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Division Spotlight
Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
Meeting Spotlight
2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott Downtown
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
Latest Magazine Issues
May 2025
Jan 2025
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Nuclear Science and Engineering
June 2025
Nuclear Technology
Fusion Science and Technology
Latest News
Beyond conventional boundaries: Innovative construction technologies pave the way for advanced reactor deployment
In a bid to tackle the primary obstacle in nuclear deployment—construction costs—those in industry and government are moving away from traditional methods and embracing innovative construction technologies.
Technical Session|Sponsored by THD
Tuesday, June 17, 2025|1:00–2:45PM CDT|Chicago Ballroom B
Session Chair:
Subash L. Sharma
Session Organizer:
Alternate Chair:
Xu Wu
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A Machine Learning Approach for Calculating Drift Velocity in Two-Phase Flow
1:00–1:20PM CDT
Tristan R. Villarreal (Univ. Texas, Austin), Ethan Rozak (Univ. Texas, Austin), Cole Gentry (Univ. Texas, Austin), Benjamin Collins (Univ. Texas, Austin), Kevin Clarno (Univ. Texas, Austin)
Paper
Advancing Nuclear R&D with Large Language Models: Case Studies in Thermal Hydraulics, Simulation Workflows, and Education
1:20–1:40PM CDT
Yang Liu (TAMU), Zavier Ndum (TAMU), Abhiram Garimidi (TAMU), Zaid Abulawi (TAMU), Doyeong Lim (TAMU)
Deep Learning based Accident Classification Method for Condition Monitoring of Heat Pipe Cooled Microreactors
1:40–2:00PM CDT
Ik Jae Jin (Ulsan Nat'l Institute Science and Technology), In Cheol Bang (Ulsan Nat'l Institute 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 (Univ. Tennessee, Knoxville), Robert K. Salko (ORNL), Xingang Zhao (Univ. Tennessee, Knoxville)
Developing Reduced-Order Models with Machine Learning for Gas Flow in Pebble Bed Reactors
2:20–2:40PM CDT
DEZHI DAI (ANL), Haoyu Wang (ANL), Haomin Yuan (ANL)
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