Numerical Reconstruction of Proton Exchange Membrane Fuel Cell Gas Diffusion Layers

Abstract

Stochastic reconstruction is widely employed for effective and flexible imitation of Gas Diffusion Layers (GDLs), e.g., to facilitate the study of their properties. However, the reconstruction often overlooks crucial factors such as fiber curvature, fiber stack arrangement, and fiber anisotropy. Consequently, the impact of these structural characteristics remains poorly understood. In this study, an in-house reconstruction procedure is developed based on the periodic surface model. This procedure enables the generation of GDLs with either straight or curved fibers, layer-by-layer or random arrangement, and different probabilities of through-plane fiber orientation angles. The porosity, domain size, and fiber diameter are extracted from an experimental image-based GDL and utilized as input data for the reconstruction. Furthermore, the different GDLs are compared in terms of pore size distribution and through-plane porosity distribution. It is concluded that introducing proper selections of these fiber features gives the reconstruction more realistic properties.