466 citations · 1.7k across the 54 of their papers we have counts for
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Physics-Informed Neural Network Method for Parabolic Differential Equations with Sharply Perturbed Initial Conditions
Yifei Zong, QiZhi He, Alexandre M. Tartakovsky
In this paper, we develop a physics-informed neural network (PINN) model for parabolic problems with a sharply perturbed initial condition. As an example of a parabolic problem, we…
Enhanced physics-constrained deep neural networks for modeling vanadium redox flow battery
QiZhi He, Yucheng Fu, Panos Stinis +1
Numerical modeling and simulation have become indispensable tools for advancing a comprehensive understanding of the underlying mechanisms and cost-effective process optimization a…
Machine Learning in Heterogeneous Porous Materials
Marta D'Elia, Hang Deng, Cedric Fraces +21
The "Workshop on Machine learning in heterogeneous porous materials" brought together international scientific communities of applied mathematics, porous media, and material scienc…