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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.
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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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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.
Taro Ueki, Forrest B. Brown, D. Kent Parsons, James S. Warsa
Nuclear Science and Engineering | Volume 148 | Number 3 | November 2004 | Pages 374-390
Technical Paper | doi.org/10.13182/NSE03-95
Articles are hosted by Taylor and Francis Online.
In the nuclear engineering community, the error propagation of the Monte Carlo fission source distribution through cycles is known to be a linear Markov process when the number of histories per cycle is sufficiently large. In the statistics community, linear Markov processes with linear observation functions are known to have an autoregressive moving average (ARMA) representation of orders p and p - 1. Therefore, one can perform ARMA fitting of the binned Monte Carlo fission source in order to compute physical and statistical quantities relevant to nuclear criticality analysis. In this work, the ARMA fitting of a binary Monte Carlo fission source has been successfully developed as a method to compute the dominance ratio, i.e., the ratio of the second-largest to the largest eigenvalues. The method is free of binning mesh refinement and does not require the alteration of the basic source iteration cycle algorithm. Numerical results are presented for problems with one-group isotropic, two-group linearly anisotropic, and continuous-energy cross sections. Also, a strategy for the analysis of eigenmodes higher than the second-largest eigenvalue is demonstrated numerically.