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Erschienen in:
2015 | OriginalPaper | Buchkapitel
Optimization of Primary Loop Pump Power of a Loop-type Liquid Metal Fast Breeder Reactor with Annular Fuel Using Genetic Algorithm
verfasst von : Shubhajit Karmakar, Swarnendu Sen, Sanjib Kumar Acharyya
Erschienen in: Proceedings of Fourth International Conference on Soft Computing for Problem Solving
Verlag: Springer India
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Abstract
The present study focuses on the optimum design based on primary loop of a liquid metal fast breeder reactor (LMFBR). Inside the core annular fuel, rods are used for better heat transfer to the liquid sodium coolant. Value of the outlet temperature of the coolant from the core, surface temperature of the fuel pin, and pumping power at different volume flow rates are studied, and genetic algorithm (GA) is used to minimize pumping power required to maintain flow in the primary loop for an optimal design parameters.