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contributor authorWang, C.
date accessioned2017-05-09T01:19:25Z
date available2017-05-09T01:19:25Z
date issued2015
identifier issn2381-6872
identifier otherfc_012_04_041006.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/158394
description abstractIn order to develop a predictive model of real cell performance, firm relationships and assumptions need to be established for the definition of the physical and microstructure parameters for solid oxide fuel cells (SOFCs). This study explores the correlations of microstructure parameters from a microscale level, together with mass transfer and electrochemical reactions inside the electrodes, providing a novel approach to predict SOFC performance numerically. Based on the physical connections and interactions of microstructure parameters, two submodel correlations (i.e., porosity–tortuosity and porosity–particle size ratio) are proposed. Three experiments from literature are selected to facilitate the validation of the numerical results with experimental data. In addition, a sensitivity analysis is performed to investigate the impact of the adopted submodel correlations to the SOFC performance predictions. Normally, the microstructural inputs in the numerical model need to be measured by experiments in order to test the real cell performance. By adopting the two submodel correlations, the simulation can be performed without obtaining relatively hardtomeasure microstructural parameters such as tortuosity and particle size, yet still accurately mimicking a realworld wellstructured SOFC operation. By accurately and rationally predicting the microstructural parameters, this study can eventually help to aid the experimental and optimization study of SOFC.
publisherThe American Society of Mechanical Engineers (ASME)
titleMicroscale Correlations Adoption in Solid Oxide Fuel Cell
typeJournal Paper
journal volume12
journal issue4
journal titleJournal of Fuel Cell Science and Technology
identifier doi10.1115/1.4031153
journal fristpage41006
journal lastpage41006
identifier eissn2381-6910
treeJournal of Fuel Cell Science and Technology:;2015:;volume( 012 ):;issue: 004
contenttypeFulltext


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