2 citations · 3 across the 8 of their papers we have counts for
3 papers · 1 filter
Discovery of Sparse Invariant Subgrid-Scale Closures via Dissipation-Controlled Training for Large Eddy Simulation on Anisotropic Grids
Samantha Friess, Aviral Prakash, John A. Evans
Neural networks offer highly expressive turbulence closures, yet their complexity obscures the physical mechanisms they aim to model, and their computational cost can limit their t…
SNF-ROM: Projection-based nonlinear reduced order modeling with smooth neural fields
Vedant Puri, Aviral Prakash, Levent Burak Kara +1
Reduced order modeling lowers the computational cost of solving PDEs by learning a low-order spatial representation from data and dynamically evolving these representations using m…
Projection-based reduced order modeling and data-driven artificial viscosity closures for incompressible fluid flows
Aviral Prakash, Yongjie Jessica Zhang
Projection-based reduced order models rely on offline-online model decomposition, where the data-based energetic spatial basis is used in the expensive offline stage to obtain equa…