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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!
Latest Magazine Issues
Aug 2025
Jan 2025
Latest Journal Issues
Nuclear Science and Engineering
September 2025
Nuclear Technology
Fusion Science and Technology
August 2025
Latest News
Faster fusion with AI?
The article “Finding the shadows in a fusion system faster with AI,” published by the Department of Energy’s Princeton Plasma Physics Laboratory, details the public-private partnership among PPPL, Commonwealth Fusion Systems, and Oak Ridge National Laboratory. The partnership has led to a new artificial intelligence approach that is faster at finding what’s known as “magnetic shadows” in a fusion vessel: “safe havens protected from the intense heat of the plasma.”
Technical Session
Wednesday, May 18, 2022|1:30–3:15PM EDT|Pointview
Session Chair:
Benjamin S. Collins (U. of Texas)
Alternate Chair:
Benoit Forget (MIT)
Session Organizer:
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Predicting the Asymptotic State of Reactor Transients Using Supervised Learning
H. Tohver (Univ. Tartu), R. de Oliveira (National Institute of Chemical Physics and Biophysics), J. Pata (National Institute of Chemical Physics and Biophysics), M. Jeltsov (National Institute of Chemical Physics and Biophysics)
Paper
Evolution of Fuel Cycle Reload Safety Analysis with Machine Learning -- Illustration on the Rod Ejection Accident
R. Spaggiari (Framatome), M. Segond (Framatome), L. Lefebvre (Framatome)
Using Physics-Informed Neural Networks to Solve a System of Coupled Nonlinear ODEs for a Reactivity Insertion Accident
Alexandra Akins (NCSU), Xu Wu (NCSU)
Improving the Predictivity of a Steam Generator Clogging Numerical Model by Global Sensitivity Analysis and Bayesian Calibration Techniques
L. Lefebvre (Framatome), M. Segond (Framatome), R. Spaggiari (Framatome), L. Le Gratiet (EDF), E. Deri (EDF), B. Iooss (EDF), G. Damblin (CEA)
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