Physics-informed neural networks (PINNs) for numerical model error approximation and superresolution

Bozhou Zhuang, Sashank Rana, Brandon Jones +1

Numerical modeling errors are unavoidable in finite element analysis. The presence of model errors inherently reflects both model accuracy and uncertainty. To date there have been…