def test_transmissibility_tpfa_no_micro_fractures(self):
g = create_grids.cart_2d()
macro_bc = pp.BoundaryCondition(g)
discr = Tpfa_DFM()
internal_faces = [1, 4, 7, 11, 12, 13, 14]
for reg in discr._interaction_regions(g):
# consider only the internal faces
if np.all(np.isin(reg.reg_ind, internal_faces)):
local_gb = LocalGridBucketSet(g.dim, reg)
local_gb.construct_local_buckets()
basis_functions, cc_assembler, cc_bc_values = lp.cell_basis_functions(
reg, local_gb, discr, {"bc": macro_bc})
_, _, trm = lp.compute_transmissibilies(
reg,
local_gb,
basis_functions,
cc_assembler,
cc_bc_values,
g,
discr,
{"bc": macro_bc},
)
self.assertTrue(np.allclose(np.abs(trm), 1))
self.assertTrue(np.allclose(np.sum(trm), 0))
def test_partition_unity_tpfa_multiple_boundary_intersecting_local_micro_fracture(
self, ):
g = create_grids.cart_2d()
pts = np.array([[0.7, 0.9, 0.815, 0.95], [1.1, 1.4, 1.35, 1]])
edges = np.array([[0, 2], [1, 3]])
internal_faces = [4]
self._check_partition_unity(g, internal_faces, Tpfa_DFM(), pts, edges)
def test_partition_unity_tpfa_multiple_intersecting_local_micro_fractures(
self):
g = create_grids.cart_2d()
pts = np.array([[0.8, 1.2, 1.1, 1.1], [1.3, 1.6, 1.4, 1.8]])
edges = np.array([[0, 2], [1, 3]])
internal_faces = [4]
self._check_partition_unity(g, internal_faces, Tpfa_DFM(), pts, edges)
def main():
# example in 2d
file_name = "network.csv"
write_network(file_name)
# load the network and split it, we assume 2d
domain = {"xmin": 0, "xmax": 1, "ymin": 0, "ymax": 1}
global_network = pp.fracture_importer.network_2d_from_csv(file_name,
domain=domain)
global_network = global_network.split_intersections()
# select a subsample of the fractures
macro_network, micro_network = split_network(global_network,
Criterion.every)
# NOTE: the explicit network is empty so far
# create the macroscopic grid
mesh_size = 2
mesh_kwargs = {
"mesh_size_frac": mesh_size,
"mesh_size_min": mesh_size / 20
}
gb = macro_network.mesh(mesh_kwargs)
# plot the suff
pp.plot_fractures(micro_network.pts, micro_network.edges,
micro_network.domain)
pp.plot_grid(gb, info="c", alpha=0)
# construct the solver
tpfa_dfm = Tpfa_DFM()
# Set data for the upscaling problem
g = gb.grids_of_dimension(gb.dim_max())[0]
d = gb.node_props(g)
# store the
# EK: We probably need to initialize some of the nested dictionaries
d[pp.PARAMETERS][tpfa_dfm.keyword][
tpfa_dfm.network_keyword] = micro_network
# set parameters and discretization variables
# EK: This must be done in this run-script - it is not the responsibility of the
# discretization. We may want to construct a model for this.
# tpfa_dfm.set_parameters(gb)
# tpfa_dfm.set_variables_discretizations(gb)
# discretize with the assembler
assembler = pp.Assembler(gb)
assembler.discretize()
A, b = assembler.assemble_matrix_rhs()
# Solve and distribute
x = spsolve(A, b)
assembler.distribute_variable(x)
def test_partition_unity_tpfa_single_local_micro_fracture(self):
g = create_grids.cart_2d()
pts = np.array([[0.8, 1.2], [1.3, 1.6]])
edges = np.array([[0], [1]])
internal_faces = [4]
self._check_partition_unity(g, internal_faces, Tpfa_DFM(), pts, edges)
def test_partition_unit_tpfa_no_micro_fractures(self):
g = create_grids.cart_2d()
internal_faces = [1, 4, 7, 11, 12, 13, 14]
self._check_partition_unity(g, internal_faces, Tpfa_DFM())