activity
20112023
most citedSub-grid modelling for two-dimensional turbulence using neural networks

294 citations · 2.9k across the 83 of their papers we have counts for

collaborators

84 papers

cs.CV2023★ 6 cited

SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning

Pu Ren, N. Benjamin Erichson, Junyi Guo +4

Super-resolution (SR) techniques aim to enhance data resolution, enabling the retrieval of finer details, and improving the overall quality and fidelity of the data representation.…

physics.flu-dyn2023

Accelerated evolution of Burgers turbulence with coarse projective integration and deep learning

Mrigank Dhingra, Omer San, Anne E. Staples

Simulating turbulence to stationarity is a major bottleneck in many engineering problems of practical importance. The problem can be cast as a multiscale problem involving energy r…

math.OC2023

On the dual advantage of placing observations through forward sensitivity analysis

Shady E Ahmed, Omer San, Sivaramakrishnan Lakshmivarahan +1

The four-dimensional variational data assimilation methodology for assimilating noisy observations into a deterministic model has been the workhorse of forecasting centers for over…

physics.flu-dyn2023

Forward Sensitivity Analysis and Mode Dependent Control for Closure Modeling of Galerkin Systems

Shady E. Ahmed, Omer San

Model reduction by projection-based approaches is often associated with losing some of the important features that contribute towards the dynamics of the retained scales. As a resu…

cs.HC2023★ 95 cited

Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions

Florian Stadtman, Adil Rasheed, Trond Kvamsdal +21

This article presents a comprehensive overview of the digital twin technology and its capability levels, with a specific focus on its applications in the wind energy industry. It c…

physics.flu-dyn2022★ 1 cited

Nonintrusive reduced order modeling of convective Boussinesq flows

Pedram H. Dabaghian, Shady E. Ahmed, Omer San

In this paper, we formulate three nonintrusive methods and systematically explore their performance in terms of the ability to reconstruct the quantities of interest and their pred…