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Meeting Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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!
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Nuclear Science and Engineering
August 2025
Nuclear Technology
Fusion Science and Technology
July 2025
Latest News
The U.S. Million Person Study of Low-Dose-Rate Health Effects
There is a critical knowledge gap regarding the health consequences of exposure to radiation received gradually over time. While there is a plethora of studies on the risks of adverse outcomes from both acute and high-dose exposures, including the landmark study of atomic bomb survivors, these are not characteristic of the chronic exposure to low-dose radiation encountered in occupational and public settings. In addition, smaller cohorts have limited numbers leading to reduced statistical power.
Technical Session|Special Topics
Tuesday, August 22, 2023|9:00–10:20AM EDT|Columbia 5-8
Session Chair:
Han Bao
Alternate Chair:
Majdi I. Radaideh
Session Organizer:
Kurshad Muftuoglu
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Machine-Learning-Aided Approach for Predicting the Thermal Expansion Behaviors in Advanced Test Reactor Capsules
9:00–9:20AM EDT
Takanori Kajihara (INL), Han Bao (INL), Nicolas E. Woolstenhulme (INL), Colby B. Jensen (INL), Daniel B. Chapman (INL), Sunming Qin (INL), Austin D. Fleming (INL)
Paper
Investigation of Machine Learning Regression Techniques to Predict Critical Heat Flux over a Large Parameter Space
9:20–9:40AM EDT
Emil Helmryd Grosfilley (Uppsala Univ.), Gustav Robertson (Uppsala Univ.), Jerol Soibam (Mälardalen Univ.), Jean-Marie Le Corre (Westinghouse Electric Sweden)
Using Machine Learning to Assess Spill Fire Data for use in Fire PRA
9:40–10:00AM EDT
Elvan Sahin (Virginia Tech), Mehran Islam (Virginia Tech), Brian Y. Lattimer (Virginia Tech), Juliana P. Duarte (Univ. Wisconsin, Madison)
Machine Learning from LES Data to Improve Coarse Grid RANS Simulations
10:00–10:20AM EDT
Arsen S. Iskhakov (NCSU), Taylor Grubbs (NCSU), Nam T. Dinh (NCSU), Victor Coppo Leite (Penn State), Elia Merzari (Penn State)
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