ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
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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
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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Latest News
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.