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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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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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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.
Thomas E. Booth
Nuclear Science and Engineering | Volume 122 | Number 1 | January 1996 | Pages 79-92
Technical Paper | doi.org/10.13182/NSE96-A28549
Articles are hosted by Taylor and Francis Online.
The interpretation of the statistical error estimates produced by Monte Carlo transport codes is still somewhat of an art. Empirically, there are variance reduction techniques whose error estimates are almost always reliable, and there are variance reduction techniques whose error estimates are often unreliable. Unreliable error estimates usually result from inadequate large-score sampling from the score distributions’tail.Statisticians believe that more accurate confidence interval statements are possible if the general nature of the score distribution can be characterized. Here, the analytic score distribution for the exponential transform applied to a simple, spatially continuous Monte Carlo transport problem is provided. Anisotropic scattering and implicit capture are included in the theory. In large part, the analytic score distributions that are derived provide the basis for the ten new statistical quality checks in MCNP.