35 citations · 122 across the 17 of their papers we have counts for
5 papers · 1 filter
SciAI4Industry -- Solving PDEs for industry-scale problems with deep learning
Philipp A. Witte, Russell J. Hewett, Kumar Saurabh +2
Solving partial differential equations with deep learning makes it possible to reduce simulation times by multiple orders of magnitude and unlock scientific methods that typically…
Neural PDE Solvers for Irregular Domains
Biswajit Khara, Ethan Herron, Zhanhong Jiang +8
Neural network-based approaches for solving partial differential equations (PDEs) have recently received special attention. However, the large majority of neural PDE solvers only a…
Breakup dynamics in primary jet atomization using mesh- and interface- refined Cahn-Hilliard Navier-Stokes
Makrand A. Khanwale, Kumar Saurabh, Masado Ishii +2
We present a technique to perform interface-resolved simulations of complex breakup dynamics in two-phase flows using the Cahn-Hilliard Navier-Stokes equations. The method dynamica…
CyRSoXS: A GPU-accelerated virtual instrument for Polarized Resonant Soft X-ray Scattering (P-RSoXS)
Kumar Saurabh, Peter J. Dudenas, Eliot Gann +9
Polarized Resonant Soft X-ray scattering (P-RSoXS) has emerged as a powerful synchrotron-based tool that combines principles of X-ray scattering and X-ray spectroscopy. P-RSoXS pro…
Scalable adaptive algorithms for next-generation multiphase flow simulations
Kumar Saurabh, Masado Ishii, Makrand A. Khanwale +2
High-fidelity flow simulations are indispensable when analyzing systems exhibiting multiphase flow phenomena. The accuracy of multiphase flow simulations is strongly contingent upo…