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Division Spotlight
Accelerator Applications
The division was organized to promote the advancement of knowledge of the use of particle accelerator technologies for nuclear and other applications. It focuses on production of neutrons and other particles, utilization of these particles for scientific or industrial purposes, such as the production or destruction of radionuclides significant to energy, medicine, defense or other endeavors, as well as imaging and diagnostics.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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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NRC updating GEIS rule for new nuclear technology
The Nuclear Regulatory Agency is issuing a proposed generic environmental impact statement (GEIS) for use in reviewing applications for new nuclear reactors.
In an April 17 memo, NRC secretary Carrie Safford wrote that the commission approved NRC staff’s recommendation to publish in the Federal Register a proposed rule amending 10 CFR Part 51, “Environmental Protection Regulations for Domestic Licensing and Related Regulatory Functions.”
Robert W. Rice, John C. Walton
Nuclear Technology | Volume 163 | Number 1 | July 2008 | Pages 15-23
Technical Paper | High-Level Radioactive Waste Management | doi.org/10.13182/NT08-A3965
Articles are hosted by Taylor and Francis Online.
A numerical experiment was performed in order to examine the ability of multiple Monte Carlo realizations of a numerical model to reproduce the risk from a hypothetically known waste disposal situation. In the analysis, the risk was summarized by several risk metrics that could be chosen by a regulatory agency to set a risk standard. In the numerical experiment, the parameters in the numerical model are systematically varied to adjust bias (conservative or nonconservative) and to increase uncertainty relative to the hypothetically known future. The influence of parameter bias and uncertainty on the accuracy of each risk metric in predicting the nominal risk was evaluated and presented graphically. These analyses concluded that the peak-of-the-mean metric provides the least stable and least accurate risk predictions, whereas the cumulative release metric and mean of the peaks are more stable and accurate. The peak-of-the-mean and peak-of-the-median metrics exhibit risk dilution (i.e., a decrease in the predicted risk with increased uncertainty) and tend to underpredict risk. Additionally, these results illustrated how risk predictions that are made using what may be considered "conservative" assumptions can be moved in a direction that may or may not be expected or intended. Simulation relative to a hypothetical future (i.e., the nominal case) provides insight into the numerical behavior and potential accuracy of our risk assessment tools and potential issues with setting regulatory standards.