most citedMemory embedded non-intrusive reduced order modeling of non-ergodic flows

57 citations · 57 across the 2 of their papers we have counts for

collaborators

5 papers

physics.flu-dyn201957 cited

Memory embedded non-intrusive reduced order modeling of non-ergodic flows

Shady E. Ahmed, Sk. Mashfiqur Rahman, Omer San +2

Generating a digital twin of any complex system requires modeling and computational approaches that are efficient, accurate, and modular. Traditional reduced order modeling techniq…

physics.comp-ph2019

A deep learning enabler for non-intrusive reduced order modeling of fluid flows

S. Pawar, S. M. Rahman, H. Vaddireddy +3

In this paper, we introduce a modular deep neural network (DNN) framework for data-driven reduced order modeling of dynamical systems relevant to fluid flows. We propose various de…

cs.CE2019

A non-intrusive reduced order modeling framework for quasi-geostrophic turbulence

Sk. Mashfiqur Rahman, Suraj Pawar, Omer San +2

In this study, we present a non-intrusive reduced order modeling (ROM) framework for large-scale quasi-stationary systems. The framework proposed herein exploits the time series pr…

physics.flu-dyn2019

A dynamic closure modeling framework for model order reduction of geophysical flows

Sk. Mashfiqur Rahman, Shady E. Ahmed, Omer San

In this paper, a dynamic closure modeling approach has been derived to stabilize the projection-based reduced order models in the long-term evolution of forced-dissipative dynamica…

physics.flu-dyn2018

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…