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Division Spotlight
Nuclear Criticality Safety
NCSD provides communication among nuclear criticality safety professionals through the development of standards, the evolution of training methods and materials, the presentation of technical data and procedures, and the creation of specialty publications. In these ways, the division furthers the exchange of technical information on nuclear criticality safety with the ultimate goal of promoting the safe handling of fissionable materials outside reactors.
Meeting Spotlight
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
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
December 2024
Nuclear Technology
Fusion Science and Technology
November 2024
Latest News
OECD NEA offers survey for young people
The OECD Nuclear Energy Agency’s Global Forum on Nuclear Education, Science, Technology, and Policy has developed the Nuclear Workforce Survey to explore how and why individuals decide to join the nuclear field and how their experiences impact decisions to stay or leave.
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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