23 citations · 31 across the 5 of their papers we have counts for
6 papers
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…
Continuous latent representations for modeling precipitation with deep learning
Gokul Radhakrishnan, Rahul Sundar, Nishant Parashar +3
The sparse and spatio-temporally discontinuous nature of precipitation data presents significant challenges for simulation and statistical processing for bias correction and downsc…
TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models
Rahul Sundar, Yucong Hu, Nishant Parashar +2
Deterministic regression-based downscaling models for climate variables often suffer from spectral bias, which can be mitigated by generative models like diffusion models. To enabl…
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…
Massive parallelization and performance enhancement of an immersed boundary method based unsteady flow solver
Rahul Sundar, Dipanjan Majumdar, Chhote Lal Shah +1
High-fidelity simulations of unsteady fluid flow are now possible with advancements in high-performance computing hardware and software frameworks. Since computational fluid dynami…
Physics-informed neural networks modeling for systems with moving immersed boundaries: application to an unsteady flow past a plunging foil
Rahul Sundar, Dipanjan Majumdar, Didier Lucor +1
Recently, physics informed neural networks (PINNs) have been explored extensively for solving various forward and inverse problems and facilitating querying applications in fluid m…