Showing physics.flu-dynShow all
2 papers · 1 filter
physics.flu-dyn2025
Sequential learning based PINNs to overcome temporal domain complexities in unsteady flow past flapping wings
Rahul Sundar, Didier Lucor, Sunetra Sarkar
For a data-driven and physics combined modelling of unsteady flow systems with moving immersed boundaries, Sundar {\it et al.} introduced an immersed boundary-aware (IBA) framework…
physics.flu-dyn2024
Understanding the training of PINNs for unsteady flow past a plunging foil through the lens of input subdomain level loss function gradients
Rahul Sundar, Didier Lucor, Sunetra Sarkar
Recently immersed boundary method-inspired physics-informed neural networks (PINNs) including the moving boundary-enabled PINNs (MB-PINNs) have shown the ability to accurately reco…