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2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Senate EPW Committee to hold Nieh nomination hearing
Nieh
The Senate Environment and Public Works Committee will hold a nomination hearing Wednesday for Ho Nieh, President Donald Trump’s nominee to serve as commission at the Nuclear Regulatory Commission.
Trump nominated Nieh on July 30 to serve as NRC commissioner the remainder of a term that will expire June 30, 2029, as Nuclear NewsWire previously reported.
Nieh has been vice president of regulatory affairs at Southern Nuclear since 2021, though since June 2024 he has been at the Institute of Nuclear Power Operations as a loaned executive.
A return to the NRC: If confirmed by the Senate, Nieh would be returning to the NRC after three previous stints totaling nearly 20 years.
Jan Peter Hessling
Nuclear Science and Engineering | Volume 184 | Number 3 | November 2016 | Pages 388-399
Technical Paper | doi.org/10.13182/NSE16-8
Articles are hosted by Taylor and Francis Online.
For evaluation of the uncertainty of nuclear power calculations, the Wilks approach has the appearance of an ideal tool. A conservatively estimated bound is obtained as the r’th most extreme model result, of a random sample of size determined by r. The methodology is noninvasive and simple and seems efficient and adequate. However, as this paper shows, these attributes come with a high price of large bias and substantial sampling variance. This jeopardizes its utilization as well as lowers its credibility and perceived efficiency. The unfortunate combination of random sampling and faithful estimation may result in a relative sampling uncertainty of the estimated bound(s) of no less than 100%. What is defined as credibility, i.e., the probability that the estimated bound is conservative relative to the true result, is well below the confidence relating the targeted bound(s) to the true result, which for the default application of the Wilks method translates into an expected failure rate of up to 10% (instead of 5%) of estimated bounds. To compensate for this deficit in credibility compared to the chosen level of confidence, adjustments of current practice are proposed. The application to modeling uncertainty is to be clearly distinguished from the original experimental sampling problem addressed by Wilks. Here, more is known but not utilized. A viable novel alternative based on so-called deterministic sampling with higher accuracy, precision, and efficiency will therefore be briefly discussed and illustrated.