r""" Details about the continum and numerical model equations can be found on: Agnaou, M., Sadeghi, M. A., Tranter, T. G., & Gostick, J. (2020). Modeling transport of charged species in pore networks: solution of the Nernst-Planck equations coupled with fluid flow and charge conservation equations. Computers & Geosciences, 104505. """ import openpnm as op from openpnm.phase import mixtures import numpy as np ws = op.Workspace() proj = ws.new_project() # Network, geometry, phase np.random.seed(0) net = op.network.Cubic(shape=[23, 15, 1], spacing=1e-6, project=proj) Ps = (net['pore.back'] * net['pore.right'] + net['pore.back'] * net['pore.left'] + net['pore.front'] * net['pore.right'] + net['pore.front'] * net['pore.left']) Ts = net['throat.surface'] op.topotools.trim(network=net, pores=net.Ps[Ps], throats=net.Ts[Ts]) np.random.seed(0) op.topotools.reduce_coordination(net, 3) np.random.seed(0) geo = op.geometry.SpheresAndCylinders(network=net, pores=net.Ps, throats=net.Ts) sw = mixtures.SalineWater(network=net) # Retrieve handles to each species for use below Na = sw.components['Na_' + sw.name] Cl = sw.components['Cl_' + sw.name] H2O = sw.components['H2O_' + sw.name] # Physics phys = op.physics.GenericPhysics(network=net, phase=sw, geometry=geo) flow = op.models.physics.hydraulic_conductance.hagen_poiseuille phys.add_model(propname='throat.hydraulic_conductance', pore_viscosity='pore.viscosity', throat_viscosity='throat.viscosity', model=flow, regen_mode='normal') current = op.models.physics.ionic_conductance.poisson phys.add_model(propname='throat.ionic_conductance', model=current, regen_mode='normal') eA_dif = op.models.physics.diffusive_conductance.ordinary_diffusion phys.add_model(propname='throat.diffusive_conductance.' + Na.name, pore_diffusivity='pore.diffusivity.' + Na.name, throat_diffusivity='throat.diffusivity.' + Na.name, model=eA_dif, regen_mode='normal') eB_dif = op.models.physics.diffusive_conductance.ordinary_diffusion phys.add_model(propname='throat.diffusive_conductance.' + Cl.name, pore_diffusivity='pore.diffusivity.' + Cl.name, throat_diffusivity='throat.diffusivity.' + Cl.name, model=eB_dif, regen_mode='normal') scheme = 'powerlaw' ad_dif_mig_Na = op.models.physics.ad_dif_mig_conductance.ad_dif_mig phys.add_model(propname='throat.ad_dif_mig_conductance.' + Na.name, pore_pressure='pore.pressure', model=ad_dif_mig_Na, ion=Na.name, s_scheme=scheme) ad_dif_Na = op.models.physics.ad_dif_conductance.ad_dif phys.add_model(propname='throat.ad_dif_conductance.' + Na.name, throat_diffusive_conductance='throat.diffusive_conductance.' + Na.name, pore_pressure='pore.pressure', model=ad_dif_Na, s_scheme=scheme) ad_dif_mig_Cl = op.models.physics.ad_dif_mig_conductance.ad_dif_mig phys.add_model(propname='throat.ad_dif_mig_conductance.' + Cl.name, pore_pressure='pore.pressure', model=ad_dif_mig_Cl, ion=Cl.name, s_scheme=scheme) # Settings for algorithms setts1 = {'solver_family': 'scipy', 'solver_max_iter': 5, 'solver_tol': 1e-08, 'solver_rtol': 1e-08, 'nlin_max_iter': 10, 'cache': False} setts2 = {'g_tol': 1e-4, 'g_max_iter': 100} # Algorithms sf = op.algorithms.StokesFlow(network=net, phase=sw, settings=setts1) sf.set_value_BC(pores=net.pores('back'), values=6) sf.set_value_BC(pores=net.pores('front'), values=1) sf.run() sw.update(sf.results()) p = op.algorithms.IonicConduction(network=net, phase=sw, settings=setts1) p.set_value_BC(pores=net.pores('left'), values=0.01) p.set_value_BC(pores=net.pores('right'), values=0.01) p.settings['charge_conservation'] = 'poisson' p.run() sw.update(p.results()) eA = op.algorithms.NernstPlanck(network=net, phase=sw, ion=Na.name, settings=setts1) eA.set_value_BC(pores=net.pores('back'), values=20) eA.set_value_BC(pores=net.pores('front'), values=10) eA.run() sw['pore.val1'] = eA['pore.concentration.Na_mix_01'] eB = op.algorithms.NernstPlanck(network=net, phase=sw, ion=Na.name, settings=setts1) eB.set_value_BC(pores=net.pores('back'), values=1) eB.set_value_BC(pores=net.pores('left'), values=0.1) eB.set_value_BC(pores=net.pores('right'), values=0.1) eB.set_outflow_BC(pores=net.pores('front')) eB.run() sw['pore.val2'] = eB['pore.concentration.Na_mix_01'] eC = op.algorithms.AdvectionDiffusion(network=net, phase=sw, settings=setts1) setts3 = setts1.copy() setts3.update( {'conductance': 'throat.ad_dif_conductance.' + Na.name, 'diffusive_conductance': 'throat.diffusive_conductance.' + Na.name, 'hydraulic_conductance': 'throat.hydraulic_conductance'}) eC.settings._update(setts3) eC.set_value_BC(pores=net.pores('back'), values=1) eC.set_value_BC(pores=net.pores('left'), values=0.1) eC.set_value_BC(pores=net.pores('right'), values=0.1) eC.set_outflow_BC(pores=net.pores('front')) eC.run() sw['pore.val3'] = eC['pore.concentration'] # Output data to Paraview # sw['pore.val2'] should be equal to sw['pore.val3'] proj.export_data(phases=[sw], filename='out', filetype='VTK')