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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.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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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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Latest News
First astatine-labeled compound shipped in the U.S.
The Department of Energy’s National Isotope Development Center (NIDC) on March 31 announced the successful long-distance shipment in the United States of a biologically active compound labeled with the medical radioisotope astatine-211 (At-211). Because previous shipments have included only the “bare” isotope, the NIDC has described the development as “unleashing medical innovation.”
Akio Yamamoto
Nuclear Technology | Volume 144 | Number 1 | October 2003 | Pages 63-75
Technical Paper | Nuclear Plant Operations and Control | doi.org/10.13182/NT03-A3429
Articles are hosted by Taylor and Francis Online.
In this paper, neural networks are used to predict core characteristics, and the predicted results are used to screen poor loading patterns in order to improve optimization efficiency. The radial peaking factor, cycle length, and maximum burnup through the cycle depletion calculations were evaluated by the neural network, and these core characteristics were used for screening. The screened loading patterns were evaluated by the core calculation code as ordinary in-core optimizations. The calculation results of the test problem indicated that the loading pattern screening using the neural network effectively improves the optimization results. Since the computation time for a cycle depletion calculation with the neural network is quite short, the computation load for the screening is negligible. Since the neural network is periodically retrained using the latest evaluation results of the core calculation code, its prediction accuracy is continuously improved during the optimization. The typical prediction accuracies of the radial peaking factor, cycle length, and maximum burnup in the latter part of the optimizations were 3 to 4%, 0.01 to 0.02 GWd/t, and 0.2 GWd/t, respectively, in the test problem. These accuracies are satisfactory for loading pattern screening.