3 citations · 4 across the 5 of their papers we have counts for
3 papers · 1 filter
Physics-Based Machine Learning Closures and Wall Models for Hypersonic Transition-Continuum Boundary Layer Predictions
Ashish S. Nair, Narendra Singh, Marco Panesi +2
Modeling rarefied hypersonic flows remains a fundamental challenge due to the breakdown of classical continuum assumptions in the transition-continuum regime, where the Knudsen num…
Understanding Latent Timescales in Neural Ordinary Differential Equation Models for Advection-Dominated Dynamical Systems
Ashish S. Nair, Shivam Barwey, Pinaki Pal +3
The neural ordinary differential equation (ODE) framework has emerged as a powerful tool for developing accelerated surrogate models of complex physical systems governed by partial…
Deep Learning Closure of the Navier-Stokes Equations for Transition-Continuum Flows
Ashish S. Nair, Justin Sirignano, Marco Panesi +1
The predictive accuracy of the Navier-Stokes equations is known to degrade at the limits of the continuum assumption, thereby necessitating expensive and often highly approximate s…