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Division Spotlight
Reactor Physics
The division's objectives are to promote the advancement of knowledge and understanding of the fundamental physical phenomena characterizing nuclear reactors and other nuclear systems. The division encourages research and disseminates information through meetings and publications. Areas of technical interest include nuclear data, particle interactions and transport, reactor and nuclear systems analysis, methods, design, validation and operating experience and standards. The Wigner Award heads the awards program.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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
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.”
Dan G. Cacuci, Mihaela Ionescu-Bujor
Nuclear Science and Engineering | Volume 165 | Number 1 | May 2010 | Pages 1-17
Technical Paper | doi.org/10.13182/NSE09-37A
Articles are hosted by Taylor and Francis Online.
When n measurements and/or computations of the same (unknown) quantity yield data points xj with corresponding standard deviations (uncertainties) j such that the distances [vertical bar]xj - xk[vertical bar] between any two data points are smaller than or comparable to the sum (j + k) of their respective uncertainties, the respective data points are considered to be consistent or to agree within error bars. However, when the distances [vertical bar]xj - xk[vertical bar] are larger than (j + k), the respective data are considered to be inconsistent or discrepant. Inconsistencies can be caused by unrecognized or ill-corrected experimental effects (e.g., background corrections, dead time of the counting electronics, instrumental resolution, sample impurities, calibration errors). Although there is a nonzero probability that genuinely discrepant data could occur (for example, for a Gaussian sampling distribution with standard deviation , the probability that two equally precise measurements would be separated by more than 2 is erfc(1) [approximately equal] 0.157), it is much more likely that apparently discrepant data actually indicate the presence of unrecognized errors.This work addresses the treatment of unrecognized errors by applying the maximum entropy principle under quadratic loss, to the discrepant data. Novel results are obtained for the posterior distribution determining the unknown mean value (i.e., unknown location parameter) of the data and also for the marginal posterior distribution of the unrecognized errors. These novel results are considerably more rigorous, are more accurate, and have a wider range of applicability than extant recipes for handling discrepant data.