Nuclear Engineering and Technology

  • 제55권8호
  • /
  • Pages.3088-3101
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  • 2023
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  • 1738-5733(pISSN)
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  • 2234-358X(eISSN)
한국원자력학회 (Korean Nuclear Society)
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Multi-fidelity modeling and analysis of a pressurized vessel-pipe-safety valve system based on MOC and surrogate modeling methods

  • Xueguan Song (School of Mechanical Engineering, Dalian University of Technology) ;
  • Qingye Li (School of Mechanical Engineering, Dalian University of Technology) ;
  • Fuwen Liu (School of Mechanical Engineering, Dalian University of Technology) ;
  • Weihao Zhou (School of Mechanical Engineering, Dalian University of Technology) ;
  • Chaoyong Zong (School of Mechanical Engineering, Dalian University of Technology)
  • 투고 : 2023.01.03
  • 심사 : 2023.04.20
  • 발행 : 2023.08.25
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초록

A pressurized vessel-pipe-safety valve (PVPSV) combination is a commonly used configuration in nuclear power plants, and a good numerical model is essential for the system design, sizing and performance optimization. However, owing to the large-scale and cross-scale features, it is still a challenge to build a system level numerical model with both high accuracy and efficiency. To overcome this, a novel system level modeling method which can synthesize the advantages of various models is proposed in this paper. For system modeling, the analytical approach, the method of characteristics (MOC) and the surrogate model approach are respectively adopted to predict the dynamics of the pressure vessel, the connecting pipe and the safety valve, and different models are connected through data interfaces. With this system model, dynamic simulations were carried out and both the stable and the unstable system responses were obtained. For the model verification purpose, the simulation results were compared with those obtained from experiments and full CFD simulations. A good agreement and a better efficiency were obtained, verifying the ability of the model and the feasibility of the modeling method proposed in this paper.

키워드

과제정보

This work was supported by the National Natural Science Foundation of China (No. 52205251). We would also like to thank the editors and the reviewers for their constructive comments and helpful suggestions. Thanks also to Beijing Super Cloud Computing Center.

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