Microstructure sensitive design and quantitative prediction of effective conductivity in fuel cell design

Hamid Garemstani, Dongsheng Li, Moe A. Khaleel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationMaterials Science Forum
Pages315-318
Number of pages4
Volume561-565
EditionPART 1
Publication statusPublished - 1 Dec 2007
Externally publishedYes
Event6th Pacific Rim International Conference on Advanced Materials and Processing, PRICM 6 - Jeju, Korea, Republic of
Duration: 5 Nov 20079 Nov 2007

Publication series

NameMaterials Science Forum
NumberPART 1
Volume561-565
ISSN (Print)02555476

Other

Other6th Pacific Rim International Conference on Advanced Materials and Processing, PRICM 6
CountryKorea, Republic of
CityJeju
Period5/11/079/11/07

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Keywords

  • Fuel cell
  • Microstructure design
  • Porous medium
  • Transport properties

ASJC Scopus subject areas

  • Materials Science(all)

Cite this

Garemstani, H., Li, D., & Khaleel, M. A. (2007). Microstructure sensitive design and quantitative prediction of effective conductivity in fuel cell design. In Materials Science Forum (PART 1 ed., Vol. 561-565, pp. 315-318). (Materials Science Forum; Vol. 561-565, No. PART 1).