CUED Publications database

Optimization algorithms for multigroup energy structures

Fleming, MJ and Morgan, LWG and Shwageraus, E (2016) Optimization algorithms for multigroup energy structures. Nuclear Science and Engineering, 183. pp. 173-184. ISSN 0029-5639

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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.

Item Type: Article
Divisions: Div A > Energy
Depositing User: Cron Job
Date Deposited: 17 Jul 2017 19:11
Last Modified: 19 Jul 2018 06:58