Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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An interactive multiple model method to identify the in-vessel phenomenon of a nuclear plant during a severe accident from the outer wall temperature of the reactor vessel

  • Khambampati, Anil Kumar (Department of Electronic Engineering, Jeju National University) ;
  • Kim, Kyung Youn (Department of Electronic Engineering, Jeju National University) ;
  • Hur, Seop (Research Div. of Autonomous Control, Korea Atomic Energy Research Institute) ;
  • Kim, Sung Joong (Department of Nuclear Engineering, Hanyang University) ;
  • Kim, Jung Taek (Research Div. of Autonomous Control, Korea Atomic Energy Research Institute)
  • Received : 2020.03.26
  • Accepted : 2020.08.06
  • Published : 2021.02.25
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Abstract

Nuclear power plants contain several monitoring systems that can identify the in-vessel phenomena of a severe accident (SA). Though a lot of analysis and research is carried out on SA, right from the development of the nuclear industry, not all the possible circumstances are taken into consideration. Therefore, to improve the efficacy of the safety of nuclear power plants, additional analytical studies are needed that can directly monitor severe accident phenomena. This paper presents an interacting multiple model (IMM) based fault detection and diagnosis (FDD) approach for the identification of in-vessel phenomena to provide the accident propagation information using reactor vessel (RV) out-wall temperature distribution during severe accidents in a nuclear power plant. The estimation of wall temperature is treated as a state estimation problem where the time-varying wall temperature is estimated using IMM employing three multiple models for temperature evolution. From the estimated RV out-wall temperature and rate of temperature, the in-vessel phenomena are identified such as core meltdown, corium relocation, reactor vessel damage, reflooding, etc. We tested the proposed method with five different types of SA scenarios and the results show that the proposed method has estimated the outer wall temperature with good accuracy.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT: Ministry of Science and ICT) (No. 2017M2A8A4017932). This research was also supported by the 2019 scientific promotion program funded by Jeju National University.

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