Research Papers

Numerical Determination of Two-Phase Material Parameters of a Gas Diffusion Layer Using Tomography Images

[+] Author and Article Information
Jürgen Becker

 Fraunhofer ITWM, Fraunhofer-Platz 1, 67663 Kaiserslautern, Germanybecker@itwm.fhg.de

Volker Schulz, Andreas Wiegmann

 Fraunhofer ITWM, Fraunhofer-Platz 1, 67663 Kaiserslautern, Germany

J. Fuel Cell Sci. Technol 5(2), 021006 (Apr 11, 2008) (9 pages) doi:10.1115/1.2821600 History: Received June 28, 2007; Revised July 06, 2007; Published April 11, 2008

In this paper, we give a complete description of the process of determining two-phase material parameters for a gas diffusion layer: Starting from a 3D tomography image of the gas diffusion layer the distribution of gas and water phases is determined using the pore morphology method. Using these 3D phase distributions, we are able to determine permeability, diffusivity, and heat conductivity as a function of the saturation of the porous medium with comparatively low numerical costs. Using a reduced model for the compression of the gas diffusion layer, the influence of the compression on the parameter values is studied.

Copyright © 2008 by American Society of Mechanical Engineers
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Figure 1

SEM-like images of the GDL model obtained from the tomography data. The pictures on the left show cuts through the whole dataset; the pictures on the right show the 716.8×716.8×210μm3 large cutout used in the calculations.

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Figure 2

Capillary pressure curves showing drainage from top (Z+) and bottom (Z−) of the GDL and repeated drainage/imbibition. The calculations were performed on the cutout shown on the right hand side of Fig. 1.

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Figure 3

Water distribution at the bubble point. The pictures show a SEM-like view of the GDL seen from the dry side with fibers (left) and without fibers (right).

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Figure 4

Pore size distribution of the 716.8×716.8×210μm3 cutout of the medium. The gray curve shows the geometrical pore size distribution, and the black one shows the result of the simulated MIP.

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Figure 5

Illustration of the method. The first picture shows a tiny 3D model, here a virtually generated fiber structure. The second picture demonstrates compression with c=0.2. In the third step, the water distribution is determined for a given capillary pressure pc, here the water is shown in blue. The last picture shown illustrates the determination of air permeability (through-plane direction): the streamlines shown are the solution of Stokes’ equation.

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Figure 6

Relative permeabilities. The chart shows the diagonal entries of K. K11 and K22 are in-plane directions. The permeability values are given in 10−12m2.

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Figure 7

Saturation dependent gas diffusivity values. The graphs show the diagonal entries of the diffusivity tensor D*. In-plane (D11 and D22) and through-plane (D33) values are clearly distinguishable.

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Figure 8

Relative heat conductivity. The chart shows the diagonal entries of β* using the parameters from Eq. 24.

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Figure 9

Effect of compression on relative diffusivity and permeability values. The charts shows in-plane and through-plane values for both the uncompressed (c=0) and the 20% compressed (c=0.2) layer. Through-plane values are averages over x and y directions. Permeability values are given in 10−12m2.

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Figure 10

Effect of compression on absolute diffusivity and permeability. The charts show the in-plane and through-plane values for the unsaturated medium in dependence on the compression factor c. Through-plane values are averages over the x and y directions. Permeability values are given in 10−12m2.




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