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Division Spotlight
Fusion Energy
This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
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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May 2025
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.
HyeonTae Kim, YuGwon Jo, Yonghee Kim
Nuclear Science and Engineering | Volume 194 | Number 4 | April 2020 | Pages 297-307
Technical Paper | doi.org/10.1080/00295639.2019.1698240
Articles are hosted by Taylor and Francis Online.
Performance enhancement of the spectral analysis method (SAM) for evaluating the real variance of local tallies from the partial current–based coarse-mesh finite difference (p-CMFD) feedback is verified and explained. In the SAM, on successive Monte Carlo (MC) cycles, the real variance is obtained from the cyclewise samples instead of an explicit evaluation of covariance. However, if the cycle correlation is strong, there is a bias and variance trade-off in the evaluated true uncertainty. This study shows that the p-CMFD feedback reduces the cycle covariance and hence eliminates the trade-off. A one-dimensional slab reactor and a three-dimensional simplified BEAVRS benchmark problem are analyzed, and the real standard deviation of the local tally is estimated from the SAM and compared with that from the conventional multibatch method. It is shown that the SAM with p-CMFD feedback can accurately calculate the real uncertainty without changing the MC algorithm and incurring computation burden.