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Stochastic 3D Carbon Cloth GDL Reconstruction and Transport Prediction

Author

Listed:
  • Yuan Gao

    (School of Automotive Studies, Tongji University, Shanghai 200000, China)

  • Teng Jin

    (School of Automotive Studies, Tongji University, Shanghai 200000, China)

  • Xiaoyan Wu

    (School of Automotive Studies, Tongji University, Shanghai 200000, China)

Abstract

This paper presents the 3D carbon cloth gas diffusion layer (GDL) to predict transport behaviors of anisotropic structure properties. A statistical characterization and stochastic reconstruction method is established to construct the 3D micro-structure using the data from the true materials. Statistics of the many microstructure characteristics, such as porosity, pore size distribution, and shape of the void, are all quantified by image-based characterization. Furthermore, the stochastic reconstruction algorithm is proposed to generate random and anisotropic 3D microstructure models. The proposed method is demonstrated by some classical simulation prediction and to give the evaluation of the transport properties. Various reconstructed GDLs are also generated to demonstrate the capability of the proposed method. In the end, the adapted structure properties are offered to optimize the carbon cloth GDLs.

Suggested Citation

  • Yuan Gao & Teng Jin & Xiaoyan Wu, 2020. "Stochastic 3D Carbon Cloth GDL Reconstruction and Transport Prediction," Energies, MDPI, vol. 13(3), pages 1-15, January.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:3:p:572-:d:312868
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    References listed on IDEAS

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    1. Fadzillah, D.M. & Rosli, M.I. & Talib, M.Z.M. & Kamarudin, S.K. & Daud, W.R.W., 2017. "Review on microstructure modelling of a gas diffusion layer for proton exchange membrane fuel cells," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 1001-1009.
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