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Conference 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
DOE on track to deliver high-burnup SNF to Idaho by 2027
The Department of Energy said it anticipated delivering a research cask of high-burnup spent nuclear fuel from Dominion Energy’s North Anna nuclear power plant in Virginia to Idaho National Laboratory by fall 2027. The planned shipment is part of the High Burnup Dry Storage Research Project being conducted by the DOE with the Electric Power Research Institute.
As preparations continue, the DOE said it is working closely with federal agencies as well as tribal and state governments along potential transportation routes to ensure safety, transparency, and readiness every step of the way.
Watch the DOE’s latest video outlining the project here.
Advances in Thermal Hydraulics (ATH 2022)
Technical Session
Tuesday, June 14, 2022|10:15AM–12:00PM PDT|Redondo
Session Chair:
Nadish Saini
Alternate Chair:
Yue Jin
Session Organizer:
W. David Pointer
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Embedded Fiber Optic Smart Parts Towards Advanced Reactor Applications
Andrew J. Boulanger (Luna Innovation), S. Derek Rountree (Luna Innovation), Connor Donlan (Virginia Commonwealth Univ.), Arturo Cabral (Virginia Commonwealth Univ.), Lane B. Carasik (Virginia Commonwealth Univ.), Adam Hehr (Fabrisonic)
Paper
Deep Learning-Based System Diagnosis for Nuclear Power Plant Using Infrared Thermal Cameras
Ik Jae Jin (Ulsan Nat'l Institute of Science and Technology), Do Yeong Lim (Ulsan Nat'l Institute of Science and Technology), In Cheol Bang (Ulsan Nat'l Institute of Science and Technology)
Machine Learning-Based Prediction of Departure from Nucleate Boiling Power for the PSBT Benchmark
Chaitee Godbole (NCSU), Gregory Delipei (NCSU), Xu Wu (NCSU), Maria Avramova (NCSU), Upendra Rohatgi (Brookhaven)
Prediction of Minimum Film Boiling Temperature Using a Physics-Informed Machine Learning-Aided Framework
K.M. Kim (Virginia Tech), P. Hurley (Virginia Tech), J.P. Duarte (Virginia Tech)
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