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Division Spotlight
Education, Training & Workforce Development
The Education, Training & Workforce Development Division provides communication among the academic, industrial, and governmental communities through the exchange of views and information on matters related to education, training and workforce development in nuclear and radiological science, engineering, and technology. Industry leaders, education and training professionals, and interested students work together through Society-sponsored meetings and publications, to enrich their professional development, to educate the general public, and to advance nuclear and radiological science and engineering.
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
Framatome signs contracts with Sizewell C
French nuclear developer Framatome is slated to deliver key equipment for Sizewell C Ltd.’s two large reactors planned for the United Kingdom’s Suffolk coast.
The agreement, reportedly worth multiple billions of euros, was announced this week and will involve Framatome from the design phase until commissioning. The company also agreed to a long-term fuel supply deal. Framatome is 80.5 percent owned by France’s EDF and 19.5 percent owned by Mitsubishi Heavy Industries.
Technical Session|Sponsored by MCD
Wednesday, June 15, 2022|1:00–2:45PM PDT|Avila B
Session Chair:
Madicken Munk (Univ. Illinois, Urbana-Champaign)
Alternate Chair:
Alex Robinson (LLNL)
Session Organizer:
Brian C. Kiedrowski (Univ. Michigan)
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Why is Uncertainty Quantification Hard for Industrial Users?
Graham Macpherson (Frazer-Nash Consultancy), Neil Headings (Frazer-Nash Consultancy)
Paper
Numerical Investigation on the Performance of a Variance Deconvolution Estimator
Kayla Clements (Oregon State ), Gianluca Geraci (Sandia), Aaron Olson (Sandia)
Quantification of Deep Neural Networks Approximation Uncertainties for Transient Simulations
Mahmoud Yaseen (NCSU), Xu Wu (NCSU)
Analysis of Nuclear Research Reactor Experiments Using Machine Learning
Roberto E. Fairhurst-Agosta (Univ. Illinois, Urbana-Champaign), Tomasz Kozlowski (Univ. Illinois, Urbana-Champaign)
Data Augmentation with Generative Adversarial Networks
Farah Alsafadi (NCSU), Xu Wu (NCSU)
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