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Division Spotlight
Thermal Hydraulics
The division provides a forum for focused technical dialogue on thermal hydraulic technology in the nuclear industry. Specifically, this will include heat transfer and fluid mechanics involved in the utilization of nuclear energy. It is intended to attract the highest quality of theoretical and experimental work to ANS, including research on basic phenomena and application to nuclear system design.
Meeting Spotlight
2024 ANS Winter Conference and Expo
November 17–21, 2024
Orlando, FL|Renaissance Orlando at SeaWorld
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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Nuclear Science and Engineering
November 2024
Nuclear Technology
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Fusion Science and Technology
Latest News
Tank waste operations resume at Idaho’s IWTU
The Department of Energy’s Office of Environmental Management announced yesterday that waste processing operations have resumed at the Integrated Waste Treatment Unit (IWTU) at the Idaho National Laboratory Site. The resumption of operations follows the completion of two maintenance campaigns at the radioactive liquid waste treatment facility.
Andrew T. Till, Marvin L. Adams, Jim E. Morel
Nuclear Science and Engineering | Volume 196 | Number 1 | January 2022 | Pages 53-74
Technical Paper | doi.org/10.1080/00295639.2021.1932224
Articles are hosted by Taylor and Francis Online.
Energy discretization of the transport equation is difficult due to numerous strong, narrow cross-section (XS) resonances. The standard traditional multigroup (MG) method can be sensitive to approximations in the weighting spectrum chosen for XS averaging, which can lead to inaccurate treatment of important phenomena such as self-shielding. We generalize the concept of a group to a discontiguous range of energies to create the Finite-Element with Discontiguous-Support (FEDS) method. FEDS uses clustering algorithms from machine learning to determine optimal definitions of discontiguous groups. By combining parts of multiple resonances into the same group, FEDS can accurately treat resonance behavior even when the number of groups is orders of magnitude smaller than the number of resonances. In this paper, we introduce the theory of the FEDS method and describe the workflow needed to use FEDS, noting that ordinary MG codes can use FEDS XSs without modification, provided these codes can handle upscattering. This allows existing MG codes to produce FEDS solutions. In the context of light water reactors, we investigate properties of FEDS XSs compared to MG XSs and compare -eigenvalue and reaction rate quantities of interest to continuous-energy Monte Carlo, showing that FEDS provides higher accuracy and less cancellation of error than MG with expert-chosen group structures.