294 citations · 2.9k across the 83 of their papers we have counts for
6 papers · 1 filter
Data-driven deconvolution for large eddy simulations of Kraichnan turbulence
Romit Maulik, Omer San, Adil Rasheed +1
In this article, we demonstrate the use of artificial neural networks as optimal maps which are utilized for convolution and deconvolution of coarse-grained fields to account for s…
Sub-grid scale model classification and blending through deep learning
Romit Maulik, Omer San, Jamey D. Jacob +1
In this article we detail the use of machine learning for spatiotemporally dynamic turbulence model classification and hybridization for the large eddy simulations (LES) of turbule…
A localized dynamic closure model for Euler turbulence
Sk. Mashfiqur Rahman, Omer San
In this work, we present a localized form of the dynamic eddy viscosity model for computationally efficient and accurate simulation of the turbulent flows governed by Euler equatio…
Sub-grid modelling for two-dimensional turbulence using neural networks
Romit Maulik, Omer San, Adil Rasheed +1
In this investigation, a data-driven turbulence closure framework is introduced and deployed for the sub-grid modelling of Kraichnan turbulence. The novelty of the proposed method…
Extreme learning machine for reduced order modeling of turbulent geophysical flows
Omer San, Romit Maulik
We investigate the application of artificial neural networks to stabilize proper orthogonal decomposition based reduced order models for quasi-stationary geophysical turbulent flow…
An artificial neural network framework for reduced order modeling of transient flows
Omer San, Romit Maulik, Mansoor Ahmed
This paper proposes a supervised machine learning framework for the non-intrusive model order reduction of unsteady fluid flows to provide accurate predictions of non-stationary st…