Numerical derivation of the absolute and relative permeability coefficient tensors from stochastically reconstructed replicas of fuel cell electrodes
A.K.M. Podias and G. Tsotridis
EC,DG JRC,Institute for Energy, NL
stochastic reconstruction, Lattice-Boltzmann Equations, Finite Volume Method, Solid Oxide Fuel Cell, Polymer Electrolyte Membrane Fuel Cell, absolute permeability tensor, relative permeability tensor
Fuel cell operation entails movement of reactants and products, ions, and electrons, with the processes in the structural elements of the cell coupled strongly and nonlinearly to each other. Several tens of operation, transport, kinetic and design parameters characterise fuel cells, most of them strongly linked. Additionally, that complexity is hidden in the microscopic details, mostly inaccessible to the experimental observation. In this paper we report on the application of low-order statistical information, obtained from two-dimensional (2D) micrographs of the pore space of a real fuel cell electrodes, to derive stochastic replicas of their three-dimensional (3D) structure. The main focus is on assessing the usefulness of stochastic reconstruction as a means of relating macroscopic transport coefficients, such as intrinsic, absolute and relative permeability to the geometry and topology of the pore space. For that purpose two modelling approaches, based on a lattice-Boltzmann equation method and a finite volume method, were employed to describe the detailed flow field in a representative 3D sample of the electrode, exclusively based on the 3D description of the geometry and topology of the porous medium, thus without the use of semi-empirical data; subsequently, transport coefficients of the porous cathode were calculated. The methods applied were compared in terms of convergence rate, and the convergence as a function of mesh resolution was analysed.
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Nanotech 2006 Conference Program Abstract