34 citations · 79 across the 18 of their papers we have counts for
4 papers · 1 filter
Data-Driven Autoencoder Numerical Solver with Uncertainty Quantification for Fast Physical Simulations
Christophe Bonneville, Youngsoo Choi, Debojyoti Ghosh +1
Traditional partial differential equation (PDE) solvers can be computationally expensive, which motivates the development of faster methods, such as reduced-order-models (ROMs). We…
Reducing Richtmyer Meshkov Instability Jet Velocity via Inverse Design
Dylan J. Kline, Michael P. Hennessey, David K. Amondson +8
In this work, we detail a novel application of inverse design and advanced manufacturing to rapidly develop and experimentally validate modifications to a shaped charge jet analogu…
Local Reduced-Order Modeling for Electrostatic Plasmas by Physics-Informed Solution Manifold Decomposition
Ping-Hsuan Tsai, Seung Whan Chung, Debojyoti Ghosh +3
Despite advancements in high-performance computing and modern numerical algorithms, computational cost remains prohibitive for multi-query kinetic plasma simulations. In this work,…
GPLaSDI: Gaussian Process-based Interpretable Latent Space Dynamics Identification through Deep Autoencoder
Christophe Bonneville, Youngsoo Choi, Debojyoti Ghosh +1
Numerically solving partial differential equations (PDEs) can be challenging and computationally expensive. This has led to the development of reduced-order models (ROMs) that are…