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Division Spotlight
Fusion Energy
This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
Meeting Spotlight
2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott Downtown
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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Jun 2025
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Nuclear Science and Engineering
July 2025
Nuclear Technology
Fusion Science and Technology
Latest News
Smarter waste strategies: Helping deliver on the promise of advanced nuclear
At COP28, held in Dubai in 2023, a clear consensus emerged: Nuclear energy must be a cornerstone of the global clean energy transition. With electricity demand projected to soar as we decarbonize not just power but also industry, transport, and heat, the case for new nuclear is compelling. More than 20 countries committed to tripling global nuclear capacity by 2050. In the United States alone, the Department of Energy forecasts that the country’s current nuclear capacity could more than triple, adding 200 GW of new nuclear to the existing 95 GW by mid-century.
Technical Session
Wednesday, May 18, 2022|3:30–5:15PM EDT|Pointview
Session Chair:
Benjamin S. Collins (U. of Texas)
Alternate Chair:
Benoit Forget (MIT)
Session Organizer:
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RAST-AI: A Standalone Nodal Diffusion/Deep Neural Network Code for Reactor Analysis and Simulation
Siarhei Dzianisau (Ulsan Nat'l Institute of Science and Technology), Fathurrahman Setiawan (Ulsan Nat'l Institute of Science and Technology), Korawit Saeju (Ulsan Nat'l Institute of Science and Technology), Jinsu Park (Ulsan Nat'l Institute of Science and Technology), Deokjung Lee (Ulsan Nat'l Institute of Science and Technology)
Paper
Using Neural Networks to Predict Pin Powers in Reflective PWR Fuel Assemblies with Varying Pin Size
Aidan Furlong (Univ. Florida), Forrest Shriver (Sentinel Devices), Justin Watson (Univ. Florida)
Prediction of Nuclear Reactor Core Parameters Using Artificial Neural Network
Wojciech Kubinski (National Centre for Nuclear Research), Piotr Darnowski (Warsaw Univ. Technology), Krzysztof Palmi (Warsaw Univ. Technology)
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