from pumapy.physicsmodels.isotropic_conductivity import IsotropicConductivity
from pumapy.physicsmodels.mpfa_conductivity import AnisotropicConductivity
from pumapy.utilities.property_maps import IsotropicConductivityMap, AnisotropicConductivityMap
[docs]def compute_thermal_conductivity(workspace, cond_map, direction, side_bc='s', prescribed_bc=None, tolerance=1e-4,
maxiter=10000, solver_type='bicgstab', display_iter=True, print_matrices=(0, 0, 0, 0, 0)):
""" Compute the thermal conductivity
:param workspace: domain
:type workspace: Workspace
:param cond_map: local constituents themal conductivities
:type cond_map: IsotropicConductivityMap or AnisotropicConductivityMap
:param direction: direction for solve ('x','y', or 'z')
:type direction: string
:param side_bc: side boundary conditions can be symmetric ('s'), periodic ('p') or dirichlet ('d')
:type side_bc: string, optional
:param prescribed_bc: 3D array holding dirichlet BC.
:type prescribed_bc: ConductivityBC, optional
:param tolerance: tolerance for iterative solver
:type tolerance: float, optional
:param maxiter: maximum Iterations for solver
:type maxiter: int, optional
:param solver_type: solver type, options: 'bicgstab', 'cg', 'gmres', 'direct'
:type solver_type: string, optional
:param display_iter: display iterations and residual
:type display_iter: bool, optional
:param print_matrices: corresponding to b, E, A, T, q decimal places. If 0, they are not printed
:type print_matrices: tuple(5 bools), optional
:return: thermal conductivity, temperature field, flux
:rtype: tuple(tuple(float, float, float), ndarray, ndarray)
:Example:
>>> import pumapy as puma
>>> ws_fiberform = puma.import_3Dtiff(puma.path_to_example_file("200_fiberform.tif"), 1.3e-6)
>>> ws_fiberform.matrix = ws_fiberform.matrix[50:150, 50:150, 50:150]
>>> cond_map = puma.IsotropicConductivityMap()
>>> cond_map.add_material((0, 89), 0.0257)
>>> cond_map.add_material((90, 255), 12)
>>> k_eff_x, T_x, q_x = puma.compute_thermal_conductivity(ws_fiberform, cond_map, 'x', 's', tolerance=1e-2, solver_type='cg')
>>> print("Effective thermal conductivity tensor:")
>>> print(k_eff_x)
"""
if isinstance(cond_map, IsotropicConductivityMap):
solver = IsotropicConductivity(workspace, cond_map, direction, side_bc, prescribed_bc, tolerance, maxiter,
solver_type, display_iter)
elif isinstance(cond_map, AnisotropicConductivityMap):
solver = AnisotropicConductivity(workspace, cond_map, direction, side_bc, prescribed_bc, tolerance, maxiter,
solver_type, display_iter, print_matrices)
else:
raise Exception("cond_map has to be an IsotropicConductivityMap or AnisotropicConductivityMap")
solver.error_check()
solver.log_input()
solver.compute()
solver.log_output()
return solver.keff, solver.T, solver.q
[docs]def compute_electrical_conductivity(workspace, cond_map, direction, side_bc='p', prescribed_bc=None, tolerance=1e-4,
maxiter=10000, solver_type='bicgstab', display_iter=True, print_matrices=(0, 0, 0, 0, 0)):
""" Compute the electrical conductivity
:param workspace: domain
:type workspace: Workspace
:param cond_map: local constituents electrical conductivities
:type cond_map: IsotropicConductivityMap or AnisotropicConductivityMap
:param direction: direction for solve ('x','y', or 'z')
:type direction: string
:param side_bc: side boundary conditions can be symmetric ('s'), periodic ('p') or dirichlet ('d')
:type side_bc: string, optional
:param prescribed_bc: 3D array holding dirichlet BC
:type prescribed_bc: ConductivityBC, optional
:param tolerance: tolerance for iterative solver
:type tolerance: float, optional
:param maxiter: maximum Iterations for solver
:type maxiter: int, optional
:param solver_type: solver type, options: 'bicgstab', 'cg', 'gmres', 'direct'
:type solver_type: string, optional
:param display_iter: display iterations and residual
:type display_iter: bool, optional
:param print_matrices: corresponding to E, A, b, T, q decimal places. If 0, they are not printed
:type print_matrices: tuple(5 bools), optional
:return: electrical conductivity, potential field, flux
:rtype: tuple(tuple(float, float, float), ndarray, ndarray)
:Example:
>>> import pumapy as puma
>>> ws_fiberform = puma.import_3Dtiff(puma.path_to_example_file("200_fiberform.tif"), 1.3e-6)
>>> ws_fiberform.matrix = ws_fiberform.matrix[50:150, 50:150, 50:150]
>>> cond_map = puma.IsotropicConductivityMap()
>>> cond_map.add_material((0, 89), 0.0257)
>>> cond_map.add_material((90, 255), 12)
>>> k_eff_x, P_x, q_x = puma.compute_electrical_conductivity(ws_fiberform, cond_map, 'x', 's', tolerance=1e-2, solver_type='cg')
>>> print("Effective electrical conductivity tensor:")
>>> print(k_eff_x)
"""
return compute_thermal_conductivity(workspace, cond_map, direction, side_bc, prescribed_bc, tolerance, maxiter,
solver_type, display_iter, print_matrices)