activity
20212024
most citedAccurate deep learning sub-grid scale models for large eddy simulations

10 citations · 23 across the 7 of their papers we have counts for

collaborators

7 papers

physics.flu-dyn2024

Linear instability in thermally-stratified quasi-Keplerian flows

Dongdong Wan, Rikhi Bose, Mengqi Zhang +1

Quasi-Keplerian flow, a special regime of Taylor-Couette co-rotating flow, is of great astrophysical interest for studying angular momentum transport in accretion disks. The well-k…

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…

physics.ao-ph2022★ 2 cited

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…

physics.ao-ph2021

Data-Based Models for Hurricane Evolution Prediction: A Deep Learning Approach

Rikhi Bose, Adam Pintar, Emil Simiu

Fast and accurate prediction of hurricane evolution from genesis onwards is needed to reduce loss of life and enhance community resilience. In this work, a novel model development…

cs.CV2021★ 2 cited

A fast accurate fine-grain object detection model based on YOLOv4 deep neural network

Arunabha M. Roy, Rikhi Bose, Jayabrata Bhaduri

Early identification and prevention of various plant diseases in commercial farms and orchards is a key feature of precision agriculture technology. This paper presents a high-perf…