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Research Papers

An X-Ray Tomography Based Lattice Boltzmann Simulation Study on Gas Diffusion Layers of Polymer Electrolyte Fuel Cells

[+] Author and Article Information
Pratap Rama

Department of Aeronautical and Automotive Engineering, Loughborough University, LE11 3TU, UKp.rama@lboro.ac.uk

Yu Liu, Rui Chen

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

Hossein Ostadi, Kyle Jiang

School of Mechanical and Manufacturing Engineering, Centre for Biomedical and Nanotechnology, University of Birmingham, B15 2TT, UK

Xiaoxian Zhang

Department of Engineering, University of Liverpool, L69 3GQ, UK

Rosemary Fisher, Michael Jeschke

 Technical Fibre Products Limited, Kendal, LA9 6PZ, UK

J. Fuel Cell Sci. Technol 7(3), 031015 (Mar 16, 2010) (12 pages) doi:10.1115/1.3211096 History: Received September 17, 2008; Revised April 15, 2009; Published March 16, 2010; Online March 16, 2010

This work reports a feasibility study into the combined full morphological reconstruction of fuel cell structures using X-ray computed micro- and nanotomography and lattice Boltzmann modeling to simulate fluid flow at pore scale in porous materials. This work provides a description of how the two techniques have been adapted to simulate gas movement through a carbon paper gas diffusion layer (GDL). The validation work demonstrates that the difference between the simulated and measured absolute permeability of air is 3%. The current study elucidates the potential to enable improvements in GDL design, material composition, and cell design to be realized through a greater understanding of the nano- and microscale transport processes occurring within the polymer electrolyte fuel cell.

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Copyright © 2010 by American Society of Mechanical Engineers
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Figures

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Figure 10

Through-plane absolute permeability in the y-direction; the simulated absolute permeability for regions 1–14, the mean simulated absolute permeability, and the measured absolute permeability for the carbon paper GDL

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Figure 11

The binary 3D images of (a) region 1, (b) region 8, and (c) region 14, as shown in Fig. 6

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Figure 12

Rotated views to show fibril packing and void spaces of (a) region 1 (moderate permeability), (b) region 8 (highest permeability), and (c) region 14 (lowest permeability)

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Figure 13

Simulated absolute permeability in in-plane directions: (a) x-direction and (b) z-direction

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Figure 14

Simulated stream tubes for a segment of region 14: (a) solid 3D structure and (b) stream tubes

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Figure 1

Fuel cell processes

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Figure 2

Active elements in a D3Q19 LB cube

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Figure 3

The 19 velocities in the three-dimensional D3Q19 scheme employed in an LB cube: (a) the x-y plane, (b) the z-x plane, and (c) the z-y plane. The origin is denoted as o.

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Figure 4

The treatment of gas-solid boundary for the bounce-back method in the x-y plane of a LB cube; the shadowed area is solid and the white is void space; the line ABC is the boundary

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Figure 5

Schematic of micro- and nanotomography systems

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Figure 6

2D cross-sectional images of a GDL carbon paper sample: (a) shadow X-ray tomographic image, (b) reconstructed image using CTAN software, and (c) binary image of the cross section shown in Fig. 3. The fiber diameter and mean pore diameter have been calculated as ∼7.5 μm and 70 μm, respectively, using CTAN software.

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Figure 7

Nanotomography of a carbon paper GDL sample with 680 nm spatial resolution. Sample size is 600×250×700(X×Y×Z) μm3.

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Figure 8

Flowchart for the X-ray microtomography and lattice Boltzmann imaging and simulation process

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Figure 9

The overall 3D shadow image of carbon paper GDL captured using X-ray microtomography and the 14 regions for the LB simulations

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