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Division Spotlight
Accelerator Applications
The division was organized to promote the advancement of knowledge of the use of particle accelerator technologies for nuclear and other applications. It focuses on production of neutrons and other particles, utilization of these particles for scientific or industrial purposes, such as the production or destruction of radionuclides significant to energy, medicine, defense or other endeavors, as well as imaging and diagnostics.
Meeting Spotlight
2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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
May 2024
Nuclear Technology
Fusion Science and Technology
Latest News
College students help develop waste-measuring device at Hanford
A partnership between Washington River Protection Solutions (WRPS) and Washington State University has resulted in the development of a device to measure radioactive and chemical tank waste at the Hanford Site. WRPS is the contractor at Hanford for the Department of Energy’s Office of Environmental Management.
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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