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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.”
Hyung Jin Shim, Chang Hyo Kim
Nuclear Science and Engineering | Volume 162 | Number 1 | May 2009 | Pages 98-108
Technical Paper | doi.org/10.13182/NSE09-2
Articles are hosted by Taylor and Francis Online.
The sample variance of a tally in Monte Carlo eigenvalue calculations is biased because of an intercycle correlation between the fission source distributions (FSDs). How to estimate the variance bias or equivalently how to calculate the real variance has been an interesting subject of study. This paper proposes a new method to estimate the real variance based on an intercycle covariance of the FSDs that can be derived from the cycle-by-cycle stochastic error propagation model. The proposed method enables one to calculate every intercycle covariance of a tally accurately, regardless of the number of active cycles. Therefore, the method can be applied satisfactorily even to problems with the dominance ratio (DR) close to 1. The accuracy of the new method is examined for small- and medium-sized pressurized water reactor core problems and a fuel storage facility problem exhibiting a slow source convergence. It is shown that the new method is capable of predicting the variance bias strikingly better than the existing methods, especially for problems with high DRs.