24 citations · 41 across the 15 of their papers we have counts for
4 papers · 1 filter
Validation and parameterization of a novel physics-constrained neural dynamics model applied to turbulent fluid flow
Varun Shankar, Gavin D. Portwood, Arvind T. Mohan +6
In fluid physics, data-driven models to enhance or accelerate solution methods are becoming increasingly popular for many application domains, such as alternatives to turbulence cl…
Improved Methods for Mixing-Limited Spray Modeling
Majid Haghshenas, Peetak P. Mitra, Chu Wang +3
The realization that interfacial features play little role in diesel spray vaporization and advection has changed the modus operandi for spray modeling. Lagrangian particle trackin…
The Eulerian Lagrangian Mixing-Oriented (ELMO) Model
David P. Schmidt, Majid Haghshenas, Peetak P. Mitra +4
Past Lagrangian/Eulerian modeling has served as a poor match for the mixing limited physics present in many sprays. Though these Lagrangian/Eulerian methods are popular for their l…
Network Compression for Machine-Learnt Fluid Simulations
Peetak Mitra, Vaidehi Venkatesan, Nomit Jangid +7
Multi-scale, multi-fidelity numerical simulations form the pillar of scientific applications related to numerically modeling fluids. However, simulating the fluid behavior characte…