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Division Spotlight
Young Members Group
The Young Members Group works to encourage and enable all young professional members to be actively involved in the efforts and endeavors of the Society at all levels (Professional Divisions, ANS Governance, Local Sections, etc.) as they transition from the role of a student to the role of a professional. It sponsors non-technical workshops and meetings that provide professional development and networking opportunities for young professionals, collaborates with other Divisions and Groups in developing technical and non-technical content for topical and national meetings, encourages its members to participate in the activities of the Groups and Divisions that are closely related to their professional interests as well as in their local sections, introduces young members to the rules and governance structure of the Society, and nominates young professionals for awards and leadership opportunities available to members.
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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Dec 2024
Jul 2024
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Nuclear Science and Engineering
January 2025
Nuclear Technology
Fusion Science and Technology
Latest News
Christmas Night
Twas the night before Christmas when all through the houseNo electrons were flowing through even my mouse.
All devices were plugged in by the chimney with careWith the hope that St. Nikola Tesla would share.
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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