Microstructure Sensitive Design and Quantitative Prediction of Effective Conductivity in Fuel Cell Design

Abstract:

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Statistical continuum approach is used to predict effective conductivity of anisotropic random porous heterogeneous media using two-point correlation functions. Probability functions play a critical role in describing the statistical distribution of different constituents in a heterogeneous media. In this study a 3-dimensional two-point correlation function is utilized to characterize the anisotropic porous media of a Cathode materials to incorporate all the details of the microstructure. These correlation functions are then linked to the effective properties using homogenization relations. An anisotropioc Green’s function solution is used to solve the set of field equations. Examples in this study demonstrated how the model captured the anisotropy in effective conductivity of the random heterogeneous media. Predicted results showed the influence of microstructure on the effective conductivity tensor.

Info:

Periodical:

Materials Science Forum (Volumes 561-565)

Main Theme:

Edited by:

Young Won Chang, Nack J. Kim and Chong Soo Lee

Pages:

315-318

DOI:

10.4028/www.scientific.net/MSF.561-565.315

Citation:

H. Garemstani et al., "Microstructure Sensitive Design and Quantitative Prediction of Effective Conductivity in Fuel Cell Design", Materials Science Forum, Vols. 561-565, pp. 315-318, 2007

Online since:

October 2007

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Price:

$35.00

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