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Nuclear Criticality Safety
NCSD provides communication among nuclear criticality safety professionals through the development of standards, the evolution of training methods and materials, the presentation of technical data and procedures, and the creation of specialty publications. In these ways, the division furthers the exchange of technical information on nuclear criticality safety with the ultimate goal of promoting the safe handling of fissionable materials outside reactors.
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2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
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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
New laws offer nuclear industry incentives for existing power plant uprates
This year, the U.S. nuclear industry received a much-needed economic boost that could help preserve operating nuclear power plants and incentivize upgrades that extend their lifespan and power output.
Signed into law in 2022, the Inflation Reduction Act offers production tax credits (PTCs) for existing nuclear power plants and either PTCs or investment tax credits (ITCs) for new carbon-free generation. These credits could make power uprates—increasing the maximum power level at which a commercial plant may operate—a much more appealing option for utilities.
F. H. Fröhner
Nuclear Science and Engineering | Volume 126 | Number 1 | May 1997 | Pages 1-18
Technical Paper | doi.org/10.13182/NSE97-A24453
Articles are hosted by Taylor and Francis Online.
Long-standing problems of assigning uncertainties to scientific data became apparent in recent years when uncertainty information (“covariance files”) had to be added to applications-oriented large libraries of evaluated nuclear data such as ENDF and JEF. Questions arose about the best way to express uncertainties, the meaning of statistical and systematic errors, the origin of correlations and the construction of covariance matrices, the combination of uncertain data from different sources, the general usefulness of results that are strictly valid only for Gaussians or only for linear statistical models, and so forth. Conventional statistical theory is often unable to give unambiguous answers and tends to fail when statistics are poor, making prior information crucial. Modern probability theory, on the other hand, incorporating results from information, decision, and group theory, is shown to provide straight and unique answers to such questions and to deal easily with prior information and small samples.