Nuclear Engineering and Technology

  • 제49권4호
  • /
  • Pages.760-768
  • /
  • 2017
  • /
  • 1738-5733(pISSN)
  • /
  • 2234-358X(eISSN)
한국원자력학회 (Korean Nuclear Society)
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Statistical analysis on the fluence factor of surveillance test data of Korean nuclear power plants

  • Lee, Gyeong-Geun (Nuclear Materials Safety Research Division, Korea Atomic Energy Research Institute) ;
  • Kim, Min-Chul (Nuclear Materials Safety Research Division, Korea Atomic Energy Research Institute) ;
  • Yoon, Ji-Hyun (Nuclear Materials Safety Research Division, Korea Atomic Energy Research Institute) ;
  • Lee, Bong-Sang (Nuclear Materials Safety Research Division, Korea Atomic Energy Research Institute) ;
  • Lim, Sangyeob (Nuclear Materials Safety Research Division, Korea Atomic Energy Research Institute) ;
  • Kwon, Junhyun (Nuclear Materials Safety Research Division, Korea Atomic Energy Research Institute)
  • 투고 : 2016.09.28
  • 심사 : 2017.02.08
  • 발행 : 2017.08.25
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초록

The transition temperature shift (TTS) of the reactor pressure vessel materials is an important factor that determines the lifetime of a nuclear power plant. The prediction of the TTS at the end of a plant's lifespan is calculated based on the equation of Regulatory Guide 1.99 revision 2 (RG1.99/2) from the US. The fluence factor in the equation was expressed as a power function, and the exponent value was determined by the early surveillance data in the US. Recently, an advanced approach to estimate the TTS was proposed in various countries for nuclear power plants, and Korea is considering the development of a new TTS model. In this study, the TTS trend of the Korean surveillance test results was analyzed using a nonlinear regression model and a mixed-effect model based on the power function. The nonlinear regression model yielded a similar exponent as the power function in the fluence compared with RG1.99/2. The mixed-effect model had a higher value of the exponent and showed superior goodness of fit compared with the nonlinear regression model. Compared with RG1.99/2 and RG1.99/3, the mixed-effect model provided a more accurate prediction of the TTS.

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참고문헌

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