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
Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
Meeting Spotlight
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
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
Jan 2025
Jul 2024
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Nuclear Science and Engineering
February 2025
Nuclear Technology
Fusion Science and Technology
Latest News
Feinstein Institutes to research novel radiation countermeasure
The Feinstein Institutes for Medical Research, home of the research institutes of New York’s Northwell Health, announced it has received a five-year, $2.9 million grant from the National Institutes of Health to investigate the potential of human ghrelin, a naturally occurring hormone, as a medical countermeasure against radiation-induced gastrointestinal syndrome (GI-ARS).
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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