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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.
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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
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.
C. van der Hoeven, E. Schneider, L. Leal
Nuclear Science and Engineering | Volume 179 | Number 1 | January 2015 | Pages 1-21
Technical Paper | doi.org/10.13182/NSE13-78
Articles are hosted by Taylor and Francis Online.
There is a need for improved molybdenum isotope covariance data for use in modeling a new uranium-molybdenum fuel form to be produced at the Y-12 National Security Complex (Y-12). Covariance data correlate the uncertainty in an isotopic cross section at a particular energy to uncertainties at other energies. While high-fidelity covariance data exist for key isotopes, the low-fidelity covariance data available for most isotopes, including the natural molybdenum isotopes considered in this work, are derived from integral measurements without meaningful correlation between energy regions. This paper provides a framework for using the Bayesian R-matrix code SAMMY to derive improved isotopic resonance region covariance data from elemental experimental cross-section data. These resonance-wise covariance data were combined with integral uncertainty data from the Atlas of Neutron Resonances, uncertainty data generated via a dispersion method, and high-energy uncertainty data previously generated with the Empire-KALMAN code to produce an improved set of covariance data for the natural molybdenum isotopes. The improved covariance data sets, along with the associated resonance parameters, were inserted into JENDL4.0 data files for the molybdenum isotopes for use in data processing and modeling codes. Additionally, a series of critical experiments featuring the new U(19.5%)-10Mo fuel form produced at Y-12 was designed. Along with existing molybdenum sensitive critical experiments, these were used to compare the performance of the new molybdenum covariance data against the existing low-fidelity evaluation. The new covariance data were found to result in reduced overall bias, reduced bias due to the molybdenum isotopes, and improved goodness of fit of computational to experimental results.