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Division Spotlight
Mathematics & Computation
Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
Meeting Spotlight
Utility Working Conference and Vendor Technology Expo (UWC 2024)
August 4–7, 2024
Marco Island, FL|JW Marriott Marco Island
Standards Program
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 engineers share their expertise at the University of Puerto Rico
Robert Roche-Rivera and Marcos Rolón-Acevedo are licensed professional engineers who work at the U.S. Nuclear Regulatory Commission. They are also alumni of the University of Puerto Rico–Mayagüez (UPRM) and have been sharing their knowledge and experience with students at their alma mater since last year, serving as adjunct professors in the university’s Department of Mechanical Engineering. During the 2023–2024 school year, they each taught two courses: Fundamentals of Nuclear Science and Engineering, and Nuclear Power Plant Engineering.
S. Varet, P. Dossantos-Uzarralde, N. Vayatis
Nuclear Science and Engineering | Volume 179 | Number 4 | April 2015 | Pages 398-410
Technical Paper | doi.org/10.13182/NSE14-07
Articles are hosted by Taylor and Francis Online.
For evaluated nuclear cross-section uncertainties, most standard approaches are based on experimental cross-section measurements, reflecting that these measurements have uncertainty on their own and, in particular, undetermined correlations. We propose here focusing on the estimation of experimental covariances and bypassing the direct empirical estimator, which cannot be used due to the small amount of available data. Because of the nonlinearity of experimental cross sections, an alternative method to the classical propagation error formula is presented. This method exploits a regression model of the experimental cross sections to generate pseudomeasurements and thereby allows an empirical estimation of experimental covariances. Moreover, thanks to a bootstrap, a quality measure for the estimation is provided. The empirical matrix estimation is then improved with shrinkage. The validity of the approach is confirmed through numerical experiments on a toy model. Finally, the procedure is applied to the real case of the 5525Mn nucleus.