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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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Latest News
NRC nominee Nieh commits to independent safety mission
During a Senate Environment and Public Works Committee hearing today, Ho Nieh, President Donald Trump’s nominee to serve as a commissioner at the Nuclear Regulatory Commission, was urged to maintain the agency’s independence regardless of political pressure from the Trump administration.
Jin Li, Volkan Seker, Andrew Ward, Thomas Downar
Nuclear Science and Engineering | Volume 199 | Number 5 | May 2025 | Pages 772-792
Research Article | doi.org/10.1080/00295639.2024.2397621
Articles are hosted by Taylor and Francis Online.
Monte Carlo codes have become increasingly popular for generating homogenized few-group cross-section data, especially for advanced reactor designs that have complex geometries and nontraditional compositions. However, the stochastic nature of Monte Carlo processes has the potential to introduce additional statistical uncertainties in the overall uncertainty in the prediction of core behavior. The work performed in this research quantified the additional uncertainty introduced by the use of Monte Carlo multigroup cross sections into the analysis of graphite-moderated pebble bed reactors. In this research, the objective was achieved by performing uncertainty quantification for the key output parameters in deterministic steady-state and transient safety calculations. The results show that when the homogenized multigroup cross sections are generated with a sufficient number of neutron histories in the Monte Carlo calculation, the uncertainties in the subsequent deterministic simulations caused by the Monte Carlo cross-section uncertainty are negligible compared to the contributions from the uncertainties of other input parameters.