def set_param_flow(self, gb, no_flow=False, kn=1e3, method="mpfa"):
# Set up flow field with uniform flow in y-direction
kw = "flow"
for g, d in gb:
parameter_dictionary = {}
perm = pp.SecondOrderTensor(kxx=np.ones(g.num_cells))
parameter_dictionary["second_order_tensor"] = perm
b_val = np.zeros(g.num_faces)
if g.dim == 2:
bound_faces = pp.face_on_side(g, ["ymin", "ymax"])
if no_flow:
b_val[bound_faces[0]] = 1
b_val[bound_faces[1]] = 1
bound_faces = np.hstack((bound_faces[0], bound_faces[1]))
labels = np.array(["dir"] * bound_faces.size)
parameter_dictionary["bc"] = pp.BoundaryCondition(
g, bound_faces, labels)
y_max_faces = pp.face_on_side(g, "ymax")[0]
b_val[y_max_faces] = 1
else:
parameter_dictionary["bc"] = pp.BoundaryCondition(g)
parameter_dictionary["bc_values"] = b_val
parameter_dictionary["mpfa_inverter"] = "python"
d[pp.PARAMETERS] = pp.Parameters(g, [kw], [parameter_dictionary])
d[pp.DISCRETIZATION_MATRICES] = {"flow": {}}
gb.add_edge_props("kn")
for e, d in gb.edges():
mg = d["mortar_grid"]
flow_dictionary = {
"normal_diffusivity": 2 * kn * np.ones(mg.num_cells)
}
d[pp.PARAMETERS] = pp.Parameters(keywords=["flow"],
dictionaries=[flow_dictionary])
d[pp.DISCRETIZATION_MATRICES] = {"flow": {}}
discretization_key = kw + "_" + pp.DISCRETIZATION
for g, d in gb:
# Choose discretization and define the solver
if method == "mpfa":
discr = pp.Mpfa(kw)
elif method == "mvem":
discr = pp.MVEM(kw)
else:
discr = pp.Tpfa(kw)
d[discretization_key] = discr
for _, d in gb.edges():
d[discretization_key] = pp.RobinCoupling(kw, discr)
def disabled_test_mono_equals_multi(self):
"""
test that the mono_dimensional elliptic solver gives the same answer as
the grid bucket elliptic
"""
g = pp.CartGrid([10, 10])
g.compute_geometry()
gb = pp.meshing.cart_grid([], [10, 10])
param_g = pp.Parameters(g)
def bc_val(g):
left = g.face_centers[0] < 1e-6
right = g.face_centers[0] > 10 - 1e-6
bc_val = np.zeros(g.num_faces)
bc_val[left] = -1
bc_val[right] = 1
return bc_val
def bc_labels(g):
bound_faces = g.tags["domain_boundary_faces"].nonzero()[0]
bound_face_centers = g.face_centers[:, bound_faces]
left = bound_face_centers[0] < 1e-6
right = bound_face_centers[0] > 10 - 1e-6
labels = np.array(["neu"] * bound_faces.size)
labels[np.logical_or(right, left)] = "dir"
bc_labels = pp.BoundaryCondition(g, bound_faces, labels)
return bc_labels
param_g.set_bc_val("flow", bc_val(g))
param_g.set_bc("flow", bc_labels(g))
gb.add_node_props(["param"])
for sub_g, d in gb:
d["param"] = pp.Parameters(sub_g)
d["param"].set_bc_val("flow", bc_val(g))
d["param"].set_bc("flow", bc_labels(sub_g))
for e, d in gb.edges():
gl, _ = gb.nodes_of_edge(e)
d_l = gb.node_props(gl)
d["kn"] = 1.0 / np.mean(d_l["param"].get_aperture())
problem_mono = pp.EllipticModel(g, {"param": param_g})
problem_mult = pp.EllipticModel(gb)
p_mono = problem_mono.solve()
p_mult = problem_mult.solve()
self.assertTrue(np.allclose(p_mono, p_mult))
def test_non_zero_bc_val(self):
"""
We mixed bc_val on domain boundary and fracture displacement in
x-direction.
"""
frac = np.array([[1, 1, 1], [1, 2, 1], [2, 2, 1], [2, 1, 1]]).T
physdims = np.array([3, 3, 2])
g = pp.meshing.cart_grid([frac], [3, 3, 2],
physdims=physdims).grids_of_dimension(3)[0]
data = {"param": pp.Parameters(g)}
# Define boundary conditions
bc_val = np.zeros((g.dim, g.num_faces))
frac_slip = np.zeros((g.dim, g.num_faces))
frac_bnd = g.tags["fracture_faces"]
dom_bnd = g.tags["domain_boundary_faces"]
frac_slip[0, frac_bnd] = np.ones(np.sum(frac_bnd))
bc_val[:, dom_bnd] = g.face_centers[:, dom_bnd]
bound = pp.BoundaryCondition(g, g.get_all_boundary_faces(), "dir")
data["param"].set_bc("mechanics", bound)
data["param"].set_bc_val("mechanics", bc_val.ravel("F"))
data["param"].set_slip_distance(frac_slip.ravel("F"))
solver = pp.FracturedMpsa()
A, b = solver.matrix_rhs(g, data)
u = np.linalg.solve(A.A, b)
u_f = solver.extract_frac_u(g, u)
u_c = solver.extract_u(g, u)
u_c = u_c.reshape((3, -1), order="F")
# Test traction
frac_faces = g.frac_pairs
frac_left = frac_faces[0]
frac_right = frac_faces[1]
T = solver.traction(g, data, u)
T = T.reshape((3, -1), order="F")
T_left = T[:, frac_left]
T_right = T[:, frac_right]
self.assertTrue(np.allclose(T_left, T_right))
# we have u_lhs - u_rhs = 1 so u_lhs should be positive
mid_ind = int(round(u_f.size / 2))
u_left = u_f[:mid_ind]
u_right = u_f[mid_ind:]
true_diff = np.atleast_2d(np.array([1, 0, 0])).T
u_left = u_left.reshape((3, -1), order="F")
u_right = u_right.reshape((3, -1), order="F")
self.assertTrue(np.all(np.abs(u_left - u_right - true_diff) < 1e-10))
# should have a positive displacement for all cells
self.assertTrue(np.all(u_c > 0))
def test_p1_1d(self):
g = pp.structured.CartGrid(1, 1)
g.compute_geometry()
kxx = np.ones(g.num_cells)
perm = pp.SecondOrderTensor(3, kxx, kyy=1, kzz=1)
bn = g.get_boundary_nodes()
bc = pp.BoundaryConditionNode(g, bn, bn.size * ["neu"])
solver = pp.P1(physics="flow")
param = pp.Parameters(g)
param.set_tensor(solver, perm)
param.set_bc(solver, bc)
M = solver.matrix(g, {"param": param}).todense()
M_known = np.matrix([[1., -1.], [-1., 1.]])
self.assertTrue(np.allclose(M, M_known))
solver = pp.P1MassMatrix(physics="flow")
M = solver.matrix(g, {"param": param}).todense()
M_known = np.matrix([[2., 1.], [1., 2.]]) / 6.
self.assertTrue(np.allclose(M, M_known))
def setup_cart_2d(nx):
frac1 = np.array([[0.2, 0.8], [0.5, 0.5]])
frac2 = np.array([[0.5, 0.5], [0.8, 0.2]])
fracs = [frac1, frac2]
gb = pp.meshing.cart_grid(fracs, nx, physdims=[1, 1])
gb.compute_geometry()
gb.assign_node_ordering()
kw = "flow"
aperture = 0.01 / np.max(nx)
for g, d in gb:
a = np.power(aperture, gb.dim_max() - g.dim) * np.ones(g.num_cells)
kxx = np.ones(g.num_cells) * a
perm = pp.SecondOrderTensor(kxx)
specified_parameters = {"second_order_tensor": perm}
if g.dim == 2:
bound_faces = g.tags["domain_boundary_faces"].nonzero()[0]
bound = pp.BoundaryCondition(g, bound_faces.ravel("F"),
["dir"] * bound_faces.size)
bc_val = np.zeros(g.num_faces)
bc_val[bound_faces] = g.face_centers[1, bound_faces]
specified_parameters.update({"bc": bound, "bc_values": bc_val})
# Initialize data and matrix dictionaries in d
pp.initialize_default_data(g, d, kw, specified_parameters)
for e, d in gb.edges():
# Compute normal permeability
gl, _ = gb.nodes_of_edge(e)
kn = 1.0 / aperture
data = {"normal_diffusivity": kn}
# Add parameters
d[pp.PARAMETERS] = pp.Parameters(keywords=[kw], dictionaries=[data])
# Initialize matrix dictionary
d[pp.DISCRETIZATION_MATRICES] = {kw: {}}
return gb
def test_rt0_1d_ani(self):
g = pp.structured.CartGrid(3, 1)
g.compute_geometry()
kxx = 1. / (np.sin(g.cell_centers[0, :]) + 1)
perm = pp.SecondOrderTensor(3, kxx, kyy=1, kzz=1)
bf = g.get_boundary_faces()
bc = pp.BoundaryCondition(g, bf, bf.size * ["dir"])
solver = pp.RT0(physics="flow")
param = pp.Parameters(g)
param.set_tensor(solver, perm)
param.set_bc(solver, bc)
M = solver.matrix(g, {"param": param}).todense()
M_known = np.matrix(
[
[0.12954401, 0.06477201, 0., 0., 1., 0., 0.],
[0.06477201, 0.29392463, 0.08219031, 0., -1., 1., 0.],
[0., 0.08219031, 0.3577336, 0.09667649, 0., -1., 1.],
[0., 0., 0.09667649, 0.19335298, 0., 0., -1.],
[1., -1., 0., 0., 0., 0., 0.],
[0., 1., -1., 0., 0., 0., 0.],
[0., 0., 1., -1., 0., 0., 0.],
]
)
self.assertTrue(np.allclose(M, M.T))
self.assertTrue(np.allclose(M, M_known))
def initial_condition(self) -> None:
"""
Initial value for the Darcy fluxes. TODO: Add to THM.
"""
for g, d in self.gb:
d[pp.PARAMETERS] = pp.Parameters()
d[pp.PARAMETERS].update_dictionaries(
[self.mechanics_parameter_key, self.scalar_parameter_key,]
)
self.update_all_apertures(to_iterate=False)
self.update_all_apertures()
super().initial_condition()
for g, d in self.gb:
d[pp.STATE]["cell_centers"] = g.cell_centers.copy()
p0 = self.initial_scalar(g)
state = {
self.scalar_variable: p0,
"u_exp_0": np.zeros(g.num_cells),
"aperture_0": self.aperture(g) * self.length_scale,
}
iterate = {
self.scalar_variable: p0,
} # For initial flux
pp.set_state(d, state)
pp.set_iterate(d, iterate)
def test_periodic_bc_with_fractues(self):
"""
We set up the test case P
|--------|
| g2| |
D | g3x g0| D
| g1| |
|--------|
P
where D are dirichlet boundaries and P the periodic boundaries.
We construct periodic solution
p = sin(pi/xmax * (x - x0)) * cos(2*pi/ymax * (y - y0))
which gives a source term on the rhs.
The domain is a 2D domain with two fractures (g1, and g2) connected
through the periodic bc and 0D intersection (g3)
"""
n = 8
xmax = 1
ymax = 1
gb = self.generate_grid_with_fractures(n, xmax, ymax)
tol = 1e-6
def analytic_p(x):
x = x.copy()
shiftx = xmax / 4
shifty = ymax / 3
x[0] = x[0] - shiftx
x[1] = x[1] - shifty
p = np.sin(np.pi / xmax * x[0]) * np.cos(2 * np.pi / ymax * x[1])
px = ((np.pi / xmax) * np.cos(np.pi / xmax * x[0]) *
np.cos(2 * np.pi / ymax * x[1]))
py = (2 * np.pi / ymax * np.sin(np.pi / xmax * x[0]) *
np.sin(2 * np.pi / ymax * x[1]))
pxx = -(np.pi / xmax)**2 * p
pyy = -(2 * np.pi / ymax)**2 * p
return p, np.vstack([px, py]), pxx + pyy
for g, d in gb:
d["param"] = pp.Parameters(g)
left = g.face_centers[0] < tol
right = g.face_centers[0] > xmax - tol
dir_bc = left + right
d["param"].set_bc("flow", pp.BoundaryCondition(g, dir_bc, "dir"))
bc_val = np.zeros(g.num_faces)
bc_val[dir_bc], _, _ = analytic_p(g.face_centers[:, dir_bc])
d["param"].set_bc_val("flow", bc_val)
aperture = 1e-6**(2 - g.dim)
d["param"].set_aperture(aperture)
pa, _, lpc = analytic_p(g.cell_centers)
src = -lpc * g.cell_volumes * aperture
d["param"].set_source("flow", src)
for _, d in gb.edges():
d["kn"] = 1e10
self.solve(gb, analytic_p)
def _set_data(self):
"""Create a Parameter object and assign data based on the returned
values from the functions (e.g., self.source(t))
"""
if "param" not in self._data:
self._data["param"] = pp.Parameters(self.grid())
self._data["param"].set_tensor(self.physics, self.diffusivity())
self._data["param"].set_bc(self.physics, self.bc())
self._data["param"].set_bc_val(self.physics, self.bc_val(0.0))
self._data["param"].set_source(self.physics, self.source(0.0))
if self.porosity() is not None:
self._data["param"].set_porosity(self.porosity())
if self.aperture() is not None:
self._data["param"].set_aperture(self.aperture())
if self.rock_specific_heat() is not None:
self._data["param"].set_rock_specific_heat(
self.rock_specific_heat())
if self.fluid_specific_heat() is not None:
self._data["param"].set_fluid_specific_heat(
self.fluid_specific_heat())
if self.rock_density() is not None:
self._data["param"].set_rock_density(self.rock_density())
if self.fluid_density() is not None:
self._data["param"].set_fluid_density(self.fluid_density())
def add_constant_darcy_flux(gb, upwind, flux, a):
"""
Adds the constant darcy_flux to all internal and mortar faces, the latter
in the "mortar_solution" field.
gb - grid bucket
upwind- upwind discretization class
flux - 3 x 1 flux at all faces [u, v, w]
a - cross-sectional area of the fractures.
"""
for g, d in gb:
aperture = np.ones(g.num_cells) * np.power(a, gb.dim_max() - g.dim)
d[pp.PARAMETERS]["transport"]["darcy_flux"] = upwind.darcy_flux(
g, flux, aperture)
for e, d in gb.edges():
g_h = gb.nodes_of_edge(e)[1]
p_h = gb.node_props(g_h, pp.PARAMETERS)
darcy_flux = p_h["transport"]["darcy_flux"]
sign = np.zeros(g_h.num_faces)
sign[g_h.get_all_boundary_faces()] = g_h.sign_of_faces(
g_h.get_all_boundary_faces())
mg = d["mortar_grid"]
sign = mg.master_to_mortar_avg() * sign
# d["param"] = pp.Parameters(g_h)
darcy_flux_e = sign * (d["mortar_grid"].master_to_mortar_avg() *
darcy_flux)
if pp.PARAMETERS not in d:
d[pp.PARAMETERS] = pp.Parameters(mg, ["transport"],
[{
"darcy_flux": darcy_flux_e
}])
else:
d[pp.PARAMETERS]["transport"]["darcy_flux"] = darcy_flux_e
def test_convergence_rt0_2d_iso_simplex_exact(self):
p_ex = lambda pt: 2 * pt[0, :] - 3 * pt[1, :] - 9
for i in np.arange(5):
g = pp.simplex.StructuredTriangleGrid([3 + i] * 2, [1, 1])
g.compute_geometry()
kxx = np.ones(g.num_cells)
perm = pp.SecondOrderTensor(3, kxx=kxx, kyy=kxx, kzz=1)
bf = g.get_boundary_faces()
bc = pp.BoundaryCondition(g, bf, bf.size * ["dir"])
bc_val = np.zeros(g.num_faces)
bc_val[bf] = p_ex(g.face_centers[:, bf])
solver = pp.RT0(physics="flow")
param = pp.Parameters(g)
param.set_tensor(solver, perm)
param.set_bc(solver, bc)
param.set_bc_val(solver, bc_val)
M, rhs = solver.matrix_rhs(g, {"param": param})
up = sps.linalg.spsolve(M, rhs)
p = solver.extract_p(g, up)
err = np.sum(np.abs(p - p_ex(g.cell_centers)))
self.assertTrue(np.isclose(err, 0))
def test_rt0_1d_iso(self):
g = pp.structured.CartGrid(3, 1)
g.compute_geometry()
kxx = np.ones(g.num_cells)
perm = pp.SecondOrderTensor(3, kxx, kyy=1, kzz=1)
bf = g.get_boundary_faces()
bc = pp.BoundaryCondition(g, bf, bf.size * ["dir"])
solver = pp.RT0(physics="flow")
param = pp.Parameters(g)
param.set_tensor(solver, perm)
param.set_bc(solver, bc)
M = solver.matrix(g, {"param": param}).todense()
M_known = np.matrix(
[
[0.11111111, 0.05555556, 0., 0., 1., 0., 0.],
[0.05555556, 0.22222222, 0.05555556, 0., -1., 1., 0.],
[0., 0.05555556, 0.22222222, 0.05555556, 0., -1., 1.],
[0., 0., 0.05555556, 0.11111111, 0., 0., -1.],
[1., -1., 0., 0., 0., 0., 0.],
[0., 1., -1., 0., 0., 0., 0.],
[0., 0., 1., -1., 0., 0., 0.],
]
)
self.assertTrue(np.allclose(M, M.T))
self.assertTrue(np.allclose(M, M_known))
def test_dual_rt0_1d_iso_line(self):
g = pp.structured.CartGrid(3, 1)
R = cg.rot(np.pi / 6., [0, 0, 1])
g.nodes = np.dot(R, g.nodes)
g.compute_geometry()
kxx = np.ones(g.num_cells)
perm = pp.SecondOrderTensor(3, kxx, kyy=1, kzz=1)
perm.rotate(R)
bf = g.get_boundary_faces()
bc = pp.BoundaryCondition(g, bf, bf.size * ["dir"])
solver = pp.RT0(physics="flow")
param = pp.Parameters(g)
param.set_tensor(solver, perm)
param.set_bc(solver, bc)
M = solver.matrix(g, {"param": param}).todense()
# Matrix computed with an already validated code
M_known = np.matrix(
[
[0.11111111, 0.05555556, 0., 0., 1., 0., 0.],
[0.05555556, 0.22222222, 0.05555556, 0., -1., 1., 0.],
[0., 0.05555556, 0.22222222, 0.05555556, 0., -1., 1.],
[0., 0., 0.05555556, 0.11111111, 0., 0., -1.],
[1., -1., 0., 0., 0., 0., 0.],
[0., 1., -1., 0., 0., 0., 0.],
[0., 0., 1., -1., 0., 0., 0.],
]
)
self.assertTrue(np.allclose(M, M.T))
self.assertTrue(np.allclose(M, M_known))
def test_p1_convergence_1d_exact(self):
p_ex = lambda pt: 2 * pt[0, :] - 3
for i in np.arange(5):
g = pp.structured.CartGrid(3 + i, 1)
g.compute_geometry()
kxx = np.ones(g.num_cells)
perm = pp.SecondOrderTensor(3, kxx, kyy=1, kzz=1)
bn = g.get_boundary_nodes()
bc = pp.BoundaryConditionNode(g, bn, bn.size * ["dir"])
bc_val = np.zeros(g.num_nodes)
bc_val[bn] = p_ex(g.nodes[:, bn])
solver = pp.P1(physics="flow")
param = pp.Parameters(g)
param.set_tensor(solver, perm)
param.set_bc(solver, bc)
param.set_bc_val(solver, bc_val)
M, rhs = solver.matrix_rhs(g, {"param": param})
p = sps.linalg.spsolve(M, rhs)
err = np.sum(np.abs(p - p_ex(g.nodes)))
self.assertTrue(np.isclose(err, 0))
def initialize_data(g,
data: Dict,
keyword: str,
specified_parameters: Optional[Dict] = None) -> Dict:
"""Initialize a data dictionary for a single keyword.
The initialization consists of adding a parameter dictionary and initializing a
matrix dictionary in the proper fields of data. If there is a Parameters object
in data, the new keyword is added using the update_dictionaries method.
Args:
g: The grid. Can be either standard grid, or mortar grid.
data: Outer data dictionary, to which the parameters will be added.
keyword: String identifying the parameters.
specified_parameters: A dictionary with specified parameters, defaults to empty
dictionary.
Returns:
data: The filled dictionary.
"""
if not specified_parameters:
specified_parameters = {}
add_discretization_matrix_keyword(data, keyword)
if pp.PARAMETERS in data:
data[pp.PARAMETERS].update_dictionaries([keyword],
[specified_parameters])
else:
data[pp.PARAMETERS] = pp.Parameters(g, [keyword],
[specified_parameters])
return data
def test_rt0_2d_iso_simplex_surf(self):
g = pp.simplex.StructuredTriangleGrid([1, 1], [1, 1])
R = cg.rot(-np.pi / 4., [1, 1, -1])
g.nodes = np.dot(R, g.nodes)
g.compute_geometry()
kxx = np.ones(g.num_cells)
perm = pp.SecondOrderTensor(3, kxx=kxx, kyy=kxx, kzz=1)
perm.rotate(R)
bf = g.get_boundary_faces()
bc = pp.BoundaryCondition(g, bf, bf.size * ["dir"])
solver = pp.RT0(physics="flow")
param = pp.Parameters(g)
param.set_tensor(solver, perm)
param.set_bc(solver, bc)
M = solver.matrix(g, {"param": param}).todense()
# Matrix computed with an already validated code
M_known = np.matrix(
[
[0.33333333, 0., 0., -0.16666667, 0., -1., 0.],
[0., 0.33333333, 0., 0., -0.16666667, 0., -1.],
[0., 0., 0.33333333, 0., 0., -1., 1.],
[-0.16666667, 0., 0., 0.33333333, 0., -1., 0.],
[0., -0.16666667, 0., 0., 0.33333333, 0., -1.],
[-1., 0., -1., -1., 0., 0., 0.],
[0., -1., 1., 0., -1., 0., 0.],
]
)
self.assertTrue(np.allclose(M, M.T))
# We test only the mass-Hdiv part
self.assertTrue(np.allclose(M, M_known))
def test_p1_2d_ani_simplex_surf(self):
g = pp.simplex.StructuredTriangleGrid([1, 1], [1, 1])
g.compute_geometry()
kxx = np.square(g.cell_centers[1, :]) + 1
kyy = np.square(g.cell_centers[0, :]) + 1
kxy = -np.multiply(g.cell_centers[0, :], g.cell_centers[1, :])
perm = pp.SecondOrderTensor(3, kxx=kxx, kyy=kyy, kxy=kxy, kzz=1)
R = cg.rot(np.pi / 3., [1, 1, 0])
perm.rotate(R)
g.nodes = np.dot(R, g.nodes)
g.compute_geometry()
bn = g.get_boundary_nodes()
bc = pp.BoundaryConditionNode(g, bn, bn.size * ["neu"])
solver = pp.P1(physics="flow")
param = pp.Parameters(g)
param.set_tensor(solver, perm)
param.set_bc(solver, bc)
M = solver.matrix(g, {"param": param}).todense()
# Matrix computed with an already validated code
M_known = np.matrix(
[
[1.11111111, -0.66666667, -0.66666667, 0.22222222],
[-0.66666667, 1.5, 0., -0.83333333],
[-0.66666667, 0., 1.5, -0.83333333],
[0.22222222, -0.83333333, -0.83333333, 1.44444444],
]
)
self.assertTrue(np.allclose(M, M.T))
self.assertTrue(np.allclose(M, M_known))
def test_p1_1d_ani(self):
g = pp.structured.CartGrid(3, 1)
g.compute_geometry()
kxx = np.sin(g.cell_centers[0, :]) + 1
perm = pp.SecondOrderTensor(3, kxx, kyy=1, kzz=1)
bn = g.get_boundary_nodes()
bc = pp.BoundaryConditionNode(g, bn, bn.size * ["neu"])
solver = pp.P1(physics="flow")
param = pp.Parameters(g)
param.set_tensor(solver, perm)
param.set_bc(solver, bc)
M = solver.matrix(g, {"param": param}).todense()
M_known = np.matrix(
[
[3.4976884, -3.4976884, 0., 0.],
[-3.4976884, 7.93596501, -4.43827662, 0.],
[0., -4.43827662, 9.65880718, -5.22053056],
[0., 0., -5.22053056, 5.22053056],
]
)
self.assertTrue(np.allclose(M, M.T))
self.assertTrue(np.allclose(M, M_known))
def test_rt0_2d_ani_simplex(self):
g = pp.simplex.StructuredTriangleGrid([1, 1], [1, 1])
g.compute_geometry()
al = np.square(g.cell_centers[1, :]) + np.square(g.cell_centers[0, :]) + 1
kxx = (np.square(g.cell_centers[0, :]) + 1) / al
kyy = (np.square(g.cell_centers[1, :]) + 1) / al
kxy = np.multiply(g.cell_centers[0, :], g.cell_centers[1, :]) / al
perm = pp.SecondOrderTensor(3, kxx=kxx, kyy=kyy, kxy=kxy, kzz=1)
bf = g.get_boundary_faces()
bc = pp.BoundaryCondition(g, bf, bf.size * ["dir"])
solver = pp.RT0(physics="flow")
param = pp.Parameters(g)
param.set_tensor(solver, perm)
param.set_bc(solver, bc)
M = solver.matrix(g, {"param": param}).todense()
# Matrix computed with an already validated code
M_known = np.matrix(
[
[0.39814815, 0., -0.0462963, -0.15740741, 0., -1., 0.],
[0., 0.39814815, 0.0462963, 0., -0.15740741, 0., -1.],
[-0.0462963, 0.0462963, 0.46296296, 0.00925926, -0.00925926, -1., 1.],
[-0.15740741, 0., 0.00925926, 0.34259259, 0., -1., 0.],
[0., -0.15740741, -0.00925926, 0., 0.34259259, 0., -1.],
[-1., 0., -1., -1., 0., 0., 0.],
[0., -1., 1., 0., -1., 0., 0.],
]
)
self.assertTrue(np.allclose(M, M.T))
self.assertTrue(np.allclose(M, M_known))
def setup_cart_2d(nx):
frac1 = np.array([[0.2, 0.8], [0.5, 0.5]])
frac2 = np.array([[0.5, 0.5], [0.8, 0.2]])
fracs = [frac1, frac2]
gb = pp.meshing.cart_grid(fracs, nx, physdims=[1, 1])
gb.compute_geometry()
gb.assign_node_ordering()
gb.add_node_props(["param"])
for g, d in gb:
kxx = np.ones(g.num_cells)
perm = pp.SecondOrderTensor(gb.dim_max(), kxx)
a = 0.01 / np.max(nx)
a = np.power(a, gb.dim_max() - g.dim)
param = pp.Parameters(g)
param.set_tensor("flow", perm)
param.set_aperture(a)
if g.dim == 2:
bound_faces = g.tags["domain_boundary_faces"].nonzero()[0]
bound = pp.BoundaryCondition(g, bound_faces.ravel("F"),
["dir"] * bound_faces.size)
bc_val = np.zeros(g.num_faces)
bc_val[bound_faces] = g.face_centers[1, bound_faces]
param.set_bc("flow", bound)
param.set_bc_val("flow", bc_val)
d["param"] = param
for e, d in gb.edges():
gl, _ = gb.nodes_of_edge(e)
d_l = gb.node_props(gl)
d["kn"] = 1. / np.mean(d_l["param"].get_aperture())
return gb
def test_two_cart_grids(self):
"""
We set up the test case -----|---------
| | |
| g1 | g2 |
| | |
-----|---------
with a linear pressure increase from left to right
"""
n = 2
xmax = 3
ymax = 1
split = 2
gb = self.generate_grids(n, xmax, ymax, split)
tol = 1e-6
for g, d in gb:
left = g.face_centers[0] < tol
right = g.face_centers[0] > xmax - tol
dir_bc = left + right
bound = pp.BoundaryCondition(g, dir_bc, "dir")
bc_val = np.zeros(g.num_faces)
bc_val[left] = xmax
bc_val[right] = 0
specified_parameters = {"bc": bound, "bc_values": bc_val}
pp.initialize_default_data(g, d, "flow", specified_parameters)
for e, d in gb.edges():
mg = d["mortar_grid"]
d[pp.PARAMETERS] = pp.Parameters(mg, ["flow"], [{}])
pp.params.data.add_discretization_matrix_keyword(d, "flow")
# assign discretization
data_key = "flow"
tpfa = pp.Tpfa(data_key)
coupler = pp.FluxPressureContinuity(data_key, tpfa)
assembler = test_utils.setup_flow_assembler(gb,
tpfa,
data_key,
coupler=coupler)
test_utils.solve_and_distribute_pressure(gb, assembler)
# test pressure
for g, d in gb:
self.assertTrue(
np.allclose(d[pp.STATE]["pressure"], xmax - g.cell_centers[0]))
# test mortar solution
for e, d_e in gb.edges():
mg = d_e["mortar_grid"]
g2, g1 = gb.nodes_of_edge(e)
master_to_m = mg.master_to_mortar_avg()
slave_to_m = mg.slave_to_mortar_avg()
master_area = master_to_m * g1.face_areas
slave_area = slave_to_m * g2.face_areas
self.assertTrue(
np.allclose(d_e[pp.STATE]["mortar_flux"] / master_area, 1))
self.assertTrue(
np.allclose(d_e[pp.STATE]["mortar_flux"] / slave_area, 1))
def add_data(gb, domain, kf, mesh_value):
"""
Define the permeability, apertures, boundary conditions and sources
"""
gb.add_node_props(['param'])
tol = 1e-5
a = 1e-4
for g, d in gb:
param = pp.Parameters(g)
# Assign apertures
a_dim = np.power(a, gb.dim_max() - g.dim)
aperture = np.ones(g.num_cells) * a_dim
param.set_aperture(aperture)
# Permeability
# Use fracture value in the fractures, i.e., the lower dimensional grids
k_frac = np.power(kf, g.dim < gb.dim_max())
p = pp.SecondOrderTensor(3, np.ones(g.num_cells) * k_frac)
param.set_tensor('flow', p)
param.set_tensor('flow', p)
# Source term
param.set_source('flow', np.zeros(g.num_cells))
# Boundaries
bound_faces = g.tags['domain_boundary_faces'].nonzero()[0]
if bound_faces.size != 0:
bound_face_centers = g.face_centers[:, bound_faces]
left = bound_face_centers[0, :] < domain['xmin'] + tol
right = bound_face_centers[0, :] > domain['xmax'] - tol
labels = np.array(['neu'] * bound_faces.size)
labels[right] = 'dir'
bc_val = np.zeros(g.num_faces)
if g.dim == 2:
# Account for the double inflow on the matrix-fracture overlap
left_mid = np.array(
np.absolute(g.face_centers[1, bound_faces[left]] -
0.5) < mesh_value)
bc_val[bound_faces[left]] = - g.face_areas[bound_faces[left]] \
+ left_mid * .5 * a
else:
bc_val[bound_faces[left]] = - \
g.face_areas[bound_faces[left]] * a
bc_val[bound_faces[right]] = np.ones(np.sum(right))
param.set_bc('flow', pp.BoundaryCondition(g, bound_faces, labels))
param.set_bc_val('flow', bc_val)
else:
param.set_bc("flow",
pp.BoundaryCondition(g, np.empty(0), np.empty(0)))
d['param'] = param
def add_data(gb, domain, kf):
"""
Define the permeability, apertures, boundary conditions
"""
gb.add_node_props(["param", "is_tangential"])
tol = 1e-5
a = 1e-4
for g, d in gb:
param = pp.Parameters(g)
# Permeability
kxx = np.ones(g.num_cells) * np.power(kf, g.dim < gb.dim_max())
if g.dim == 2:
perm = pp.SecondOrderTensor(g.dim, kxx=kxx, kyy=kxx, kzz=1)
else:
perm = pp.SecondOrderTensor(g.dim, kxx=kxx, kyy=1, kzz=1)
param.set_tensor("flow", perm)
# Source term
param.set_source("flow", np.zeros(g.num_cells))
# Assign apertures
aperture = np.power(a, gb.dim_max() - g.dim)
param.set_aperture(np.ones(g.num_cells) * aperture)
# Boundaries
bound_faces = g.tags["domain_boundary_faces"].nonzero()[0]
if bound_faces.size != 0:
bound_face_centers = g.face_centers[:, bound_faces]
left = bound_face_centers[0, :] < domain["xmin"] + tol
right = bound_face_centers[0, :] > domain["xmax"] - tol
labels = np.array(["neu"] * bound_faces.size)
labels[right] = "dir"
bc_val = np.zeros(g.num_faces)
bc_val[bound_faces[left]] = -aperture * g.face_areas[bound_faces[left]]
bc_val[bound_faces[right]] = 1
param.set_bc("flow", pp.BoundaryCondition(g, bound_faces, labels))
param.set_bc_val("flow", bc_val)
else:
param.set_bc("flow", pp.BoundaryCondition(g, np.empty(0), np.empty(0)))
d["is_tangential"] = True
d["param"] = param
# Assign coupling permeability
gb.add_edge_props("kn")
for e, d in gb.edges():
g_l = gb.nodes_of_edge(e)[0]
mg = d["mortar_grid"]
check_P = mg.low_to_mortar_avg()
gamma = check_P * gb.node_props(g_l, "param").get_aperture()
d["kn"] = kf * np.ones(mg.num_cells) / gamma
def test_unit_slip(self):
"""
test unit slip of fractures
"""
frac = np.array([[1, 1, 1], [1, 2, 1], [2, 2, 1], [2, 1, 1]]).T
physdims = np.array([3, 3, 2])
g = pp.meshing.cart_grid([frac], [3, 3, 2],
physdims=physdims).grids_of_dimension(3)[0]
data = {"param": pp.Parameters(g)}
bound = pp.BoundaryConditionVectorial(g, g.get_all_boundary_faces(),
"dir")
data["param"].set_bc("mechanics", bound)
frac_slip = np.zeros((g.dim, g.num_faces))
frac_bnd = g.tags["fracture_faces"]
frac_slip[:, frac_bnd] = np.ones((g.dim, np.sum(frac_bnd)))
data["param"].set_slip_distance(frac_slip.ravel("F"))
solver = pp.FracturedMpsa()
A, b = solver.matrix_rhs(g, data, inverter="python")
u = np.linalg.solve(A.A, b)
u_f = solver.extract_frac_u(g, u)
u_c = solver.extract_u(g, u)
u_c = u_c.reshape((3, -1), order="F")
# obtain fracture faces and cells
frac_faces = g.frac_pairs
frac_left = frac_faces[0]
frac_right = frac_faces[1]
cell_left = np.ravel(np.argwhere(g.cell_faces[frac_left, :])[:, 1])
cell_right = np.ravel(np.argwhere(g.cell_faces[frac_right, :])[:, 1])
# Test traction
T = solver.traction(g, data, u)
T = T.reshape((3, -1), order="F")
T_left = T[:, frac_left]
T_right = T[:, frac_right]
self.assertTrue(np.allclose(T_left, T_right))
# we have u_lhs - u_rhs = 1 so u_lhs should be positive
self.assertTrue(np.all(u_c[:, cell_left] > 0))
self.assertTrue(np.all(u_c[:, cell_right] < 0))
mid_ind = int(round(u_f.size / 2))
u_left = u_f[:mid_ind]
u_right = u_f[mid_ind:]
self.assertTrue(np.all(np.abs(u_left - u_right - 1) < 1e-10))
# fracture displacement should be symetric since everything else is
# symetric
self.assertTrue(np.allclose(u_left, 0.5))
self.assertTrue(np.allclose(u_right, -0.5))
def set_params(self, gb, kn, kf):
kw = "flow"
for g, d in gb:
parameter_dictionary = {}
aperture = np.power(1e-2, gb.dim_max() - g.dim)
parameter_dictionary["aperture"] = aperture * np.ones(g.num_cells)
b_val = np.zeros(g.num_faces)
if g.dim == 2:
bound_faces = pp.face_on_side(g, ["ymin", "ymax"])
bound_faces = np.hstack((bound_faces[0], bound_faces[1]))
labels = np.array(["dir"] * bound_faces.size)
parameter_dictionary["bc"] = pp.BoundaryCondition(
g, bound_faces, labels)
y_max_faces = pp.face_on_side(g, "ymax")[0]
b_val[y_max_faces] = 1
perm = pp.SecondOrderTensor(kxx=np.ones(g.num_cells))
parameter_dictionary["second_order_tensor"] = perm
else:
perm = pp.SecondOrderTensor(kxx=kf * np.ones(g.num_cells))
parameter_dictionary["second_order_tensor"] = perm
parameter_dictionary["bc"] = pp.BoundaryCondition(g)
parameter_dictionary["bc_values"] = b_val
parameter_dictionary["mpfa_inverter"] = "python"
d[pp.PARAMETERS] = pp.Parameters(g, [kw], [parameter_dictionary])
d[pp.DISCRETIZATION_MATRICES] = {"flow": {}}
gb.add_edge_props("kn")
for _, d in gb.edges():
mg = d["mortar_grid"]
flow_dictionary = {
"normal_diffusivity": kn * np.ones(mg.num_cells)
}
d[pp.PARAMETERS] = pp.Parameters(keywords=["flow"],
dictionaries=[flow_dictionary])
d[pp.DISCRETIZATION_MATRICES] = {"flow": {}}
def add_data_advection(gb, domain, tol):
# Porosity
phi_m = 1e-1
phi_f = 9 * 1e-1
# Density
rho_w = 1e3 # kg m^{-3}
rho_s = 2 * 1e3 # kg m^{-3}
# heat capacity
c_w = 4 * 1e3 # J kg^{-1} K^{-1}
c_s = 8 * 1e2 # J kg^{-1} K^{-1}
c_m = phi_m * rho_w * c_w + (1 - phi_m) * rho_s * c_s
c_f = phi_f * rho_w * c_w + (1 - phi_f) * rho_s * c_s
for g, d in gb:
param = d["param"]
rock = g.dim == gb.dim_max()
source = np.zeros(g.num_cells)
param.set_source("transport", source)
param.set_porosity(1)
param.set_discharge(d["discharge"])
bound_faces = g.tags["domain_boundary_faces"].nonzero()[0]
if bound_faces.size != 0:
bound_face_centers = g.face_centers[:, bound_faces]
bottom = bound_face_centers[1, :] < domain["ymin"] + tol
left = bound_face_centers[0, :] < domain["xmin"] + tol
right = bound_face_centers[0, :] > domain["xmax"] - tol
boundary = np.logical_or(left, right)
labels = np.array(["neu"] * bound_faces.size)
labels[boundary] = ["dir"]
bc_val = np.zeros(g.num_faces)
bc_val[bound_faces[left]] = 1
param.set_bc("transport",
pp.BoundaryCondition(g, bound_faces, labels))
param.set_bc_val("transport", bc_val)
else:
param.set_bc("transport",
pp.BoundaryCondition(g, np.empty(0), np.empty(0)))
d["param"] = param
# Assign coupling discharge
gb.add_edge_prop("param")
for e, d in gb.edges_props():
g = gb.sorted_nodes_of_edge(e)[1]
discharge = gb.node_prop(g, "param").get_discharge()
d["param"] = pp.Parameters(g)
d["param"].set_discharge(discharge)
def add_data(gb, domain, kf):
"""
Define the permeability, apertures, boundary conditions
"""
gb.add_node_props(['param'])
tol = 1e-5
a = 1e-4
for g, d in gb:
param = pp.Parameters(g)
# Permeability
kxx = np.ones(g.num_cells) * np.power(kf, g.dim < gb.dim_max())
if g.dim == 2:
perm = pp.SecondOrderTensor(g.dim, kxx=kxx, kyy=kxx, kzz=1)
else:
perm = pp.SecondOrderTensor(g.dim, kxx=kxx, kyy=1, kzz=1)
param.set_tensor("flow", perm)
# Source term
param.set_source("flow", np.zeros(g.num_cells))
# Assign apertures
aperture = np.power(a, gb.dim_max() - g.dim)
param.set_aperture(np.ones(g.num_cells) * aperture)
# Boundaries
bound_faces = g.tags['domain_boundary_faces'].nonzero()[0]
if bound_faces.size != 0:
bound_face_centers = g.face_centers[:, bound_faces]
left = bound_face_centers[0, :] < domain['xmin'] + tol
right = bound_face_centers[0, :] > domain['xmax'] - tol
labels = np.array(['neu'] * bound_faces.size)
labels[right] = 'dir'
bc_val = np.zeros(g.num_faces)
bc_val[bound_faces[left]] = -aperture \
* g.face_areas[bound_faces[left]]
bc_val[bound_faces[right]] = 1
param.set_bc("flow", pp.BoundaryCondition(g, bound_faces, labels))
param.set_bc_val("flow", bc_val)
else:
param.set_bc("flow",
pp.BoundaryCondition(g, np.empty(0), np.empty(0)))
d['param'] = param
# Assign coupling permeability
gb.add_edge_props('kn')
for e, d in gb.edges():
gn = gb.nodes_of_edge(e)
aperture = np.power(a, gb.dim_max() - gn[0].dim)
d['kn'] = np.ones(gn[0].num_cells) * kf / aperture
def add_data(gb, domain, kf):
"""
Define the permeability, apertures, boundary conditions
"""
gb.add_node_props(["param", "is_tangential"])
tol = 1e-5
a = 1e-4
for g, d in gb:
# Assign aperture
a_dim = np.power(a, gb.dim_max() - g.dim)
aperture = np.ones(g.num_cells) * a_dim
# Effective permeability, scaled with aperture.
kxx = np.ones(g.num_cells) * np.power(kf,
g.dim < gb.dim_max()) * aperture
if g.dim == 2:
perm = pp.SecondOrderTensor(kxx=kxx, kyy=kxx, kzz=1)
else:
perm = pp.SecondOrderTensor(kxx=kxx, kyy=1, kzz=1)
specified_parameters = {"second_order_tensor": perm}
# Boundaries
bound_faces = g.tags["domain_boundary_faces"].nonzero()[0]
if bound_faces.size != 0:
bound_face_centers = g.face_centers[:, bound_faces]
left = bound_face_centers[0, :] < domain["xmin"] + tol
right = bound_face_centers[0, :] > domain["xmax"] - tol
labels = np.array(["neu"] * bound_faces.size)
labels[right] = "dir"
bc_val = np.zeros(g.num_faces)
bc_val[
bound_faces[left]] = -a_dim * g.face_areas[bound_faces[left]]
bc_val[bound_faces[right]] = 1
bound = pp.BoundaryCondition(g, bound_faces, labels)
specified_parameters.update({"bc": bound, "bc_values": bc_val})
else:
bound = pp.BoundaryCondition(g, np.empty(0), np.empty(0))
specified_parameters.update({"bc": bound})
d["is_tangential"] = True
pp.initialize_default_data(g, d, "flow", specified_parameters)
# Assign coupling permeability
for _, d in gb.edges():
mg = d["mortar_grid"]
kn = 2 * kf * np.ones(mg.num_cells) / a
d[pp.PARAMETERS] = pp.Parameters(mg, ["flow"],
[{
"normal_diffusivity": kn
}])
d[pp.DISCRETIZATION_MATRICES] = {"flow": {}}
def setup_3d(nx, simplex_grid=False):
f1 = np.array([[0.2, 0.2, 0.8, 0.8], [0.2, 0.8, 0.8, 0.2],
[0.5, 0.5, 0.5, 0.5]])
f2 = np.array([[0.2, 0.8, 0.8, 0.2], [0.5, 0.5, 0.5, 0.5],
[0.2, 0.2, 0.8, 0.8]])
f3 = np.array([[0.5, 0.5, 0.5, 0.5], [0.2, 0.8, 0.8, 0.2],
[0.2, 0.2, 0.8, 0.8]])
fracs = [f1, f2, f3]
if not simplex_grid:
gb = pp.meshing.cart_grid(fracs, nx, physdims=[1, 1, 1])
else:
mesh_kwargs = {}
mesh_size = 0.3
mesh_kwargs = {
"mesh_size_frac": mesh_size,
"mesh_size_bound": 2 * mesh_size,
"mesh_size_min": mesh_size / 20,
}
domain = {"xmin": 0, "ymin": 0, "xmax": 1, "ymax": 1}
gb = pp.meshing.simplex_grid(fracs, domain, **mesh_kwargs)
gb.add_node_props(["param"])
for g, d in gb:
a = 0.01 / np.max(nx)
a = np.power(a, gb.dim_max() - g.dim)
param = pp.Parameters(g)
param.set_aperture(a)
# BoundaryCondition
left = g.face_centers[0] < 1e-6
top = g.face_centers[2] > 1 - 1e-6
dir_faces = np.argwhere(left)
bc_cond = pp.BoundaryCondition(g, dir_faces, ["dir"] * dir_faces.size)
bc_val = np.zeros(g.num_faces)
bc_val[dir_faces] = 3
bc_val[top] = 2.4
param.set_bc("flow", bc_cond)
param.set_bc_val("flow", bc_val)
# Source and sink
src = np.zeros(g.num_cells)
src[0] = np.pi
src[-1] = -np.pi
param.set_source("flow", src)
d["param"] = param
gb.add_edge_props("kn")
for e, d in gb.edges():
g = gb.nodes_of_edge(e)[0]
mg = d["mortar_grid"]
check_P = mg.slave_to_mortar_avg()
d["kn"] = 1 / (check_P * gb.node_props(g, "param").get_aperture())
return gb
def add_data_darcy(gb, domain, tol):
gb.add_node_props(["param", "if_tangent"])
apert = 1e-2
km = 7.5 * 1e-10 # 2.5*1e-11
kf = 5 * 1e-5
for g, d in gb:
param = pp.Parameters(g)
d["if_tangent"] = True
if g.dim == gb.dim_max():
kxx = km
else:
kxx = kf
perm = pp.SecondOrderTensor(g.dim, kxx * np.ones(g.num_cells))
param.set_tensor("flow", perm)
param.set_source("flow", np.zeros(g.num_cells))
param.set_aperture(np.power(apert, gb.dim_max() - g.dim))
bound_faces = g.tags["domain_boundary_faces"].nonzero()[0]
if bound_faces.size != 0:
bound_face_centers = g.face_centers[:, bound_faces]
top = bound_face_centers[2, :] > domain["zmax"] - tol
bottom = bound_face_centers[2, :] < domain["zmin"] + tol
boundary = np.logical_or(top, bottom)
labels = np.array(["neu"] * bound_faces.size)
labels[boundary] = ["dir"]
bc_val = np.zeros(g.num_faces)
p = np.abs(domain["zmax"] - domain["zmin"]) * 1e3 * 9.81
bc_val[bound_faces[bottom]] = p
param.set_bc("flow", pp.BoundaryCondition(g, bound_faces, labels))
param.set_bc_val("flow", bc_val)
else:
param.set_bc("flow", pp.BoundaryCondition(g, np.empty(0), np.empty(0)))
d["param"] = param
# Assign coupling permeability
gb.add_edge_prop("kn")
for e, d in gb.edges_props():
g = gb.sorted_nodes_of_edge(e)[0]
d["kn"] = kf / gb.node_prop(g, "param").get_aperture()
