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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.
Ruixian Fang, Dan G. Cacuci (Univ of South Carolina)
Proceedings | 2018 International Congress on Advances in Nuclear Power Plants (ICAPP 2018) | Charlotte, NC, April 8-11, 2018 | Pages 451-459
The “predictive modeling for coupled multi-physics systems (PM_CMPS)” methodology is applied in this work to the numerical simulation model of the mechanical draft cooling tower (MDCT) located in the F-area at Savannah River National Laboratory (SRNL) in order to improve the predictions of this model by combining computational information with measurements of outlet air humidity, outlet air and outlet water temperatures. At the outlet of this cooling tower, where measurements of the quantities of interest are available, the PM_CMPS reduces the predicted uncertainties for these quantities to values that are smaller than either the computed or the measured uncertainties. The PM_CMPS has also been applied to reduce the uncertainties for quantities of interest inside the tower’s fill section, where no direct measurements are available. The maximum reductions of uncertainties occur at the locations where direct measurements are available. At other locations, the predicted response uncertainties are reduced by the PM_CMPS methodology to values that are smaller than the modeling uncertainties arising from the imprecisely known model parameters.