ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
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Division Spotlight
Isotopes & Radiation
Members are devoted to applying nuclear science and engineering technologies involving isotopes, radiation applications, and associated equipment in scientific research, development, and industrial processes. Their interests lie primarily in education, industrial uses, biology, medicine, and health physics. Division committees include Analytical Applications of Isotopes and Radiation, Biology and Medicine, Radiation Applications, Radiation Sources and Detection, and Thermal Power Sources.
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
X-energy receives federal tax credit for TRISO fuel facility
Advanced reactor company X-energy has been awarded $148.5 million in tax credits under the Inflation Reduction Act for construction of its TRISO-X fuel fabrication facility in Oak Ridge, Tenn.
Technical Session
Tuesday, May 17, 2022|3:30–5:15PM EDT|Pointview
Session Chair:
Benoit Forget (MIT)
Session Organizer:
Alternate Chair:
Benjamin S. Collins (U. of Texas)
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Optimization of the Deep Neural Network Parameters for Generating Homogenized Fuel Assembly Data for Nodal Codes
Korawit Saeju (Ulsan Nat'l Institute of Science and Technology), Siarhei Dzianisau (Ulsan Nat'l Institute of Science and Technology), Muhammad Farid Khandaq (Ulsan Nat'l Institute of Science and Technology), Deokjung Lee (Ulsan Nat'l Institute of Science and Technology)
Paper
Genetic Algorithm-Based Optimisation of the Few-Group Structure for Lead Fast Reactors Analysis
M. Massone (Karlsruher Institut for Technologie), N. Abrate (Politecnico di Torino), G.F. Nallo (Politecnico di Torino), S. Dulla (Politecnico di Torino), P. Ravetto (Politecnico di Torino), D. Valerio (Politecnico di Torino)
Quantification of Neural Networks Uncertainties with Applications to SAFARI-1 Axial Neutron Flux Profiles
Lesego E. Moloko (South African Nuclear Energy Corp.), Pavel M. Bokov (South African Nuclear Energy Corp.), Xu Wu (NCSU), Kostadin N. Ivanov (NCSU)
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