• Journal of the Korean Society of Safety
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• v.16 no.1
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• pp.84-87
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• 2001

Severe accident management can be defined as the use of existing and alternative resources, systems, and actions to prevent or mitigate a core-melt accident in nuclear power plants. TRAIN (Training pRogram for AMP In NPP), developed for training control room staff and the technical group, is introduced in this paper. The TRAIN composes of phenomenological knowledge base (KB), accident sequence KB and accident management procedures with AM strategy control diagrams and information needs. This TRAIN might contribute to training them by obtaining phenomenological knowledge of severe accidents, understanding plant vulnerabilities, and solving problems under high stress.

• Nuclear Engineering and Technology
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• v.36 no.6
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• pp.497-511
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• 2004

A PSV (pressurizer safety valve) popping test carried out in the early phases of a refueling outage may trigger a test-induced LOCA(loss of coolant accident) if a PSV fails to fully close and is stuck in a partially open position. According to a KSNP (Korea standard nuclear power plant) low power and shutdown PSA (probabilistic safety assessment), the failure of a high pressure safety injection (HPSI) accompanied by the failure of a PSV to fully close was identified as a dominant accident sequence with a significant impact on low power and shutdown risks (LPSR). In this study, we aim to investigate and verify a new means for mitigating this type of accident using a thermal-hydraulic analysis. In particular, we explore the applicability of an aggressive cool-down combined with operator actions. The results of the various sensitivity studies performed there will help reduce LPSR and improve Refueling outage safety.

• Journal of Radiation Protection and Research
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• v.46 no.2
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• pp.66-79
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• 2021

Background: The Japan Atomic Energy Agency (JAEA) is specified in the Disaster Counter-measures Basic Act as a designated public corporation for dealing with nuclear disasters. Materials and Methods: The Nuclear Emergency Assistance and Training Center (NEAT) was established in 2002 as the activity base providing technical assistance to both national and local governments during nuclear emergencies. The NEAT has a robust structure and utilities and special installations, and it organizes training and exercises. Results and Discussion: Due to an offshore earthquake that caused a devastating tsunami in March 2011, a nuclear accident occurred at the Tokyo Electric Power Company's Fukushima Daiichi Nuclear Power Station. The NEAT responded by conducting off-site environmental radiation monitoring and contamination screening, dispatching special vehicles, offering telephone consultations, and calculating the dispersion of radioactive materials. An examination of the emergency response activities revealed that the organization was prepared for these types of disasters and was able to plan long-term response. Conclusion: As a designated public corporation, the JAEA technically supports the national government, the Fukushima prefectural government, and the Ibaraki prefectural government, all of which responded to the off-site emergencies resulting from the March 2011 Fukushima Daiichi accident

• Korean Journal of Agricultural Science
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• v.44 no.4
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• pp.620-635
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• 2017

This study was intended to identify the main factors responsible for the decline in purchase of imported agricultural and fish products after Japan's nuclear power plant accident in 2011 and to compare the effects on imported agricultural produce and imported fish products. Logit model and multiple regression model analyses were performed using consumers' survey data. Psychological and qualitative factors reflecting consumers' food safety awareness and purchasing preferences, which were extracted by Factor analysis, were included as the models' explanatory variables, along with socio-demographic and economic factors. The Logit estimation showed aged, married, and low-income households had significantly higher probability of reducing their purchases of imported agricultural and fish products. However, the multiple regression results pointed out that the actual rate of decrease of imported agricultural and fish products purchases were more significantly affected by non-socio demographic factors such as past experience of purchasing imported agricultural and fish products, future intention to purchasing Japanese agricultural and fish products, and the ratio of imported to domestic agricultural and fish products before the nuclear accident, as well as consumers' feeling of food insecurity and their purchasing preferences. Moreover, the results showed that Korean consumers have reacted more sensitively to the decline in imported fish products than imported agricultural produce after the nuclear accident based on the marginal effects of various socio-demographic and economic factors.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.21 no.1
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• pp.95-114
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• 2023

During the decades after the Fukushima Daiichi Nuclear Power Station (FDNPS) accident, ambient dose rates have markedly decreased when compared to those at the early state of the accident. Government projects have been continuously conducted by surveying the ambient dose rate and radiocesium distributions. Airborne surveys using crewed helicopters and unmanned aerial vehicles (UAVs) are the best methods for obtaining an overall picture of the distribution. However, ground-based surveys are required for accurate measurements near the population. The differences between these methods include the knowledge of the post depositional behavior of radionuclides in land use. The survey results form the basis for policy decisions such as lifting evacuation zones, decontamination, and other countermeasures. These surveys contain crucial findings regarding post-accident responses. This paper reviews the survey methods of government projects and current situation around the FDNPS. The visualization methods and databases of ambient dose rates are also reviewed to provide information to the population.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.814-826
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• 2023

Sensor faults in nuclear power plant instrumentation have the potential to spread negative effects from wrong signals that can cause an accident misdiagnosis by plant operators. To detect sensor faults and make accurate accident diagnoses, prior studies have developed a supervised learning-based sensor fault detection model and an accident diagnosis model with faulty sensor isolation. Even though the developed neural network models demonstrated satisfactory performance, their diagnosis performance should be reevaluated considering real-time connection. When operating in real-time, the diagnosis model is expected to indiscriminately accept fault data before receiving delayed fault information transferred from the previous fault detection model. The uncertainty of neural networks can also have a significant impact following the sensor fault features. In the present work, a pilot study was conducted to connect two models and observe actual outcomes from a real-time application with an integrated system. While the initial results showed an overall successful diagnosis, some issues were observed. To recover the diagnosis performance degradations, additive logics were applied to minimize the diagnosis failures that were not observed in the previous validations of the separate models. The results of a case study were then analyzed in terms of the real-time diagnosis outputs that plant operators would actually face in an emergency situation.

• Nuclear Engineering and Technology
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• v.47 no.2
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• pp.139-147
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• 2015

Recently, severe accidents in nuclear power plants (NPPs) have become a global concern. The aim of this paper is to predict the hydrogen buildup within containment resulting from severe accidents. The prediction was based on NPPs of an optimized power reactor 1,000. The increase in the hydrogen concentration in severe accidents is one of the major factors that threaten the integrity of the containment. A method using a fuzzy neural network (FNN) was applied to predict the hydrogen concentration in the containment. The FNN model was developed and verified based on simulation data acquired by simulating MAAP4 code for optimized power reactor 1,000. The FNN model is expected to assist operators to prevent a hydrogen explosion in severe accident situations and manage the accident properly because they are able to predict the changes in the trend of hydrogen concentration at the beginning of real accidents by using the developed FNN model.

• Nuclear Engineering and Technology
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• v.50 no.4
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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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• v.48 no.5
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• pp.1206-1218
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• 2016

This article proposes a highly reliable power and communication system that guarantees the protection of essential instruments in a nuclear power plant under a severe accident. Both power and communication lines are established with not only conventional wired channels, but also the proposed wireless channels for emergency reserve. An inductive power transfer system is selected due to its robust power transfer characteristics under high temperature, high pressure, and highly humid environments with a large amount of scattered debris after a severe accident. A thermal insulation box and a glass-fiber reinforced plastic box are proposed to protect the essential instruments, including vulnerable electronic circuits, from extremely high temperatures of up to $627^{\circ}C$ and pressure of up to 5 bar. The proposed wireless power and communication system is experimentally verified by an inductive power transfer system prototype having a dipole coil structure and prototype Zigbee modules over a 7-m distance, where both the thermal insulation box and the glass-fiber reinforced plastic box are fabricated and tested using a high-temperature chamber. Moreover, an experiment on the effects of a high radiation environment on various electronic devices is conducted based on the radiation test having a maximum accumulated dose of 27 Mrad.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3599-3616
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• 2023

After a nuclear power plant (NPP) accident, it would be helpful to predict the movement of the radioactive plume emitted from the NPP as accurately as possible to protect the nearby population. Radioactive plumes are mainly affected by wind direction and speed. Since it is difficult to identify the wind direction and speed immediately after the accident, a good understanding of the historical wind data could save many lives and ensure smoother evacuation procedures. In this study, wind data for the past 10 years are analyzed for the five NPPs in the Republic of Korea (ROK). The analyzed data include wind direction and wind speed from 2012 to 2021. In particular, the characteristics of the wind field blowing from the NPPs to the nearest densely populated regions are examined. Finally, suggestions to improve evacuation plans are made.