10 citations · 21 across the 4 of their papers we have counts for
4 papers
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…
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…
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…
Simulation of Atlantic Hurricane Tracks and Features: A Deep Learning Approach
Rikhi Bose, Adam L. Pintar, Emil Simiu
The objective of this paper is to employ machine learning (ML) and deep learning (DL) techniques to obtain from input data (storm features) available in or derived from the HURDAT2…