 48.0))) mt = meshtags(msh, 1, free_end_facets, 1) ds = ufl.Measure("ds", subdomain_data=mt) # Homogeneous boundary condition in displacement u_bc = Function(U) u_bc.x.array[:] = 0 # Displacement BC is applied to the left side left_facets = locate_entities_boundary(msh, 1, lambda x: np.isclose(x[0], 0.0)) bdofs = locate_dofs_topological(U, 1, left_facets) bc = dirichletbc(u_bc, bdofs) # Elastic stiffness tensor and Poisson ratio E, nu = 1.0, 1.0 / 3.0 def sigma_u(u): """Constitutive relation for stress-strain. Assuming plane-stress in XY""" eps = 0.5 * (ufl.grad(u) + ufl.grad(u).T) sigma = E / (1.0 - nu**2) * ((1.0 - nu) * eps + nu * ufl.Identity(2) * ufl.tr(eps)) return sigma a00 = ufl.inner(sigma, tau) * ufl.dx a10 = -ufl.inner(sigma, ufl.grad(v)) * ufl.dx a01 = -ufl.inner(sigma_u(u), tau) * ufl.dx f = ufl.as_vector([0.0, 1.0 / 16]) b1 = form(-ufl.inner(f, v) * ds(1), dtype=PETSc.ScalarType) # type: ignore # JIT compile individual blocks tabulation kernels ufcx00, _, _ = ffcx_jit(msh.comm, a00, form_compiler_options={"scalar_type": PETSc.ScalarType}) # type: ignore kernel00 = getattr(ufcx00.form_integrals[0], f"tabulate_tensor_{np.dtype(PETSc.ScalarType).name}") # type: ignore ufcx01, _, _ = ffcx_jit(msh.comm, a01, form_compiler_options={"scalar_type": PETSc.ScalarType}) # type: ignore kernel01 = getattr(ufcx01.form_integrals[0], f"tabulate_tensor_{np.dtype(PETSc.ScalarType).name}") # type: ignore ufcx10, _, _ = ffcx_jit(msh.comm, a10, form_compiler_options={"scalar_type": PETSc.ScalarType}) # type: ignore kernel10 = getattr(ufcx10.form_integrals[0], f"tabulate_tensor_{np.dtype(PETSc.ScalarType).name}") # type: ignore ffi = cffi.FFI() cffi_support.register_type(ffi.typeof("double _Complex"), numba.types.complex128) # Get local dofmap sizes for later local tensor tabulations Ssize = S.element.space_dimension Usize = U.element.space_dimension @numba.cfunc(ufcx_signature(PETSc.ScalarType, PETSc.RealType), nopython=True) # type: ignore def tabulate_A(A_, w_, c_, coords_, entity_local_index, permutation=ffi.NULL): """Element kernel that applies static condensation.""" # Prepare target condensed local element tensor A = numba.carray(A_, (Usize, Usize), dtype=PETSc.ScalarType) # Tabulate all sub blocks locally A00 = np.zeros((Ssize, Ssize), dtype=PETSc.ScalarType) kernel00(ffi.from_buffer(A00), w_, c_, coords_, entity_local_index, permutation) A01 = np.zeros((Ssize, Usize), dtype=PETSc.ScalarType) kernel01(ffi.from_buffer(A01), w_, c_, coords_, entity_local_index, permutation) A10 = np.zeros((Usize, Ssize), dtype=PETSc.ScalarType) kernel10(ffi.from_buffer(A10), w_, c_, coords_, entity_local_index, permutation) # A = - A10 * A00^{-1} * A01 A[:, :] = -A10 @ np.linalg.solve(A00, A01) # Prepare a Form with a condensed tabulation kernel formtype = form_cpp_class(PETSc.ScalarType) # type: ignore cells = np.arange(msh.topology.index_map(msh.topology.dim).size_local) integrals = {IntegralType.cell: [(-1, tabulate_A.address, cells)]} a_cond = Form(formtype([U._cpp_object, U._cpp_object], integrals, [], [], False, {}, None)) A_cond = assemble_matrix(a_cond, bcs=[bc]) A_cond.assemble() b = assemble_vector(b1) apply_lifting(b, [a_cond], bcs=[[bc]]) b.ghostUpdate(addv=PETSc.InsertMode.ADD, mode=PETSc.ScatterMode.REVERSE) # type: ignore set_bc(b, [bc]) uc = Function(U) solver = PETSc.KSP().create(A_cond.getComm()) # type: ignore solver.setOperators(A_cond) solver.solve(b, uc.x.petsc_vec) # Pure displacement based formulation a = form(-ufl.inner(sigma_u(u), ufl.grad(v)) * ufl.dx) A = assemble_matrix(a, bcs=[bc]) A.assemble() # Create bounding box for function evaluation bb_tree = geometry.bb_tree(msh, 2) # Check against standard table value p = np.array([[48.0, 52.0, 0.0]], dtype=np.float64) cell_candidates = geometry.compute_collisions_points(bb_tree, p) cells = geometry.compute_colliding_cells(msh, cell_candidates, p).array uc.x.scatter_forward() if len(cells) > 0: value = uc.eval(p, cells[0]) print(value[1]) assert np.isclose(value[1], 23.95, rtol=1.0e-2) # Check the equality of displacement based and mixed condensed global # matrices, i.e. check that condensation is exact assert np.isclose((A - A_cond).norm(), 0.0) ```