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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.
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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
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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.
P. K. Sarkar, M. A. Prasad
Nuclear Science and Engineering | Volume 87 | Number 2 | June 1984 | Pages 136-151
Technical Paper | doi.org/10.13182/NSE84-A17708
Articles are hosted by Taylor and Francis Online.
Based on the theory of contributions, a new Monte Carlo method known as the contributon Monte Carlo method has recently been developed. The method has found applications in several practical shielding problems. We analyze theoretically the variance and efficiency of the new method, by taking moments around the score. In order to compare the contributon game with a game of simple geometrical splitting and also to get the optimal placement of the contributon volume, the moments equations were solved numerically for a one-dimensional, one-group problem using a 10-mfp-thick homogeneous slab. It is found that the optimal placement of the contributon volume is adjacent to the detector; even at its most optimal the contributon Monte Carlo is less efficient than geometrical splitting.