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Members focus on the dissemination of knowledge and information in the area of power reactors with particular application to the production of electric power and process heat. The division sponsors meetings on the coverage of applied nuclear science and engineering as related to power plants, non-power reactors, and other nuclear facilities. It encourages and assists with the dissemination of knowledge pertinent to the safe and efficient operation of nuclear facilities through professional staff development, information exchange, and supporting the generation of viable solutions to current issues.
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November 16–19, 2020
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Elementary school resources added to Navigating Nuclear
Elementary school lesson plans are the latest additions to the Navigating Nuclear: Energizing Our World website. The two lesson plans were created to help students in grades 3-5 understand the power of the atom and how to investigate different energy sources.
Navigating Nuclear is a K-12 nuclear science and energy curriculum created in partnership by the American Nuclear Society and Discovery Education, with lead funding from the Department of Energy's Office of Nuclear Energy.
M. Dion, G. Marleau
Nuclear Science and Engineering | Volume 183 | Number 2 | June 2016 | Pages 261-274
Technical Paper | dx.doi.org/10.13182/NSE15-60
Articles are hosted by Taylor and Francis Online.
The sensitivity coefficients of self-shielded cross sections to isotopic densities are computed for a subgroup resonance self-shielding model. The method we propose is based on the derivatives of the collision probabilities used in the slowing-down equation. In this work, we look at how the sensitivities vary as a function of the position inside a fuel pin or of the position of a fuel pin within an assembly. Moreover, we evaluate the importance of the superhomogenization factors, used to correct self-shielded cross sections for the subgroup method, on the cross-section sensitivities. We also present a comparison with the Monte Carlo code Serpent where the sensitivity coefficients are approximated using a finite difference method.