def geneFunctionSpace(self):
P2 = fe.FiniteElement('P', fe.triangle, 2)
element = fe.MixedElement([P2, P2])
if self.domain.haveMesh == False:
self.domain.geneMesh()
self.V = fe.FunctionSpace(self.domain.mesh, element)
self.haveFunctionSpace = True
def initWeakFormulation():
"""Define function spaces etc. to initialize weak formulation."""
P = fe.FiniteElement('P', mesh.ufl_cell(), 1)
V = fe.FunctionSpace(mesh, 'P', 1)
auxP = []
for k in range(nEvenMoments):
auxP.append(P)
VVec = fe.FunctionSpace(mesh, fe.MixedElement(auxP))
auxV = []
for k in range(nEvenMoments):
auxV.append(V)
assigner = fe.FunctionAssigner(auxV, VVec)
v = fe.TestFunctions(VVec)
u = fe.TrialFunctions(VVec)
uSol = fe.Function(VVec)
uSolComponents = []
for k in range(nEvenMoments):
uSolComponents.append(fe.Function(V))
# FEniCS work-around
if N_PN == 1:
solAssignMod = lambda uSolComponents, uSol: [
assigner.assign(uSolComponents[0], uSol)
]
else:
solAssignMod = lambda uSolComponents, uSol: assigner.assign(
uSolComponents, uSol)
return u, v, V, uSol, uSolComponents, solAssignMod
def _create_function_spaces(t, T, a, b, fineness_t, fineness_x):
"""Here we create the function spaces involved (and also the
mesh as well).
"""
nx = round((b - a) / fineness_x) # number of space steps
### Define periodic boundary
class PeriodicBoundary(fc.SubDomain):
def inside(self, x, on_boundary):
return bool(x[0] < fc.DOLFIN_EPS and
x[0] > -fc.DOLFIN_EPS and
on_boundary)
# Map right boundary to left boundary
def map(self, x, y):
y[0] = x[0] - (b - a)
### Create mesh and define function spaces
mesh = fc.IntervalMesh(nx, a, b)
F_ele = fc.FiniteElement("CG", mesh.ufl_cell(), 1)
V = fc.FunctionSpace(mesh, F_ele,
constrained_domain=PeriodicBoundary())
W = fc.FunctionSpace(mesh, fc.MixedElement([F_ele, F_ele]),
constrained_domain=PeriodicBoundary())
return V, W, mesh
def __init__(self,
mesh: fe.Mesh,
density: fe.Expression,
constitutive_model: ConstitutiveModelBase,
bf: fe.Expression = fe.Expression('0', degree=0)):
self._mesh = mesh
self._density = density
self._constitutive_model = constitutive_model
self.bf = bf
element_v = fe.VectorElement("P", mesh.ufl_cell(), 1)
element_s = fe.FiniteElement("P", mesh.ufl_cell(), 1)
mixed_element = fe.MixedElement([element_v, element_v, element_s])
W = fe.FunctionSpace(mesh, mixed_element)
# Unknowns, values at previous step and test functions
w = fe.Function(W)
self.u, self.v, self.p = fe.split(w)
w0 = fe.Function(W)
self.u0, self.v0, self.p0 = fe.split(w0)
self.a0 = fe.Function(fe.FunctionSpace(mesh, element_v))
self.ut, self.vt, self.pt = fe.TestFunctions(W)
self.F = kin.def_grad(self.u)
self.F0 = kin.def_grad(self.u0)
def dynamic_solver_func(ncells=10, # количество узлов на заданном итервале
init_time=0, # начальный момент времени
end_time=10, # конечный момент времени
dxdphi=1, # производная от потенциала по х
dydphi=1, # производня от потенциала по у
x0=0, # начальное положение по оси х
vx0=1, # проекция начальной скорости на ось х
y0=0, # начальное положение по оси у
vy0=1): # проекция начальной скорости на ось у
""" Функция на вход которой подается производная от потенциала
гравитационного поля, возвращающая координаты смещенных
материальных точек (частиц).
"""
# генерация сетки на заданном интервале времени
mesh = fen.IntervalMesh(ncells, 0, end_time-init_time)
welm = fen.MixedElement([fen.FiniteElement('Lagrange', fen.interval, 2),
fen.FiniteElement('Lagrange', fen.interval, 2),
fen.FiniteElement('Lagrange', fen.interval, 2),
fen.FiniteElement('Lagrange', fen.interval, 2)])
# генерация функционального рростаанства
W = fen.FunctionSpace(mesh, welm)
# постановка начальных условий задачи
bcsys = [fen.DirichletBC(W.sub(0), fen.Constant(x0), 'near(x[0], 0)'),
fen.DirichletBC(W.sub(1), fen.Constant(vx0), 'near(x[0], 0)'),
fen.DirichletBC(W.sub(2), fen.Constant(y0), 'near(x[0], 0)'),
fen.DirichletBC(W.sub(3), fen.Constant(vy0), 'near(x[0], 0)')]
# опееделение тестовых функций для решения задачи
up = fen.Function(W)
x_cor, v_x, y_cor, v_y = fen.split(up)
v1, v2, v3, v4 = fen.split(fen.TestFunction(W))
# постановка задачи drdt = v; dvdt = - grad(phi) в проекциях на оси системы координат
weak_form = (x_cor.dx(0) - v_x) * v1 * fen.dx + (v_x.dx(0) + dxdphi) * v2 * fen.dx \
+ (y_cor.dx(0) - v_y) * v3 * fen.dx + (v_y.dx(0) + dydphi) * v4 * fen.dx
# решние поставленной задачи
fen.solve(weak_form == 0, up, bcs=bcsys)
# определение момента времени
time = fen.Point(end_time - init_time)
# расчет координат и скоростей
x_end_time = up(time.x())[0]
vx_end_time = up(time.x())[1]
y_end_time = up(time.x())[2]
vy_end_time = up(time.x())[3]
return x_end_time, y_end_time, vx_end_time, vy_end_time
def setup_element(self):
""" Implement the mixed element per @cite{danaila2014newton}. """
pressure_element = fenics.FiniteElement(
"P", self.mesh.ufl_cell(), self.temperature_element_degree)
velocity_element = fenics.VectorElement(
"P", self.mesh.ufl_cell(), self.temperature_element_degree + 1)
temperature_element = fenics.FiniteElement(
"P", self.mesh.ufl_cell(), self.temperature_element_degree)
self.element = fenics.MixedElement(
[pressure_element, velocity_element, temperature_element])
def make_mixed_fe(cell):
""" Define the mixed finite element.
MixedFunctionSpace used to be available but is now deprecated.
To create the mixed space, I'm using the approach from https://fenicsproject.org/qa/11983/mixedfunctionspace-in-2016-2-0
"""
velocity_degree = pressure_degree + 1
velocity_element = fenics.VectorElement("P", cell, velocity_degree)
pressure_element = fenics.FiniteElement("P", cell, pressure_degree)
temperature_element = fenics.FiniteElement("P", cell, temperature_degree)
mixed_element = fenics.MixedElement(
[velocity_element, pressure_element, temperature_element])
return mixed_element
def __init__(self,
mesh: fe.Mesh,
constitutive_model: ConstitutiveModelBase,
u_order=1,
p_order=0):
# TODO a lot here...
element_v = fe.VectorElement("P", mesh.ufl_cell(), u_order)
element_s = fe.FiniteElement("DG", mesh.ufl_cell(), p_order)
# mixed_element = fe.MixedElement([element_v, element_v, element_s])
mixed_element = fe.MixedElement([element_v, element_s])
self.W = fe.FunctionSpace(mesh, mixed_element)
self.V, self.Q = self.W.split()
self.w = fe.Function(self.W)
self.u, self.p = fe.split(self.w)
w0 = fe.Function(self.W)
self.u0, self.p0 = fe.split(w0)
self.ut, self.pt = fe.TestFunctions(self.W)
self.F = kin.def_grad(self.u)
self.F0 = kin.def_grad(self.u0)
S_iso = constitutive_model.iso_stress(self.u)
mod_p = constitutive_model.p(self.u)
J = fe.det(self.F)
F_inv = fe.inv(self.F)
if mod_p is None:
mod_p = J**2 - 1.
else:
mod_p -= self.p
S = S_iso + J * self.p * F_inv * F_inv.T
self.d_LHS = fe.inner(fe.grad(self.ut), self.F * S) * fe.dx \
+ fe.inner(mod_p, self.pt) * fe.dx
# + fe.inner(mod_p, fe.tr(fe.nabla_grad(self.ut)*fe.inv(self.F))) * fe.dx
self.d_RHS = (fe.inner(fe.Constant((0., 0., 0.)), self.ut) * fe.dx)
# Create mesh and define function space
size = width, height = 1.0, 0.75
mesh = fn.RectangleMesh(fn.Point(-width / 2, 0.0), fn.Point(width / 2, height),
52, 39) # 52 * 0.75 = 39, elements are square
nn = fn.FacetNormal(mesh)
# Defintion of function spaces
Vh = fn.VectorElement("CG", mesh.ufl_cell(), 2)
Zh = fn.FiniteElement("CG", mesh.ufl_cell(), 1)
Qh = fn.FiniteElement("CG", mesh.ufl_cell(), 2)
# spaces for displacement and total pressure should be compatible
# whereas the space for fluid pressure can be "anything". In particular the one for total pressure
Hh = fn.FunctionSpace(mesh, fn.MixedElement([Vh, Zh, Qh]))
(u, phi, p) = fn.TrialFunctions(Hh)
(v, psi, q) = fn.TestFunctions(Hh)
fileU = fn.File(mesh.mpi_comm(), "Output/2_5_1_Footing_wall_removed/u.pvd")
filePHI = fn.File(mesh.mpi_comm(), "Output/2_5_1_Footing_wall_removed/phi.pvd")
fileP = fn.File(mesh.mpi_comm(), "Output/2_5_1_Footing_wall_removed/p.pvd")
# ******** Model constants ********** #
E = 3.0e4
nu = 0.4995
lmbda = E * nu / ((1. + nu) * (1. - 2. * nu))
mu = E / (2. * (1. + nu))
c0 = 1.0e-3
mesh = fe.Mesh('step.xml')
# Control pannel
MODEL = False # flag to use SA model
b = fe.Expression(('0', '0'), degree=DEG) # forcing
nu = fe.Constant(2e-6)
rho = fe.Constant(1)
RE = 0.01
lmx = 1 # mixing length
dt = 0.1
# Re = 10 / 1e-4 = 1e5
V = fe.VectorElement("Lagrange", mesh.ufl_cell(), 2)
P = fe.FiniteElement("Lagrange", mesh.ufl_cell(), 1)
NU = fe.FiniteElement("Lagrange", mesh.ufl_cell(), 1)
if MODEL: M = fe.MixedElement([V, P, NU])
else: M = fe.MixedElement([V, P])
W = fe.FunctionSpace(mesh, M)
W0 = fe.Function(W)
We = fe.Function(W)
u0, p0 = fe.split(We)
#u0 = fe.Function((W0[0], W0[1]), 'Velocity000023.vtu')
#p0 = fe.Function(W0[2])
v, q = fe.TestFunctions(W)
#u, p = fe.split(W0)
u, p = (fe.as_vector((W0[0], W0[1])), W0[2])
#-------------------------------------------------------
# Defining essential/Dirichlet boundary conditions
# Step 1: Identify all boundary segments forming Gamma_d
fn.parameters["form_compiler"]["cpp_optimize"] = True
# file outputs
fileE = fn.File("Output/1_4_Karma/E.pvd")
filen = fn.File("Output/1_4_Karma/n.pvd")
t = 0.0; dt = 0.3; Tfinal = 600.0; frequency = 100;
# mesh
L = 6.72; nps = 64;
mesh = fn.RectangleMesh(fn.Point(0, 0), fn.Point(L, L),
nps, nps, "crossed")
# element and function spaces
Mhe = fn.FiniteElement("CG", mesh.ufl_cell(), 1)
Mh = fn.FunctionSpace(mesh, Mhe)
Nh = fn.FunctionSpace(mesh, fn.MixedElement([Mhe,Mhe]))
# trial and test functions
v, n = fn.TrialFunctions(Nh)
w, m = fn.TestFunctions(Nh)
# solution
Ksol = fn.Function(Nh)
# model constants
diffScale = fn.Constant(1e-3)
D0 = 1.1 * diffScale
tauv = fn.Constant(2.5)
taun = fn.Constant(250.0)
Re = fn.Constant(1.0)
M = fn.Constant(5.0)
def navierStokes(projectId, mesh, faceSets, boundarySets, config):
log("Navier Stokes Analysis has started")
# this is the default directory, when user request for download all files in this directory is being compressed and sent to the user
resultDir = "./Results/"
if len(config["steps"]) > 1:
return "more than 1 step is not supported yet"
# config is a dictionary containing all the user inputs for solver configurations
t_init = 0.0
t_final = float(config['steps'][0]["finalTime"])
t_num = int(config['steps'][0]["iterationNo"])
dt = ((t_final - t_init) / t_num)
t = t_init
#
# Viscosity coefficient.
#
nu = float(config['materials'][0]["viscosity"])
rho = float(config['materials'][0]["density"])
#
# Declare Finite Element Spaces
# do not use triangle directly
P2 = fn.VectorElement("P", mesh.ufl_cell(), 2)
P1 = fn.FiniteElement("P", mesh.ufl_cell(), 1)
TH = fn.MixedElement([P2, P1])
V = fn.VectorFunctionSpace(mesh, "P", 2)
Q = fn.FunctionSpace(mesh, "P", 1)
W = fn.FunctionSpace(mesh, TH)
#
# Declare Finite Element Functions
#
(u, p) = fn.TrialFunctions(W)
(v, q) = fn.TestFunctions(W)
w = fn.Function(W)
u0 = fn.Function(V)
p0 = fn.Function(Q)
#
# Macros needed for weak formulation.
#
def contract(u, v):
return fn.inner(fn.nabla_grad(u), fn.nabla_grad(v))
def b(u, v, w):
return 0.5 * (fn.inner(fn.dot(u, fn.nabla_grad(v)), w) -
fn.inner(fn.dot(u, fn.nabla_grad(w)), v))
# Define boundaries
bcs = []
for BC in config['BCs']:
if BC["boundaryType"] == "wall":
for edge in json.loads(BC["edges"]):
bcs.append(
fn.DirichletBC(W.sub(0),
fn.Constant((0.0, 0.0, 0.0)),
boundarySets,
int(edge),
method='topological'))
if BC["boundaryType"] == "inlet":
vel = json.loads(BC['value'])
for edge in json.loads(BC["edges"]):
bcs.append(
fn.DirichletBC(W.sub(0),
fn.Expression(
(str(vel[0]), str(vel[1]), str(vel[2])),
degree=2),
boundarySets,
int(edge),
method='topological'))
if BC["boundaryType"] == "outlet":
for edge in json.loads(BC["edges"]):
bcs.append(
fn.DirichletBC(W.sub(1),
fn.Constant(float(BC['value'])),
boundarySets,
int(edge),
method='topological'))
f = fn.Constant((0.0, 0.0, 0.0))
# weak form NSE
NSE = (1.0/dt)*fn.inner(u, v)*fn.dx + b(u0, u, v)*fn.dx + nu * \
contract(u, v)*fn.dx - fn.div(v)*p*fn.dx + q*fn.div(u)*fn.dx
LNSE = fn.inner(f, v) * fn.dx + (1. / dt) * fn.inner(u0, v) * fn.dx
velocity_file = fn.XDMFFile(resultDir + "/vel.xdmf")
pressure_file = fn.XDMFFile(resultDir + "/pressure.xdmf")
velocity_file.parameters["flush_output"] = True
velocity_file.parameters["functions_share_mesh"] = True
pressure_file.parameters["flush_output"] = True
pressure_file.parameters["functions_share_mesh"] = True
#
# code for projecting a boundary condition into a file for visualization
#
# for bc in bcs:
# bc.apply(w.vector())
# fn.File("para_plotting/bc.pvd") << w.sub(0)
for jj in range(0, t_num):
t = t + dt
# print('t = ' + str(t))
A, b = fn.assemble_system(NSE, LNSE, bcs)
fn.solve(A, w.vector(), b)
# fn.solve(NSE==LNSE,w,bcs)
fn.assign(u0, w.sub(0))
fn.assign(p0, w.sub(1))
# Save Solutions to Paraview File
if (jj % 20 == 0):
velocity_file.write(u0, t)
pressure_file.write(p0, t)
sendFile(projectId, resultDir + "vel.xdmf")
sendFile(projectId, resultDir + "vel.h5")
sendFile(projectId, resultDir + "pressure.xdmf")
sendFile(projectId, resultDir + "pressure.h5")
statusUpdate(projectId, "STARTED", {"progress": jj / t_num * 100})
import fenics
import matplotlib
N = 4
mesh = fenics.UnitSquareMesh(N, N)
P2 = fenics.VectorElement('P', mesh.ufl_cell(), 2)
P1 = fenics.FiniteElement('P', mesh.ufl_cell(), 1)
P2P1 = fenics.MixedElement([P2, P1])
W = fenics.FunctionSpace(mesh, P2P1)
psi_u, psi_p = fenics.TestFunctions(W)
w = fenics.Function(W)
u, p = fenics.split(w)
dynamic_viscosity = 0.01
mu = fenics.Constant(dynamic_viscosity)
inner, dot, grad, div, sym = fenics.inner, fenics.dot, fenics.grad, fenics.div, fenics.sym
momentum = dot(psi_u, dot(grad(u), u)) - div(psi_u) * p + 2. * mu * inner(
sym(grad(psi_u)), sym(grad(u)))
mass = -psi_p * div(u)
def xest_implement_2d_myosin(self):
#Parameters
total_time = 1.0
number_of_time_steps = 100
delta_t = total_time / number_of_time_steps
nx = ny = 100
domain_size = 1.0
lambda_ = 5.0
mu = 2.0
gamma = 1.0
eta_b = 0.0
eta_s = 1.0
k_b = 1.0
k_u = 1.0
# zeta_1 = -0.5
zeta_1 = 0.0
zeta_2 = 1.0
mu_a = 1.0
K_0 = 1.0
K_1 = 0.0
K_2 = 0.0
K_3 = 0.0
D = 0.25
alpha = 3
c = 0.1
# Sub domain for Periodic boundary condition
class PeriodicBoundary(fenics.SubDomain):
# Left boundary is "target domain" G
def inside(self, x, on_boundary):
# return True if on left or bottom boundary AND NOT on one of the two corners (0, 1) and (1, 0)
return bool(
(fenics.near(x[0], 0) or fenics.near(x[1], 0)) and
(not ((fenics.near(x[0], 0) and fenics.near(x[1], 1)) or
(fenics.near(x[0], 1) and fenics.near(x[1], 0))))
and on_boundary)
def map(self, x, y):
if fenics.near(x[0], 1) and fenics.near(x[1], 1):
y[0] = x[0] - 1.
y[1] = x[1] - 1.
elif fenics.near(x[0], 1):
y[0] = x[0] - 1.
y[1] = x[1]
else: # near(x[1], 1)
y[0] = x[0]
y[1] = x[1] - 1.
periodic_boundary_condition = PeriodicBoundary()
#Set up finite elements
mesh = fenics.RectangleMesh(fenics.Point(0, 0),
fenics.Point(domain_size, domain_size), nx,
ny)
vector_element = fenics.VectorElement('P', fenics.triangle, 2, dim=2)
single_element = fenics.FiniteElement('P', fenics.triangle, 2)
mixed_element = fenics.MixedElement(vector_element, single_element)
V = fenics.FunctionSpace(
mesh,
mixed_element,
constrained_domain=periodic_boundary_condition)
v, r = fenics.TestFunctions(V)
full_trial_function = fenics.Function(V)
u, rho = fenics.split(full_trial_function)
full_trial_function_n = fenics.Function(V)
u_n, rho_n = fenics.split(full_trial_function_n)
#Define non-linear weak formulation
def epsilon(u):
return 0.5 * (fenics.nabla_grad(u) + fenics.nabla_grad(u).T
) #return sym(nabla_grad(u))
def sigma_e(u):
return lambda_ * ufl.nabla_div(u) * fenics.Identity(
2) + 2 * mu * epsilon(u)
def sigma_d(u):
return eta_b * ufl.nabla_div(u) * fenics.Identity(
2) + 2 * eta_s * epsilon(u)
# def sigma_a(u,rho):
# return ( -zeta_1*rho/(1+zeta_2*rho)*mu_a*fenics.Identity(2)*(K_0+K_1*ufl.nabla_div(u)+
# K_2*ufl.nabla_div(u)*ufl.nabla_div(u)+K_3*ufl.nabla_div(u)*ufl.nabla_div(u)*ufl.nabla_div(u)))
def sigma_a(u, rho):
return -zeta_1 * rho / (
1 + zeta_2 * rho) * mu_a * fenics.Identity(2) * (K_0)
F = (gamma * fenics.dot(u, v) * fenics.dx -
gamma * fenics.dot(u_n, v) * fenics.dx +
fenics.inner(sigma_d(u), fenics.nabla_grad(v)) * fenics.dx -
fenics.inner(sigma_d(u_n), fenics.nabla_grad(v)) * fenics.dx -
delta_t *
fenics.inner(sigma_e(u) + sigma_a(u, rho), fenics.nabla_grad(v)) *
fenics.dx + rho * r * fenics.dx - rho_n * r * fenics.dx +
ufl.nabla_div(rho * u) * r * fenics.dx -
ufl.nabla_div(rho * u_n) * r * fenics.dx - D * delta_t *
fenics.dot(fenics.nabla_grad(rho), fenics.nabla_grad(r)) *
fenics.dx + delta_t *
(-k_u * rho * fenics.exp(alpha * ufl.nabla_div(u)) + k_b *
(1 - c * ufl.nabla_div(u))) * r * fenics.dx)
# F = ( gamma*fenics.dot(u,v)*fenics.dx - gamma*fenics.dot(u_n,v)*fenics.dx + fenics.inner(sigma_d(u),fenics.nabla_grad(v))*fenics.dx -
# fenics.inner(sigma_d(u_n),fenics.nabla_grad(v))*fenics.dx - delta_t*fenics.inner(sigma_e(u)+sigma_a(u,rho),fenics.nabla_grad(v))*fenics.dx
# +rho*r*fenics.dx-rho_n*r*fenics.dx + ufl.nabla_div(rho*u)*r*fenics.dx - ufl.nabla_div(rho*u_n)*r*fenics.dx -
# D*delta_t*fenics.dot(fenics.nabla_grad(rho),fenics.nabla_grad(r))*fenics.dx +delta_t*(-k_u*rho*fenics.exp(alpha*ufl.nabla_div(u))+k_b*(1-c*ufl.nabla_div(u))))
vtkfile_rho = fenics.File(
os.path.join(os.path.dirname(__file__), 'output', 'myosin_2d',
'solution_rho.pvd'))
vtkfile_u = fenics.File(
os.path.join(os.path.dirname(__file__), 'output', 'myosin_2d',
'solution_u.pvd'))
# rho_0 = fenics.Expression(((('0.0'),('0.0'),('0.0')),('sin(x[0])')), degree=1 )
# full_trial_function_n = fenics.project(rho_0, V)
time = 0.0
for time_index in range(number_of_time_steps):
# Update current time
time += delta_t
# Compute solution
fenics.solve(F == 0, full_trial_function)
# Save to file and plot solution
vis_u, vis_rho = full_trial_function.split()
vtkfile_rho << (vis_rho, time)
vtkfile_u << (vis_u, time)
full_trial_function_n.assign(full_trial_function)
def __init__(self, L, ne, r0, Q0, E, h0, theta, dt, degA=1, degQ=1):
# -- Setup domain
self.L = L
self.ne = ne
self.dt = dt
self.mesh = fe.IntervalMesh(ne, 0, L)
QE = fe.FiniteElement("Lagrange",
cell=self.mesh.ufl_cell(),
degree=degQ)
AE = fe.FiniteElement("Lagrange",
cell=self.mesh.ufl_cell(),
degree=degA)
ME = fe.MixedElement([AE, QE])
# -- Setup functionspaces
self.V = fe.FunctionSpace(self.mesh, ME)
self.V_A = self.V.sub(0)
self.V_Q = self.V.sub(1)
(self.v1, self.v2) = fe.TestFunctions(self.V)
self.dv1 = fe.grad(self.v1)[0]
self.dv2 = fe.grad(self.v2)[0]
self.E = E
self.h0 = h0
self.beta = E * h0 * np.sqrt(np.pi)
self.A0 = np.pi * r0**2
self.Q0 = Q0
self.U0 = fe.Function(self.V)
self.Un = fe.Function(self.V)
# -- Setup initial conditions
self.U0.assign(fe.Expression(('A0', 'Q0'), A0=self.A0, Q0=Q0,
degree=1))
self.Un.assign(fe.Expression(('A0', 'Q0'), A0=self.A0, Q0=Q0,
degree=1))
(self.u01, self.u02) = fe.split(self.U0)
(self.un1, self.un2) = fe.split(self.Un)
self.du01 = fe.grad(self.u01)[0]
self.du02 = fe.grad(self.u02)[0]
self.dun1 = fe.grad(self.un1)[0]
self.dun2 = fe.grad(self.un2)[0]
(self.W1_initial,
self.W2_initial) = self.getCharacteristics(self.A0, self.Q0)
# -- Setup weakform terms
B0 = self.getB(self.u01, self.u02)
Bn = self.getB(self.un1, self.un2)
H0 = self.getH(self.u01, self.u02)
Hn = self.getH(self.un1, self.un2)
HdUdz0 = matMult(H0, [self.du01, self.du02])
HdUdzn = matMult(Hn, [self.dun1, self.dun2])
# -- Setup weakform
wf = -self.un1 * self.v1 - self.un2 * self.v2
wf += self.u01 * self.v1 + self.u02 * self.v2
wf += -dt * theta * (HdUdzn[0] + Bn[0]) * self.v1 - dt * theta * (
HdUdzn[1] + Bn[1]) * self.v2
wf += -dt * (1 - theta) * (HdUdz0[0] + B0[0]) * self.v1 - dt * (
1 - theta) * (HdUdz0[1] + B0[1]) * self.v2
wf = wf * fe.dx
self.wf = wf
self.J = fe.derivative(wf, self.Un, fe.TrialFunction(self.V))
def discretize(self):
"""Builds function space, call again after introducing constraints"""
# FEniCS interface
self.mesh = fn.IntervalMesh(self.N, self.x0_scaled, self.x1_scaled)
# http://www.femtable.org/
# Argyris* ARG
# Arnold-Winther* AW
# Brezzi-Douglas-Fortin-Marini* BDFM
# Brezzi-Douglas-Marini BDM
# Bubble B
# Crouzeix-Raviart CR
# Discontinuous Lagrange DG
# Discontinuous Raviart-Thomas DRT
# Hermite* HER
# Lagrange CG
# Mardal-Tai-Winther* MTW
# Morley* MOR
# Nedelec 1st kind H(curl) N1curl
# Nedelec 2nd kind H(curl) N2curl
# Quadrature Q
# Raviart-Thomas RT
# Real R
# construct test and trial function space from elements
# spanned by Lagrange polynomials for the pyhsical variables of
# potential and concentration and global elements with a single degree
# of freedom ('Real') for constraints.
# For an example of this approach, refer to
# https://fenicsproject.org/docs/dolfin/latest/python/demos/neumann-poisson/demo_neumann-poisson.py.html
# For another example on how to construct and split function spaces
# for solving coupled equations, refer to
# https://fenicsproject.org/docs/dolfin/latest/python/demos/mixed-poisson/demo_mixed-poisson.py.html
P = fn.FiniteElement('Lagrange', fn.interval, 3)
R = fn.FiniteElement('Real', fn.interval, 0)
elements = [P] * (1 + self.M) + [R] * self.K
H = fn.MixedElement(elements)
self.W = fn.FunctionSpace(self.mesh, H)
# solution functions
self.w = fn.Function(self.W)
# set initial values if available
P = fn.FunctionSpace(self.mesh, 'P', 1)
dof2vtx = fn.vertex_to_dof_map(P)
if self.ui0 is not None:
x = np.linspace(self.x0_scaled, self.x1_scaled, self.ui0.shape[0])
ui0 = scipy.interpolate.interp1d(x, self.ui0)
# use linear interpolation on mesh
self.u0_func = fn.Function(P)
self.u0_func.vector()[:] = ui0(self.X)[dof2vtx]
fn.assign(self.w.sub(0),
fn.interpolate(self.u0_func,
self.W.sub(0).collapse()))
if self.ni0 is not None:
x = np.linspace(self.x0_scaled, self.x1_scaled, self.ni0.shape[1])
ni0 = scipy.interpolate.interp1d(x, self.ni0)
self.p0_func = [fn.Function(P)] * self.ni0.shape[0]
for k in range(self.ni0.shape[0]):
self.p0_func[k].vector()[:] = ni0(self.X)[k, :][dof2vtx]
fn.assign(
self.w.sub(1 + k),
fn.interpolate(self.p0_func[k],
self.W.sub(k + 1).collapse()))
# u represents voltage , p concentrations
uplam = fn.split(self.w)
self.u, self.p, self.lam = (uplam[0], [*uplam[1:(self.M + 1)]],
[*uplam[(self.M + 1):]])
# v, q and mu represent respective test functions
vqmu = fn.TestFunctions(self.W)
self.v, self.q, self.mu = (vqmu[0], [*vqmu[1:(self.M + 1)]],
[*vqmu[(self.M + 1):]])
def xest_implement_1d_myosin(self):
#Parameters
total_time = 10.0
number_of_time_steps = 1000
# delta_t = fenics.Constant(total_time/number_of_time_steps)
delta_t = total_time / number_of_time_steps
nx = 1000
domain_size = 1.0
b = fenics.Constant(6.0)
k = fenics.Constant(0.5)
z_1 = fenics.Constant(-10.5) #always negative
# z_1 = fenics.Constant(0.0) #always negative
z_2 = 0.1 # always positive
xi_0 = fenics.Constant(1.0) #always positive
xi_1 = fenics.Constant(1.0) #always positive
xi_2 = 0.001 #always positive
xi_3 = 0.0001 #always negative
d = fenics.Constant(0.15)
alpha = fenics.Constant(1.0)
c = fenics.Constant(0.1)
# Sub domain for Periodic boundary condition
class PeriodicBoundary(fenics.SubDomain):
# Left boundary is "target domain" G
def inside(self, x, on_boundary):
return bool(-fenics.DOLFIN_EPS < x[0] < fenics.DOLFIN_EPS
and on_boundary)
def map(self, x, y):
y[0] = x[0] - 1
periodic_boundary_condition = PeriodicBoundary()
#Set up finite elements
mesh = fenics.IntervalMesh(nx, 0.0, 1.0)
vector_element = fenics.FiniteElement('P', fenics.interval, 1)
single_element = fenics.FiniteElement('P', fenics.interval, 1)
mixed_element = fenics.MixedElement(vector_element, single_element)
V = fenics.FunctionSpace(
mesh,
mixed_element,
constrained_domain=periodic_boundary_condition)
# V = fenics.FunctionSpace(mesh, mixed_element)
v, r = fenics.TestFunctions(V)
full_trial_function = fenics.Function(V)
u, rho = fenics.split(full_trial_function)
full_trial_function_n = fenics.Function(V)
u_n, rho_n = fenics.split(full_trial_function_n)
u_initial = fenics.Constant(0.0)
# rho_initial = fenics.Expression('1.0*sin(pi*x[0])*sin(pi*x[0])+1.0/k0', degree=2,k0 = k)
rho_initial = fenics.Expression('1/k0', degree=2, k0=k)
u_n = fenics.interpolate(u_initial, V.sub(0).collapse())
rho_n = fenics.interpolate(rho_initial, V.sub(1).collapse())
# perturbation = np.zeros(rho_n.vector().size())
# perturbation[:int(perturbation.shape[0]/2)] = 1.0
rho_n.vector().set_local(
np.array(rho_n.vector()) + 1.0 *
(0.5 - np.random.random(rho_n.vector().size())))
# u_n.vector().set_local(np.array(u_n.vector())+4.0*(0.5-np.random.random(u_n.vector().size())))
fenics.assign(full_trial_function_n, [u_n, rho_n])
u_n, rho_n = fenics.split(full_trial_function_n)
F = (u * v * fenics.dx - u_n * v * fenics.dx + delta_t *
(b + (z_1 * rho) /
(1 + z_2 * rho) * c * xi_1) * u.dx(0) * v.dx(0) * fenics.dx -
delta_t * (z_1 * rho) / (1 + z_2 * rho) * c * c * xi_2 / 2.0 *
u.dx(0) * u.dx(0) * v.dx(0) * fenics.dx + delta_t * (z_1 * rho) /
(1 + z_2 * rho) * c * c * c * xi_3 / 6.0 * u.dx(0) * u.dx(0) *
u.dx(0) * v.dx(0) * fenics.dx - delta_t * z_1 * rho /
(1 + z_2 * rho) * xi_0 * v.dx(0) * fenics.dx +
u.dx(0) * v.dx(0) * fenics.dx - u_n.dx(0) * v.dx(0) * fenics.dx +
rho * r * fenics.dx - rho_n * r * fenics.dx -
rho * u * r.dx(0) * fenics.dx + rho * u_n * r.dx(0) * fenics.dx +
delta_t * d * rho.dx(0) * r.dx(0) * fenics.dx +
delta_t * k * fenics.exp(alpha * u.dx(0)) * rho * r * fenics.dx -
delta_t * r * fenics.dx + delta_t * c * u.dx(0) * r * fenics.dx)
vtkfile_rho = fenics.File(
os.path.join(os.path.dirname(__file__), 'output', 'myosin_2d',
'solution_rho.pvd'))
vtkfile_u = fenics.File(
os.path.join(os.path.dirname(__file__), 'output', 'myosin_2d',
'solution_u.pvd'))
# rho_0 = fenics.Expression(((('0.0'),('0.0'),('0.0')),('sin(x[0])')), degree=1 )
# full_trial_function_n = fenics.project(rho_0, V)
# print('initial u and rho')
# print(u_n.vector())
# print(rho_n.vector())
time = 0.0
not_initialised = True
plt.figure()
for time_index in range(number_of_time_steps):
# Update current time
time += delta_t
# Compute solution
fenics.solve(F == 0, full_trial_function)
# Save to file and plot solution
vis_u, vis_rho = full_trial_function.split()
plt.subplot(311)
fenics.plot(vis_u, color='blue')
plt.ylim(-0.5, 0.5)
plt.subplot(312)
fenics.plot(-vis_u.dx(0), color='blue')
plt.ylim(-2, 2)
plt.title('actin density change')
plt.subplot(313)
fenics.plot(vis_rho, color='blue')
plt.title('myosin density')
plt.ylim(0, 7)
plt.tight_layout()
if not_initialised:
animation_camera = celluloid.Camera(plt.gcf())
not_initialised = False
animation_camera.snap()
print('time is')
print(time)
# plt.savefig(os.path.join(os.path.dirname(__file__),'output','this_output_at_time_' + '{:04d}'.format(time_index) + '.png'))
# print('this u and rho')
# print(np.array(vis_u.vector()))
# print(np.array(vis_rho.vector()))
# vtkfile_rho << (vis_rho, time)
# vtkfile_u << (vis_u, time)
full_trial_function_n.assign(full_trial_function)
animation = animation_camera.animate()
animation.save(
os.path.join(os.path.dirname(__file__), 'output', 'myosin_1D.mp4'))
def demo64(self, permeability, obs_case=1):
mesh = UnitSquareMesh(63, 63)
ak_values = permeability
flux_order = 3
s = scenarios.darcy_problem_1()
DRT = fenics.FiniteElement("DRT", mesh.ufl_cell(), flux_order)
# Lagrange
CG = fenics.FiniteElement("CG", mesh.ufl_cell(), flux_order + 1)
if s.integral_constraint:
# From https://fenicsproject.org/qa/14184/how-to-solve-linear-system-with-constaint
R = fenics.FiniteElement("R", mesh.ufl_cell(), 0)
W = fenics.FunctionSpace(mesh, fenics.MixedElement([DRT, CG, R]))
# Define trial and test functions
(sigma, u, r) = fenics.TrialFunctions(W)
(tau, v, r_) = fenics.TestFunctions(W)
else:
W = fenics.FunctionSpace(mesh, DRT * CG)
# Define trial and test functions
(sigma, u) = fenics.TrialFunctions(W)
(tau, v) = fenics.TestFunctions(W)
f = s.source_function
g = s.g
# Define property field function
W_CG = fenics.FunctionSpace(mesh, "Lagrange", 1)
if s.ak is None:
ak = property_field.get_conductivity(W_CG, ak_values)
else:
ak = s.ak
# Define variational form
a = (fenics.dot(sigma, tau) + fenics.dot(ak * fenics.grad(u), tau) +
fenics.dot(sigma, fenics.grad(v))) * fenics.dx
L = -f * v * fenics.dx + g * v * fenics.ds
# L = 0
if s.integral_constraint:
# Lagrange multiplier? See above link.
a += r_ * u * fenics.dx + v * r * fenics.dx
# Define Dirichlet BC
bc = fenics.DirichletBC(W.sub(1), s.dirichlet_bc, s.gamma_dirichlet)
# Compute solution
w = fenics.Function(W)
fenics.solve(a == L, w, bc)
# fenics.solve(a == L, w)
if s.integral_constraint:
(sigma, u, r) = w.split()
else:
(sigma, u) = w.split()
x = u.compute_vertex_values(mesh)
x2 = sigma.compute_vertex_values(mesh)
p = x
pre = p.reshape((64, 64))
vx = x2[:4096].reshape((64, 64))
vy = x2[4096:].reshape((64, 64))
if obs_case == 1:
dd = np.zeros([8, 8])
pos = np.full((8 * 8, 2), 0)
col = [4, 12, 20, 28, 36, 44, 52, 60]
position = [4, 12, 20, 28, 36, 44, 52, 60]
for i in range(8):
for j in range(8):
row = position
pos[8 * i + j, :] = [col[i], row[j]]
dd[i, j] = pre[col[i], row[j]]
like = dd.reshape(8 * 8, )
return like, pre, vx, vy, ak_values, pos
for cycle in range(initial_hot_wall_refinement_cycles):
edge_markers = fenics.MeshFunction("bool", mesh, 1, False)
hot_wall.mark(edge_markers, True)
fenics.adapt(mesh, edge_markers)
mesh = mesh.child()
P1 = fenics.FiniteElement('P', mesh.ufl_cell(), 1)
P2 = fenics.VectorElement('P', mesh.ufl_cell(), 2)
mixed_element = fenics.MixedElement([P1, P2, P1])
W = fenics.FunctionSpace(mesh, mixed_element)
psi_p, psi_u, psi_T = fenics.TestFunctions(W)
w = fenics.Function(W)
p, u, T = fenics.split(w)
prandtl_number = 56.2
Pr = fenics.Constant(prandtl_number)
rayleigh_number = 3.27e5
time = np.linspace(0,(T/2+(0.25-0.165)),int(nt))
dt = time[1]-time[0]
time = np.array(time)
Pin = 2e4*np.sin(2*np.pi*time/T) * np.heaviside(T/2-time,1)
Ain = (Pin*A0/beta+np.sqrt(A0))**2;
# -- Spatial domain
ne = 2**7
L = 15
mesh = fe.IntervalMesh(int(ne),0,L)
degQ = 1
degA = 1
QE = fe.FiniteElement("Lagrange", cell=mesh.ufl_cell(), degree=degQ)
AE = fe.FiniteElement("Lagrange", cell=mesh.ufl_cell(), degree=degA)
ME = fe.MixedElement([AE,QE])
V = fe.FunctionSpace(mesh,ME)
V_A = V.sub(0)
V_Q = V.sub(1)
(v1,v2) = fe.TestFunctions(V)
dv1 = fe.grad(v1)[0]
dv2 = fe.grad(v2)[0]
(u1,u2) = fe.TrialFunctions(V)
U0 = fe.Function(V)
U0.assign( fe.Expression( ( 'A0', 'Q0' ) , A0=A0, Q0=Q0, degree=1 ) )
Un = fe.Function(V)
Un.assign( fe.Expression( ( 'A0', 'Q0' ) , A0=A0, Q0=Q0, degree=1 ) )
(u01,u02) = fe.split(U0)
(un1,un2) = fe.split(Un)
du01 = fe.grad(u01)[0] ; du02 = fe.grad(u02)[0]
dun1 = fe.grad(un1)[0] ; dun2 = fe.grad(un2)[0]
mesh, dx, ds, boundaries = load_2d_muscle_geo()
cell = mesh.ufl_cell()
dim = 2
# Notation
# u: displacement field
# p: lagrange multiplier, pressure
# v: velocity field
element_u = fe.VectorElement('CG', cell, 2)
element_p = fe.FiniteElement('CG', cell, 1)
element_v = fe.VectorElement('CG', cell, 2)
# define mixed elements
mix_up = fe.MixedElement([element_u, element_p])
mix_uv = fe.MixedElement([element_u, element_v])
mix_pv = fe.MixedElement([element_p, element_v])
mix_upv = fe.MixedElement([element_u, element_p, element_v])
# define function spaces
V_u = fe.FunctionSpace(mesh, element_u)
V_p = fe.FunctionSpace(mesh, element_p)
V_v = fe.FunctionSpace(mesh, element_v)
V_up = fe.FunctionSpace(mesh, mix_up)
V_uv = fe.FunctionSpace(mesh, mix_uv)
V_pv = fe.FunctionSpace(mesh, mix_pv)
V_upv = fe.FunctionSpace(mesh, mix_upv)
# Material constants
c_10 = fe.Constant(1e4)
def demo16(self, permeability, obs_case=1):
"""This demo program solves the mixed formulation of Poisson's
equation:
sigma + grad(u) = 0 in Omega
div(sigma) = f in Omega
du/dn = g on Gamma_N
u = u_D on Gamma_D
The corresponding weak (variational problem)
<sigma, tau> + <grad(u), tau> = 0
for all tau
- <sigma, grad(v)> = <f, v> + <g, v>
for all v
is solved using DRT (Discontinuous Raviart-Thomas) elements
of degree k for (sigma, tau) and CG (Lagrange) elements
of degree k + 1 for (u, v) for k >= 1.
"""
mesh = UnitSquareMesh(15, 15)
ak_values = permeability
flux_order = 3
s = scenarios.darcy_problem_1()
DRT = fenics.FiniteElement("DRT", mesh.ufl_cell(), flux_order)
# Lagrange
CG = fenics.FiniteElement("CG", mesh.ufl_cell(), flux_order + 1)
if s.integral_constraint:
# From https://fenicsproject.org/qa/14184/how-to-solve-linear-system-with-constaint
R = fenics.FiniteElement("R", mesh.ufl_cell(), 0)
W = fenics.FunctionSpace(mesh, fenics.MixedElement([DRT, CG, R]))
# Define trial and test functions
(sigma, u, r) = fenics.TrialFunctions(W)
(tau, v, r_) = fenics.TestFunctions(W)
else:
W = fenics.FunctionSpace(mesh, DRT * CG)
# Define trial and test functions
(sigma, u) = fenics.TrialFunctions(W)
(tau, v) = fenics.TestFunctions(W)
f = s.source_function
g = s.g
# Define property field function
W_CG = fenics.FunctionSpace(mesh, "Lagrange", 1)
if s.ak is None:
ak = property_field.get_conductivity(W_CG, ak_values)
else:
ak = s.ak
# Define variational form
a = (fenics.dot(sigma, tau) + fenics.dot(ak * fenics.grad(u), tau) +
fenics.dot(sigma, fenics.grad(v))) * fenics.dx
L = -f * v * fenics.dx + g * v * fenics.ds
# L = 0
if s.integral_constraint:
# Lagrange multiplier? See above link.
a += r_ * u * fenics.dx + v * r * fenics.dx
# Define Dirichlet BC
bc = fenics.DirichletBC(W.sub(1), s.dirichlet_bc, s.gamma_dirichlet)
# Compute solution
w = fenics.Function(W)
fenics.solve(a == L, w, bc)
# fenics.solve(a == L, w)
if s.integral_constraint:
(sigma, u, r) = w.split()
else:
(sigma, u) = w.split()
x = u.compute_vertex_values(mesh)
x2 = sigma.compute_vertex_values(mesh)
p = x
pre = p.reshape((16, 16))
vx = x2[:256].reshape((16, 16))
vy = x2[256:].reshape((16, 16))
if obs_case == 1:
dd = np.zeros([8, 8])
pos = np.full((8 * 8, 2), 0)
col = [1, 3, 5, 7, 9, 11, 13, 15]
position = [1, 3, 5, 7, 9, 11, 13, 15]
for i in range(8):
for j in range(8):
row = position
pos[8 * i + j, :] = [col[i], row[j]]
dd[i, j] = pre[col[i], row[j]]
like = dd.reshape(8 * 8, )
return like, pre, vx, vy, ak_values, pos
import fenics as fn
# set parameters
fn.parameters["form_compiler"]["representation"] = "uflacs"
fn.parameters["form_compiler"]["cpp_optimize"] = True
# mesh setup
nps = 64 # number of points
mesh = fn.UnitSquareMesh(nps, nps)
fileu = fn.File(mesh.mpi_comm(), "Output/1_3_Schnackenberg/u.pvd")
filev = fn.File(mesh.mpi_comm(), "Output/1_3_Schnackenberg/v.pvd")
# function spaces
P1 = fn.FiniteElement("Lagrange", mesh.ufl_cell(), 1)
Mh = fn.FunctionSpace(mesh, "Lagrange", 1)
Nh = fn.FunctionSpace(mesh, fn.MixedElement([P1, P1]))
Sol = fn.Function(Nh)
# trial and test functions
u, v = fn.TrialFunctions(Nh)
uT, vT = fn.TestFunctions(Nh)
# model constants
a = fn.Constant(0.1305)
b = fn.Constant(0.7695)
c1 = fn.Constant(0.05)
c2 = fn.Constant(1.0)
d = fn.Constant(170.0)
# initial value
uinit = fn.Expression('a + b + 0.001 * exp(-100.0 * (pow(x[0] - 1.0/3, 2)' +
' + pow(x[1] - 0.5, 2)))',
with fn.XDMFFile("meshing/Dmesh.xdmf") as infile:
infile.read(mesh)
mvc = fn.MeshValueCollection("size_t", mesh, 2)
with fn.XDMFFile("meshing/Dmf.xdmf") as infile:
infile.read(mvc, "name_to_read")
mf = fn.cpp.mesh.MeshFunctionSizet(mesh, mvc)
# %%
M = 2 #species
Poly = fn.FiniteElement('Lagrange', mesh.ufl_cell(), 2)
Multi = fn.FiniteElement('Real', mesh.ufl_cell(), 0)
ElemP = [Poly] * (M + 1)
ElemR = [Multi] * (M)
Elem = [ElemP + ElemR][0]
Mixed = fn.MixedElement(Elem)
V = fn.FunctionSpace(mesh, Mixed)
# %%
# define potentials and concentrations
u_GND = fn.Expression('0', degree=2) #Ground
u_DD = fn.Expression('0.5', degree=2) #pontential
c_avg = fn.Expression('0.0001', degree=2) #average concentration
# set boundary conditions
bcs = []
bcs += [fn.DirichletBC(V.sub(0), u_DD, mf, 3)]
bcs += [fn.DirichletBC(V.sub(0), u_GND, mf, 1)]
# define problem
UC = fn.Function(V)
def compute_conv_diff_reac_video(self, initial_condition=None, video_ref=None, video_size=None):
names = {'Cl', 'K'}
P1 = FiniteElement('P', fe.triangle, 1)
element = fe.MixedElement([P1, P1])
V_single = FunctionSpace(self.mesh, P1)
V = FunctionSpace(self.mesh, element)
self.V_conc = V
# load video
video = VideoData(element=P1)
video.load_video(self.video_filename)
if( video_ref is not None and video_size is not None):
video.set_reference_frame(video_ref, video_size)
print(video)
dt = 0.05
t = 0.
t_end = 20.
u_init = Function(V)
(u_cl, u_k) = TrialFunction(V)
(v_cl, v_k) = TestFunction(V)
#u_na = video
if initial_condition is None:
#initial_condition = Expression(("f*exp(-0.5*((x[0]-a)*(x[0]-a)+(x[1]-b)*(x[1]-b))/var)/(sqrt(2*pi)*var)",
# "0."), a = 80, b= 55, var=10, f=10, pi=fe.pi, element=element)
initial_condition = Expression(("f",
"0."), a=80, b=55, var=0.1, f=0.1, pi=fe.pi, element=element)
u_init = fe.interpolate(initial_condition, V)
u_init_cl = u_init[0]
u_init_k = u_init[1]
u_init_na : VideoData= video
assert (self.flow is not None)
n = fe.FacetNormal(self.mesh)
dx, ds = self.dx, self.ds
flow = 5. * self.flow
f_in = fe.Constant(0.00)
f_in_cl = fe.Constant(-0.05)
D = fe.Constant(0.1)
C_na = fe.Constant(0.1)
k1 = fe.Constant(0.2)
k_1 = fe.Constant(0.00001)
# explicit
F = (
(u_cl - u_init_cl) * v_cl * dx
+ dt * D * inner(grad(u_cl), grad(v_cl)) * dx
+ dt * inner(flow, grad(u_cl)) * v_cl * dx
#+ (u_na - u_init_na) * v_na * dx
#+ dt * D * inner(grad(u_na), grad(v_na)) * dx
#+ dt * inner(flow, grad(u_na)) * v_na * dx
+ (u_k - u_init_k) * v_k * dx
+ dt * D * inner(grad(u_k), grad(v_k)) * dx
+ dt * inner(flow, grad(u_k)) * v_k * dx
+ f_in_cl * v_cl * dx
#+ f_in * v_na * dx
+ f_in * v_k * dx
+ dt * k1 * u_init_cl * C_na * u_init_na * v_cl * dx
#+ dt * k1 * u_init_cl * u_init_na * v_na * dx
- dt * k1 * u_init_cl * C_na * u_init_na * v_k * dx
- dt * k_1 * u_init_k * v_cl * dx
#- dt * k_1 * u_init_k * v_na * dx
+ dt * k_1 * u_init_k * v_k * dx
)
# implicit
F = (
(u_cl - u_init_cl) * v_cl * dx
+ dt * D * inner(grad(u_cl), grad(v_cl)) * dx
+ dt * inner(flow, grad(u_cl)) * v_cl * dx
# + (u_na - u_init_na) * v_na * dx
# + dt * D * inner(grad(u_na), grad(v_na)) * dx
# + dt * inner(flow, grad(u_na)) * v_na * dx
+ (u_k - u_init_k) * v_k * dx
+ dt * D * inner(grad(u_k), grad(v_k)) * dx
+ dt * inner(flow, grad(u_k)) * v_k * dx
+ f_in_cl * v_cl * dx
# + f_in * v_na * dx
+ f_in * v_k * dx
+ dt * k1 * u_cl * C_na * u_init_na * v_cl * dx
# + dt * k1 * u_init_cl * u_init_na * v_na * dx
- dt * k1 * u_cl * C_na * u_init_na * v_k * dx
- dt * k_1 * u_k * v_cl * dx
# - dt * k_1 * u_init_k * v_na * dx
+ dt * k_1 * u_k * v_k * dx
)
self.F = F
a, L = fe.lhs(F), fe.rhs(F)
a_mat = fe.assemble(a)
L_vec = fe.assemble(L)
output1 = fe.File('/tmp/cl_dyn.pvd')
output2 = fe.File('/tmp/na_dyn.pvd')
output3 = fe.File('/tmp/k_dyn.pvd')
output4 = fe.File('/tmp/all_dyn.pvd')
# solve
self.sol = []
u_na = Function(V_single)
u_na = fe.interpolate(u_init_na,V_single)
na_inflow = 0
t_plot = 0.5
t_last_plot = 0
while t < t_end:
t = t + dt
t_last_plot += dt
print(t)
u = Function(V)
u_init_na.set_time(5*t)
a_mat = fe.assemble(a)
L_vec = fe.assemble(L)
fe.solve(a_mat, u.vector(), L_vec)
# NonlinearVariationalProblem(F,u)
u_init.assign(u)
u_cl, u_k = u.split()
# u_init_cl.assign(u_cl)
# u_init_na.assign(u_na)
# u_init_k.assign(u_k)
u_na = fe.interpolate(u_init_na, V_single)
u_cl.rename("cl", "cl")
u_na.rename("na", "na")
u_k.rename("k", "k")
output1 << u_cl, t
output2 << u_na, t
output3 << u_k, t
self.sol.append((u_cl, u_na, u_k))
print( fe.assemble(u_cl*self.dx))
if t_last_plot > t_plot:
t_last_plot = 0
plt.figure(figsize=(8,16))
plt.subplot(211)
fe.plot(u_cl)
plt.subplot(212)
fe.plot(u_k)
plt.show()
self.u_cl = u_cl
#self.u_na = u_na
self.u_k = u_k
