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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.
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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Latest News
Proposed rule for more flexible licensing under Part 53 is open for comment
The Nuclear Regulatory Commission has published a proposed rule that has been almost five years in the making: Risk-Informed, Technology-Inclusive Regulatory Framework for Advanced Reactors. The rule, which by law must take its final form before the end of 2027, would let the NRC and license applicants use technology-inclusive approaches and risk-informed, performance-based techniques to effectively license any nuclear technology. This is a departure from two licensing options with light water reactor–specific regulatory requirements that applicants can already choose.
Shahid Ahmed, R. E. Clark, D. R. Metcalf+
Nuclear Technology | Volume 59 | Number 2 | November 1982 | Pages 238-245
Technical Paper | Nuclear Safety | doi.org/10.13182/NT82-A33027
Articles are hosted by Taylor and Francis Online.
A method is developed to propagate uncertainties in the basic event unavailabilities through a logic model to obtain the transient overpower event unavailability. The method consists of combining probability distributions in the discrete form without performing any sampling. The results are shown to be sufficiently accurate and contain no sampling errors; the computation time is considerably less compared to Monte Carlo simulation and histogram propagation. Uncertainty propagation methods are found to be sensitive to the spread of the basic event unavailability distributions; the proposed method produces results less conservative compared to those from propagation of moments or Monte Carlo simulation.