Abstract: Detailed physics-based computer models of fuel cells can be computationally prohibitive for applications such as optimization and uncertainty quantification. Such applications can require a very high number of runs in order ...

Abstract: Neural network models have a long history in fuel cell and battery modeling. With the recent advent of deep learning, there is potential for further improvements in these models. Conversely, deep learning is primarily ...