Spatially smoothed fuel cell models: Variability of dependent variables underneath flow fields

Spatial smoothing can be applied to reduce a three-dimensional (3D) fuel cell model to a computationally cost-efficient two-dimensional (2D) counterpart. In this study, the averaged dependent variables in the streamwise direction are augmented with a statistical measure of their distribution in the spanwise direction in the form of standard deviations. A functional form of the latter is postulated and justified a posteriori by comparing the predictions from the 2D spatially-smoothed model with the original 3D counterpart: good agreement is found. This measure of the variability thus complements the average predictions of existing spatially smoothed models.