def hyperelasticity(domain, q, p, nf=0):
# Based on https://github.com/firedrakeproject/firedrake-bench/blob/experiments/forms/firedrake_forms.py
V = ufl.FunctionSpace(domain, ufl.VectorElement('P', domain.ufl_cell(), q))
P = ufl.FunctionSpace(domain, ufl.VectorElement('P', domain.ufl_cell(), p))
v = ufl.TestFunction(V)
du = ufl.TrialFunction(V) # Incremental displacement
u = ufl.Coefficient(V) # Displacement from previous iteration
B = ufl.Coefficient(V) # Body force per unit mass
# Kinematics
I = ufl.Identity(domain.ufl_cell().topological_dimension())
F = I + ufl.grad(u) # Deformation gradient
C = F.T*F # Right Cauchy-Green tensor
E = (C - I)/2 # Euler-Lagrange strain tensor
E = ufl.variable(E)
# Material constants
mu = ufl.Constant(domain) # Lame's constants
lmbda = ufl.Constant(domain)
# Strain energy function (material model)
psi = lmbda/2*(ufl.tr(E)**2) + mu*ufl.tr(E*E)
S = ufl.diff(psi, E) # Second Piola-Kirchhoff stress tensor
PK = F*S # First Piola-Kirchoff stress tensor
# Variational problem
it = ufl.inner(PK, ufl.grad(v)) - ufl.inner(B, v)
f = [ufl.Coefficient(P) for _ in range(nf)]
return ufl.derivative(reduce(ufl.inner,
list(map(ufl.div, f)) + [it])*ufl.dx, u, du)
def stf3d2(rank2_2d):
r"""
Return the 3D symmetric and trace-free part of a 2D 2-tensor.
.. warning::
Return a 2-tensor with the same dimensions as the input tensor.
For the :math:`2 \times 2` case, return the 3D symmetric and
trace-free (dev(sym(.)))
:math:`B \in \mathbb{R}^{2 \times 2}`
of the 2D 2-tensor
:math:`A \in \mathbb{R}^{2 \times 2}`.
.. math::
A &= \begin{pmatrix}
a_{xx} & a_{xy} \\
a_{yx} & a_{yy}
\end{pmatrix}
\\
B &= (A)_\mathrm{dev} = \frac{1}{2} (A)_\mathrm{sym}
- \frac{1}{3} \mathrm{tr}(A) I_{2 \times 2}
"""
dim = len(rank2_2d[:, 0])
symm = 1 / 2 * (rank2_2d + ufl.transpose(rank2_2d))
return symm - (1 / 3) * ufl.tr(symm) * ufl.Identity(dim)
def stress0(self, u):
strain = self.eps(u)
lmbda = self.lmbda
mu = self.mu
sigma = 2 * mu * strain + lmbda * ufl.tr(strain) * ufl.Identity(
self.model_dimension)
return sigma
def T(v, p):
"""Constitutive relation for Bingham - Cauchy stress as a function of velocity and pressure."""
# Deviatoric strain rate
D_ = ufl.dev(D(v)) # == D(v) if div(v)=0
# Second invariant
rJ2_ = rJ2(D_)
# Regularisation
mu_effective = mu + tau_zero * 1.0 / (2. * (rJ2_ + tau_zero_regularisation))
# Cauchy stress
T = -p * ufl.Identity(2) + 2.0 * mu_effective * D_
return T
def problem():
mesh = dolfin.UnitCubeMesh(MPI.comm_world, 10, 10, 10)
cell = mesh.ufl_cell()
vec_element = dolfin.VectorElement("Lagrange", cell, 1)
# scl_element = dolfin.FiniteElement("Lagrange", cell, 1)
Q = dolfin.FunctionSpace(mesh, vec_element)
# Qs = dolfin.FunctionSpace(mesh, scl_element)
# Coefficients
v = dolfin.function.argument.TestFunction(Q) # Test function
du = dolfin.function.argument.TrialFunction(Q) # Incremental displacement
u = dolfin.Function(Q) # Displacement from previous iteration
B = dolfin.Constant((0.0, -0.5, 0.0), cell) # Body force per unit volume
T = dolfin.Constant((0.1, 0.0, 0.0),
cell) # Traction force on the boundary
# B, T = dolfin.Function(Q), dolfin.Function(Q)
# Kinematics
d = u.geometric_dimension()
F = ufl.Identity(d) + grad(u) # Deformation gradient
C = F.T * F # Right Cauchy-Green tensor
# Invariants of deformation tensors
Ic = tr(C)
J = det(F)
# Elasticity parameters
E, nu = 10.0, 0.3
mu = dolfin.Constant(E / (2 * (1 + nu)), cell)
lmbda = dolfin.Constant(E * nu / ((1 + nu) * (1 - 2 * nu)), cell)
# mu, lmbda = dolfin.Function(Qs), dolfin.Function(Qs)
# Stored strain energy density (compressible neo-Hookean model)
psi = (mu / 2) * (Ic - 3) - mu * ln(J) + (lmbda / 2) * (ln(J))**2
# Total potential energy
Pi = psi * dx - dot(B, u) * dx - dot(T, u) * ds
# Compute first variation of Pi (directional derivative about u in the direction of v)
F = ufl.derivative(Pi, u, v)
# Compute Jacobian of F
J = ufl.derivative(F, u, du)
return J, F
def eigenstate_legacy(A):
"""Eigenvalues and eigenprojectors of the 3x3 (real-valued) tensor A.
Provides the spectral decomposition A = sum_{a=0}^{2} λ_a * E_a
with eigenvalues λ_a and their associated eigenprojectors E_a = n_a^R x n_a^L
ordered by magnitude.
The eigenprojectors of eigenvalues with multiplicity n are returned as 1/n-fold projector.
Note: Tensor A must not have complex eigenvalues!
"""
if ufl.shape(A) != (3, 3):
raise RuntimeError(
f"Tensor A of shape {ufl.shape(A)} != (3, 3) is not supported!")
#
eps = 1.0e-10
#
A = ufl.variable(A)
#
# --- determine eigenvalues λ0, λ1, λ2
#
# additively decompose: A = tr(A) / 3 * I + dev(A) = q * I + B
q = ufl.tr(A) / 3
B = A - q * ufl.Identity(3)
# observe: det(λI - A) = 0 with shift λ = q + ω --> det(ωI - B) = 0 = ω**3 - j * ω - b
j = ufl.tr(
B * B
) / 2 # == -I2(B) for trace-free B, j < 0 indicates A has complex eigenvalues
b = ufl.tr(B * B * B) / 3 # == I3(B) for trace-free B
# solve: 0 = ω**3 - j * ω - b by substitution ω = p * cos(phi)
# 0 = p**3 * cos**3(phi) - j * p * cos(phi) - b | * 4 / p**3
# 0 = 4 * cos**3(phi) - 3 * cos(phi) - 4 * b / p**3 | --> p := sqrt(j * 4 / 3)
# 0 = cos(3 * phi) - 4 * b / p**3
# 0 = cos(3 * phi) - r with -1 <= r <= +1
# phi_k = [acos(r) + (k + 1) * 2 * pi] / 3 for k = 0, 1, 2
p = 2 / ufl.sqrt(3) * ufl.sqrt(j + eps**2) # eps: MMM
r = 4 * b / p**3
r = ufl.Max(ufl.Min(r, +1 - eps), -1 + eps) # eps: LMM, MMH
phi = ufl.acos(r) / 3
# sorted eigenvalues: λ0 <= λ1 <= λ2
λ0 = q + p * ufl.cos(phi + 2 / 3 * ufl.pi) # low
λ1 = q + p * ufl.cos(phi + 4 / 3 * ufl.pi) # middle
λ2 = q + p * ufl.cos(phi) # high
#
# --- determine eigenprojectors E0, E1, E2
#
E0 = ufl.diff(λ0, A).T
E1 = ufl.diff(λ1, A).T
E2 = ufl.diff(λ2, A).T
#
return [λ0, λ1, λ2], [E0, E1, E2]
def hyperelasticity_action_forms(mesh, vec_el):
cell = mesh.ufl_cell()
Q = dolfin.FunctionSpace(mesh, vec_el)
# Coefficients
v = dolfin.function.argument.TestFunction(Q) # Test function
du = dolfin.function.argument.TrialFunction(Q) # Incremental displacement
u = dolfin.Function(Q) # Displacement from previous iteration
u.vector().set(0.5)
B = dolfin.Constant((0.0, -0.5, 0.0), cell) # Body force per unit volume
T = dolfin.Constant((0.1, 0.0, 0.0), cell) # Traction force on the boundary
# Kinematics
d = u.geometric_dimension()
F = ufl.Identity(d) + grad(u) # Deformation gradient
C = F.T * F # Right Cauchy-Green tensor
# Invariants of deformation tensors
Ic = tr(C)
J = det(F)
# Elasticity parameters
E, nu = 10.0, 0.3
mu = dolfin.Constant(E / (2 * (1 + nu)), cell)
lmbda = dolfin.Constant(E * nu / ((1 + nu) * (1 - 2 * nu)), cell)
# Stored strain energy density (compressible neo-Hookean model)
psi = (mu / 2) * (Ic - 3) - mu * ln(J) + (lmbda / 2) * (ln(J)) ** 2
# Total potential energy
Pi = psi * dx - dot(B, u) * dx - dot(T, u) * ds
# Compute first variation of Pi (directional derivative about u in the direction of v)
F = ufl.derivative(Pi, u, v)
# Compute Jacobian of F
J = ufl.derivative(F, u, du)
w = dolfin.Function(Q)
w.vector().set(1.2)
L = ufl.action(J, w)
return None, L, None
def test_metric_math(dim):
"""
Check that the metric exponential and
metric logarithm are indeed inverses.
"""
mesh = uniform_mesh(dim, 1)
P0_ten = firedrake.TensorFunctionSpace(mesh, "DG", 0)
I = ufl.Identity(dim)
M = firedrake.interpolate(2 * I, P0_ten)
logM = metric_logarithm(M)
expected = firedrake.interpolate(np.log(2) * I, P0_ten)
assert np.allclose(logM.dat.data, expected.dat.data)
M_ = metric_exponential(logM)
assert np.allclose(M.dat.data, M_.dat.data)
expM = metric_exponential(M)
expected = firedrake.interpolate(np.exp(2) * I, P0_ten)
assert np.allclose(expM.dat.data, expected.dat.data)
M_ = metric_logarithm(expM)
assert np.allclose(M.dat.data, M_.dat.data)
def eig(A):
"""Eigenvalues of 3x3 tensor"""
eps = 1.0e-12
q = ufl.tr(A) / 3.0
p1 = 0.5 * (A[0, 1]**2 + A[1, 0]**2 + A[0, 2]**2 + A[2, 0]**2 +
A[1, 2]**2 + A[2, 1]**2)
p2 = (A[0, 0] - q)**2 + (A[1, 1] - q)**2 + (A[2, 2] - q)**2 + 2 * p1
p = ufl.sqrt(p2 / 6)
B = (A - q * ufl.Identity(3))
r = ufl.det(B) / (2 * p**3)
r = ufl.Max(ufl.Min(r, 1.0 - eps), -1.0 + eps)
phi = ufl.acos(r) / 3.0
eig0 = ufl.conditional(p2 < eps, q, q + 2 * p * ufl.cos(phi))
eig2 = ufl.conditional(p2 < eps, q,
q + 2 * p * ufl.cos(phi + (2 * numpy.pi / 3)))
eig1 = ufl.conditional(p2 < eps, q, 3 * q - eig0 -
eig2) # since trace(A) = eig1 + eig2 + eig3
return eig0, eig1, eig2
def eps_sh_au(t):
"""Autogeneous shrinkage strain
Parameters
----------
t: Time [days]
Note
----
The Book, page 722, formulas (D.17, D.18, D.19, D.20)
with parameters for cement type from table D.4
"""
if args.ct == "R":
r_alpha = 1.0
r_eps = -3.5
eps_aucem = 210 * 1.0e-6
t_aucem = 1.0
elif args.ct == "RS":
r_alpha = 1.40
r_eps = -3.5
eps_aucem = -84 * 1.0e-6
t_aucem = 41.0
elif args.ct == "SL":
r_alpha = 1.0
r_eps = -3.5
eps_aucem = 0.0
t_aucem = 1.0
# Autogeneous shrinkage
eps_infty_sh_au = (eps_aucem * (ac / 6.0)**-0.75 * (wc / 0.38)**r_eps)
tau_au = t_aucem * (wc / 0.38)**3.0
au_alpha = r_alpha * wc / 0.38
return -eps_infty_sh_au * (1.0 +
(tau_au / t)**au_alpha)**-4.5 * ufl.Identity(3)
def D_rebar_map(A):
"""Unit stiffness tensor (rebars) mapping strain -> stress."""
return lambda_rebar_ * ufl.tr(A) * ufl.Identity(3) + 2 * mu_rebar * A
def sigma_law(u):
return lame[0] * ufl.nabla_div(u) * ufl.Identity(
2) + 2 * lame[1] * symgrad(u)
def sigma(v):
return (1/(1+Nu))*strain(v) + ((1*Nu)/((1+Nu)*(1-2*Nu)))*ufl.tr(strain(v))*ufl.Identity(v.geometric_dimension()) #v.cell().d
m, δm = [u], [δu]
# Boundary conditions
alpha, u2 = 0.25 * np.pi / 8, 0.40
def u_bar(x):
return np.array([x[2] * (x[0] - (x[0] * np.cos(alpha) - x[1] * np.sin(alpha))),
x[2] * (x[1] - (x[0] * np.sin(alpha) + x[1] * np.cos(alpha))),
x[2] * u2])
u_.interpolate(u_bar)
# Kinematics
F = ufl.Identity(3) + ufl.grad(u)
C = F.T * F
# C = F.T + F - ufl.Identity(3) # linearised C
# Spectral decomposition of C
(c0, c1, c2), (E0, E1, E2) = dolfiny.invariants.eigenstate(C)
# Squares of principal stretches
c = ufl.as_vector([c0, c1, c2])
c = ufl.variable(c)
# Variation of squares of principal stretches
δc = dolfiny.expression.derivative(c, m, δm)
# Elasticity parameters
E = dolfinx.fem.Constant(mesh, 10.0)
nu = dolfinx.fem.Constant(mesh, 0.4)
mu = E / (2 * (1 + nu))
a11 = None
L0 = ufl.inner(f, v) * ufl.dx
L1 = ufl.inner(dolfinx.fem.Constant(mesh, PETSc.ScalarType(0.0)), q) * ufl.dx
# No prescribed shear stress
n = ufl.FacetNormal(mesh)
g_tau = tangential_proj(dolfinx.fem.Constant(
mesh, PETSc.ScalarType(((0, 0), (0, 0)))) * n, n)
ds = ufl.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
a00 -= ufl.inner(ufl.outer(n, n) * ufl.dot(2 * mu * sym_grad(u), n), v) * ds
a01 -= ufl.inner(ufl.outer(n, n) * ufl.dot(
- p * ufl.Identity(u.ufl_shape[0]), n), v) * ds
L0 += ufl.inner(g_tau, v) * ds
a = [[dolfinx.fem.form(a00), dolfinx.fem.form(a01)],
[dolfinx.fem.form(a10), dolfinx.fem.form(a11)]]
L = [dolfinx.fem.form(L0), dolfinx.fem.form(L1)]
# Assemble LHS matrix and RHS vector
with dolfinx.common.Timer("~Stokes: Assemble LHS and RHS"):
A = dolfinx_mpc.create_matrix_nest(a, [mpc, mpc_q])
dolfinx_mpc.assemble_matrix_nest(A, a, [mpc, mpc_q], bcs)
A.assemble()
b = dolfinx_mpc.create_vector_nest(L, [mpc, mpc_q])
dolfinx_mpc.assemble_vector_nest(b, L, [mpc, mpc_q])
def sigma_u(u):
"""Consitutive relation for stress-strain. Assuming plane-stress in XY"""
eps = 0.5 * (ufl.grad(u) + ufl.grad(u).T)
sigma = E / (1. - nu**2) * (
(1. - nu) * eps + nu * ufl.Identity(2) * ufl.tr(eps))
return sigma
def sigma(v):
return (2.0 * mu * ufl.sym(ufl.grad(v))
+ lmbda * ufl.tr(ufl.sym(ufl.grad(v))) * ufl.Identity(len(v)))
def D_map(A):
"""Unit stiffness tensor mapping strain -> stress."""
return lambda_ * ufl.tr(A) * ufl.Identity(3) + 2 * mu * A
# Jacobi matrix of map reference -> undeformed
J0 = ufl.geometry.Jacobian(mesh)
# Tangent basis
gs = J0[:, 0]
gη = ufl.as_vector([0, 1, 0]) # unit vector e_y (assume curve in x-z plane)
gξ = ufl.cross(gs, gη)
# Unit tangent basis
gs /= ufl.sqrt(ufl.dot(gs, gs))
gη /= ufl.sqrt(ufl.dot(gη, gη))
gξ /= ufl.sqrt(ufl.dot(gξ, gξ))
# Interpolate normal vector
dolfiny.interpolation.interpolate(gξ, n0i)
# ----------------------------------------------------------------------------
# Orthogonal projection operator (assumes sufficient geometry approximation)
P = ufl.Identity(mesh.geometry.dim) - ufl.outer(n0i, n0i)
# Thickness variable
X = dolfinx.FunctionSpace(mesh, ("DG", q))
ξ = dolfinx.Function(X, name='ξ')
# Undeformed configuration: director d0 and placement b0
d0 = n0i # normal of manifold mesh, interpolated
b0 = x0 + ξ * d0
# Deformed configuration: director d and placement b, assumed kinematics, director uses rotation matrix
d = ufl.as_matrix([[ufl.cos(r), 0, ufl.sin(r)], [0, 1, 0],
[-ufl.sin(r), 0, ufl.cos(r)]]) * d0
b = x0 + ufl.as_vector([u, 0, w]) + ξ * d
# Configuration gradient, undeformed configuration
def assemble_test(cell_batch_size: int):
mesh = dolfin.UnitCubeMesh(MPI.comm_world, 40, 40, 40)
def isochoric(F):
C = F.T*F
I_1 = tr(C)
I4_f = dot(e_f, C*e_f)
I4_s = dot(e_s, C*e_s)
I8_fs = dot(e_f, C*e_s)
def cutoff(x):
return 1.0/(1.0 + ufl.exp(-(x - 1.0)*30.0))
def scaled_exp(a0, a1, argument):
return a0/(2.0*a1)*(ufl.exp(b*argument) - 1)
E_1 = scaled_exp(a, b, I_1 - 3.)
E_f = cutoff(I4_f)*scaled_exp(a_f, b_f, (I4_f - 1.)**2)
E_s = cutoff(I4_s)*scaled_exp(a_s, b_s, (I4_s - 1.)**2)
E_3 = scaled_exp(a_fs, b_fs, I8_fs**2)
E = E_1 + E_f + E_s + E_3
return E
cell = mesh.ufl_cell()
lamda = dolfin.Constant(0.48, cell)
a = dolfin.Constant(1.0, cell)
b = dolfin.Constant(1.0, cell)
a_s = dolfin.Constant(1.0, cell)
b_s = dolfin.Constant(1.0, cell)
a_f = dolfin.Constant(1.0, cell)
b_f = dolfin.Constant(1.0, cell)
a_fs = dolfin.Constant(1.0, cell)
b_fs = dolfin.Constant(1.0, cell)
# For more fun, make these general vector fields rather than
# constants:
e_s = dolfin.Constant([0.0, 1.0, 0.0], cell)
e_f = dolfin.Constant([1.0, 0.0, 0.0], cell)
V = dolfin.FunctionSpace(mesh, ufl.VectorElement("CG", cell, 1))
u = dolfin.Function(V)
du = dolfin.function.argument.TrialFunction(V)
v = dolfin.function.argument.TestFunction(V)
# Misc elasticity related tensors and other quantities
F = grad(u) + ufl.Identity(3)
F = ufl.variable(F)
J = det(F)
Fbar = J**(-1.0/3.0)*F
# Define energy
E_volumetric = lamda*0.5*ln(J)**2
psi = isochoric(Fbar) + E_volumetric
# Find first Piola-Kircchoff tensor
P = ufl.diff(psi, F)
# Define the variational formulation
F = inner(P, grad(v))*dx
# Take the derivative
J = ufl.derivative(F, u, du)
a, L = J, F
if cell_batch_size > 1:
cxx_flags = "-O2 -ftree-vectorize -funroll-loops -march=native -mtune=native"
else:
cxx_flags = "-O2"
assembler = dolfin.fem.assembling.Assembler([[a]], [L], [],
form_compiler_parameters={"cell_batch_size": cell_batch_size,
"enable_cross_cell_gcc_ext": True,
"cpp_optimize_flags": cxx_flags})
t = -time.time()
A, b = assembler.assemble(
mat_type=dolfin.cpp.fem.Assembler.BlockType.monolithic)
t += time.time()
return A, b, t
def test_neohooke():
mesh = dolfinx.mesh.create_unit_cube(MPI.COMM_WORLD, 7, 7, 7)
V = dolfinx.fem.VectorFunctionSpace(mesh, ("P", 1))
P = dolfinx.fem.FunctionSpace(mesh, ("P", 1))
L = dolfinx.fem.FunctionSpace(mesh, ("DG", 0))
u = dolfinx.fem.Function(V, name="u")
v = ufl.TestFunction(V)
p = dolfinx.fem.Function(P, name="p")
q = ufl.TestFunction(P)
lmbda0 = dolfinx.fem.Function(L)
d = mesh.topology.dim
Id = ufl.Identity(d)
F = Id + ufl.grad(u)
C = F.T * F
J = ufl.det(F)
E_, nu_ = 10.0, 0.3
mu, lmbda = E_ / (2 * (1 + nu_)), E_ * nu_ / ((1 + nu_) * (1 - 2 * nu_))
psi = (mu / 2) * (ufl.tr(C) -
3) - mu * ufl.ln(J) + lmbda / 2 * ufl.ln(J)**2 + (p -
1.0)**2
pi = psi * ufl.dx
F0 = ufl.derivative(pi, u, v)
F1 = ufl.derivative(pi, p, q)
# Number of eigenvalues to find
nev = 8
opts = PETSc.Options("neohooke")
opts["eps_smallest_magnitude"] = True
opts["eps_nev"] = nev
opts["eps_ncv"] = 50 * nev
opts["eps_conv_abs"] = True
# opts["eps_non_hermitian"] = True
opts["eps_tol"] = 1.0e-14
opts["eps_max_it"] = 1000
opts["eps_error_relative"] = "ascii::ascii_info_detail"
opts["eps_monitor"] = "ascii"
slepcp = dolfiny.slepcblockproblem.SLEPcBlockProblem([F0, F1], [u, p],
lmbda0,
prefix="neohooke")
slepcp.solve()
# mat = dolfiny.la.petsc_to_scipy(slepcp.eps.getOperators()[0])
# eigvals, eigvecs = linalg.eigsh(mat, which="SM", k=nev)
with dolfinx.io.XDMFFile(MPI.COMM_WORLD, "eigvec.xdmf", "w") as ofile:
ofile.write_mesh(mesh)
for i in range(nev):
eigval, ur, ui = slepcp.getEigenpair(i)
# Expect first 6 eignevalues 0, i.e. rigid body modes
if i < 6:
assert np.isclose(eigval, 0.0)
for func in ur:
name = func.name
func.name = f"{name}_eigvec_{i}_real"
ofile.write_function(func)
func.name = name
def T(u: Expr, p: Expr, mu: Expr):
return 2 * mu * sym_grad(u) - p * ufl.Identity(u.ufl_shape[0])
def sigma(v):
return 2.0*mu*epsilon(v) + lmbda*ufl.tr(epsilon(v)) \
* ufl.Identity(v.geometric_dimension())
def S(tau):
return tau - ufl.Identity(2) * ufl.tr(tau)
u = dolfinx.fem.Function(Uf, name="u")
ut = dolfinx.fem.Function(Uf, name="ut")
utt = dolfinx.fem.Function(Uf, name="utt")
u_ = dolfinx.fem.Function(Uf, name="u_") # boundary conditions
δu = ufl.TestFunction(Uf)
# Define state and rate as (ordered) list of functions
m, mt, mtt, δm = [u], [ut], [utt], [δu]
# Time integrator
odeint = dolfiny.odeint.ODEInt2(t=time, dt=dt, x=m, xt=mt, xtt=mtt, rho=0.95)
# Configuration gradient
I = ufl.Identity(u.geometric_dimension()) # noqa: E741
F = I + ufl.grad(u) # deformation gradient as function of displacement
# Strain measures
# E = E(u) total strain
E = 1 / 2 * (F.T * F - I)
# S = S(E) stress
S = 2 * mu * E + la * ufl.tr(E) * I
# Variation of rate of Green-Lagrange strain
δE = dolfiny.expression.derivative(E, m, δm)
# Weak form (as one-form)
f = ufl.inner(δu, rho * utt) * dx + ufl.inner(δu, eta * ut) * dx \
+ ufl.inner(δE, S) * dx \
- ufl.inner(δu, rho * b) * dx
def compile_forms(iv0,
iv1,
w0,
w1,
f,
g,
heat_flux,
water_flux,
co2_flux,
t,
dt,
reb_dx,
con_dx,
damage_off=False,
randomize=0.0):
"""Return Jacobian and residual forms"""
t0 = time()
mesh = w0["displ"].function_space.mesh
# Prepare zero initial guesses, test and trial fctions, global
w_displ_trial = ufl.TrialFunction(w0["displ"].function_space)
w_displ_test = ufl.TestFunction(w0["displ"].function_space)
w_temp_trial = ufl.TrialFunction(w0["temp"].function_space)
w_temp_test = ufl.TestFunction(w0["temp"].function_space)
w_phi_trial = ufl.TrialFunction(w0["phi"].function_space)
w_phi_test = ufl.TestFunction(w0["phi"].function_space)
w_co2_trial = ufl.TrialFunction(w0["co2"].function_space)
w_co2_test = ufl.TestFunction(w0["co2"].function_space)
#
# Creep, shrinkage strains
#
# Autogenous shrinkage increment
deps_sh_au = (mps.eps_sh_au(t + dt) - mps.eps_sh_au(t))
# Thermal strain increment
deps_th = (misc.beta_C * (w1["temp"] - w0["temp"]) * ufl.Identity(3))
# Drying shrinkage increment
deps_sh_dr = (mps.k_sh * (w1["phi"] - w0["phi"]) * ufl.Identity(3))
eta_dash_mid = mps.eta_dash(iv0["eta_dash"], dt / 2.0, w0["temp"],
w0["phi"])
# Prepare creep factors
beta_cr = mps.beta_cr(dt)
lambda_cr = mps.lambda_cr(dt, beta_cr)
creep_v_mid = mps.creep_v(t + dt / 2.0)
if randomize > 0.0:
# Randomize Young's modulus
# This helps convergence at the point where crack initiation begins
# Randomized E fluctuates uniformly in [E-eps/2, E+eps/2]
rnd = Function(iv0["eta_dash"].function_space)
rnd.vector.array[:] = 1.0 - randomize / 2 + np.random.rand(
*rnd.vector.array.shape) * randomize
else:
rnd = 1.0
E_kelv = rnd * mps.E_kelv(creep_v_mid, lambda_cr, dt, t, eta_dash_mid)
gamma0 = []
for i in range(mps.M):
gamma0.append(iv0[f"gamma_{i}"])
deps_cr_kel = mps.deps_cr_kel(beta_cr, gamma0, creep_v_mid)
deps_cr_dash = mps.deps_cr_dash(iv0["sigma"], eta_dash_mid, dt)
deps_el = mech.eps_el(w1["displ"] - w0["displ"], deps_th, deps_cr_kel,
deps_cr_dash, deps_sh_dr, deps_sh_au)
# Water vapour saturation pressure
p_sat = water.p_sat(0.5 * (w1["temp"] + w0["temp"]))
water_cont = water.water_cont(0.5 * (w1["phi"] + w0["phi"]))
dw_dphi = water.dw_dphi(0.5 * (w1["phi"] + w0["phi"]))
# Rate of CaCO_3 concentration change
dot_caco3 = co2.dot_caco3(dt * 24 * 60 * 60, iv0["caco3"], w1["phi"],
w1["co2"], w1["temp"])
#
# Balances residuals
#
sigma_eff = iv0["sigma"] + mech.stress(E_kelv, deps_el)
eps_eqv = ufl.Max(
damage_rankine.eps_eqv(sigma_eff, mps.E_static(creep_v_mid)),
iv0["eps_eqv"])
f_c = mech.f_c(t)
f_t = mech.f_t(f_c)
G_f = mech.G_f(f_c)
dmg = damage_rankine.damage(eps_eqv, mesh, mps.E_static(creep_v_mid), f_t,
G_f)
# Prepare stress increments
if damage_off:
dmg = 0.0 * dmg
eps_eqv = iv0["eps_eqv"]
sigma_rebar = mech.stress_rebar(mech.E_rebar, w1["displ"])
sigma = (1.0 - dmg) * sigma_eff
_con_dx = []
for dx in con_dx:
_con_dx += [dx(metadata={"quadrature_degree": quad_degree_stress})]
_con_dx = ufl.classes.MeasureSum(*_con_dx)
_reb_dx = []
for dx in reb_dx:
_reb_dx += [dx(metadata={"quadrature_degree": quad_degree_stress})]
_reb_dx = ufl.classes.MeasureSum(*_reb_dx)
# Momentum balance for concrete material
mom_balance = -ufl.inner(sigma, ufl.grad(w_displ_test)) * _con_dx
# Momentum balance for rebar material
if len(reb_dx) > 0:
mom_balance += -ufl.inner(sigma_rebar,
ufl.grad(w_displ_test)) * _reb_dx
# Add volume body forces
for measure, force in g.items():
mom_balance -= ufl.inner(force, w_displ_test) * measure
# Add surface forces to mom balance
for measure, force in f.items():
mom_balance += ufl.inner(force, w_displ_test) * measure
_thc_dx = []
for dx in con_dx + reb_dx:
_thc_dx += [dx(metadata={"quadrature_degree": quad_degree_thc})]
_thc_dx = ufl.classes.MeasureSum(*_thc_dx)
# Energy balance = evolution of temperature
energy_balance = (
mech.rho_c * misc.C_pc / (dt * 24 * 60 * 60) * ufl.inner(
(w1["temp"] - w0["temp"]), w_temp_test) * _thc_dx + misc.lambda_c *
ufl.inner(ufl.grad(w1["temp"]), ufl.grad(w_temp_test)) * _thc_dx +
water.h_v * water.delta_p * ufl.inner(ufl.grad(
w1["phi"] * p_sat), ufl.grad(w_temp_test)) * _thc_dx +
co2.alpha3 * dot_caco3 * w_temp_test * _thc_dx)
# Water balance = evolution of humidity
water_balance = (ufl.inner(
dw_dphi * 1.0 / (dt * 24 * 60 * 60) *
(w1["phi"] - w0["phi"]), w_phi_test) * _thc_dx + ufl.inner(
dw_dphi * water.D_ws(water_cont) * ufl.grad(w1["phi"]) +
water.delta_p * ufl.grad(w1["phi"] * p_sat), ufl.grad(w_phi_test))
* _thc_dx + co2.alpha2 * dot_caco3 * w_phi_test * _thc_dx)
for measure, flux in water_flux.items():
water_balance -= ufl.inner(flux, w_phi_test) * measure
co2_balance = (
ufl.inner(1.0 / (dt * 24 * 60 * 60) *
(w1["co2"] - w0["co2"]), w_co2_test) * _thc_dx +
ufl.inner(co2.D_co2 * ufl.grad(w1["co2"]), ufl.grad(w_co2_test)) *
_thc_dx + co2.alpha4 * dot_caco3 * w_co2_test * _thc_dx)
for measure, flux in co2_flux.items():
co2_balance -= ufl.inner(flux, w_co2_test) * measure
J_mom = ufl.derivative(mom_balance, w1["displ"], w_displ_trial)
J_energy_temp = ufl.derivative(energy_balance, w1["temp"], w_temp_trial)
J_energy_hum = ufl.derivative(energy_balance, w1["phi"], w_phi_trial)
J_energy_co2 = ufl.derivative(energy_balance, w1["co2"], w_co2_trial)
J_energy = J_energy_hum + J_energy_temp + J_energy_co2
J_water_temp = ufl.derivative(water_balance, w1["temp"], w_temp_trial)
J_water_hum = ufl.derivative(water_balance, w1["phi"], w_phi_trial)
J_water_co2 = ufl.derivative(water_balance, w1["co2"], w_co2_trial)
J_water = J_water_temp + J_water_hum + J_water_co2
J_co2_temp = ufl.derivative(co2_balance, w1["temp"], w_temp_trial)
J_co2_hum = ufl.derivative(co2_balance, w1["phi"], w_phi_trial)
J_co2_co2 = ufl.derivative(co2_balance, w1["co2"], w_co2_trial)
J_co2 = J_co2_temp + J_co2_hum + J_co2_co2
# Put all Jacobians together
J_all = J_mom + J_energy + J_water + J_co2
# Lower algebra symbols and apply derivatives up to terminals
# This is needed for the Replacer to work properly
preserve_geometry_types = (ufl.CellVolume, ufl.FacetArea)
J_all = ufl.algorithms.apply_algebra_lowering.apply_algebra_lowering(J_all)
J_all = ufl.algorithms.apply_derivatives.apply_derivatives(J_all)
J_all = ufl.algorithms.apply_geometry_lowering.apply_geometry_lowering(
J_all, preserve_geometry_types)
J_all = ufl.algorithms.apply_derivatives.apply_derivatives(J_all)
J_all = ufl.algorithms.apply_geometry_lowering.apply_geometry_lowering(
J_all, preserve_geometry_types)
J_all = ufl.algorithms.apply_derivatives.apply_derivatives(J_all)
J = extract_blocks(J_all,
[w_displ_test, w_temp_test, w_phi_test, w_co2_test],
[w_displ_trial, w_temp_trial, w_phi_trial, w_co2_trial])
J[0][0]._signature = "full" if not damage_off else "dmgoff"
# Just make sure these are really empty Forms
assert len(J[1][0].arguments()) == 0
assert len(J[2][0].arguments()) == 0
assert len(J[3][0].arguments()) == 0
F = [-mom_balance, -energy_balance, -water_balance, -co2_balance]
rank = MPI.COMM_WORLD.rank
if rank == 0:
logger.info("Compiling tangents J...")
J_compiled = [
Form(J[0][0]),
[[Form(J[i][j]) for j in range(1, 4)] for i in range(1, 4)]
]
if rank == 0:
logger.info("Compiling residuals F...")
F_compiled = [Form(F[0]), [Form(F[i]) for i in range(1, 4)]]
expr = OrderedDict()
eta_dash1 = mps.eta_dash(iv0["eta_dash"], dt, w1["temp"], w1["phi"])
expr["eta_dash"] = (eta_dash1,
iv0["eta_dash"].function_space.ufl_element())
expr["caco3"] = (iv0["caco3"] + dt * 24 * 60 * 60 * dot_caco3,
iv0["caco3"].function_space.ufl_element())
expr["eps_cr_kel"] = (iv0["eps_cr_kel"] + deps_cr_kel,
iv0["eps_cr_kel"].function_space.ufl_element())
expr["eps_cr_dash"] = (iv0["eps_cr_dash"] + deps_cr_dash,
iv0["eps_cr_dash"].function_space.ufl_element())
expr["eps_sh_dr"] = (iv0["eps_sh_dr"] + deps_sh_dr,
iv0["eps_sh_dr"].function_space.ufl_element())
expr["eps_th"] = (iv0["eps_th"] + deps_th,
iv0["eps_th"].function_space.ufl_element())
expr["sigma"] = (iv0["sigma"] + mech.stress(E_kelv, deps_el),
iv0["sigma"].function_space.ufl_element())
expr["eps_eqv"] = (eps_eqv, iv0["eps_eqv"].function_space.ufl_element())
expr["dmg"] = (dmg, iv0["dmg"].function_space.ufl_element())
for i in range(mps.M):
expr[f"gamma_{i}"] = (lambda_cr[i] * (iv1["sigma"] - iv0["sigma"]) +
(beta_cr[i]) * gamma0[i],
gamma0[i].function_space.ufl_element())
expr_compiled = OrderedDict()
for name, item in expr.items():
if rank == 0:
logger.info(f"Compiling expressions for {name}...")
expr_compiled[name] = CompiledExpression(item[0], item[1])
if rank == 0:
logger.info(f"[Timer] UFL forms setup and compilation: {time() - t0}")
return J_compiled, F_compiled, expr_compiled
def C_map(A):
"""unit compliance tensor mapping stress -> strain."""
return -lambda_ / (2.0 * mu * (3.0 * lambda_ + 2.0 * mu)
) * ufl.tr(A) * ufl.Identity(3) + 1.0 / (2 * mu) * A
def tangential_proj(u, n):
"""
See for instance:
https://link.springer.com/content/pdf/10.1023/A:1022235512626.pdf
"""
return (ufl.Identity(u.ufl_shape[0]) - ufl.outer(n, n)) * u
def sigma(w, gdim):
return 2.0 * mu * ufl.sym(grad(w)) + lmbda * ufl.tr(
grad(w)) * ufl.Identity(gdim)
def test_mixed_element(cell_type, ghost_mode):
N = 4
mesh = dolfinx.mesh.create_unit_square(
MPI.COMM_WORLD, N, N, cell_type=cell_type, ghost_mode=ghost_mode)
# Inlet velocity Dirichlet BC
bc_facets = dolfinx.mesh.locate_entities_boundary(
mesh, mesh.topology.dim - 1, lambda x: np.isclose(x[0], 0.0))
other_facets = dolfinx.mesh.locate_entities_boundary(
mesh, mesh.topology.dim - 1, lambda x: np.isclose(x[0], 1.0))
arg_sort = np.argsort(other_facets)
mt = dolfinx.mesh.meshtags(mesh, mesh.topology.dim - 1,
other_facets[arg_sort], np.full_like(other_facets, 1))
# Rotate the mesh to induce more interesting slip BCs
th = np.pi / 4.0
rot = np.array([[np.cos(th), -np.sin(th)],
[np.sin(th), np.cos(th)]])
gdim = mesh.geometry.dim
mesh.geometry.x[:, :gdim] = (rot @ mesh.geometry.x[:, :gdim].T).T
# Create the function space
Ve = ufl.VectorElement("Lagrange", mesh.ufl_cell(), 2)
Qe = ufl.FiniteElement("Lagrange", mesh.ufl_cell(), 1)
V = dolfinx.fem.FunctionSpace(mesh, Ve)
Q = dolfinx.fem.FunctionSpace(mesh, Qe)
W = dolfinx.fem.FunctionSpace(mesh, Ve * Qe)
inlet_velocity = dolfinx.fem.Function(V)
inlet_velocity.interpolate(
lambda x: np.zeros((mesh.geometry.dim, x[0].shape[0]), dtype=np.double))
inlet_velocity.x.scatter_forward()
# -- Nested assembly
dofs = dolfinx.fem.locate_dofs_topological(V, 1, bc_facets)
bc1 = dolfinx.fem.dirichletbc(inlet_velocity, dofs)
# Collect Dirichlet boundary conditions
bcs = [bc1]
mpc_v = dolfinx_mpc.MultiPointConstraint(V)
n_approx = dolfinx_mpc.utils.create_normal_approximation(V, mt, 1)
mpc_v.create_slip_constraint(V, (mt, 1), n_approx, bcs=bcs)
mpc_v.finalize()
mpc_q = dolfinx_mpc.MultiPointConstraint(Q)
mpc_q.finalize()
f = dolfinx.fem.Constant(mesh, PETSc.ScalarType((0, 0)))
(u, p) = ufl.TrialFunction(V), ufl.TrialFunction(Q)
(v, q) = ufl.TestFunction(V), ufl.TestFunction(Q)
a00 = ufl.inner(ufl.grad(u), ufl.grad(v)) * ufl.dx
a01 = - ufl.inner(p, ufl.div(v)) * ufl.dx
a10 = - ufl.inner(ufl.div(u), q) * ufl.dx
a11 = None
L0 = ufl.inner(f, v) * ufl.dx
L1 = ufl.inner(
dolfinx.fem.Constant(mesh, PETSc.ScalarType(0.0)), q) * ufl.dx
n = ufl.FacetNormal(mesh)
g_tau = ufl.as_vector((0.0, 0.0))
ds = ufl.Measure("ds", domain=mesh, subdomain_data=mt, subdomain_id=1)
a00 -= ufl.inner(ufl.outer(n, n) * ufl.dot(ufl.grad(u), n), v) * ds
a01 -= ufl.inner(ufl.outer(n, n) * ufl.dot(
- p * ufl.Identity(u.ufl_shape[0]), n), v) * ds
L0 += ufl.inner(g_tau, v) * ds
a_nest = dolfinx.fem.form(((a00, a01),
(a10, a11)))
L_nest = dolfinx.fem.form((L0, L1))
# Assemble MPC nest matrix
A_nest = dolfinx_mpc.create_matrix_nest(a_nest, [mpc_v, mpc_q])
dolfinx_mpc.assemble_matrix_nest(A_nest, a_nest, [mpc_v, mpc_q], bcs)
A_nest.assemble()
# Assemble original nest matrix
A_org_nest = dolfinx.fem.petsc.assemble_matrix_nest(a_nest, bcs)
A_org_nest.assemble()
# MPC nested rhs
b_nest = dolfinx_mpc.create_vector_nest(L_nest, [mpc_v, mpc_q])
dolfinx_mpc.assemble_vector_nest(b_nest, L_nest, [mpc_v, mpc_q])
dolfinx.fem.petsc.apply_lifting_nest(b_nest, a_nest, bcs)
for b_sub in b_nest.getNestSubVecs():
b_sub.ghostUpdate(addv=PETSc.InsertMode.ADD,
mode=PETSc.ScatterMode.REVERSE)
bcs0 = dolfinx.fem.bcs_by_block(
dolfinx.fem.extract_function_spaces(L_nest), bcs)
dolfinx.fem.petsc.set_bc_nest(b_nest, bcs0)
# Original dolfinx rhs
b_org_nest = dolfinx.fem.petsc.assemble_vector_nest(L_nest)
dolfinx.fem.petsc.apply_lifting_nest(b_org_nest, a_nest, bcs)
for b_sub in b_org_nest.getNestSubVecs():
b_sub.ghostUpdate(addv=PETSc.InsertMode.ADD,
mode=PETSc.ScatterMode.REVERSE)
dolfinx.fem.petsc.set_bc_nest(b_org_nest, bcs0)
# -- Monolithic assembly
dofs = dolfinx.fem.locate_dofs_topological((W.sub(0), V), 1, bc_facets)
bc1 = dolfinx.fem.dirichletbc(inlet_velocity, dofs, W.sub(0))
bcs = [bc1]
V, V_to_W = W.sub(0).collapse()
mpc_vq = dolfinx_mpc.MultiPointConstraint(W)
n_approx = dolfinx_mpc.utils.create_normal_approximation(V, mt, 1)
mpc_vq.create_slip_constraint(W.sub(0), (mt, 1), n_approx, bcs=bcs)
mpc_vq.finalize()
f = dolfinx.fem.Constant(mesh, PETSc.ScalarType((0, 0)))
(u, p) = ufl.TrialFunctions(W)
(v, q) = ufl.TestFunctions(W)
a = (
ufl.inner(ufl.grad(u), ufl.grad(v)) * ufl.dx
- ufl.inner(p, ufl.div(v)) * ufl.dx
- ufl.inner(ufl.div(u), q) * ufl.dx
)
L = ufl.inner(f, v) * ufl.dx + ufl.inner(
dolfinx.fem.Constant(mesh, PETSc.ScalarType(0.0)), q) * ufl.dx
# No prescribed shear stress
n = ufl.FacetNormal(mesh)
g_tau = ufl.as_vector((0.0, 0.0))
ds = ufl.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 -= ufl.inner(ufl.outer(n, n) * ufl.dot(ufl.grad(u), n), v) * ds
a -= ufl.inner(ufl.outer(n, n) * ufl.dot(
- p * ufl.Identity(u.ufl_shape[0]), n), v) * ds
L += ufl.inner(g_tau, v) * ds
a, L = dolfinx.fem.form(a), dolfinx.fem.form(L)
# Assemble LHS matrix and RHS vector
A = dolfinx_mpc.assemble_matrix(a, mpc_vq, bcs)
A.assemble()
A_org = dolfinx.fem.petsc.assemble_matrix(a, bcs)
A_org.assemble()
b = dolfinx_mpc.assemble_vector(L, mpc_vq)
b_org = dolfinx.fem.petsc.assemble_vector(L)
# Set Dirichlet boundary condition values in the RHS
dolfinx_mpc.apply_lifting(b, [a], [bcs], mpc_vq)
b.ghostUpdate(addv=PETSc.InsertMode.ADD, mode=PETSc.ScatterMode.REVERSE)
dolfinx.fem.petsc.set_bc(b, bcs)
dolfinx.fem.petsc.apply_lifting(b_org, [a], [bcs])
b_org.ghostUpdate(addv=PETSc.InsertMode.ADD, mode=PETSc.ScatterMode.REVERSE)
dolfinx.fem.petsc.set_bc(b_org, bcs)
# -- Verification
def nest_matrix_norm(A):
assert A.getType() == "nest"
nrows, ncols = A.getNestSize()
sub_A = [A.getNestSubMatrix(row, col)
for row in range(nrows) for col in range(ncols)]
return sum(map(lambda A_: A_.norm()**2 if A_ else 0.0, sub_A))**0.5
# -- Ensure monolithic and nest matrices are the same
assert np.isclose(nest_matrix_norm(A_nest), A.norm())
