Nuclear Engineering and Technology

  • 제52권10호
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  • Pages.2221-2229
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  • 2020
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  • 1738-5733(pISSN)
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  • 2234-358X(eISSN)
한국원자력학회 (Korean Nuclear Society)
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Development of MURCC code for the efficient multi-unit level 3 probabilistic safety assessment

  • Jung, Woo Sik (Sejong University, Nuclear Engineering Department) ;
  • Lee, Hye Rin (Sejong University, Nuclear Engineering Department) ;
  • Kim, Jae-Ryang (Sejong University, Nuclear Engineering Department) ;
  • Lee, Gee Man (Sejong University, Nuclear Engineering Department)
  • 투고 : 2019.11.26
  • 심사 : 2020.03.10
  • 발행 : 2020.10.25
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초록

After the Fukushima Daiichi nuclear power plant (NPP) accident, level 3 probabilistic safety assessment (PSA) has emerged as an important task in order to assess the risk level of the multi-unit NPPs in a single nuclear site. Accurate calculation of the radionuclide concentrations and exposure doses to the public is required if a nuclear site has multi-unit NPPs and large number of people live near NPPs. So, there has been a great need to develop a new method or procedure for the fast and accurate offsite consequence calculation for the multi-unit NPP accident analysis. Since the multi-unit level 3 PSA is being currently performed assuming that all the NPPs are located at the same position such as a center of mass (COM) or base NPP position, radionuclide concentrations or exposure doses near NPPs can be drastically distorted depending on the locations, multi-unit NPP alignment, and the wind direction. In order to overcome this disadvantage of the COM method, the idea of a new multiple location (ML) method was proposed and implemented into a new tool MURCC (multi-unit radiological consequence calculator). Furthermore, the MURCC code was further improved for the multi-unit level 3 PSA that has the arbitrary number of multi-unit NPPs. The objectives of this study are to (1) qualitatively and quantitatively compare COM and ML methods, and (2) demonstrate the strength and efficiency of the ML method. The strength of the ML method was demonstrated by the applications to the multi-unit long-term station blackout (LTSBO) accidents at the four-unit Vogtle NPPs. Thus, it is strongly recommended that this ML method be employed for the offsite consequence analysis of the multi-unit NPP accidents.

키워드

참고문헌

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피인용 문헌

  1. Multi-unit nuclear power plant probabilistic risk assessment: A comprehensive survey vol.213, 2021, https://doi.org/10.1016/j.ress.2021.107782