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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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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.
O. J. Wallace
Nuclear Science and Engineering | Volume 78 | Number 1 | May 1981 | Pages 78-85
Technical Note | doi.org/10.13182/NSE81-A19609
Articles are hosted by Taylor and Francis Online.
Calculations based on the integration of the point kernel over a finite source region are widely used in obtaining gamma-ray fluxes, dose rates, and heating rates. For most cases of practical interest, this integration must be done numerically. The relative merits of the trapezoidal rule, Gauss quadrature, and the semi-Gauss automatic quadrature algorithm of Patterson are discussed as they apply to the integration of the point kernel. The Patterson algorithm is superior to other quadrature algorithms for this application because it allows results to be calculated to a predetermined relative error, wastes no function evaluations, is accurate, and supplies relative error data along with the answer. It is efficient with respect to both engineering and computer time. The implementation of this algorithm for point-kernel integrations is described in detail.