1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2026
High-fidelity Modeling of Full-scale Pressurized Water Reactor Flow Fields for Machine Learning Applications
Logan A. Burnett, Hyungjun Kim, Hsien-Cheng Chou +5
This work presents a high-fidelity computational fluid dynamics (CFD) and data-driven modeling framework for assembly-level flow characterization in a four-loop pressurized water r…
physics.flu-dyn2023★ 1 cited
Development of a Two-Level ML Spatial-temporal Framework for Industrial Thermal Striping Applications
Yu-Jou Wang, Emilio Baglietto, Koroush Shirvan
A data-driven framework for spatial-temporal prediction is proposed for reducing the computational cost of industrial thermal striping applications. The framework aims to efficient…