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Research on the calculation method of sensitivity coefficients of reactor power to material density based on Monte Carlo perturbation theory

  • Wu Wang (Department of Engineering Physics, Tsinghua University) ;
  • Kaiwen Li (Department of Engineering Physics, Tsinghua University) ;
  • Yuchuan Guo (Institute of Nuclear Physics and Chemistry, China Academy of Engineering Physics) ;
  • Conglong Jia (Department of Engineering Physics, Tsinghua University) ;
  • Zeguang Li (Department of Engineering Physics, Tsinghua University) ;
  • Kan Wang (Department of Engineering Physics, Tsinghua University)
  • Received : 2023.05.30
  • Accepted : 2023.08.25
  • Published : 2023.12.25

Abstract

The ability to calculate the material density sensitivity coefficients of power with respect to the material density has broad application prospects for accelerating Monte Carlo-Thermal Hydraulics iterations. The second-order material density sensitivity coefficients for the general Monte Carlo score have been derived based on the differential operator sampling method in this paper, and the calculation of the sensitivity coefficients of cell power scores with respect to the material density has been realized in continuous-energy Monte Carlo code RMC. Based on the power-density sensitivity coefficients, the sensitivity coefficients of power scores to some other physical quantities, such as power-boron concentration coefficients and power-temperature coefficients considering only the thermal expansion, were subsequently calculated. The effectiveness of the proposed method is demonstrated in the power-density coefficients problems of the pressurized water reactor (PWR) moderator and the heat pipe reactor (HPR) reflectors. The calculations were carried out using RMC and the ENDF/B-VII.1 neutron nuclear data. It is shown that the calculated sensitivity coefficients can be used to predict the power scores accurately over a wide range of boron concentration of the PWR moderator and a wide range of temperature of HPR reflectors.

Keywords

Acknowledgement

The authors would like to thank the fellowship of China Postdoctoral Science Foundation for its financial support of this research project (Grant No.2022M721793).

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