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Division Spotlight
Fuel Cycle & Waste Management
Devoted to all aspects of the nuclear fuel cycle including waste management, worldwide. Division specific areas of interest and involvement include uranium conversion and enrichment; fuel fabrication, management (in-core and ex-core) and recycle; transportation; safeguards; high-level, low-level and mixed waste management and disposal; public policy and program management; decontamination and decommissioning environmental restoration; and excess weapons materials disposition.
Meeting Spotlight
2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
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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August 2024
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.
N. Shenhav, Y. Segal, A. Notea
Nuclear Science and Engineering | Volume 80 | Number 1 | January 1982 | Pages 61-73
Technical Paper | doi.org/10.13182/NSE82-A21404
Articles are hosted by Taylor and Francis Online.
A general approach to the application of neutron count moment analysis to passive assay is presented. The higher moments of the neutron count distribution are derived with the aid of the probability generating function and are used to formulate an analytic relation between the measurement uncertainty and the assay system parameters. The measurement uncertainty, expressed by the relative resolving power function, for the reduced variance method is developed and analyzed in detail. The study suggests an iterative approach for data processing where the interpretational models are chosen to yield the lowest possible resolving power.