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

• Published in: Nuclear engineering and technology Vol. 53; no. 2; pp. 532 - 548
• Main Authors: Khambampati, Anil Kumar, Kim, Kyung Youn, Hur, Seop, Kim, Sung Joong, Kim, Jung Taek
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01-02-2021; Elsevier; 한국원자력학회
• Subjects: Fault detection; Identification of in-vessel phenomena; Interactive multiple model; RV out-wall temperature; State estimation; 원자력공학; Interactive multiple model; Identification of in-vessel phenomena; RV out-wall temperature; Fault detection; State estimation
• ISSN: 1738-5733; 2234-358X
• DOI: 10.1016/j.net.2020.08.008

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.