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Fuel Cycle & Waste Management
Devoted to all aspects of the nuclear fuel cycle including waste management, worldwide. Division specific areas of interest and involvement include uranium conversion and enrichment; fuel fabrication, management (in-core and ex-core) and recycle; transportation; safeguards; high-level, low-level and mixed waste management and disposal; public policy and program management; decontamination and decommissioning environmental restoration; and excess weapons materials disposition.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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
Strontium: Supply-and-demand success for the DOE’s Isotope Program
The Department of Energy’s Isotope Program (DOE IP) announced last week that it would end its “active standby” capability for strontium-82 production about two decades after beginning production of the isotope for cardiac diagnostic imaging. The DOE IP is celebrating commercialization of the Sr-82 supply chain as “a success story for both industry and the DOE IP.” Now that the Sr-82 market is commercially viable, the DOE IP and its National Isotope Development Center can “reassign those dedicated radioisotope production capacities to other mission needs”—including Sr-89.
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.