• Korean journal of communication and information
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• v.76
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• pp.124-150
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• 2016

The aim of this study is to see the change of the general characteristics and frame of nuclear power plant news in Korea from comparing the before Fukushima nuclear accident in Japan on March 11, 2011 with the after. To this aim, the national daily newspapers and the local daily newspapers in Busan located nuclear power plants were selected, and the content analysis of the newspaper stories about nuclear power plants was done. In research results, the stories about nuclear power plants in Korean newspapers increased greatly after Fukushima nuclear accident. Before the accident the nuclear power plant stories about economy held a large majority, while after the accident the stories about society held. Fukushima nuclear accident served as the momentum that the nuclear power plant stories in Korea became main news. Meanwhile, the frame of nuclear power plant stories in Korean newspapers changed greatly after the accident. Justly the environmental security frame increased greatly, because of increasing greatly the stories about security of nuclear power plants with Fukushima nuclear accident. Particularly in the local daily newspapers in Busan before the accident the environmental security frame was 29.3% of stories about nuclear power plants, and after the accident the frame was 77.6%.

• Nuclear Engineering and Technology
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• v.49 no.2
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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.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1261-1270
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• 2022

This study was conducted to investigate the possibility of using gaze entropy to evaluate an operator's situation awareness in an emergency accident situation of a nuclear power plant. Gaze entropy can be an effective measure for evaluating an operator's situation awareness at a nuclear power plant because it can express gaze movement as a single comprehensive number. In order to determine the relationship between situation awareness and gaze entropy for an emergency accident situation of a nuclear power plant, an experiment was conducted to measure situation awareness and gaze entropy using simulators created for emergency accident situations LOCA, SGTR, SLB, and LOV. The experiment was to judge the accident situation of nuclear power plants presented in the simulator. The results showed that situation awareness and Shannon, dwell time, and Markov entropy had a significant negative correlation, while visual attention entropy (VAE) did not show any significant correlation with situation awareness. The results determined that Shannon entropy, dwell time entropy, and Markov entropy could be used as measures to evaluate situation awareness.

• Journal of Science Education
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• v.37 no.2
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• pp.294-309
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• 2013

This study addressed the awareness of social issues related to science of future elementary school teachers. Fukushima Nuclear Power Plant Accident was used by concrete issue connected with SSI for this study. Twelve second-year students attending a university of education participated in the study, who were taking a class of science teacher preparation at that time that consists of the content of the elementary science education courses. The study revealed that all the pre-service elementary teachers recognized Fukushima Nuclear Power Plant Accident and received such information through various medias. In particular, they were receiving more information about the Nuclear Power Plant Accident through the internet than any other media by using the internet a lot, and also gained additional information through the internet. However, despite the fact that they recognized Nuclear Power Plant Accident, they neither had much information about it nor had been interested in SSI such as the Nuclear Power Plant Accident. Moreover, they had been basically uneducated about SSI. Despite of having no interest in SSI such as Nuclear Power Plant Accident, the study revealed that the pre-service elementary teachers recognized that scientific problems such as Nuclear Power Plant Accident may affect a society closely. In addition, they together sympathized with the point that SSI education should be applied on the current education courses by identifying the problem in application. As the study revealed above, the application of SSI education to the formal education courses as well as more lively research on that subject is very important and urgent for boosting interest in science subjects and enlightening the nature of science that is one of the objectives of science education.

• 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.49 no.3
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• pp.632-637
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• 2017

Even though the potential for an accident in nuclear power plants is very low, multiple emergency plans are necessary because the impact of such an accident to the public is enormous. One of these emergency plans involves a robotic system for investigating accidents under conditions of high radiation and contaminated air. To develop a robot suitable for operation in a nuclear power plant, we focused on eliminating the three major obstacles that challenge robots in such conditions: the disconnection of radio communication, falling on uneven floors, and loss of localization. To solve the radio problem, a Wi-Fi extender was used in radio shadow areas. To reinforce the walking, we developed two- and four-leg convertible walking, a floor adaptive foot, a roly-poly defensive falling design, and automatic standing recovery after falling methods were developed. To allow the robot to determine its location in the containment building, a bar code landmark reading method was chosen. When a severe accident occurs, this robot will be useful for accident condition monitoring. We also anticipate the robot can serve as a workman aid in a high radiation area during normal operations.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.426-433
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• 2017

This paper describes the development process, the innovative techniques used and insights gained from the latest integrated, full scope, multistate Level 2 PSA analysis conducted at the Leibstadt Nuclear Power Plant (KKL), Switzerland. KKL is a modern single-unit General Electric Boiling Water Reactor (BWR/6) with Mark III Containment, and a power output of $3600MW_{th}/1200MW_e$, the highest among the five operating reactors in Switzerland. A Level 2 Probabilistic Safety Assessment (PSA) analyses accident phenomena in nuclear power plants, identifies ways in which radioactive releases from plants can occur and estimates release pathways, magnitude and frequency. This paper attempts to give an overview of the advanced modeling techniques that have been developed and implemented for the recent KKL Level 2 PSA update, with the aim of systematizing the analysis and modeling processes, as well as complying with the relatively prescriptive Swiss requirements for PSA. The analysis provides significant insights into the absolute and relative importances of risk contributors and accident prevention and mitigation measures. Thanks to several newly developed techniques and an integrated approach, the KKL Level 2 PSA report exhibits a high degree of reviewability and maintainability, and transparently highlights the most important risk contributors to Large Early Release Frequency (LERF) with respect to initiating events, components, operator actions or seismic component failure probabilities (fragilities).

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.2
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• pp.61-68
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• 2020

Nuclear power plants have a lower cost of power generation, and they are more eco-friendly than other power generation plants. Also, we need to prepare nuclear plant accidents because of their severe damage. In the event of a safety accident, such as a radiation leak, by applying a wireless sensor network to a nuclear power plant, many sensor nodes can be used to monitor radiation and transmit information to an external base station to appropriately respond to the accident. However, applying a wireless sensor network to nuclear power plants requires routing protocols that consider the sensor network size and bypass obstacles such as plant buildings. In general, the hierarchical-based routing protocols are efficient in energy consumption. In this study, we look into the problems that may occur if hierarchical-based routing protocols are applied to nuclear power plants and propose improved routing protocols to solve these problems. Simulation results show that the proposed routing protocol is more effective in energy consumption than the existing LEACH protocol.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.5 no.2
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• pp.35-39
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• 2009

In this study, Event Type Analysis System (ETAS) is developed for the accident evaluation in nuclear power plant. The ETAS system can be used in supporting regulator and/or operator under event situation in nuclear power plants. The ETAS system can categorize the all transient events to 3 categories such as Down-2000, Down-2173, and Slow Fluctuation. We develop the program structure for ETAS system and web-based ETAS system. The ETAS system will be used as sub module of Knowledge-Based Event Evaluation Network (K-EvENT) which is developing for the against the accident in nuclear power plants.

• Journal of the Korea Safety Management & Science
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• v.7 no.4
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• pp.85-99
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• 2005

The main objective of this paper is to search whether containment vessel's best pressure may increase until how long when loss of coolant accident (LOCA) happened in containment vessel of Ulchin nuclear power plant 1 and 2. Another goal of this research is to find the influential factors that increase containment vessel pressure. Model for this research is Ulchin nuclear power plant 1 with 10 cycles. Data were collected by simulator of Ulchin nuclear power plant 1 and design of experiment was used for data analysis. For the experiment, seven factors that are going to influence in containment vessel pressure were chosen. It was found that fatter which influences in early rise of containment vessel pressure after LOCA is only explosion size. Also, containment vessel's best pressure (3.74 bar.a) was much lower than limit (4.86 bar.a) of FSAR (Final Safety Analysis Report).