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Radiation Protection & Shielding
The Radiation Protection and Shielding Division is developing and promoting radiation protection and shielding aspects of nuclear science and technology — including interaction of nuclear radiation with materials and biological systems, instruments and techniques for the measurement of nuclear radiation fields, and radiation shield design and evaluation.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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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
First astatine-labeled compound shipped in the U.S.
The Department of Energy’s National Isotope Development Center (NIDC) on March 31 announced the successful long-distance shipment in the United States of a biologically active compound labeled with the medical radioisotope astatine-211 (At-211). Because previous shipments have included only the “bare” isotope, the NIDC has described the development as “unleashing medical innovation.”
Axel Hoefer, Oliver Buss, Michael Schmid
Nuclear Technology | Volume 205 | Number 12 | December 2019 | Pages 1578-1587
Technical Paper | doi.org/10.1080/00295450.2018.1560784
Articles are hosted by Taylor and Francis Online.
A general Bayesian framework for best-estimate plus uncertainty predictions of multidimensional continuous observables is presented. Parameterizing uncertainties in terms of multivariate normal distribution models, this Multivariate normal Bayesian model (MNBM) framework allows one to include both measured data and linear constraints in a mathematically consistent way. The resulting updating formulas are generalizations of the updating formulas of the Generalized Linear Least Squares (GLLS) framework, which is widely used for the generation of adjusted nuclear data libraries. While the GLLS methodology is restricted to first-order perturbation theory, there is no such restriction for the considered MNBM framework. This makes it possible to use Monte Carlo uncertainty propagation and to apply the updating formulas directly to the observables of interest without having to first update the input parameter distributions. After a general presentation of the MNBM framework and a brief discussion of its possible applications, the generation of bounding burnup-dependent axial burnup profiles of light water reactor fuel assemblies for the purpose of criticality safety analysis is discussed as an example application.