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Conference Spotlight
2026 Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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
Dec 2025
Jul 2025
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Nuclear Science and Engineering
January 2026
Nuclear Technology
December 2025
Fusion Science and Technology
November 2025
Latest News
What’s the most difficult question you’ve been asked as a maintenance instructor?
Blye Widmar
"Where are the prints?!"
This was the final question in an onslaught of verbal feedback, comments, and critiques I received from my students back in 2019. I had two years of instructor experience and was teaching a class that had been meticulously rehearsed in preparation for an accreditation visit. I knew the training material well and transferred that knowledge effectively enough for all the students to pass the class. As we wrapped up, I asked the students how they felt about my first big system-level class, and they did not hold back.
“Why was the exam from memory when we don’t work from memory in the plant?” “Why didn’t we refer to the vendor documents?” “Why didn’t we practice more on the mock-up?” And so on.
Technical Session
Tuesday, May 17, 2022|3:30–5:15PM EDT|Pointview
Session Chair:
Benoit Forget (MIT)
Session Organizer:
Alternate Chair:
Benjamin S. Collins (U. of Texas)
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Optimization of the Deep Neural Network Parameters for Generating Homogenized Fuel Assembly Data for Nodal Codes
Korawit Saeju (Ulsan Nat'l Institute of Science and Technology), Siarhei Dzianisau (Ulsan Nat'l Institute of Science and Technology), Muhammad Farid Khandaq (Ulsan Nat'l Institute of Science and Technology), Deokjung Lee (Ulsan Nat'l Institute of Science and Technology)
Paper
Genetic Algorithm-Based Optimisation of the Few-Group Structure for Lead Fast Reactors Analysis
M. Massone (Karlsruher Institut for Technologie), N. Abrate (Politecnico di Torino), G.F. Nallo (Politecnico di Torino), S. Dulla (Politecnico di Torino), P. Ravetto (Politecnico di Torino), D. Valerio (Politecnico di Torino)
Quantification of Neural Networks Uncertainties with Applications to SAFARI-1 Axial Neutron Flux Profiles
Lesego E. Moloko (South African Nuclear Energy Corp.), Pavel M. Bokov (South African Nuclear Energy Corp.), Xu Wu (NCSU), Kostadin N. Ivanov (NCSU)
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