activity
20192022
most citedOn closures for reduced order models A spectrum of first-principle to machine-learned avenues

147 citations · 396 across the 9 of their papers we have counts for

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12 papers · 1 filter

physics.comp-ph2022

Hyperparameter Search using Genetic Algorithm for Surrogate Modeling of Geophysical Flows

Suraj Pawar, Omer San, Gary G. Yen

The computational models for geophysical flows are computationally very expensive to employ in multi-query tasks such as data assimilation, uncertainty quantification, and hence su…

physics.comp-ph2021

A nonintrusive hybrid neural-physics modeling of incomplete dynamical systems: Lorenz equations

Suraj Pawar, Omer San, Adil Rasheed +1

This work presents a hybrid modeling approach to data-driven learning and representation of unknown physical processes and closure parameterizations. These hybrid models are suitab…

physics.comp-ph2021

Hybrid analysis and modeling for next generation of digital twins

Suraj Pawar, Shady E. Ahmed, Omer San +1

The physics-based modeling has been the workhorse for many decades in many scientific and engineering applications ranging from wind power, weather forecasting, and aircraft design…

physics.comp-ph2020

Distributed deep reinforcement learning for simulation control

Suraj Pawar, Romit Maulik

Several applications in the scientific simulation of physical systems can be formulated as control/optimization problems. The computational models for such systems generally contai…

physics.comp-ph2020

Interface learning in fluid dynamics: statistical inference of closures within micro-macro coupling models

Suraj Pawar, Shady E. Ahmed, Omer San

Many complex multiphysics systems in fluid dynamics involve using solvers with varied levels of approximations in different regions of the computational domain to resolve multiple…

physics.comp-ph2020

A nudged hybrid analysis and modeling approach for realtime wake-vortex transport and decay prediction

Shady Ahmed, Suraj Pawar, Omer San +2

We put forth a long short-term memory (LSTM) nudging framework for the enhancement of reduced order models (ROMs) of fluid flows utilizing noisy measurements for air traffic improv…