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Division Spotlight
Education, Training & Workforce Development
The Education, Training & Workforce Development Division provides communication among the academic, industrial, and governmental communities through the exchange of views and information on matters related to education, training and workforce development in nuclear and radiological science, engineering, and technology. Industry leaders, education and training professionals, and interested students work together through Society-sponsored meetings and publications, to enrich their professional development, to educate the general public, and to advance nuclear and radiological science and engineering.
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
Jun 2025
Jan 2025
Latest Journal Issues
Nuclear Science and Engineering
July 2025
Nuclear Technology
Fusion Science and Technology
Latest News
Smarter waste strategies: Helping deliver on the promise of advanced nuclear
At COP28, held in Dubai in 2023, a clear consensus emerged: Nuclear energy must be a cornerstone of the global clean energy transition. With electricity demand projected to soar as we decarbonize not just power but also industry, transport, and heat, the case for new nuclear is compelling. More than 20 countries committed to tripling global nuclear capacity by 2050. In the United States alone, the Department of Energy forecasts that the country’s current nuclear capacity could more than triple, adding 200 GW of new nuclear to the existing 95 GW by mid-century.
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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