62 citations · 123 across the 5 of their papers we have counts for
8 papers
Reduced order modeling of fluid flows: Machine learning, Kolmogorov barrier, closure modeling, and partitioning
Shady Ahmed, Suraj Pawar, Omer San +1
In this paper, 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. We bui…
Long short-term memory embedded nudging schemes for nonlinear data assimilation of geophysical flows
Suraj Pawar, Shady E. Ahmed, Omer San +2
Reduced rank nonlinear filters are increasingly utilized in data assimilation of geophysical flows, but often require a set of ensemble forward simulations to estimate forecast cov…
A long short-term memory embedding for hybrid uplifted reduced order models
Shady E. Ahmed, Omer San, Adil Rasheed +1
In this paper, we introduce an uplifted reduced order modeling (UROM) approach through the integration of standard projection based methods with long short-term memory (LSTM) embed…
An evolve-then-correct reduced order model for hidden fluid dynamics
Suraj Pawar, Shady E. Ahmed, O. San +1
In this paper, we put forth an evolve-then-correct reduced order modeling approach that combines intrusive and nonintrusive models to take hidden physical processes into account. S…
Data-driven recovery of hidden physics in reduced order modeling of fluid flows
Suraj Pawar, Shady E. Ahmed, Omer San +1
In this article, we introduce a modular hybrid analysis and modeling (HAM) approach to account for hidden physics in reduced order modeling (ROM) of parameterized systems relevant…
Sampling and resolution characteristics in reduced order models of shallow water equations: intrusive vs non-intrusive
Shady E. Ahmed, Omer San, Diana A. Bistrian +1
We investigate the sensitivity of reduced order models (ROMs) to training data resolution as well as sampling rate. In particular, we consider proper orthogonal decomposition (POD)…