2 citations · 6 across the 14 of their papers we have counts for
5 papers · 1 filter
Theory and numerics of subspace approximation of eigenvalue problems
Siu Wun Cheung, Youngsoo Choi, Seung Whan Chung +3
Large-scale eigenvalue problems arise in various fields of science and engineering and demand computationally efficient solutions. In this study, we investigate the subspace approx…
Scalable nonlinear manifold reduced order model for dynamical systems
Ivan Zanardi, Alejandro N. Diaz, Seung Whan Chung +2
The domain decomposition (DD) nonlinear-manifold reduced-order model (NM-ROM) represents a computationally efficient method for integrating underlying physics principles into a neu…
Scalable physics-guided data-driven component model reduction for steady Navier-Stokes flow
Seung Whan Chung, Youngsoo Choi, Pratanu Roy +6
Computational physics simulation can be a powerful tool to accelerate industry deployment of new scientific technologies. However, it must address the challenge of computationally…
Scaled-up prediction of steady Navier-Stokes equation with component reduced order modeling
Seung Whan Chung, Youngsoo Choi, Pratanu Roy +6
Scaling up new scientific technologies from laboratory to industry often involves demonstrating performance on a larger scale. Computer simulations can accelerate design and predic…
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,…