• Nuclear Engineering and Technology
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• 제50권4호
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• pp.562-569
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• 2018

Recently, human errors have very rarely occurred during power generation at nuclear power plants. For this reason, many countries are conducting research on smart support systems of nuclear power plants. Smart support systems can help with operator decisions in severe accident occurrences. In this study, a smart support system was developed by integrating accident prediction functions from previous research and enhancing their prediction capability. Through this system, operators can predict accident scenarios, accident locations, and accident information in advance. In addition, it is possible to decide on the integrity of instruments and predict the life of instruments. The data were obtained using Modular Accident Analysis Program code to simulate severe accident scenarios for the Optimized Power Reactor 1000. The prediction of the accident scenario, accident location, and accident information was conducted using artificial intelligence methods.

• Nuclear Engineering and Technology
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• 제46권2호
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• pp.207-216
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• 2014

This paper revisits the Fukushima accident to draw lessons in the aspect of nuclear safety considering the fact that the Fukushima accident resulted in core damage for three nuclear power plants simultaneously and that there is a high possibility of a failure of the integrity of reactor vessel and primary containment vessel. A brief review on the accident progression at Fukushima nuclear power plants is discussed to highlight the nature and characteristic of the event. As the severe accident management measures at the Fukushima Daiich nuclear power plants seem to be not fully effective, limitations of current severe accident management strategy are discussed to identify the areas for the potential improvements including core cooling strategy, containment venting, hydrogen control, depressurization of primary system, and proper indication of event progression. The gap between the Fukushima accident event progression and current understanding of severe accident phenomenology including the core damage, reactor vessel failure, containment failure, and hydrogen explosion are discussed. Adequacy of current safety goals are also discussed in view of the socio-economic impact of the Fukushima accident. As a conclusion, it is suggested that an investigation on a coherent integrated safety principle for the severe accident and development of innovative mitigation features is necessary for robust and resilient nuclear power system.

• Nuclear Engineering and Technology
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• 제54권7호
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• pp.2475-2490
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• 2022

The Accident Tolerant Fuel (ATF) is a new concept of fuel, which can not only withstand the consequences of the accident for a longer time, but also maintain or improve the performance under operating conditions. ISAA is a self-developed severe accident analysis code, which uses modular structures to simulate the development processes of severe accidents in nuclear plants. The basic version of ISAA is developed based on UO₂-Zr fuel. To study the potential safety gain of ATF cladding, an improved version of ISAA, referred to as ISAA-ATF, is introduced to analyze the station blackout accident of PWR using ATF cladding. The results show that ATF cladding enable the core to maintain a longer time compared to zirconium alloy cladding, thereby enhancing the accident mitigation capability. Meanwhile, the generation of hydrogen is significantly reduced and delayed, which proves that ATF can improve the safety characteristics of the nuclear reactor.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 추계학술발표회논문집(1)
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• pp.695-700
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• 1997

To enhance the safety of nuclear power plants, implementation of accident management has been suggested as one of most important programs. Specially, accident management strategies are suggested as one of key elements considered in development of the accident management program. In this study, generally applicable accident management strategies to domestic nuclear power plants are identified through reviewing several accident management programs for the other countries and considering domestic conditions. Identified strategies are as follows; 1) Injection into the Reactor Coolant System, 2) Depressurize the Reactor Coolant System, 3) Depressurize the Steam Generator, 4) Injection into the Steam Generator, 5) Injection into the Containment, 6) Spray into the Containment, 7) Control Hydrogen in the Containment. In addition, the systems and instrumentation necessary for the implementation of .each strategy are also investigated.

• Nuclear Engineering and Technology
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• 제44권4호
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• pp.393-404
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• 2012

After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.

• Nuclear Engineering and Technology
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• 제50권4호
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• pp.582-588
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• 2018

Accident diagnosis is one of the complex tasks for nuclear power plant (NPP) operators. In abnormal or emergency situations, the diagnostic activity of the NPP states is burdensome though necessary. Numerous computer-based methods and operator support systems have been suggested to address this problem. Among them, the recurrent neural network (RNN) has performed well at analyzing time series data. This study proposes an algorithm for accident diagnosis using long short-term memory (LSTM), which is a kind of RNN, which improves the limitation for time reflection. The algorithm consists of preprocessing, the LSTM network, and postprocessing. In the LSTM-based algorithm, preprocessed input variables are calculated to output the accident diagnosis results. The outputs are also postprocessed using softmax to determine the ranking of accident diagnosis results with probabilities. This algorithm was trained using a compact nuclear simulator for several accidents: a loss of coolant accident, a steam generator tube rupture, and a main steam line break. The trained algorithm was also tested to demonstrate the feasibility of diagnosing NPP accidents.

• Nuclear Engineering and Technology
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• 제44권3호
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• pp.311-322
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• 2012

Since the crisis at the Fukushima plants, severe accident progression during a station blackout accident in nuclear power plants is recognized as a very important area for accident management and emergency planning. The purpose of this study is to investigate the comparative characteristics of anticipated severe accident progression among the three typical types of nuclear reactors. A station blackout scenario, where all off-site power is lost and the diesel generators fail, is simulated as an initiating event of a severe accident sequence. In this study a comparative analysis was performed for typical pressurized water reactor (PWR), boiling water reactor (BWR), and pressurized heavy water reactor (PHWR). The study includes the summarization of design differences that would impact severe accident progressions, thermal hydraulic/severe accident phenomenological analysis during a station blackout initiated-severe accident; and an investigation of the core damage process, both within the reactor vessel before it fails and in the containment afterwards, and the resultant impact on the containment.

• Nuclear Engineering and Technology
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• 제49권2호
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• pp.313-326
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• 2017

The systematic management of plant risk is crucial for enhancing the safety of nuclear power plants and for designing new nuclear power plants. Accident sequence precursor (ASP) analysis may be able to provide risk significance of operational experience by using probabilistic risk assessment to evaluate an operational event quantitatively in terms of its impact on core damage. In this study, an ASP methodology for two operation mode, full power and low power/shutdown operation, has been developed and applied to significant accident precursors that may occur during the operation of nuclear power plants. Two operational events, loss of feedwater and steam generator tube rupture, are identified as ASPs. Therefore, the ASP methodology developed in this study may contribute to identifying plant risk significance as well as to enhancing the safety of nuclear power plants by applying this methodology systematically.

• 한국언론정보학보
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• 제76권
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• pp.124-150
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• 2016

이 연구는 후쿠시마 원전 사고 이전과 이후를 비교해 우리나라 원전 보도의 일반적 특성과 보도 프레임 차이를 확인하기 위한 것이다. 이를 위해 중앙 일간신문과 원전 소재 지역 일간신문을 선정해 이들 신문이 게재한 원전 관련 기사에 대한 내용 분석을 실시했다. 연구 결과, 후쿠시마 원전 사고 이후 우리나라 원전에 대한 보도는 크게 늘어난 것으로 나타났다. 또한 이전에 주로 경제적 측면이 강조됐던 우리나라 원전 보도는 후쿠시마 원전 사고 이후 사회적 차원이 강조되기 시작했다. 그리고 우리나라 원전 보도 기사가 주요 기사로 다뤄지는 계기가 됐다. 한편 후쿠시마 원전 사고 이후 우리나라 원전 보도의 프레임 역시 크게 변화했다. 당연하게도 환경 안전 프레임이 크게 증가한 것으로 나타났다. 이는 후쿠시마 원전 사고를 계기로 우리나라 원전의 안정성과 관련된 보도가 대폭 늘어났기 때문으로 보인다. 특히 원전 소재 지역의 일간신문에서 환경 안전 프레임은 후쿠시마 원전 사고 이전에도 다른 프레임과 비교해 가장 많은 29.3%였는데, 그 이후에는 77.6%로까지 증가한 것으로 확인됐다.

• Nuclear Engineering and Technology
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• 제48권4호
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• pp.975-981
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• 2016

The containment response during the first 24 hours of a low-pressure severe accident scenario in a nuclear power plant with a two-loop Westinghouse-type pressurized water reactor was simulated with the CONTAIN 2.0 computer code. The accident considered in this study is a large-break loss-of-coolant accident, which is not successfully mitigated by the action of safety systems. The analysis includes pressure and temperature responses, as well as investigation into the influence of spray on the retention of fission products and the prevention of hydrogen combustion in the containment.