5 citations · 13 across the 4 of their papers we have counts for
4 papers
The High-Frequency and Rare Events Barriers to Neural Closures of Atmospheric Dynamics
Mickaël D. Chekroun, Honghu Liu, Kaushik Srinivasan +1
Recent years have seen a surge in interest for leveraging neural networks to parameterize small-scale or fast processes in climate and turbulence models. In this short paper, we po…
Turbulence closure with small, local neural networks: Forced two-dimensional and -plane flows
Kaushik Srinivasan, Mickael D. Chekroun, James C. McWilliams
We parameterize sub-grid scale (SGS) fluxes in sinusoidally forced two-dimensional turbulence on the -plane at high Reynolds numbers (Re25000) using simple 2-layer Convolu…
Gaussian processes at the Helm(holtz): A more fluid model for ocean currents
Renato Berlinghieri, Brian L. Trippe, David R. Burt +5
Given sparse observations of buoy velocities, oceanographers are interested in reconstructing ocean currents away from the buoys and identifying divergences in a current vector fie…
On a separation criterion for symmetric elliptic bluff body flows
Kaushik Srinivasan
A new analytical criterion that captures the onset of separation of flow past elliptic cylinders is derived by considering the variation of the wall normal velocity in Reynolds num…