Application of Simulated Annealing Algorithm in Core Flow Distribution Optimization

Zixuan Wang, Yan Wang (), Haipeng Xu and Heng Xie
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Zixuan Wang: Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China
Yan Wang: Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China
Haipeng Xu: Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China
Heng Xie: Institute of Nuclear and New Energy Technology, Tsinghua University, Beijing 100084, China

Energies, 2022, vol. 15, issue 21, 1-12

Abstract: Core flow distribution is closely related to the thermal–hydraulic performance and safety of reactors. For natural circulation reactors with a limited driving force, flow distribution optimization is of particular significance, which can be contrived by suitably assigning the inlet resistance of a core assembly channel in reactor design. In the present work, core flow distribution optimization during the fuel life cycle is regarded as a global optimization problem. The optimization objective is to minimize the maximal outlet temperature difference of assembly channels during the fuel life cycle, while the input variable is the inlet resistance coefficient of each assembly channel. The simulated annealing algorithm is applied to the optimization code. The results show that the maximal outlet temperature difference is significantly reduced after optimization, and the resultant core outlet temperature distribution becomes more uniformed. Further evaluation indicates that the optimal solution has good applicability and stability under different reactor conditions. A comparison of the optimization objective function using different temperature difference definitions is also studied in the current study.

Keywords: flow distribution optimization; natural circulation; global optimization; simulated annealing algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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