AI/ML Applications in Thermal Hydraulics

A Machine Learning Approach for Calculating Drift Velocity in Two-Phase Flow

1:00–1:20PM CDT

Tristan R. Villarreal (University of Texas at Austin), Ethan Rozak (University of Texas at Austin), Cole Gentry (University of Texas at Austin), Benjamin Collins (University of Texas at Austin), Kevin Clarno (University of Texas at Austin)

Advancing Nuclear R&D with Large Language Models: Case Studies in Thermal Hydraulics, Simulation Workflows, and Education

1:20–1:40PM CDT

Yang Liu (Texas A&M University), Zavier Ndum (Texas A&M University), Abhiram Garimidi (Texas A&M University), Zaid Abulawi (Texas A&M University), Doyeong Lim (Texas A&M University)

Deep Learning based Accident Classification Method for Condition Monitoring of Heat Pipe Cooled Microreactors

1:40–2:00PM CDT

Ik Jae Jin (Ulsan National Institute of Science and Technology (UNIST)), In Cheol Bang (Ulsan National Institute of Science and Technology)

Physics-Informed Machine Learning for Void Fraction Prediction in Upward and Downward Two-Phase Flows

2:00–2:20PM CDT

davide rotilio (Reactor Physics Division), Jacob Petersen (University of Tennessee Knoxville), Robert K. Salko (Oak Ridge National Laboratory), Xingang Zhao (University of Tennessee Knoxville)

Developing Reduced-Order Models with Machine Learning for Gas Flow in Pebble Bed Reactors

2:20–2:40PM CDT

DEZHI DAI (Argonne National Laboratory), Haoyu Wang (Argonne National Laboratory), Haomin Yuan (Argonne National Laboratory)