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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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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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PR: American Nuclear Society welcomes Senate confirmation of Ted Garrish as the DOE’s nuclear energy secretary
Washington, D.C. — The American Nuclear Society (ANS) applauds the U.S. Senate's confirmation of Theodore “Ted” Garrish as Assistant Secretary for Nuclear Energy at the U.S. Department of Energy (DOE).
“On behalf of over 11,000 professionals in the fields of nuclear science and technology, the American Nuclear Society congratulates Mr. Garrish on being confirmed by the Senate to once again lead the DOE Office of Nuclear Energy,” said ANS President H.M. "Hash" Hashemian.
John Pevey, Ondřej Chvála, Sarah Davis, Vladimir Sobes, J. Wes Hines
Nuclear Technology | Volume 206 | Number 4 | April 2020 | Pages 609-619
Technical Paper | doi.org/10.1080/00295450.2019.1664198
Articles are hosted by Taylor and Francis Online.
This paper discusses the design of a fast spectrum subcritical assembly utilizing a genetic algorithm. The facility proposed in this paper would be a flexible platform for expanding the knowledge of fast spectrum neutron cross sections needed for next-generation fast reactor designs. The Fast Neutron Source (FNS) would be composed of both a fast and a thermal region to minimize the amount of uranium fuel and reduce overall material costs while maintaining flexibility for many potential fast neutron cross-section experiments. The FNS would be customizable and interchangeable down to 1 × 1 × 10-in.-volume sections. An optimal core design requires the adjustment of many factors to both reduce the cost and accurately reproduce the spectra of interest during an experiment. A genetic algorithm was developed to optimize this complex design problem while reducing design time and expert judgment. The genetic algorithm was able to vary multiple design factors in an unattended fashion from a random initial population of designs and arrived at a design comparable to an expertly designed assembly.