Understanding the training of PINNs for unsteady flow past a plunging foil through the lens of input subdomain level loss function gradients

no code implementations • 27 Feb 2024 • Rahul Sundar, Didier Lucor, Sunetra Sarkar

To quantify which spatial zone drives the training, two novel metrics are computed from the zonal loss component gradient statistics and the proportion of sample points in each zone.

Physics-informed neural networks modeling for systems with moving immersed boundaries: application to an unsteady flow past a plunging foil

no code implementations • 23 Jun 2023 • Rahul Sundar, Dipanjan Majumdar, Didier Lucor, Sunetra Sarkar

Hence, in the present work, an immersed boundary aware framework has been explored for developing surrogate models for unsteady flows past moving bodies.