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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
2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott Downtown
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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BREAKING NEWS: Trump issues executive orders to overhaul nuclear industry
The Trump administration issued four executive orders today aimed at boosting domestic nuclear deployment ahead of significant growth in projected energy demand in the coming decades.
During a live signing in the Oval Office, President Donald Trump called nuclear “a hot industry,” adding, “It’s a brilliant industry. [But] you’ve got to do it right. It’s become very safe and environmental.”
L. L. Carter, T. L. Miles, S. E. Binney
Nuclear Science and Engineering | Volume 113 | Number 4 | April 1993 | Pages 324-338
Technical Paper | doi.org/10.13182/NSE93-A15332
Articles are hosted by Taylor and Francis Online.
Statistical uncertainties for neutron transport calculations using the Monte Carlo method are typically evaluated during the calculation by using the first and second moments of the tallies. There are concerns that these statistical uncertainties may be substantially nonconservative in some classes of problems, especially reactor eigenvalue problems with the additional complication of a generation-to-generation source. Optimization of the Monte Carlo random walks may introduce further nonconservatism. Calculations are reported that quantify the reliability of the uncertainty by comparing an ensemble of Monte Carlo predictions of means and uncertainties to the true means for a liquid-metal fast reactor. It was found that the number of samples falling beyond a 90% confidence limit interval was typically not far from the expected 10%. However, 2 samples out of ∼300 were beyond four standard deviations, while for a normal distribution there is <1 chance in 10 000 that a sample will be beyond four standard deviations.