2 papers
cs.LG2026
Physics-Informed Neural Networks for Methane Sorption: Cross-Gas Transfer Learning, Ensemble Collapse Under Physics Constraints, and Monte Carlo Dropout Uncertainty Quantification
Mohammad Nooraiepour, Zezhang Song, Wei Li +1
Accurate methane sorption prediction across heterogeneous coal ranks requires models that combine thermodynamic consistency, efficient knowledge transfer across data-scarce geologi…
cs.CE2024
A semi-Lagrangian method for the direct numerical simulation of crystallization and precipitation at the pore scale
Sarah Perez, Jean-Matthieu Etancelin, Philippe Poncet
This article introduces a new efficient particle method for the numerical simulation of crystallization and precipitation at the pore scale of real rock geometries extracted by X-R…