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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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Latest News
DOE on track to deliver high-burnup SNF to Idaho by 2027
The Department of Energy said it anticipated delivering a research cask of high-burnup spent nuclear fuel from Dominion Energy’s North Anna nuclear power plant in Virginia to Idaho National Laboratory by fall 2027. The planned shipment is part of the High Burnup Dry Storage Research Project being conducted by the DOE with the Electric Power Research Institute.
As preparations continue, the DOE said it is working closely with federal agencies as well as tribal and state governments along potential transportation routes to ensure safety, transparency, and readiness every step of the way.
Watch the DOE’s latest video outlining the project here.
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.