activity
20182021
most citedConvective, absolute and global azimuthal magnetorotational instabilities

8 citations · 11 across the 2 of their papers we have counts for

collaborators

5 papers

physics.flu-dyn20218 cited

Convective, absolute and global azimuthal magnetorotational instabilities

A. Mishra, G. Mamatsashvili, V. Galindo +1

We study the convective and absolute forms of azimuthal magnetorotational instability (AMRI) in a Taylor-Couette (TC) flow with an imposed azimuthal magnetic field. We show that th…

physics.acc-ph20213 cited

Improving Surrogate Model Accuracy for the LCLS-II Injector Frontend Using Convolutional Neural Networks and Transfer Learning

Lipi Gupta, Auralee Edelen, Nicole Neveu +3

Machine learning models of accelerator systems (`surrogate models') are able to provide fast, accurate predictions of accelerator physics phenomena. However, approaches to date typ…

physics.flu-dyn2021

Interpretable Data-driven Methods for Subgrid-scale Closure in LES for Transcritical LOX/GCH4 Combustion

Wai Tong Chung, Aashwin Ananda Mishra, Matthias Ihme

Many practical combustion systems such as those in rockets, gas turbines, and internal combustion engines operate under high pressures that surpass the thermodynamic critical limit…

physics.flu-dyn2020

Data-assisted combustion simulations with dynamic submodel assignment using random forests

Wai Tong Chung, Aashwin Ananda Mishra, Nikolaos Perakis +1

In this investigation, we outline a data-assisted approach that employs random forest classifiers for local and dynamic combustion submodel assignment in turbulent-combustion simul…

physics.flu-dyn2018

An uncertainty estimation module for turbulence model predictions in SU2

Aashwin Ananda Mishra, Jayant Mukhopadhaya, Gianluca Iaccarino +1

With the advent of improved computational resources, aerospace design has testing-based process to a simulation-driven procedure, wherein uncertainties in design and operating cond…