LAPSE:2023.5527
Published Article
LAPSE:2023.5527
Transport Parameter Correlations for Digitally Created PEFC Gas Diffusion Layers by Using OpenPNM
February 23, 2023
Abstract
A polymer electrolyte fuel cell (PEFC) is an electrochemical device that converts chemical energy into electrical energy and heat. The energy conversion is simple; however, the multiphysics phenomena involved in the energy conversion process must be analyzed in detail. The gas diffusion layer (GDL) provides a diffusion media for reactant gases and gives mechanical support to the fuel cell. It is a complex medium whose properties impact the fuel cell’s efficiency. Therefore, an in-depth analysis is required to improve its mechanical and physical properties. In the current study, several transport phenomena through three-dimensional digitally created GDLs have been analyzed. Once the porous microstructure is generated and the transport phenomena are mimicked, transport parameters related to the fluid flow and mass diffusion are computed. The GDLs are approximated to the carbon paper represented as a grouped package of carbon fibers. Several correlations, based on the fiber diameter, to predict their transport properties are proposed. The digitally created GDLs and the transport phenomena have been modeled using the open-source library named Open Pore Network Modeling (OpenPNM). The proposed correlations show a good fit with the obtained data with an R-square of approximately 0.98.
Keywords
Delaunay tessellation, gas diffusion layer, OpenPNM, polymer electrolyte fuel cell, transport parameters, Voronoi algorithm
Suggested Citation
Encalada-Dávila Á, Espinoza-Andaluz M, Barzola-Monteses J, Li S, Andersson M. Transport Parameter Correlations for Digitally Created PEFC Gas Diffusion Layers by Using OpenPNM. (2023). LAPSE:2023.5527
Author Affiliations
Encalada-Dávila Á: Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ingeniería Mecánica y Ciencias de la Producción, Campus Gustavo Galindo Km. 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil 090112, Ecuador [ORCID]
Espinoza-Andaluz M: Escuela Superior Politécnica del Litoral, ESPOL, Facultad de Ingeniería Mecánica y Ciencias de la Producción, Centro de Energías Renovables y Alternativas, Campus Gustavo Galindo Km. 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil 090112, Ecuado [ORCID]
Barzola-Monteses J: Artificial Intelligence and Information Technology Research Group, University of Guayaquil, Avda. Kennedy y Avda. Delta, P.O. Box 471, Guayaquil 090514, Ecuador; Department of Computer Science and Artificial Intelligence, Escuela Técnica Superior de Inge [ORCID]
Li S: Marine Engineering College, Dalian Maritime University, Dalian 116026, China [ORCID]
Andersson M: School of Materials and Energy, University of Electronic Science and Technology of China, 2006 Xiyuan Ave, West Hi-Tech Zone, Chengdu 610054, China; Department of Energy Sciences, Faculty of Engineering, Lund University, P.O. Box 118, 22100 Lund, Sweden [ORCID]
Journal Name
Processes
Volume
9
Issue
7
First Page
1141
Year
2021
Publication Date
2021-06-30
ISSN
2227-9717
Version Comments
Original Submission
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PII: pr9071141, Publication Type: Journal Article
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LAPSE:2023.5527
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https://doi.org/10.3390/pr9071141
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