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Impact of Random Geometric Distortions on the Performance and Reliability of an SOFC
Author(s) -
Cornu T. M.,
Wuillemin Z.
Publication year - 2011
Publication title -
fuel cells
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.485
H-Index - 69
eISSN - 1615-6854
pISSN - 1615-6846
DOI - 10.1002/fuce.201000120
Subject(s) - durability , reliability (semiconductor) , sensitivity (control systems) , stack (abstract data type) , computational fluid dynamics , monte carlo method , anode , deformation (meteorology) , plane (geometry) , solid oxide fuel cell , flow (mathematics) , materials science , set (abstract data type) , computer science , structural engineering , reliability engineering , mechanics , geometry , electronic engineering , mathematics , engineering , composite material , power (physics) , physics , statistics , electrode , quantum mechanics , programming language
A method based on Monte Carlo simulations (MCS) is developed to assess the impact of manufacturing tolerances on the durability of performance and on the reliability of solid oxide fuel cells (SOFCs). Computational fluid dynamics (CFD) simulations of the gas distribution pattern (GDP) at the anode are carried out for a set of deformed geometries. An automated code allows generating standardized deformations in a random manner on the original meshed geometry taken as input. In the scope of this study, the fuel flow uniformity is taken as the indicator of the performance and reliability of SOFCs. Statistical sensitivity analyses are carried out to assess the impact of dimensional tolerances on repeat‐elements both taken individually and stacked together. The implemented method is evaluated with two standard GDPs. Results show that the sensitivity to thickness variations is predominant on the sensitivity to in‐plane deformations of channels. Besides, the magnitude of sensitivity largely depends on the GDP and on the extent of the deformation, too. In addition, negative effects of deformations are shown to be exacerbated in stack situation. The method proved successful in getting quick insights on the quality of GDPs with respect to dimensional tolerances.