106 citations · 165 across the 3 of their papers we have counts for
3 papers
physics.flu-dyn2021★ 59 cited
Three-dimensional deep learning-based reduced order model for unsteady flow dynamics with variable Reynolds number
Rachit Gupta, Rajeev Jaiman
We present a deep learning-based reduced order model (DL-ROM) for predicting the fluid forces and unsteady vortex patterns. We consider flow past a sphere to examine the accuracy o…
physics.flu-dyn2021
A hybrid partitioned deep learning methodology for moving interface and fluid-structure interaction
Rachit Gupta, Rajeev Kumar Jaiman
We present a hybrid partitioned deep learning framework for the reduced-order modeling of fluid-structure interaction. Using the discretized Navier-Stokes in the arbitrary Lagrangi…
physics.flu-dyn2020★ 106 cited
Assessment of unsteady flow predictions using hybrid deep learning based reduced order models
Sandeep Reddy Bukka, Rachit Gupta, Allan Ross Magee +1
In this paper, we present two deep learning-based hybrid data-driven reduced order models for the prediction of unsteady fluid flows. The first model projects the high-fidelity tim…