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Research Papers

An Improved MRT Lattice Boltzmann Model for Calculating Anisotropic Permeability of Compressed and Uncompressed Carbon Cloth Gas Diffusion Layers Based on X-Ray Computed Micro-Tomography

[+] Author and Article Information
Yuan Gao1

School of Engineering,  University of Liverpool, Brownlow Street, Liverpool, L69 3GQ UKYuan.Gao@liverpool.ac.uk

Xiaoxian Zhang

School of Engineering,  University of Liverpool, Brownlow Street, Liverpool, L69 3GQ UK

Pratap Rama, Rui Chen

Department of Aeronautical and Automotive Engineering,  Loughborough University, Loughborough LE11 3TU, UK

Hossein Ostadi, Kyle Jiang

Micro Engineering and Nano Technology, Department of Mechanical and Manufacturing Engineering,  University of Birmingham, Birmingham B15 2TT, UK

1

Corresponding author.

J. Fuel Cell Sci. Technol 9(4), 041010 (Jun 19, 2012) (10 pages) doi:10.1115/1.4006796 History: Received June 04, 2011; Revised April 01, 2012; Published June 19, 2012; Online June 19, 2012

The gas diffusion layers (GDLs) in polymer proton exchange membrane fuel cells are under compression in operation. Understanding and then being able to quantify the reduced ability of GDLs to conduct gases due to the compression is hence important in fuel cell design. In this paper, we investigated the change of anisotropic permeability of GDLs under different compressions using the improved multiple-relaxation time (MRT) lattice Boltzmann model and X-ray computed micro-tomography. The binary 3D X-ray images of GDLs under different compressions were obtained using the technologies we developed previously, and the permeability of the GDLs in both through-plane and in-plane directions was calculated by simulating gas flow at micron scale through the 3D images. The results indicated that, in comparison with the single-relaxation time (SRT) lattice Boltzmann model commonly used in the literature, the MRT model is robust and flexible in choosing model parameters. The SRT model can give accurate results only when using a specific relaxation parameter whose value varies with porosity. The simulated results using the MRT model reveal that compression could lead to a significant decrease in permeability in both through-plane and in-plane directions, and that the relationship between the decreased permeability and porosity can be well described by both Kozeny-Carman relation and the equation derived by Tomadakis and Sotirchos (1993, “Ordinary and Transition Rdgime Diffusion in Random Fiber Structure,” AIChE J., 39 , pp. 397–412) for porosity in the range from 50% to 85%. Since GDLs compression takes place mainly in the through-plane direction, the results presented in this work could provide an easy way to estimate permeability reduction in both through-plane and in-plane directions when the compressive pressure is known.

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Copyright © 2012 by American Society of Mechanical Engineers
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Figures

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Figure 1

The 19 lattice velocities in the D3Q19 LB model

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Figure 2

SEM image of the uncompressed GDL used in this work (a); the whole image (b), and the four regions of the image shown in (b) used for the simulations (c)–(f)

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Figure 3

The 3D image of the compressed GDL under 0.3 MPa (a), and the four regions used for simulations (b)–(e)

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Figure 4

The 3D image of the compressed GDL under 20 MPa (a), and the four regions used for simulations (b)–(e)

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Figure 5

Procedure of the methodology from image acquiring to simulations

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Figure 6

Comparison of the permeability simulated by SRT and MRT models using different relaxation parameters for the uncompressed GDL when flow is in the z direction: permeability kzx (a), permeability kzy (b), and permeability kzz (c)

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Figure 7

Comparison of the permeability simulated by SRT and MRT models using different relaxation parameters for the compressed GDL under 0.3 MPa when flow is in the z direction: permeability kzx (a), permeability kzy (b), and permeability kzz (c)

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Figure 8

Comparison of the permeability simulated by SRT and MRT models using different relaxation parameters for the compressed GDL under 20 MPa when flow is in the z direction: permeability kzx (a), permeability kzy (b), and permeability kzz (c)

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Figure 9

Change of the simulated permeability by MRT with porosity with the predictions of T-S and the K-C relations in the through-plane direction (a), and in the in-plane direction (b)

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Figure 10

Streamlines and pressure distribution in the uncompressed GDL when the mean gas flow is in the through-plane direction (a), and in the in-plane direction (b)

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Figure 11

Streamlines and pressure distribution in the uncompressed GDL when the mean gas flow is in the through-plane direction (a), and in the in-plane direction (b)

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