3 papers
physics.flu-dyn2026
Accurate wetting dynamics via a conservative Allen-Cahn based lattice Boltzmann approach for multiphase flows
Paolo Bello, Luca Mander, Marco Lauricella +3
In this work we propose a local geometric wetting boundary condition for a conservative Allen--Cahn-based lattice Boltzmann framework. The prescribed contact angle is imposed throu…
physics.comp-ph2025
Physics-Informed Neural Networks for microflows: Rarefied Gas Dynamics in Cylinder Arrays
Jean-Michel Tucny, Marco Lauricella, Mihir Durve +3
Accurate prediction of rarefied gas dynamics is crucial for optimizing flows through microelectromechanical systems, air filtration devices, and shale gas extraction. Traditional m…
cs.LG2024
Can physical information aid the generalization ability of Neural Networks for hydraulic modeling?
Gianmarco Guglielmo, Andrea Montessori, Jean-Michel Tucny +2
Application of Neural Networks to river hydraulics is fledgling, despite the field suffering from data scarcity, a challenge for machine learning techniques. Consequently, many pur…