10 citations · 23 across the 7 of their papers we have counts for
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physics.flu-dyn2023
Mixed mode transition in boundary layers: Helical instability
Rikhi Bose, Paul A. Durbin
Recent (Bose \& Durbin, \textit{Phys. Rev. Fluids}, 1, 073602, 2016) direct numerical simulations (DNS) of adverse- and zero-pressure-gradient boundary layers beneath moderate leve…
physics.flu-dyn2023★ 10 cited
Accurate deep learning sub-grid scale models for large eddy simulations
Rikhi Bose, Arunabha M. Roy
We present two families of sub-grid scale (SGS) turbulence models developed for large-eddy simulation (LES) purposes. Their development required the formulation of physics-informed…
cs.LG2023★ 9 cited
Physics-aware deep learning framework for linear elasticity
Arunabha M. Roy, Rikhi Bose
The paper presents an efficient and robust data-driven deep learning (DL) computational framework developed for linear continuum elasticity problems. The methodology is based on th…