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• W4307633856 abstract "A low-performance fuel cell significantly hinders the application and commercialization of fuel cell technology. Computational fluid dynamics modeling could predict and evaluate the performance of a proton exchange membrane fuel cell (PEMFC) with less time consumption and cost-effectiveness. PEMFC performance is influenced by the distribution of reactants, water, heat, and current density. An uneven distribution of reactants leads to the localization of current density that produces heat and water, which are the by-products of the reaction to be concentrated at the location. The simplification of model geometry can affect performance prediction. Numerical investigations are commonly validated with experimental results to validate the method’s accuracy. Poor prediction of PEMFC results has not been discussed. Thus, this study aims to predict the effect of geometry modeling on fuel cell performance. Two contrasting 3D model dimensions, particularly single-channel and small-scale seven-channel models were employed. Both 3D models are correlated with a multi-channel model to assess the effect of modeling dimension on the PEMFC performance. Similar stoichiometry and channel dimensions were imposed on each model, where theoretically, the PEMFC performance should be identical. The simulation findings showed that the single-channel model produced a higher current density per cm2. From the contours of water and current density, the single-channel model does not show flow distribution. Thus, this leads to a higher current density generation than the small-scale model. The prediction of PEMFC performance is not thorough for the single-channel model. Therefore, the prediction of PEMFC performance is adaptable in a small-scale or comprehensive flow field." @default.
• W4307633856 created "2022-11-04" @default.
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• W4307633856 date "2022-10-26" @default.
• W4307633856 modified "2023-10-11" @default.
• W4307633856 title "Performance Analysis of PEMFC with Single-Channel and Multi-Channels on the Impact of the Geometrical Model" @default.
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• W4307633856 doi "https://doi.org/10.3390/en15217960" @default.
• W4307633856 hasPublicationYear "2022" @default.
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