pumapy.material_properties

pumapy.material_properties.anisotropic_radiation

class pumapy.material_properties.anisotropic_radiation.AnisotropicRadiation(workspace, void_cutoff, sources_number, direction, bin_density, export_plot)[source]

Bases: object

compute()[source]
error_check()[source]
log_input()[source]
log_output()[source]
pumapy.material_properties.anisotropic_radiation.compute_extinction_coefficients_anisotropic(ws, rays_distances, sources_number, bin_density=10000, export_pathname=None)[source]

Compute the extinction coefficient based on the ray casting radiation simulation (this is normally a step inside the compute_radiation function)

Parameters

  • ws (pumapy.Workspace) – domain

  • rays_distances (np.ndarray) – rays distances, as output by compute_radiation function

  • sources_number (int) – number of light sources spread randomly in the void space (i.e. 0)

  • bin_density (int) – number of bins used to create histogram of ray distances

  • export_pathname (str) – path to save curve plot of ray distance distribution

Returns

extinction coefficient (beta), its standard deviation

Return type

(float, float)

pumapy.material_properties.anisotropic_radiation.compute_radiation_anisotropic(workspace, void_cutoff, sources_number, bin_density=10000, export_pathname=None)[source]

Compute the anisotropic radiative thermal conductivity through ray tracing

Parameters

  • workspace (pumapy.Workspace) – domain

  • void_cutoff ((int, int)) – specify the void phase

  • sources_number (int) – number of light sources spread randomly in the void space (i.e. 0)

  • bin_density (int) – number of bins used to create histogram of ray distances

  • export_pathname (str) – path to save curve plot of ray distance distribution

Returns

extinction coefficient (beta), its standard deviation and of ray distances

Return type

(float, float, np.ndarray)

pumapy.material_properties.conductivity

Further explained in publication: Semeraro, F., Ferguson, J.C., Acin, M., Panerai, F. and Mansour, N.N., 2021. Anisotropic analysis of fibrous and woven materials part 2: Computation of effective conductivity. Computational Materials Science, 186, p.109956. https://www.sciencedirect.com/science/article/abs/pii/S092702562030447X

pumapy.material_properties.conductivity.compute_electrical_conductivity(workspace, cond_map, direction, side_bc='p', prescribed_bc=None, tolerance=1e-05, maxiter=10000, solver_type='bicgstab', display_iter=True, method='fv', matrix_free=True)[source]

Compute the electrical conductivity

Parameters

  • workspace (pumapy.Workspace) – domain

  • cond_map (IsotropicConductivityMap or AnisotropicConductivityMap) – local constituents electrical conductivities

  • direction (string) – direction for solve (‘x’,’y’,’z’, or ‘’ for prescribed_bc). If provided, prescribed_bc is ignored

  • side_bc (string) – side boundary conditions can be symmetric (‘s’) or periodic (‘p’). Only periodic available when method=’fe’

  • prescribed_bc (pumapy.IsotropicConductivityBC or pumapy.AnisotropicConductivityBC or None) – object holding dirichlet BC, only available for isotropic of MPFA implementations. Need to set direction=’’ in order to provide it. When prescribed_bc is provided, keff is not printed but it is computed as if direction==’x’ for testing purposes.

  • tolerance (float) – tolerance for iterative solver

  • maxiter (int) – maximum Iterations for solver

  • solver_type (string) – solver type, options: ‘bicgstab’ (default), ‘cg’, ‘gmres’, ‘minres’ (only for method=’fe’), ‘direct’

  • display_iter (bool) – display iterations and residual

  • method (string) – whether to use finite volume solver (‘fv’, either isotropic solver if IsotropicConductivityMap is passed, or mpfa if AnisotropicConductivityMap) or finite element Q1-Q1 EBE solver (‘fe’). For the latter method, it is recommended to use solver_type=’minres’ as lighter and faster

  • matrix_free (bool) – if True, then use matrix-free method if possible (only available for fv isotropic solver or for fe solver when the solver type is not ‘direct’)

Returns

electrical conductivity, potential field, flux

Return type

((float, float, float), numpy.ndarray, numpy.ndarray)

pumapy.material_properties.conductivity.compute_thermal_conductivity(workspace, cond_map, direction, side_bc='p', prescribed_bc=None, tolerance=1e-05, maxiter=10000, solver_type='bicgstab', display_iter=True, method='fv', matrix_free=True)[source]

Compute the thermal conductivity

Parameters

  • workspace (pumapy.Workspace) – domain

  • cond_map (IsotropicConductivityMap or AnisotropicConductivityMap) – local constituents themal conductivities

  • direction (string) – direction for solve (‘x’,’y’,’z’, or ‘’ for prescribed_bc). If provided, prescribed_bc is ignored

  • side_bc (string) – side boundary conditions can be symmetric (‘s’) or periodic (‘p’). Only periodic available when method=’fe’

  • prescribed_bc (pumapy.IsotropicConductivityBC or pumapy.AnisotropicConductivityBC or None) – object holding dirichlet BC, only available for isotropic of MPFA implementations. Need to set direction=’’ in order to provide it. When prescribed_bc is provided, keff is not printed but it is computed as if direction==’x’ for testing purposes.

  • tolerance (float) – tolerance for iterative solver

  • maxiter (int) – maximum Iterations for solver

  • solver_type (string) – solver type, options: ‘bicgstab’ (default), ‘cg’, ‘gmres’, ‘minres’ (only for method=’fe’), ‘direct’

  • display_iter (bool) – display iterations and residual

  • method (string) – whether to use finite volume solver (‘fv’, either isotropic solver if IsotropicConductivityMap is passed, or mpfa if AnisotropicConductivityMap) or finite element Q1-Q1 EBE solver (‘fe’). For the latter method, it is recommended to use solver_type=’minres’ as lighter and faster

  • matrix_free (bool) – if True, then use matrix-free method if possible (only available for fv isotropic solver or for fe solver when the solver type is not ‘direct’)

Returns

thermal conductivity, temperature field, flux

Return type

((float, float, float), numpy.ndarray, numpy.ndarray)

Example

>>> import pumapy as puma
>>> ws_fiberform = puma.import_3Dtiff(puma.path_to_example_file("200_fiberform.tif"), 1.3e-6)
Importing .../200_fiberform.tif ... Done
>>> ws_fiberform.rescale(0.5, segmented=False)
Rescaled workspace size: (100, 100, 100)
>>> # Conductivity with Isotropic local phases
>>> 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', matrix_free=True)
Approximate memory requirement for simulation...
>>> # Conductivity with Anisotropic local phases
>>> puma.compute_orientation_st(ws_fiberform, cutoff=(90, 255))
First gradient computation...
>>> cond_map = puma.AnisotropicConductivityMap()
>>> # conductivity of the void phase to be 0.0257 (air at STP)
>>> cond_map.add_isotropic_material((0, 89), 0.0257)
>>> # axial fiber conductivity of 12, radial fiber conductivity of 0.7
>>> cond_map.add_material_to_orient((90, 255), 12., 0.7)
>>> k_eff_z, T_z, q_z = puma.compute_thermal_conductivity(ws_fiberform, cond_map, 'z', 's')  # method='fe' for finite element
Approximate memory requirement for simulation...
>>> # plot_conductivity_fields(ws, T_z, q_z)  # to visualize fields
>>> # export_conductivity_fields_vti("path/to/folder", ws, T_z, q_z)  # to export fields
pumapy.material_properties.conductivity.export_conductivity_fields_vti(filepath, workspace, T, q)[source]

Export conductivity fields, as output by the conductivity function

Parameters

  • filepath (string) –

  • workspace (puma.Workspace or numpy.ndarray) – domain

  • T (numpy.ndarray) – temperature field

  • q (numpy.ndarray) – flux field

pumapy.material_properties.conductivity.plot_conductivity_fields(workspace, T, q, show_cbar=True, show_edges=False, xy_view=False, rm_id=None, notebook=False)[source]

Plot the workspace colored by the temperature and flux fields, as output by the conductivity function

Parameters

  • workspace (pumapy.Workspace) – domain

  • T (numpy.ndarray) – temperature field

  • q (numpy.ndarray) – flux field

  • show_cbar (bool) – show colorbar in each plot

  • show_edges (bool) – show edges in mesh

  • xy_view (bool) – show plot aligned with xy plane

  • rm_id (float or None) – remove a phase of the material from thresholded mesh

  • notebook (bool) – plotting interactively in a jupyter notebook (overwrites show_grid to False)

pumapy.material_properties.elasticity

pumapy.material_properties.elasticity.compute_elasticity(workspace, elast_map, direction, side_bc='p', tolerance=1e-05, maxiter=100000, solver_type='bicgstab', display_iter=True, method='fv', matrix_free=True)[source]

Compute the effective elasticity coefficient

Parameters

  • workspace (pumapy.Workspace) – domain

  • elast_map (pumapy.ElasticityMap) – local elasticity of the constituents

  • direction (string) – direction for solve (‘x’,’y’, ‘z’, ‘yz’, ‘xz’, ‘xy’)

  • side_bc (string) – side boundary conditions can be symmetric (‘s’) or periodic (‘p’). Only periodic available when method=’fe’

  • tolerance – tolerance for iterative solver

  • maxiter (int) – maximum Iterations for solver

  • solver_type (string) – solver type, options: ‘bicgstab’ (default), ‘minres’ (only for method=’fe’), ‘gmres’, ‘direct’

  • display_iter (bool) – display iterations and residual

  • method (string) – whether to use finite volume solver (‘fv’, i.e. mpsa) or finite element Q1-Q1 EBE solver (‘fe’). For the latter method, it is recommended to use solver_type=’minres’ as lighter and faster

  • matrix_free (bool) – if True, then use matrix-free method if possible (only available for fe solver when the solver type is not ‘direct’)

Type

tolerance: float

Returns

elasticity, displacement field, direct stresses (sigma xx, yy, zz), shear stresses (tau yz, xz, xy)

Return type

((float, float, float, float, float, float), numpy.ndarray, numpy.ndarray, numpy.ndarray)

Example

>>> import pumapy as puma
>>> ws = puma.Workspace.from_shape_value((20, 20, 20), 1)
>>> ws[int(ws.matrix.shape[0] / 2):] = 2
>>> elast_map = puma.experimental.ElasticityMap()
>>> elast_map.add_isotropic_material((1, 1), 200, 0.3)
>>> elast_map.add_isotropic_material((2, 2), 400, 0.1)
>>> C = np.zeros((6, 6))
>>> C[:, 0], u, s, t = puma.experimental.compute_elasticity(ws, elast_map, direction='x', solver_type='direct')
Approximate memory requirement for simulation: ...
>>> C[:, 1], u, s, t = puma.experimental.compute_elasticity(ws, elast_map, direction='y', solver_type='direct')
Approximate memory requirement for simulation: ...
>>> C[:, 2], u, s, t = puma.experimental.compute_elasticity(ws, elast_map, direction='z', solver_type='direct')
Approximate memory requirement for simulation: ...
>>> C[:, 3], u, s, t = puma.experimental.compute_elasticity(ws, elast_map, direction='yz', solver_type='direct')
Approximate memory requirement for simulation: ...
>>> C[:, 4], u, s, t = puma.experimental.compute_elasticity(ws, elast_map, direction='xz', solver_type='direct')
Approximate memory requirement for simulation: ...
>>> C[:, 5], u, s, t = puma.experimental.compute_elasticity(ws, elast_map, direction='xy', solver_type='direct')
Approximate memory requirement for simulation: ...
>>> coeffs = puma.experimental.get_E_nu_from_elasticity(C)
E1 ...
>>> #puma.plot_elasticity_fields(ws, u, s, t)  # to visualize fields
>>> #puma.warp_elasticity_fields(ws, u, s, t, 5)  # to visualize fields
>>> #puma.export_elasticity_fields_vti("path/to/folder", ws, u, s, t)  # to export fields
>>> C1, u, s, t = puma.experimental.compute_elasticity(ws, elast_map, direction='x', solver_type='direct', method='fe')  # finite element solver
Approximate memory requirement for simulation: ...
pumapy.material_properties.elasticity.compute_stress_analysis(workspace, elast_map, prescribed_bc, side_bc='p', tolerance=1e-05, maxiter=100000, solver_type='bicgstab', display_iter=True)[source]

Compute stress analysis based on specific user-input dirichlet boundary conditions

Parameters

  • workspace (pumapy.Workspace) – domain

  • elast_map (pumapy.ElasticityMap) – local elasticity of the constituents

  • prescribed_bc (pumapy.ElasticityBC) – object holding the elasticity dirichlet boundary conditions

  • side_bc (string) – side boundary conditions can be symmetric (‘s’) or periodic (‘p’)

  • tolerance – tolerance for iterative solver

  • maxiter (int) – maximum Iterations for solver

  • solver_type (string) – solver type, options: ‘gmres’ (default), ‘bicgstab’, ‘direct’

  • display_iter (bool) – display iterations and residual

Type

tolerance: float

Returns

elasticity, displacement field, direct stresses (sigma xx, yy, zz), shear stresses (tau yz, xz, xy)

Return type

(numpy.ndarray, numpy.ndarray, numpy.ndarray)

Example

>>> import pumapy as puma
>>> ws = puma.Workspace.from_shape_value((20, 22, 22), 1)
>>> ws[ws.matrix.shape[0]//2:] = 2
>>> ws[:, [0, -1]] = 0
>>> ws[:, :, [0, -1]] = 0
>>> elast_map = puma.experimental.ElasticityMap()
>>> elast_map.add_isotropic_material((0, 0), 1e-5, 0.3)
>>> elast_map.add_isotropic_material((1, 1), 200, 0.3)
>>> elast_map.add_isotropic_material((2, 2), 400, 0.1)
>>> bc = puma.experimental.ElasticityBC(ws)
>>> bc.xfaces[0, :, :, 0] = 0
>>> bc.xfaces[0, :, :, 1] = 0
>>> bc.xfaces[0, :, :, 2] = 0
>>> bc.xfaces[1, :, :, 0] = 0
>>> bc.xfaces[1, :, :, 1] = 1
>>> bc.xfaces[1, :, :, 2] = 0
>>> u, s, t = puma.experimental.compute_stress_analysis(ws, elast_map, bc)
Approximate memory requirement for simulation: ...
>>> # puma.warp_elasticity_fields(ws[:, 1:-1, 1:-1], u[:, 1:-1, 1:-1], s[:, 1:-1, 1:-1], t[:, 1:-1, 1:-1], 20, show_original=0., show_edges=True)  # to visualize
pumapy.material_properties.elasticity.export_elasticity_fields_vti(filepath, workspace, u, s, t)[source]

Export conductivity fields, as output by the conductivity function

Parameters

  • filepath (string) –

  • workspace (puma.Workspace or numpy.ndarray) – domain

  • u (numpy.ndarray) – displacement field

  • s (numpy.ndarray) – direct stress field

  • t (numpy.ndarray) – shear stress field

pumapy.material_properties.elasticity.get_E_nu_from_elasticity(C)[source]

Compute Young’s moduli E1, E2, E3, Shear moduli G23, G13, G12, and Poisson’s ratios nu23, nu13, nu12 for an orthotropic material from its symmetric elastic stiffness tensor

Parameters

C (np.ndarray) – 6x6 elasticity tensor

Returns

Young’s moduli E1, E2, E3, Shear moduli G23, G13, G12, and Poisson’s ratios nu23, nu13, nu12

Return type

(float, float, float, float, float, float, float, float, float)

pumapy.material_properties.elasticity.plot_elasticity_fields(workspace, u, s, t, show_cbar=True, show_edges=False, xy_view=False, rm_id=None, notebook=False)[source]

Plot the workspace according to the displacement and stress fields output by the elasticity functions

Parameters

  • workspace (pumapy.Workspace) – domain

  • u (numpy.ndarray) – displacement field

  • s (numpy.ndarray) – direct stress field

  • t (numpy.ndarray) – shear stress field

  • show_cbar (bool) – show colorbar in each plot

  • show_edges (bool) – show edges in mesh

  • xy_view (bool) – show plot aligned with xy plane

  • rm_id (float or None) – remove a phase of the material from thresholded mesh

  • notebook (bool) – plotting interactively in a jupyter notebook (overwrites show_grid to False)

pumapy.material_properties.elasticity.remove_rbms(workspace, void_id, direction)[source]

Remove Rigid Body Movements (RBMs), i.e. unconnected or “floating” voxels, in a segmented domain along a specified direction

Parameters

  • workspace (pumapy.Workspace) – domain

  • void_id (int) – specify the void ID to discard from RBMs identification

  • direction (str) – Cartesian direction that has to be connected, options: ‘x’, ‘y’, ‘z’

Returns

workspace without the possible RBMs determined by not being connected from side to side N.B. The output workspace is segmented into 0=void, 1=solid

Return type

pumapy.Workspace

Example

>>> import pumapy as puma
>>> workspace = puma.import_3Dtiff(puma.path_to_example_file("100_fiberform.tif"))
Importing ...
>>> workspace.binarize(103)
>>> new_ws = puma.experimental.remove_rbms(workspace, void_id=0, direction='y')
>>> # puma.render_volume(workspace, (1, 1), solid_color=(255, 255, 255))  # to visualize before and after
>>> # puma.render_volume(new_ws, (1, new_ws.max()), solid_color=(255, 255, 255))
pumapy.material_properties.elasticity.warp_elasticity_fields(workspace, u, s, t, scale_factor=1, show_original=0.0, show_cbar=True, show_edges=False, xy_view=False, rm_id=None, show_axes=True, notebook=False)[source]

Warp the workspace according to the displacement field output by the elasticity functions, and colored by displacement and stress components

Parameters

  • workspace (pumapy.Workspace) – domain

  • u (numpy.ndarray) – displacement field

  • s (numpy.ndarray) – direct stress field

  • t (numpy.ndarray) – shear stress field

  • scale_factor (float) – scaling factor for warp

  • show_original (float) – opacity of the original workspace before warp

  • show_cbar (bool) – show colorbar in each plot

  • show_edges (bool) – show edges in mesh

  • xy_view (bool) – show plot aligned with xy plane

  • rm_id (float or None) – remove a phase of the material from warped mesh (only works for 2D slice)

  • show_axes (float) – show the axes and side dimensions

  • notebook (bool) – plotting interactively in a jupyter notebook (overwrites show_grid to False)

pumapy.material_properties.mean_intercept_length

pumapy.material_properties.mean_intercept_length.compute_mean_intercept_length(workspace, void_cutoff)[source]

Computation of the mean intercept length

Parameters

  • workspace (pumapy.Workspace) – domain

  • void_cutoff ((int, int)) – specify the void or gaseous phase of the domain

Returns

mean intercept length in x,y,z

Return type

(float, float, float)

Example

>>> import pumapy as puma
>>> ws = puma.import_3Dtiff(puma.path_to_example_file("200_fiberform.tif"), 1.3e-6)
Importing ...
>>> mil = puma.compute_mean_intercept_length(ws, (0, 89))

pumapy.material_properties.orientation

Further explained in publication: Semeraro, F., Ferguson, J.C., Panerai, F., King, R.J. and Mansour, N.N., 2020. Anisotropic analysis of fibrous and woven materials part 1: Estimation of local orientation. Computational Materials Science, 178, p.109631. (https://www.sciencedirect.com/science/article/abs/pii/S0927025620301221)

class pumapy.material_properties.orientation.OrientationST(ws, sigma, rho, cutoff, edt)[source]

Bases: object

compute()[source]
error_check()[source]
log_input()[source]
log_output()[source]
pumapy.material_properties.orientation.compute_angular_differences(matrix, orientation1, orientation2, cutoff)[source]

Compute angular difference between two orientation ndarrays

Parameters

  • matrix (np.ndarray) – domain matrix

  • orientation1 (np.ndarray) – orientation as (x, y, z, 3)

  • orientation2 (np.ndarray) – orientation as (x, y, z, 3)

  • cutoff ((int, int)) – to binarize domain

Returns

angle_errors in degrees, mean, std

Return type

(np.ndarray, float, float)

pumapy.material_properties.orientation.compute_orientation_st(ws, cutoff, sigma=0.7, rho=1.4, edt=False)[source]

Compute orientation of the material by the structure tensor algorithm

Parameters

  • ws (pumapy.Workspace) – domain

  • cutoff ((int, int)) – which grayscales to consider

  • sigma (float) – kernel size parameter for Gaussian derivatives (should be lower than rho)

  • rho (float) – kernel size parameter for Gaussian filter of derivatives of grayscales (should be higher than sigma)

  • edt (bool) – indicating if we need to apply Euclidean Distance Transform before computing ST

Returns

True if successful, False otherwise.

Return type

bool

Example

>>> import pumapy as puma
>>> import pyvista as pv
>>> ws = puma.import_3Dtiff(puma.path_to_example_file("100_fiberform.tif"), 1.3e-6)  # import example file
Importing ...
>>> puma.compute_orientation_st(ws, cutoff=(90, 255), sigma=0.7, rho=1.4)  # compute orientation
First gradient computation ...
>>> # p = pv.Plotter(shape=(1, 2))  # to visualize the orientation field
>>> # p.subplot(0, 0)
>>> # p.add_text("Microstructure")
>>> # puma.render_contour(ws, (90, 255), add_to_plot=p, plot_directly=False)
>>> # p.subplot(0, 1)
>>> # p.add_text("Detected fiber orientation")
>>> # puma.render_orientation(ws, add_to_plot=p, plot_directly=False)
>>> # p.show()  # to visualize it

pumapy.material_properties.permeability

The following FE numerical method and implementation are based on the following research paper:

Lopes, P.C., Vianna, R.S., Sapucaia, V.W., Semeraro, F., Leiderman, R. and Pereira, A.M., 2023. Simulation toolkit for digital material characterization of large image-based microstructures. Computational Materials Science, 219, p.112021. (https://www.sciencedirect.com/science/article/pii/S0927025623000150)

pumapy.material_properties.permeability.compute_permeability(workspace, solid_cutoff, direction='xyz', tol=1e-08, maxiter=10000, solver_type='minres', display_iter=True, matrix_free=True, precondition=False, output_fields=True)[source]

Compute the permeability using first-order Q1-Q1 Finite Element solver and periodic BC on the sides.

Note: the iterative solvers have been observed to struggle converging for some cases. This is often connected to having the preconditioner option as True.

Parameters

  • workspace (pumapy.Workspace) – domain

  • solid_cutoff ((int, int)) – specify the solid phase

  • direction (str) – direction for solve (‘xyz’,’x’,’y’,’z’). Note that if solver_type=”direct”, then the direction is considered as “xyz” automatically because there is no need to invert the A sparse matrix multiple times

  • tol (float) – tolerance for iterative solver

  • maxiter (int) – maximum Iterations for solver

  • solver_type (string) – solver type, options: ‘minres’ (default, only works if precondition=False), ‘cg’, ‘direct’

  • display_iter (bool) – display iteration in iterative solver

  • matrix_free (bool) – solve system using matrix-free method (True, recommended) or building the sparse A matrix (False)

  • precondition (bool) – solve system with Jacobi preconditioner (True) or without (False, default because it reduces memory, but more iterations. The default minres iterative solver does not support this kind of preconditioner)

  • output_fields (bool) – export velocity and pressure fields (True, default) or not (False, lower memory)

Returns

effective permeability (3x3 matrix) and, if output_fields=True, the normalized velocity field for the corresponding direction (arranged as tuple of numpy.ndarrays, i.e. (ux, uy, uz). If output_fields=False, then (None, None, None) is output

Return type

numpy.ndarray, (numpy.ndarray, numpy.ndarray, numpy.ndarray)

Example

>>> import pumapy as puma
>>> import pyvista as pv
>>> ws = puma.generate_random_fibers_transverseisotropic(shape=(50, 50, 50), radius=2, porosity=0.7, direction='x', variation=15, length=200, allow_intersect=True, segmented=True)
 Fibers created...
>>> keff, (ux, _, _) = puma.compute_permeability(ws, (1, ws.max()), direction='x', tol=1e-7)
Approximate memory requirement for simulation: ...
>>> # p = pv.Plotter()  # to visualize it
>>> # puma.render_orientation(ux, add_to_plot=p, scale_factor=2e12, plot_directly=False)
>>> # ws.voxel_length = 1  # the voxel_length is converted to 1 for plotting the workspace together with the velocity
>>> # puma.render_volume(ws, cutoff=(1, ws.max()), add_to_plot=p, plot_directly=False, cmap='jet')
>>> # p.show()

pumapy.material_properties.radiation

class pumapy.material_properties.radiation.Radiation(workspace, void_cutoff, sources_number, particles_number, boundary_behavior, bin_density, export_plot)[source]

Bases: object

compute()[source]
error_check()[source]
generate_sources()[source]
log_input()[source]
log_output()[source]
pumapy.material_properties.radiation.compute_extinction_coefficients(ws, rays_distances, sources_number, particles_number, bin_density=10000, export_pathname=None)[source]

Compute the extinction coefficient based on the ray casting radiation simulation (this is normally a step inside the compute_radiation function)

Parameters

  • ws (pumapy.Workspace) – domain

  • rays_distances (np.ndarray) – rays distances, as output by compute_radiation function

  • sources_number (int) – number of light sources spread randomly in the void space (i.e. 0)

  • degree_accuracy (int) – angle difference between rays emitted in degrees (has to be an exact divider of 180°)

  • bin_density (int) – number of bins used to create histogram of ray distances

  • export_pathname (str) – path to save curve plot of ray distance distribution

Returns

extinction coefficient (beta), its standard deviation

Return type

(float, float)

pumapy.material_properties.radiation.compute_radiation(workspace, void_cutoff, sources_number, particles_number, boundary_behavior=1, bin_density=10000, export_pathname=None)[source]

Compute the radiative thermal conductivity through ray tracing (N.B. 0 material ID in workspace refers to gas phases unless otherwise specified)

Parameters

  • workspace (pumapy.Workspace) – domain

  • void_cutoff ((int, int)) – specify the void phase

  • sources_number (int) – number of light sources spread randomly in the void space (i.e. 0)

  • particles_number (int) – number of particles emitted at each source point

  • boundary_behavior (int) – how to treat particles exiting the domain: 0=kill, 1=periodic (default)

  • bin_density (int) – number of bins used to create histogram of ray distances

  • export_pathname (str) – path to save curve plot of ray distance distribution

Returns

extinction coefficient (beta), its standard deviation and of ray distances

Return type

(float, float, np.ndarray)

Example

>>> import pumapy as puma
>>> ws_fiberform = puma.import_3Dtiff(puma.path_to_example_file("200_fiberform.tif"), 0.65e-6)
Importing ...
>>> beta, beta_std, rays_distances = puma.experimental.compute_radiation(ws_fiberform, (0, 89), 100, 500)
 Number of particles in Ray Tracing simulation...

pumapy.material_properties.surface_area

class pumapy.material_properties.surface_area.SurfaceArea(workspace, cutoff, flag_gaussian)[source]

Bases: object

compute()[source]
log_input()[source]
log_output()[source]
pumapy.material_properties.surface_area.compute_surface_area(workspace, cutoff, flag_gaussian=False)[source]

Computation of the surface area based on isosurface

Parameters

  • workspace (pumapy.Workspace) – domain

  • cutoff ((int, int)) – specify the solid phase

  • flag_gaussian (bool) – apply Gaussian filter before generating surface

Returns

area, specific_area

Return type

(float, float)

Example

>>> import pumapy as puma
>>> ws = puma.import_3Dtiff(puma.path_to_example_file("200_fiberform.tif"), 1.3e-6) # import workspace
Importing ...
>>> area, specific_area = puma.compute_surface_area(ws, cutoff=(90, 255)) # computing surface area

pumapy.material_properties.tortuosity

pumapy.material_properties.tortuosity.compute_continuum_tortuosity(workspace, cutoff, direction, side_bc='p', prescribed_bc=None, tolerance=0.0001, maxiter=10000, solver_type='cg', display_iter=True, matrix_free=True)[source]

Compute the tortuosity modelling the local conductivity as isotropic

Parameters

  • workspace (pumapy.Workspace) – domain

  • cutoff ((int, int)) – cutoff to binarize domain specifying the void phase

  • direction (string) – direction for solve (‘x’,’y’, or ‘z’)

  • side_bc (string) – side boundary conditions (string) can be symmetric (‘s’), periodic (‘p’) or dirichlet (‘d’)

  • prescribed_bc (pumapy.IsotropicConductivityBC or None) – 3D array holding dirichlet BC

  • tolerance (float) – tolerance for iterative solver

  • maxiter (int) – maximum Iterations for solver

  • solver_type (string) – solver type, options: ‘cg’ (default), ‘bicgstab’, ‘direct’

  • display_iter (bool) – display iterations and residual

  • matrix_free (bool) – if True, then use matrix-free method

Returns

tortuosity, diffusivity, porosity, concentration field

Return type

((float, float, float), float, float, numpy.ndarray)

Example

>>> import pumapy as puma
>>> ws_fiberform = puma.import_3Dtiff(puma.path_to_example_file("200_fiberform.tif"), 1.3e-6)
Importing ...
>>> n_eff_x, Deff_x, poro, C_x = puma.compute_continuum_tortuosity(ws_fiberform, (0, 89), 'x', side_bc='s', tolerance=1e-4)
Approximate memory requirement for simulation...
pumapy.material_properties.tortuosity.divide_zero(x, y)[source]

pumapy.material_properties.volume_fraction

class pumapy.material_properties.volume_fraction.VolumeFraction(workspace, cutoff, display)[source]

Bases: object

compute()[source]
error_check()[source]
log_input()[source]
log_output()[source]
pumapy.material_properties.volume_fraction.compute_volume_fraction(workspace, cutoff, display=True)[source]

Compute the volume fraction

Parameters

  • workspace (pumapy.Workspace or np.ndarray) – domain

  • cutoff ((int, int)) – to binarize domain

  • display (bool) – print result

Returns

volume fraction

Return type

float

Example

>>> import pumapy as puma
>>> ws = puma.import_3Dtiff(puma.path_to_example_file("100_fiberform.tif"), 1.3e-6) # import example file
Importing ...
>>> vf = puma.compute_volume_fraction(ws, cutoff=(90, 255)) # compute volume fraction
Volume Fraction for cutoff ...