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Comprehensive statistical analysis of heterogeneous transport characteristics in multifunctional porous gas diffusion layers using lattice Boltzmann method for fuel cell applications

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  • Liu, Jiawen
  • Shin, Seungho
  • Um, Sukkee

Abstract

Comprehensive computational modeling based on a full statistical approach is performed to investigate the heterogeneous multi-transport characteristics in the gas diffusion layers of fuel cells. For the purposes, a series of carbon paper gas diffusion layers are randomly generated at a 95% confidence level to reflect the heterogeneous microstructures. A representative element volume is determined based on the relative porosity gradient errors to minimize the uncertainty in the statistical analysis. Subsequently, a single-phase three-dimensional lattice Boltzmann method is applied to obtain the velocity distribution throughout the porous layers, enabling to calculate the average tortuosity. The effective mass diffusivity in the diffusion layers is then derived from the tortuosity factor. Additionally, three directional permeabilities are derived from the pressure gradient to account for the anisotropic characteristics of the porous diffusion layers. The relationship between the permeability and porosity is found to match the modified Kozeny–Carman equations. Further, a path-finding algorithm based on the percolation theory is developed to simulate electron and thermal conduction along the carbon fibers in the in-plane and through-plane directions. The present model can be utilized to investigate the heterogeneous transport characteristics of fibrous porous diffusion media for various electrochemical systems.

Suggested Citation

  • Liu, Jiawen & Shin, Seungho & Um, Sukkee, 2019. "Comprehensive statistical analysis of heterogeneous transport characteristics in multifunctional porous gas diffusion layers using lattice Boltzmann method for fuel cell applications," Renewable Energy, Elsevier, vol. 139(C), pages 279-291.
    • Handle: RePEc:eee:renene:v:139:y:2019:i:c:p:279-291
    DOI: 10.1016/j.renene.2019.02.089
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    References listed on IDEAS

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    1. Kim, Ah-Reum & Shin, Seungho & Um, Sukkee, 2016. "Multidisciplinary approaches to metallic bipolar plate design with bypass flow fields through deformable gas diffusion media of polymer electrolyte fuel cells," Energy, Elsevier, vol. 106(C), pages 378-389.
    2. Zamel, Nada & Litovsky, Efim & Shakhshir, Saher & Li, Xianguo & Kleiman, Jacob, 2011. "Measurement of in-plane thermal conductivity of carbon paper diffusion media in the temperature range of −20°C to +120°C," Applied Energy, Elsevier, vol. 88(9), pages 3042-3050.
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    Cited by:

    1. Ying Da Wang & Quentin Meyer & Kunning Tang & James E. McClure & Robin T. White & Stephen T. Kelly & Matthew M. Crawford & Francesco Iacoviello & Dan J. L. Brett & Paul R. Shearing & Peyman Mostaghimi, 2023. "Large-scale physically accurate modelling of real proton exchange membrane fuel cell with deep learning," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Akbar, Ali & Um, Sukkee, 2022. "Influence of external clamping pressure on nanoscopic mechanical deformation and catalyst utilization of quaternion PtC catalyst layers for PEMFCs," Renewable Energy, Elsevier, vol. 194(C), pages 195-210.
    3. Akbar, Ali & Liu, Jiawen & Chung, Sung-Jae & Um, Sukkee, 2021. "Statistical characterization of non-linear microscopic mechanical deformation through randomly oriented fibrous porous transport layers for advanced electrochemical energy systems," Renewable Energy, Elsevier, vol. 178(C), pages 1106-1118.

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