most citedUsing recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models

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physics.flu-dyn2020

Reduced-order modeling of advection-dominated systems with recurrent neural networks and convolutional autoencoders

Romit Maulik, Bethany Lusch, Prasanna Balaprakash

A common strategy for the dimensionality reduction of nonlinear partial differential equations relies on the use of the proper orthogonal decomposition (POD) to identify a reduced…

physics.flu-dyn2019

A turbulent eddy-viscosity surrogate modeling framework for Reynolds-Averaged Navier-Stokes simulations

Romit Maulik, Himanshu Sharma, Saumil Patel +2

The Reynolds-averaged Navier-Stokes (RANS) equations for steady-state assessment of incompressible turbulent flows remain the workhorse for practical computational fluid dynamics (…