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• W2948296275 abstract "The optimization problem of nuclear fuel management, reported in the present study aimed at arriving at the optimal number of subassemblies in the two fuel enrichment zones of the core of a 500 MWe Fast Breeder Reactor. The elitist multi-objective approach of Genetic Algorithm, namely Non-dominated Sorting Genetic Algorithm-II (NSGA-II), was employed in the study. The five parameters considered for optimization are: core excess reactivity, liner heat ratings of inner and outer fuel enrichment zones of the core, fissile material inventory, and breeding ratio. The results obtained from the study indicate that the algorithm is able to produce feasible solutions in an efficient manner while preserving the diversity amongst them. The fast convergence and the diversity-preserving feature of the algorithm are described. The major objective of the work is to study the viability of applying the NSGA-II into the nuclear fuel management problems of fast breeder reactors." @default.
• W2948296275 created "2019-06-14" @default.
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• W2948296275 date "2019-04-17" @default.
• W2948296275 modified "2023-09-27" @default.
• W2948296275 title "Application of Multi Objective Genetic Algorithm for Optimization of Core Configuration Design of a Fast Breeder Reactor" @default.
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