def s(theta, theta0=prm.theta_m, eps=em.EPS):
return dolfin.conditional(
abs(theta - theta0) < eps,
prm.cp_m * eps + prm.L_m / 2,
dolfin.conditional(theta > theta0,
prm.cp_s * eps + prm.L_m,
prm.cp_s * eps))
def updateCoefficients(self):
x, y = SpatialCoordinate(self.mesh)
# r = .1*sqrt((x-np.pi)**2 + (y-np.pi)**2)
# self.u_ = pow(r,1.5) * sin(x) * sin(y)
# Set up explicit solution
self.u_ = sin(x) * sin(y)
# Init coefficient matrix
self.a1 = as_matrix([[2, .5], [
0.5, 1.5
]]) + conditional(x * y > 0, 1., -1.) * as_matrix([[1., .5], [.5, .5]])
self.a2 = as_matrix([[1.5, .5], [
0.5, 2.
]]) + conditional(x * y > 0, 1., -1.) * as_matrix([[.5, .5], [.5, 1.]])
self.a = self.gamma[0] * self.a1 + (1. - self.gamma[0]) * self.a2
# Init right-hand side
self.f1 = inner(self.a1, grad(grad(self.u_)))
self.f2 = inner(self.a2, grad(grad(self.u_)))
self.fcond = conditional(x * y > 0, 0., 1.)
# self.f = self.fcond * self.f1 + (1.-self.fcond) * self.f2
self.f = self.gamma[0] * self.f1 + (1. - self.gamma[0]) * self.f2
# conditional(x*x*x-y>0.0,2.0,1.0)]])
# self.f = inner(self.a, grad(grad(self.u_)))
# Set boundary conditions to exact solution
self.g = Constant(0.0)
def nu_PWC_harm(phi, cc):
A = df.conditional(df.gt(phi, 0.975), 1.0, 0.0)
B = df.conditional(df.lt(phi, 0.025), 1.0, 0.0)
nu = A * cc[r"\nu_1"]\
+ B * cc[r"\nu_2"]\
+ (1.0 - A - B) * 2.0 / (1.0 / cc[r"\nu_1"] + 1.0 / cc[r"\nu_2"])
return nu
def updateCoefficients(self):
# Init coefficient matrix
x = SpatialCoordinate(self.mesh)[0]
self.a = as_matrix([[.5 * (x * self.gamma[0] * self.sigmax)**2]])
self.b = as_vector([x * (self.gamma[0] * (self.mu - self.r) + self.r)])
self.c = Constant(0.0)
# Init right-hand side
self.f = Constant(0.0)
self.u_ = exp(
((self.mu - self.r)**2 / (2 * self.sigmax**2) * self.alpha /
(1 - self.alpha) + self.r * self.alpha) *
(self.T[1] - self.t)) * (x**self.alpha) / self.alpha
self.u_T = (x**self.alpha) / self.alpha
# Set boundary conditions
# self.g_t = lambda t : [(Constant(0.0), "near(x[0],0)")]
self.g = Constant(0.0)
# self.g_t = lambda t : self.u_t(t)
self.gamma_star = [
Constant((self.mu - self.r) / (self.sigmax**2 * (1 - self.alpha)))
]
self.loc = conditional(x > 0.5, conditional(x < 1.5, 1, 0), 0)
def nu_PWC_arit(phi, cc):
A = df.conditional(df.gt(phi, 0.975), 1.0, 0.0)
B = df.conditional(df.lt(phi, 0.025), 1.0, 0.0)
nu = A * cc[r"\nu_1"]\
+ B * cc[r"\nu_2"]\
+ (1.0 - A - B) * 0.5 * (cc[r"\nu_1"] + cc[r"\nu_2"])
return nu
def hs_C0():
if type(x) == np.ndarray:
y = 0.0*x
for pos, val in enumerate(x):
if abs(val - x0) < eps:
y[pos] = (val-x0)/(2*eps)+0.5
elif val > x0:
y[pos] = 1
else:
y[pos] = 0
return y
return dolfin.conditional(abs(x-x0)<eps,(x-x0)/(2*eps)+0.5, dolfin.conditional(x>x0, 1, 0))
def _speed_squared(self, state):
""" The velocity speed with turbine cut in and out speed limits """
speed_sq = dot(state[0], state[0]) + dot(state[1], state[1])
if self._cut_in_speed is not None:
speed_sq *= conditional(speed_sq < self._cut_in_speed**2, self._eps, 1)
if self._cut_out_speed is not None:
speed_sq = conditional(speed_sq > self._cut_out_speed**2,
self._cut_out_speed**2, speed_sq)
return speed_sq
def updateCoefficients(self):
x, y = SpatialCoordinate(self.mesh)
self.a = as_matrix([[1.0, 0.], [0., 1.]])
# Init right-hand side
xi = 0.5 + pi / 100
self.u_ = conditional(x <= xi, 0.0, 0.5 * (x - xi)**2)
# self.f = inner(self.a, grad(grad(self.u_)))
self.f = conditional(x <= xi, 0.0, 1.0)
# Set boundary conditions to exact solution
self.g = self.u_
def sign(x, x0=0.0):
""" Give sign of the argument x-x0.
Parameters
----------
x: float
Input argument which position with respect to x0 we want to know
x0: float, optional
Center point.
Returns
-------
-1,1,0: float
A float representing the sign of the argument x-x0
"""
return dolfin.conditional(x<x0-dolfin.DOLFIN_EPS,-1,dolfin.conditional((x-x0)<dolfin.DOLFIN_EPS,0,1))
def navier_stokes_stabilization_penalties(
simulation,
nu,
velocity_continuity_factor_D12=0,
pressure_continuity_factor=0,
no_coeff=False,
):
"""
Calculate the stabilization parameters needed in the DG scheme
"""
ndim = simulation.ndim
mpm = simulation.multi_phase_model
mesh = simulation.data['mesh']
use_const = simulation.input.get_value(
'solver/spatially_constant_penalty', False, 'bool'
)
if no_coeff:
mu_min = mu_max = 1.0
else:
mu_min, mu_max = mpm.get_laminar_dynamic_viscosity_range()
P = simulation.data['Vu'].ufl_element().degree()
if use_const:
simulation.log.info(' Using spatially constant elliptic penalty')
penalty_dS = define_penalty(
mesh, P, mu_min, mu_max, boost_factor=3, exponent=1.0
)
penalty_ds = penalty_dS * 2
simulation.log.info(
' DG SIP penalty: dS %.1f ds %.1f' % (penalty_dS, penalty_ds)
)
penalty_dS = Constant(penalty_dS)
penalty_ds = Constant(penalty_ds)
else:
simulation.log.info(' Using spatially varying elliptic penalties')
penalty_dS = define_spatially_varying_penalty(
simulation, P, mu_min, mu_max, boost_factor=3, exponent=1.0
)
penalty_ds = penalty_dS * 2
penalty_dS = dolfin.conditional(
dolfin.lt(penalty_dS('+'), penalty_dS('-')),
penalty_dS('-'),
penalty_dS('+'),
)
if velocity_continuity_factor_D12:
D12 = Constant([velocity_continuity_factor_D12] * ndim)
else:
D12 = Constant([0] * ndim)
if pressure_continuity_factor:
h = simulation.data['h']
h = Constant(1.0)
D11 = avg(h / nu) * Constant(pressure_continuity_factor)
else:
D11 = None
return penalty_dS, penalty_ds, D11, D12
def forms_theta_linear(self, psih0, uh, dt, theta_map,
theta_L=Constant(1.0), dpsi0=Constant(0.), dpsi00=Constant(0.),
h=Constant(0.), neumann_idx=99, zeta=Constant(0)):
(psi, lamb, psibar) = self.__trial_functions()
(w, tau, wbar) = self.__test_functions()
beta_map = self.beta_map
n = self.n
facet_integral = self.facet_integral
psi_star = psih0 + (1-theta_L)*dpsi00 + theta_L * dpsi0
# LHS contributions
gamma = conditional(ge(dot(uh, n), 0), 0, 1)
# Standard formulation
N_a = facet_integral(beta_map*dot(psi, w)) \
+ zeta * dot(grad(psi), grad(w)) * dx
G_a = dot(lamb, w)/dt * dx - theta_map * dot(uh, grad(lamb))*w*dx \
+ theta_map * (1-gamma) * dot(uh, n) * \
lamb * w * self.ds(neumann_idx)
L_a = -facet_integral(beta_map * dot(psibar, w)) # \
H_a = facet_integral(dot(uh, n)*psibar * tau) \
- dot(uh, n)*psibar * tau * self.ds(neumann_idx)
B_a = facet_integral(beta_map * dot(psibar, wbar))
# RHS contributions
Q_a = dot(Constant(0), w) * dx
R_a = dot(psi_star, tau)/dt*dx \
+ (1-theta_map)*dot(uh, grad(tau))*psih0*dx \
- (1-theta_map) * (1-gamma) * dot(uh, n) * psi_star * tau * self.ds(neumann_idx) \
- gamma*dot(h, tau) * self.ds(neumann_idx)
S_a = facet_integral(Constant(0) * wbar)
return self.__fem_forms(N_a, G_a, L_a, H_a, B_a, Q_a, R_a, S_a)
def get_colour_function(self, k):
"""
Return the colour function on timestep t^{n+k}
"""
if k == 0:
if self.continuous_fields:
c = self.continuous_c
else:
c = self.simulation.data['c']
elif k == -1:
if self.continuous_fields:
c = self.continuous_c_old
else:
c = self.simulation.data['cp']
elif k == -2:
if self.continuous_fields:
c = self.continuous_c_oldold
else:
c = self.simulation.data['cpp']
if self.force_bounded:
c = dolfin.max_value(dolfin.min_value(c, Constant(1.0)),
Constant(0.0))
if self.force_sharp:
c = dolfin.conditional(dolfin.ge(c, 0.5), Constant(1.0),
Constant(0.0))
return c
def get_transition_bounds(self):
'''Returns dictionary of `(lower, upper)` bounds for energy
transitions. See :py:meth:`get_transition_lower_bounds` for more.
'''
lowers = self.get_transition_lower_bounds()
upper_bound = ufl.as_ufl(self.inf_upper_bound.m_as(self.energy_unit))
r = {}
for k, lower in lowers.items():
lst = []
for k2, lower2 in lowers.items():
if k == k2: continue
# FIXME: this is WRONG if lower is exactly equal to lower2
lst.append(
dolfin.conditional(
ufl.as_ufl(lower2.m) < lower.m, upper_bound, lower2.m))
if not lst:
lst.append(upper_bound)
upper = self._ufl_minimum(lst)
r[k] = (lower, upper * lower.units)
return r
def get_strandberg_I(self):
u = self.unit_registry
h = u('1 planck_constant')
c = u('1 speed_of_light')
kT = self.pdd.kT
mu = self.pdd.mesh_util
n_r = 1
K = (8 * dolfin.pi * n_r **2) / (h**3 * c**2)
E_L, E_U = self.get_absorption_bounds()
# equivalent to flipping integration bounds if E_U < E_L
sign = dolfin.conditional(dolfin.gt(
E_U.magnitude,
E_L.m_as(E_U.units)), +1, -1)
# antiderivative of `E^2 exp(E/kT)`
def F(E):
return -kT*(2*kT**2 + 2*E*kT + E**2) * mu.exp(-E/kT)
I = F(E_U) - F(E_L)
ans = K * I * sign
# to evaluate integrals
# ans = (ans.m((0.0, 0.0)) * ans.units).to("1 / centimeter ** 2 / second")
# print(self.src_band.key, self.dst_band.key, ans)
return ans
def main():
fsr = FunctionSubspaceRegistry()
deg = 2
mesh = dolfin.UnitSquareMesh(100, 3)
muc = mesh.ufl_cell()
el_w = dolfin.FiniteElement('DG', muc, deg - 1)
el_j = dolfin.FiniteElement('BDM', muc, deg)
el_DG0 = dolfin.FiniteElement('DG', muc, 0)
el = dolfin.MixedElement([el_w, el_j])
space = dolfin.FunctionSpace(mesh, el)
DG0 = dolfin.FunctionSpace(mesh, el_DG0)
fsr.register(space)
facet_normal = dolfin.FacetNormal(mesh)
xyz = dolfin.SpatialCoordinate(mesh)
trial = dolfin.Function(space)
test = dolfin.TestFunction(space)
w, c = dolfin.split(trial)
v, phi = dolfin.split(test)
sympy_exprs = derive_exprs()
exprs = {
k: sympy_dolfin_printer.to_ufl(sympy_exprs['R'], mesh, v)
for k, v in sympy_exprs['quantities'].items()
}
f = exprs['f']
w0 = dolfin.project(dolfin.conditional(dolfin.gt(xyz[0], 0.5), 1.0, 0.3),
DG0)
w_BC = exprs['w']
dx = dolfin.dx()
form = (+v * dolfin.div(c) * dx - v * f * dx +
dolfin.exp(w + w0) * dolfin.dot(phi, c) * dx +
dolfin.div(phi) * w * dx -
(w_BC - w0) * dolfin.dot(phi, facet_normal) * dolfin.ds() -
(w0('-') - w0('+')) * dolfin.dot(phi('+'), facet_normal('+')) *
dolfin.dS())
solver = NewtonSolver(form,
trial, [],
parameters=dict(relaxation_parameter=1.0,
maximum_iterations=15,
extra_iterations=10,
relative_tolerance=1e-6,
absolute_tolerance=1e-7))
solver.solve()
with closing(XdmfPlot("out/qflop_test.xdmf", fsr)) as X:
CG1 = dolfin.FunctionSpace(mesh, dolfin.FiniteElement('CG', muc, 1))
X.add('w0', 1, w0, CG1)
X.add('w_c', 1, w + w0, CG1)
X.add('w_e', 1, exprs['w'], CG1)
X.add('f', 1, f, CG1)
X.add('cx_c', 1, c[0], CG1)
X.add('cx_e', 1, exprs['c'][0], CG1)
def updateCoefficients(self):
x, y = SpatialCoordinate(self.mesh)
# Init coefficient matrix
self.a = as_matrix([[
2.0,
sin(pi * (20 * x * y + .5)) * conditional(x * y > 0, 1, -1)
], [sin(pi * (20 * x * y + .5)) * conditional(x * y > 0, 1, -1), 2.0]])
self.u_ = x * y * sin(2 * pi * x) * \
sin(3 * pi * y) / (x ** 2 + y ** 2 + 1)
# Init right-hand side
self.f = inner(self.a, grad(grad(self.u_)))
# Set boundary conditions to exact solution
self.g = self.u_
def inside_absorption_bounds_conditional(self, E, value):
E_L, E_U = self.get_absorption_bounds()
E_L = E_L.m_as('eV')
E_U = E_U.m_as('eV')
E = E.m_as('eV')
return value.units * dolfin.conditional(
ufl.And(E_L <= E, E < E_U), value.magnitude, 0)
def norm_theta_grad_local():
delta_local = 1.5
local_proj = dolfin.conditional(abs(theta-prm.theta_m)<delta_local,1.,0.)
norm_theta_grad = dolfin.project(local_proj*dolfin.sqrt(dolfin.inner(dolfin.grad(theta),dolfin.grad(theta))),theta.function_space(),solver_type="cg",preconditioner_type="hypre_amg")
return norm_theta_grad.vector().norm('linf')
def initControl(self):
# Initialize control spaces
self.controlSpace = [FunctionSpace(self.mesh, "DG", 0)]
# Initialize controls
u_lapl = Dx(Dx(self.u, 0), 0) + Dx(Dx(self.u, 1), 1)
# Method 1:
self.gamma = [conditional(u_lapl >= 0, self.alpha0, self.alpha1)]
def df_C0():
if type(x) == np.ndarray:
y = 0.0*x
for pos, val in enumerate(x):
if abs(val - x0) < eps:
y[pos] = (1.0/(eps**2))*(eps-np.sign(val-x0)*(val-x0))
else:
y[pos] = 0
return y
return dolfin.conditional(abs(x-x0)<eps,(1.0/(eps**2))*(eps-sign(x-x0)*(x-x0)), 0)
def df_disC():
if type(x) == np.ndarray:
y = 0.0*x
for pos, val in enumerate(x):
if abs(val - x0) < eps:
y[pos] = 1.0/(2*eps)
else:
y[pos] = 0
return y
return dolfin.conditional(abs(x-x0)<eps,1.0/(2*eps), 0.)
def initControl(self):
# Initialize control spaces
self.controlSpace = [FunctionSpace(self.mesh, "DG", 0)]
# Initialize controls
u_x = Dx(self.u, 0)
u_y = Dx(self.u, 1)
u_lapl = Dx(u_x, 0) + Dx(u_y, 1)
self.gamma = [conditional(u_lapl >= 0, self.alpha0, self.alpha1)]
def df_C1():
if type(x) == np.ndarray:
y = 0.0*x
for pos, val in enumerate(x):
if abs(val - x0) < eps:
y[pos] = 15/(16*eps**5)*(((val-x0)+eps)**2*((val-x0)-eps)**2)
else:
y[pos] = 0
return y
return dolfin.conditional(abs(x-x0)<eps, 15/(16*eps**5)*(((x-x0)+eps)**2*((x-x0)-eps)**2), 0)
def subplus(x):
r"""
Ramp function
.. math::
\max\{x,0\}
"""
return dolfin.conditional(dolfin.ge(x, 0.0), x, 0.0)
def heaviside(x):
r"""
Heaviside function
.. math::
\frac{\mathrm{d}}{\mathrm{d}x} \max\{x,0\}
"""
return dolfin.conditional(dolfin.ge(x, 0.0), 1.0, 0.0)
def after_last_compute(self, get):
self.mag_ta_wss = get("Magnitude_TimeIntegral_WSS-OSI")
self.ta_mag_wss = get("TimeIntegral_Magnitude_WSS-OSI")
#print self.name, " Calling after_last_compute"
expr = conditional(self.ta_mag_wss < 1e-15,
0.0,
0.5 * (1.0 - self.mag_ta_wss / self.ta_mag_wss))
self.osi.assign(project(expr, self.osi.function_space()))
return self.osi
def updateCoefficients(self):
# Init coefficient matrix
x, y = SpatialCoordinate(self.mesh)
self.a = as_matrix([[.02, .01],
[0.01, conditional(x**3 - y > 0.0, 2.0, 1.0)]])
# Init right-hand side
self.f = -1.0
# Set boundary conditions to exact solution
self.g = Constant(0.0)
def setUp(self):
self.mesh = mesh = dolfin.UnitSquareMesh(20, 2, "left")
self.DG0_element = DG0e = dolfin.FiniteElement("DG", mesh.ufl_cell(),
0)
self.DG0v_element = DG0ve = dolfin.VectorElement(
"DG", mesh.ufl_cell(), 0)
self.DG0 = DG0 = dolfin.FunctionSpace(mesh, DG0e)
self.DG0v = DG0v = dolfin.FunctionSpace(mesh, DG0ve)
self.fsr = fsr = FunctionSubspaceRegistry()
fsr.register(DG0)
fsr.register(DG0v)
self.cellmid = cm = CellMidpointExpression(mesh, element=DG0ve)
self.n = n = dolfin.FacetNormal(mesh)
self.u = u = dolfin.Function(DG0)
self.v = v = dolfin.TestFunction(DG0)
u_bc = dolfin.Expression('x[0]', degree=2)
x = dolfin.SpatialCoordinate(mesh)
self.rho = rho = dolfin.conditional(
dolfin.lt((x[0] - 0.5)**2 + (x[1] - 0.5)**2, 0.2**2), 0.0, 0.0)
dot = dolfin.dot
cellsize = dolfin.CellSize(mesh)
self.h = h = cm('+') - cm('-')
self.h_boundary = h_boundary = 2 * n * dot(x - cm, n)
self.E = E = h / dot(h, h) * (u('-') - u('+'))
self.E_boundary = E_boundary = h_boundary / dot(
h_boundary, h_boundary) * (u - u_bc)
dS = dolfin.dS
eps = 1e-8
class BL(dolfin.SubDomain):
def inside(self, x, on_boundary):
return abs(x[0]) < eps
class BR(dolfin.SubDomain):
def inside(self, x, on_boundary):
return abs(x[0] - 1) < eps
ff = dolfin.FacetFunction('size_t', mesh, 0)
BL().mark(ff, 1)
BR().mark(ff, 1)
ds = dolfin.Measure('ds', domain=mesh, subdomain_data=ff)
self.F = (dot(E, n('+')) * v('+') * dS + dot(E, n('-')) * v('-') * dS -
v * rho * dolfin.dx + dot(E_boundary, n) * v * ds(1))
def initControl(self):
# Initialize control spaces
self.controlSpace = []
self.controlSpace.append(FunctionSpace(self.mesh, "DG", 0))
self.controlSpace.append(FunctionSpace(self.mesh, "DG", 1))
self.controlSpace.append(FunctionSpace(self.mesh, "DG", 1))
# Initialize controls
u_x = Dx(self.u, 0)
u_y = Dx(self.u, 1)
u_lapl = Dx(u_x, 0) + Dx(u_y, 1)
g_a = conditional(u_lapl >= 0, self.alpha0, self.alpha1)
u_norm = sqrt(u_x**2 + u_y**2)
g_x = conditional(u_norm > 0, u_x / u_norm, 0)
g_y = conditional(u_norm > 0, u_y / u_norm, 0)
self.gamma = []
self.gamma.append(g_a)
self.gamma.append(g_x)
self.gamma.append(g_y)
def initControl(self):
# Initialize control spaces
self.controlSpace = [FunctionSpace(self.mesh, "DG", 1)]
# Initialize controls
x = SpatialCoordinate(self.mesh)[0]
u_x = Dx(self.u, 0)
u_xx = Dx(u_x, 0)
g1 = conditional(
x > 0, -(self.mu - self.r) * u_x / (x * self.sigmax**2 * u_xx), 0)
self.gamma = [g1]
def updateCoefficients(self):
# Init coefficient matrix
x, y = SpatialCoordinate(self.mesh)
off_diag = conditional(x * y > 0, 1.0, -1.0)
self.a = as_matrix([[2.0, off_diag], [off_diag, 2.0]])
self.u_ = x * y * (1 - exp(1 - abs(x))) * (1 - exp(1 - abs(y)))
# Init right-hand side
self.f = inner(self.a, grad(grad(self.u_)))
# Set boundary conditions to exact solution
self.g = self.u_
def _normalize(self, graceful = True):
if not isinstance(self, Function):
raise Exception("Cannot normalize '%s'." % type(self))
f = self.copy(True)
v = TestFunction(f.function_space())
# if graceful = True: (0,0,0) -> (1,0,0)
# False: (0,0,0) -> (0,0,0)
fx = 1.0 if graceful else 0.0
expr = conditional(eq(inner(f, f), 0.0), \
Constant((fx, 0.0, 0.0)), \
f / sqrt(inner(f, f)))
result = Function(f.function_space())
assemble(inner(v, expr) * dP, result.vector())
setattr(self._state, self.name(), result)
def compute(self, get):
# Requires the fields Magnitude(TimeIntegral("WSS", label="OSI")) and
# TimeIntegral(Magnitude("WSS"), label="OSI")
#self.mag_ta_wss = get("Magnitude_TimeIntegral_WSS_OSI")
#self.ta_mag_wss = get("TimeIntegral_Magnitude_WSS_OSI")
self.mag_ta_wss = get("Magnitude_TimeIntegral_WSS-OSI")
self.ta_mag_wss = get("TimeIntegral_Magnitude_WSS-OSI")
if self.params.finalize:
return None
elif self.mag_ta_wss == None or self.ta_mag_wss == None:
return None
else:
expr = conditional(self.ta_mag_wss < 1e-15,
0.0,
0.5 * (1.0 - self.mag_ta_wss / self.ta_mag_wss))
self.osi.assign(project(expr, self.osi.function_space()))
return self.osi
