@inproceedings{89f11b80fea64ad0a374d9ebb15a11a0,
title = "Method for optimization of enrichment and burnable absorber distributions within fuel assemblies based on manufacturing constraints",
abstract = "Athree-dimensional method for optimizing the enrichment and burnable absorber distributions within fuel bundles is developed using Genetic Algorithms as the optimization approach with discrete fuel rod designs as the decision variables. The method allows inclusion of constraints based on fuel manufacturing in the optimization problem. Here, it is applied to the process of BWR bundle design. To model the axial heterogeneous fuel bundle, an approach based on the generation of two dimensional lattice within the different physical axial zones of the BWR bundle is developed accounting for the nominal behavior of the axial power and void distribution. The optimization is applied to the problem of optimizing a GE 10x10 bundle design based on a palette of available fuel rod designs with the objective of minimizing the boiling transition factor and subject to a constraint on bundle reactivity.",
keywords = "Fuel Cycle, Genetic Algorithm, Optimization",
author = "Brian Andersen and David Kropaczek",
note = "Publisher Copyright: {\textcopyright} 2018 by PHYSOR 2018. All Rights Reserved.; 2018 International Conference on Physics of Reactors: Reactor Physics Paving the Way Towards More Efficient Systems, PHYSOR 2018 ; Conference date: 22-04-2018 Through 26-04-2018",
year = "2018",
language = "English",
series = "International Conference on Physics of Reactors, PHYSOR 2018: Reactor Physics Paving the Way Towards More Efficient Systems",
publisher = "Sociedad Nuclear Mexicana, A.C.",
pages = "3497--3507",
booktitle = "International Conference on Physics of Reactors, PHYSOR 2018",
}