124 citations · 124 across the 3 of their papers we have counts for
3 papers
Physics-Informed Neural Networks and Sequence Encoder: Application to heating and early cooling of thermo-stamping process
Mouad Elaarabi, Domenico Borzacchiello, Philippe Le Bot +2
In a previous work (Elaarabi et al., 2025b), the Sequence Encoder for online dynamical system identification (Elaarabi et al., 2025a) and its combination with PINN (PINN-SE) were i…
Sensitivity analysis using Physics-informed neural networks
John M. Hanna, José V. Aguado, Sebastien Comas-Cardona +2
The goal of this paper is to provide a simple approach to perform local sensitivity analysis using Physics-informed neural networks (PINN). The main idea lies in adding a new term…
Residual-based adaptivity for two-phase flow simulation in porous media using Physics-informed Neural Networks
John M. Hanna, Jose V. Aguado, Sebastien Comas-Cardona +2
This paper aims to provide a machine learning framework to simulate two-phase flow in porous media. The proposed algorithm is based on Physics-informed neural networks (PINN). A no…