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Division Spotlight
Mathematics & Computation
Division members promote the advancement of mathematical and computational methods for solving problems arising in all disciplines encompassed by the Society. They place particular emphasis on numerical techniques for efficient computer applications to aid in the dissemination, integration, and proper use of computer codes, including preparation of computational benchmark and development of standards for computing practices, and to encourage the development on new computer codes and broaden their use.
Meeting Spotlight
International Conference on Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2025)
April 27–30, 2025
Denver, CO|The Westin Denver 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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Argonne’s METL gears up to test more sodium fast reactor components
Argonne National Laboratory has successfully swapped out an aging cold trap in the sodium test loop called METL (Mechanisms Engineering Test Loop), the Department of Energy announced April 23. The upgrade is the first of its kind in the United States in more than 30 years, according to the DOE, and will help test components and operations for the sodium-cooled fast reactors being developed now.
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.