Estimation of Relative Transport Properties in Porous Transport Layers Using Pore-Scale and Pore-Network Simulations. Issue 6 (1st June 2021)

• Record Type: Journal Article
• Authors: Jung, Seongyeop; Sabharwal, Mayank; Jarauta, Alex; Wei, Fei; Gingras, Murray; Gostick, Jeff; Secanell, Marc
• Is Part Of: Journal of the Electrochemical Society. Volume 168:Issue 6(2021)
• Publication Date: 2021-06-01
• Subjects: Pore network modeling -- Direct numerical simulation -- Full morphology -- Micro X-ray computed tomography -- Two-phase flow -- Mercury intrusion porosimetry; Electrochemistry -- Periodicals; 541.3705
• DOI: 10.1149/1945-7111/ac03f2
• Languages: English
• ISSNs: 0013-4651

Abstract

Abstract : Improvements in imaging techniques have enabled the reconstruction of complex porous media which can be analyzed by computer simulations. The two most popular methods for numerical analysis of transport in porous media are direct numerical simulation (DNS) and pore network modeling (PNM). This work aims at assessing the suitability of these techniques to study dry and wet transport properties of porous transport layers for fuel cells and electrolyzers by comparing numerical predictions to experimental data for mercury intrusion, and transport properties. The microstructures of different materials are obtained using micro X-ray computed tomography and characterized by measuring mercury intrusion porosimetry (MIP) curves, dry permeability and diffusivity. Their results are compared to numerically predicted MIP, and dry and wet permeability and diffusivity. Results show that DNS is capable of accurately predicting intrusion, and transport properties without using any fitting parameters. Accurate predictions could be achieved with a PNM when the inscribed diameter method was used for pore size distribution, and the equivalent diameter was used to estimate pore transport properties. While DNS provides more accurate results without necessitating any calibration, a properly constructed PNM is shown to provide relatively good estimations of transport properties at a reduced computational expense.