2014
DOI: 10.1016/j.energy.2014.03.052
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Numerical modeling of interconnect flow channel design and thermal stress analysis of a planar anode-supported solid oxide fuel cell stack

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Cited by 80 publications
(37 citation statements)
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“…4 that the fuel cell performance at 1023 K is better than that obtained at 923 K. This is because ohmic overpotential drops dramatically with the enhancement of the operating temperature. This trend is also consistent with other experimental and simulation results reported elsewhere [14,20]. Fig.…”
Section: Effect Of Cell Operating Temperaturesupporting
confidence: 93%
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“…4 that the fuel cell performance at 1023 K is better than that obtained at 923 K. This is because ohmic overpotential drops dramatically with the enhancement of the operating temperature. This trend is also consistent with other experimental and simulation results reported elsewhere [14,20]. Fig.…”
Section: Effect Of Cell Operating Temperaturesupporting
confidence: 93%
“…Some thermal stresses are also observed in the system and these may be caused by a mismatch between the coefficients of thermal expansion of the construction materials [14,25].…”
Section: Effect Of Cell Operating Temperaturementioning
confidence: 98%
“…The results obtained by [17] revealed that the use of Grancrete cell support reduced the maximum principal stress of the planar fuel cell and the calculated maximum von Mises stress was lower that the yield strength of stainless steel. Based on the evidence that it was possible to optimize construction of the planar SOFC stack, a similar approach was developed and is presented in this paper with respect to a microtubular Solid Oxide Fuel Cell stack.…”
Section: Introductionmentioning
confidence: 86%
“…The key feature of the model consists in numerical coupling of the three-dimensional Computational Fluid Dynamics technique, used for an accurate evaluation of the flow and temperature distributions inside the mSOFC stack, with Computational Structural Mechanics Finite Element Method (FEM) analysis that allows to predict thermal stresses. A similar approach was applied by Wei et al [17], Yakabe et al [8,12], Nakajo et al [13], Liu et al [18] and Peksen [19,20].…”
Section: Introductionmentioning
confidence: 99%
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