2 citations · 4 across the 11 of their papers we have counts for
4 papers · 1 filter
Train Small, Model Big: Scalable Physics Simulators via Reduced Order Modeling and Domain Decomposition
Seung Whan Chung, Youngsoo Choi, Pratanu Roy +7
Numerous cutting-edge scientific technologies originate at the laboratory scale, but transitioning them to practical industry applications is a formidable challenge. Traditional pi…
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…
Accelerating Flow Simulations using Online Dynamic Mode Decomposition
Seung Won Suh, Seung Whan Chung, Peer-Timo Bremer +1
We develop an on-the-fly reduced-order model (ROM) integrated with a flow simulation, gradually replacing a corresponding full-order model (FOM) of a physics solver. Unlike offline…
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,…