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The transformation of the NRC: 50 years of commissioners
The dust is beginning to settle following the whirlwind of changes at the Nuclear Regulatory Commission over the past year, and 2025 ultimately may be viewed as a transformative year, as well as the year the NRC celebrated its golden anniversary. The 12 months of that milestone year brought more change to the agency in its composition, its mandate, and its relationship to the executive branch than any comparable period in the preceding four decades.
Now at 51 years and counting, the NRC is working with a full commission and issuing new rulemakings to both regulate and support the next round of nuclear deployments. With the turbulence of 2025 still fresh in our minds, Nuclear News decided it was a good time to revisit the professional backgrounds of all 42 NRC commissioners who have served over the agency’s 50-year history to see how the composition of the commission has evolved over time.
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.