Comparative Analysis of Pore Network Modelling (PNM) and Computational Fluid Dynamics (CFD) for Transport Modeling in Alkaline Water Electrolyser Porous Electrode

Abstract

Green hydrogen production via alkaline water electrolysis (A-WE) is a crucial technology for sustainable energy transition. The efficiency and durability of electrolyzers strongly depend on the transport properties within porous electrodes. This thesis presents a comparative analysis of two numerical modelling approaches, Pore Network Modeling (PNM) and Computational Fluid Dynamics (CFD), to predict transport phenomena in realistic 3D microstructures of sintered nickel electrodes obtained from X-ray microtomography (μCT). Microtomography μCT image was processed and SNOW2 algorithm was used to extract detailed pore networks. The porosity and interfacial area per volume were computed. These geometric properties were validated against image analysis data with agreement, confirming the accuracy of the reconstruction method. Subsequently, single-phase flow simulations were conducted using the pore network (PN) (OpenPNM) with various geometric models and CFD (OpenFOAM) directly on meshed μCT data to evaluate absolute permeability and tortuosity. Results demonstrated a strong correlation between PNM and CFD for tortuosity prediction, with 1.4% relative error, highlighting PNM’s ability to reliably represent the complexity of diffusion pathways. Permeability predictions showed larger variations depending on pore and throat geometry, with relative errors ranging from 17% (cones and cylinders) to 260% (cubes and cuboids). PNM simulations was performed in 15 minutes while CFD simulation took around 7 hours. These results show PNM computational efficiency and its flexibility to simulate multiple geometric configurations rapidly, enabling comprehensive parametric studies and optimization of porous media microstructures. This capability supports accelerated design of porous layers with enhanced transport properties, potentially improving electrolyzer performance and lifespan while reducing experimental costs. So, validated by CFD or experimental data, PNM proves to be an effective tool for predicting transport phenomena in porous electrodes. Its ability to efficiently explore diverse pore geometries makes it invaluable for guiding rational design and innovation in alkaline water electrolysis technology and other electrochemical applications.