import numpy as np import openpnm as op from numpy.testing import assert_allclose class DiffusiveConductanceTest: def setup_class(self): self.net = op.network.Cubic(shape=[5, 5, 5]) self.net['pore.diameter'] = 1.0 self.net['throat.diameter'] = 0.5 self.net['pore.area'] = 1.0 self.net['throat.cross_sectional_area'] = 1.0 self.phase = op.phase.Phase(network=self.net) self.phase['pore.diffusivity'] = 1.3 self.phase['pore.molecular_weight'] = 0.029 self.phase['pore.temperature'] = 345.0 self.size_factors = np.ones([self.net.Nt, 3])*(0.123, 0.981, 0.551) def test_generic_diffusive_size_factors_as_dict(self): self.net['throat.diffusive_size_factors'] = self.size_factors mod = op.models.physics.diffusive_conductance.generic_diffusive self.phase.add_model(propname='throat.diffusive_conductance', model=mod) self.phase.regenerate_models() actual = self.phase['throat.diffusive_conductance'].mean() assert_allclose(actual, desired=0.091204832 * 1.3) del self.net["throat.diffusive_size_factors"] def test_generic_diffusive_size_factors_as_array(self): self.net['throat.diffusive_size_factors'] = 0.896 mod = op.models.physics.diffusive_conductance.generic_diffusive self.phase.add_model(propname='throat.diffusive_conductance', model=mod) self.phase.regenerate_models() actual = self.phase['throat.diffusive_conductance'].mean() assert_allclose(actual, desired=0.896 * 1.3) del self.net["throat.diffusive_size_factors"] def test_generic_diffusive_partial_domain(self): net = op.network.Cubic(shape=[5, 5, 5]) phase = op.phase.Phase(network=net) phase.set_label('pore.left', pores=net['pore.left']) phase.set_label(label='left', throats=net.find_neighbor_throats(net.pores('left'))) phase['pore.diffusivity'] = 1.3 net['throat.diffusive_size_factors'] = 0.5 mod = op.models.physics.diffusive_conductance.generic_diffusive phase.add_model(propname='throat.diffusive_conductance', model=mod, domain='left', regen_mode='deferred') phase.regenerate_models() actual = phase['throat.diffusive_conductance'].mean() # assert_allclose(actual, 0.65) # assert len(phase['throat.diffusive_conductance']) == 5 def test_ordinary_diffusion_size_factors_given_as_dict(self): self.net['throat.diffusive_size_factors'] = self.size_factors mod = op.models.physics.diffusive_conductance.ordinary_diffusion self.phase.add_model(propname='throat.diffusive_conductance', model=mod) self.phase.regenerate_models() actual = self.phase['throat.diffusive_conductance'].mean() assert_allclose(actual, desired=0.091204832 * 1.3) del self.net["throat.diffusive_size_factors"] def test_ordinary_diffusion_size_factors_given_as_array(self): self.net['throat.diffusive_size_factors'] = 0.896 mod = op.models.physics.diffusive_conductance.ordinary_diffusion self.phase.add_model(propname='throat.diffusive_conductance', model=mod) self.phase.regenerate_models() actual = self.phase['throat.diffusive_conductance'].mean() assert_allclose(actual, desired=0.896 * 1.3) del self.net["throat.diffusive_size_factors"] def test_mixed_diffusion(self): self.net['throat.diffusive_size_factors'] = self.size_factors mod = op.models.physics.diffusive_conductance.mixed_diffusion self.phase.add_model(propname='throat.diffusive_conductance', model=mod) self.phase.regenerate_models() actual = self.phase['throat.diffusive_conductance'].mean() assert_allclose(actual, desired=0.117568, rtol=1e-5) del self.net["throat.diffusive_size_factors"] # def test_multiphase_diffusion(self): # net = op.network.Cubic(shape=[1, 6, 1]) # net['throat.diffusive_size_factors'] = self.size_factors_dict # air = op.phase.Air(network=net) # water = op.phase.Water(network=net) # water['pore.diffusivity'] = 1e-11 # from openpnm import contrib # m = contrib.MultiPhase(network=net, phases=[air, water]) # m.set_occupancy(phase=air, pores=[0, 1, 2]) # m.set_occupancy(phase=water, pores=[3, 4, 5]) # const = op.models.misc.constant # K_water_air = 0.5 # m.set_binary_partition_coef(phases=[water, air], model=const, value=K_water_air) # m._set_automatic_throat_occupancy() # mdiff = op.models.physics.diffusive_conductance.multiphase_diffusion # m.add_model(propname="throat.diffusive_conductance", model=mdiff) # g = m["throat.diffusive_conductance"] # # Diffusive conductance for MultiPhase must be Nt by 2 (not Nt by 1) # assert g.shape == (net.Nt, 2) # # Columns 1, 2 of conductance must be equal except for interface throat # assert_allclose(g[:, 0][[0, 1, 3, 4]], g[:, 1][[0, 1, 3, 4]]) # # G12 and G21 at interface must differ (ratio must be K_water_air) # assert_allclose(g[2, 0] / g[2, 1], 1 / K_water_air) # assert_allclose(g.mean(), 7.64303956e-7, rtol=1e-5) def test_taylor_aris_diffusion(self): self.net['throat.diffusive_size_factors'] = self.size_factors self.phase['pore.pressure'] = np.linspace(0, 20, self.net.Np) self.phase['throat.hydraulic_conductance'] = 1 mod = op.models.physics.diffusive_conductance.taylor_aris_diffusion self.phase.add_model(propname='throat.diffusive_conductance', model=mod) self.phase.regenerate_models() actual = np.array([ self.phase['throat.diffusive_conductance'].mean(), self.phase['throat.diffusive_conductance'].max(), self.phase['throat.diffusive_conductance'].min()] ) desired = np.array([0.121193, 0.126131, 0.118578]) assert_allclose(actual, desired, rtol=1e-5) if __name__ == '__main__': t = DiffusiveConductanceTest() self = t t.setup_class() for item in t.__dir__(): if item.startswith('test'): print(f'Running test: {item}') t.__getattribute__(item)()