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The division's objectives are to promote the advancement of knowledge and understanding of the fundamental physical phenomena characterizing nuclear reactors and other nuclear systems. The division encourages research and disseminates information through meetings and publications. Areas of technical interest include nuclear data, particle interactions and transport, reactor and nuclear systems analysis, methods, design, validation and operating experience and standards. The Wigner Award heads the awards program.
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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. J. Fleming, L. W. G. Morgan, E. Shwageraus
Nuclear Science and Engineering | Volume 183 | Number 2 | June 2016 | Pages 173-184
Technical Paper | dx.doi.org/10.13182/NSE15-55
Articles are hosted by Taylor and Francis Online.
Modeling of nuclide densities as a function of time within magnetic confinement fusion devices such as the JET, ITER, and proposed DEMO tokamaks is performed using Monte Carlo transport codes coupled with a Bateman equation solver. The generation of reaction rates occurs through either pointwise interpolation of energy-dependent tracked particle data with nuclear data or multigroup (MG) convolution of binned fluxes with binned cross sections. The MG approach benefits from decreased computational expense and data portability, but introduces errors through effects such as self-shielding. Depending on the MG structure and nuclear data used, this method can introduce unacceptable errors without warning. We present a MG optimization method that utilizes a modified particle swarm algorithm to generate seed solutions for a nonstochastic string-tightening algorithm. This procedure has been used with a semihomogenized one-dimensional DEMO-like reactor design to produce an optimized energy group structure for tritium breeding. In this example, the errors introduced by the Vitamin-J 175 MG are reduced by two orders of magnitude in the optimized group structure.