• Nuclear Engineering and Technology
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• v.47 no.1
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• pp.1-10
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• 2015

After the Fukushima Daiichi nuclear power plant (NPP) accident, new regulatory requirements were enforced in July 2013 and a backfit was required for all existing nuclear power plants. It is required to take measures to prevent severe accidents and mitigate their radiological consequences. The Regulatory Standard and Research Department, Secretariat of Nuclear Regulation Authority (S/NRA/R) has been conducting numerical studies and experimental studies on relevant severe accident phenomena and countermeasures. This article highlights fission product (FP) release and hydrogen risk as two major areas. Relevant activities in the S/NRA/R are briefly introduced, as follows: 1. For FP release: Identifying the source terms and leak mechanisms is a key issue from the viewpoint of understanding the progression of accident phenomena and planning effective countermeasures that take into account vulnerabilities of containment under severe accident conditions. To resolve these issues, the activities focus on wet well venting, pool scrubbing, iodine chemistry (in-vessel and ex-vessel), containment failure mode, and treatment of radioactive liquid effluent. 2. For hydrogen risk: because of three incidents of hydrogen explosion in reactor buildings, a comprehensive reinforcement of the hydrogen risk management has been a high priority topic. Therefore, the activities in evaluation methods focus on hydrogen generation, hydrogen distribution, and hydrogen combustion.

• Nuclear Engineering and Technology
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• v.46 no.1
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• pp.27-38
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• 2014

The Fukushima Dai-Ichi accident in 2011 has affected various aspects of the nuclear society worldwide. The accident revealed some problems in the conventional approaches used to ensure the safety of nuclear installations. To prevent such disastrous accidents in the future, we have to learn from them and improve the conventional approaches in a more systematic manner. In this paper, we will cover three issues. The first is to identify the key issues that affected the progress of the Fukushima Dai-Ichi accident greatly. We examine the accident from a defense-in-depth point of view to identify such issues. The second is to develop a more systematic approach to enhance the safety of nuclear installations. We reexamine nuclear safety from a risk point of view. We use the concepts of residual and unknown risks in classifying the risk space. All possible accident scenarios types are reviewed to clarify the characteristics of the identified issues. An approach is proposed to improve our conventional approaches used to ensure nuclear safety including the design of safety features and the safety assessments from a risk point of view. Finally, we address some issues to be improved in the conventional risk assessment and management framework and/or practices to enhance nuclear safety.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.493-505
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• 2023

Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3787-3800
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• 2023

Reactivity Initiated Accident (RIA) scenarios require special attention using advanced simulation techniques due to their complexity and importance for nuclear power plant (NPP) safety. While the conservative approach has traditionally been used for safety analysis, it may lead to unrealistic results which calls for the use of best estimate plus uncertainty (BEPU) approach, especially with the current advances in computational power which makes the BEPU analysis feasible. In this work an Uncontrolled Control Element Assembly (CEA) Withdrawal at Full Power accident scenario is analyzed using the BEPU approach by loosely coupling the thermal hydraulics best-estimate system code (RELAP5/SCDAPSIM/MOD3.4) to the statistical analysis software (DAKOTA) using a Python interface. Results from the BEPU analysis indicate that a realistic treatment of the accident scenario yields a larger safety margin and is therefore encouraged for accident analysis as it may enable more economic and flexible operation.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.481-486
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• 1996

Safety management may be classified into three dimensions: (1) risk management, (2) accident management, and (3) emergency management. This paper addresses the recent trends of safety management in nuclear industry, focussing on risk management and accident management.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1199-1209
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• 2018

After the Fukushima-Daiichi accident in 2011, the multi-unit risk, i.e., the risk due to several nuclear power plants (NPPs) in a site has become an important issue in several countries such as Korea, Canada, and China. However, the multi-unit risk has been discussed for a long time in the nuclear community before the Fukushima-Daiichi nuclear accident occurred. The regulatory authorities around the world and the international organizations had proposed requirements or guidelines to reduce the multi-unit risk. The concerns regarding the multi-unit risk can be summarized in the following three questions: How much the accident of an NPP in a site affects the safety of other NPPs in the same site? What is the total risk of a site with many NPPs? Will the risk of the simultaneous accidents at several NPPs in a site such as the Fukushima Daiichi accident be low enough? The multi-unit risk assessment (MURA) in an integrated framework is a practical approach to obtain the answers for the above questions. Even though there were few studies to assess the multi-unit risk before the Fukushima-Daiichi nuclear accident, there are still several issues to be resolved to perform the complete MURA. This article aims to provide an overview of the multi-unit risk issues and its assessment. We discuss the several critical issues in the current MURA to get useful insights regarding the multi-unit risk with the current state art of probabilistic safety assessment (PSA) technologies. Also, the qualitative answers for the above questions are addressed.

• Nuclear Engineering and Technology
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• v.47 no.1
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• pp.74-84
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• 2015

If a transient occurs in a nuclear power plant (NPP), operators will try to protect the NPP by estimating the kind of abnormality and mitigating it based on recommended procedures. Similarly, operators take actions based on severe accident management guidelines when there is the possibility of a severe accident occurrence in an NPP. In any such situation, information about the occurrence time of severe accident-related events can be very important to operators to set up severe accident management strategies. Therefore, support systems that can quickly provide this kind of information will be very useful when operators try to manage severe accidents. In this research, the occurrence times of several events that could happen during a severe accident were predicted using support vector machines with short time variations of plant status variables inputs. For the preliminary step, the break location and size of a loss of coolant accident (LOCA) were identified. Training and testing data sets were obtained using the MAAP5 code. The results show that the proposed algorithm can correctly classify the break location of the LOCA and can estimate the break size of the LOCA very accurately. In addition, the occurrence times of severe accident major events were predicted under various severe accident paths, with reasonable error. With these results, it is expected that it will be possible to apply the proposed algorithm to real NPPs because the algorithm uses only the early phase data after the reactor SCRAM, which can be obtained accurately for accident simulations.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.2
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• pp.247-253
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• 2023

According to NSSC Notice No. 2021-10, safety analysis needs to be introduced in the decommissioning plan. Public and occupational dose analyses should be conducted, specifically for unexpected radiological accidents. Herein, based on the risk matrix and analytic hierarchy process, the method of selecting accident scenarios during the decommissioning of nuclear power plants has been proposed. During decommissioning, the generated spent resin exhibits relatively higher activity than other generated wastes. When accidents occur, the release fraction varies depending on the conditioning method of radioactive waste and type of radioactive nuclides or accidents. Occupational dose analyses for 2 (fire and drop) among 11 accident scenarios have been performed. The radiation doses of the additional exposures caused by the fire and drop accidents are 1.67 and 4.77 mSv, respectively.

• Nuclear Engineering and Technology
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• v.42 no.2
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• pp.151-162
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• 2010

A severe accident training simulator that can simulate important severe accident phenomena and nuclear plant behaviors is developed. The simulator also provides several interactive control devices, which are helpful to assess results of a particular accident management behavior. A simple and direct dynamic linked library (DLL) data communication method is used for the development of the simulator. Using the DLL method, various control devices were implemented to provide an interactive control function during simulation. Finally, a training model is suggested for accident mitigation training and its performance is verified through application runs.

• Nuclear Engineering and Technology
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• v.50 no.5
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• pp.717-723
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• 2018

Thermal analysis of accident conditions is an important problem during safety assessment of the dry spent nuclear fuel storage facilities. Thermal aspects of accident conditions with channel blockage of ventilated storage containers are considered in this article. Analysis of flow structure inside ventilated containers is carried out by numerical simulation. The main mechanisms of heat and mass transfer, which take part in spent nuclear fuel cooling, were detected. Classification of accidents on the basis of their influence on the maximum temperatures inside storage casks is proposed.