2 papers
cond-mat.dis-nn2025
Rheological Parameter Identification in Granular Materials Using Physics-Informed Neural Networks
Barbara Baldoni, Mickaël Delcey, Yoann Cheny +3
Physics-Informed Neural Networks (PINNs) have recently emerged as a promising tool for fluid dynamics, particularly for flow reconstruction and parameter identification. In the con…
physics.flu-dyn2025
Quantitative Assessment of PINN Inference on Experimental Data for Gravity Currents Flows
Mickaël Delcey, Yoann Cheny, Jean Schneider +2
In this paper, we apply Physics Informed Neural Networks (PINNs) to infer velocity and pressure field from Light Attenuation Technique (LAT) measurements for gravity current induce…