Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Risk-informed design optimization method and application in a lead-based research reactor

  • Jiaqun Wang (Wuhan 2nd Ship Design and Research Institute) ;
  • Qianglong Wang (Wuhan 2nd Ship Design and Research Institute) ;
  • Jinrong Qiu (Wuhan 2nd Ship Design and Research Institute) ;
  • Jin Wang (International Academy of Neutron Science) ;
  • Fang Wang (International Academy of Neutron Science) ;
  • Yazhou Li (International Academy of Neutron Science)
  • Received : 2022.08.07
  • Accepted : 2023.03.04
  • Published : 2023.06.25
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Abstract

Risk-informed approach has been widely applied in the safety design, regulation, and operation of nuclear reactors. It has been commonly accepted that risk-informed design optimization should be used in the innovative reactor designs to make nuclear system highly safe and reliable. In spite of the risk-informed approach has been used in some advanced nuclear reactors designs, such as Westinghouse IRIS, Gen-IV sodium fast reactors and lead-based fast reactors, the process of risk-informed design of nuclear reactors is hardly to carry out when passive system reliability should be integrated in the framework. A practical method for new passive safety reactors based on probabilistic safety assessment (PSA) and passive system reliability analyze linking is proposed in this paper. New three-dimension frequency-consequence curve based on risk concept with three variables is used in this method. The proposed method has been applied to the determination optimization of design options selection in a 10 MWth lead-based research reactor(LR) to obtain one optimized system design in conceptual design stage, using the integrated reliability and probabilistic safety assessment program RiskA, and the computation resources and time consumption in this process was demonstrated reasonable and acceptable.

Keywords

Acknowledgement

We thank other authors and contributors of references cited. This work is supported by the National Natural Science Foundation of China (72001201).

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