• Journal of the Korean Society of Earth Science Education
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• v.6 no.3
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• pp.174-184
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• 2013

The purpose of this study was to investigate the awareness of elementary school teachers on the socio-scientific issues. Fukushima Nuclear Power Plant Accident was used by concrete issue connected with SSI for this study. Participants in this study were twelve elementary school teachers studying at K University Graduate School of Education, located in the central region, who underwent a semi-structured interview. The study method was the phenomenological research method which is one of the qualitative research methods, and the interview papers had been examined by three scientific experts. As a result of the study, it was divided into twenty six themes, eight theme clusters, and two categories, and considered the thoughts on the Fukushima nuclear power plant accident, its influence on Korea, the relationship between science and society as a result of the Fukushima nuclear power plant accident, interested in social issues related to science, application in class, response from students and the influence on students. Teachers had a general understanding of science-related social issues, but did not have much interest in the subject. However, they mentioned that to apply the issues in the curriculum would have a positive influence and encourage scientific motivation in students and, furthermore, helped them to develop the awareness of science in their surroundings. A greater interest in socio-scientific issues need to require from teachers and, through including these issues in the curriculum, we should have positive influence in developing science education.

• Journal of Radiation Protection and Research
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• v.46 no.4
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• pp.184-193
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• 2021

Background: The radionuclides released by the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident 9 years ago are still being monitored by various research teams and the Japanese government. Comparison of different surveys' results could help evaluate the exposure doses and the mechanism of radiocesium behavior in the urban environment in the area. In this study, we clarified the relationship between land use and temporal changes in the ambient dose rates (air dose rates) using big data. Materials and Methods: We set a series of 1 × 1 km² meshes within the 80 km zone of the FDNPP to compare the different survey results. We then prepared an analysis dataset from all survey meshes to analyze the temporal change in the air dose rate. The selected meshes included data from all survey types (airborne, fixed point, backpack, and carborne) obtained through the all-time survey campaigns. Results and Discussion: The characteristics of each survey's results were then evaluated using this dataset, as they depended on the measurement object. The dataset analysis revealed that, for example, the results of the carborne survey were smaller than those of the other surveys because the field of view of the carborne survey was limited to paved roads. The location factor of different land uses was also evaluated considering the characteristics of the four survey methods. Nine years after the FDNPP accident, the location factor ranged from 0.26 to 0.49, while the half-life of the air dose rate ranged from 1.2 to 1.6. Conclusion: We found that the decreasing trend in the air dose rate of the FDNPP accident was similar to the results obtained after the Chernobyl accident. These parameters will be useful for the prediction of the future exposure dose at the post-accident.

• 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.

• Journal of the Korean Society of Systems Engineering
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• v.18 no.2
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• pp.58-74
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• 2022

Deterministic accident analysis plays a central role in the nuclear power plant (NPP) safety evaluation and licensing process. Traditionally the conservative approach opted for the point kinetics model, expressing the reactor core parameters in the form of reactivity and power tables. However, with the current advances in computational power, high fidelity multi-physics simulations using real-time code coupling, can provide more detailed core behavior and hence more realistic plant's response. This is particularly relevant for transients where the core is undergoing reactivity anomalies and uneven power distributions with strong feedback mechanisms, such as reactivity initiated accidents (RIAs). This work addresses a RIA, specifically a control element assembly (CEA) withdrawal at power, using the multi-physics analysis tool RELAP5/MOD 3.4/3DKIN. The thermal-hydraulics (TH) code, RELAP5, is internally coupled with the nodal kinetics (NK) code, 3DKIN, and both codes exchange relevant data to model the nuclear power plant (NPP) response as the CEA is withdrawn from the core. The coupled model is more representative of the complex interactions between the thermal-hydraulics and neutronics; therefore the results obtained using a multi-physics simulation provide a larger safety margin and hence more operational flexibility compared to those of the point kinetics model reported in the safety analysis report for APR1400. The systems engineering approach is used to guide the development of the work ensuring a systematic and more efficient execution.

• Journal of Information Technology Services
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• v.8 no.2
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• pp.147-156
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• 2009

As the result of the rapid development of IT technology, an on-line diagnostic system using the field bus communication network coupled with a smart sensor module will be widely used at the nuclear power plant in the near future. The smart sensor system is very useful for the prompt understanding of abnormal state of the key equipments installed in the nuclear power plant. In this paper, it is assumed that a smart sensor system based on the fieldbus communication network for the surveillance and diagnostics of safety-critical equipments will be installed in the harsh-environment of the nuclear power plant. It means that the key components of fieldbus communication system including microprocessor, FPGA, and ASIC devices, are to be installed in the RPV (reactor pressure vessel) and the RCS (reactor coolant system) area, which is the area of a high dose-rate gamma irradiation fields. Gamma radiation constraints for the DBA (design basis accident) qualification of the RTD sensor installed in the harsh environment of nuclear power plant, are typically on the order of 4 kGy/h. In order to use a field bus communication network as an ad-hoc diagnostics sensor network in the vicinity of the RCS pump area of the nuclear power plant, the robust survivability of IT-based micro-electronic components in such intense gamma-radiation fields therefore should be verified. An intelligent CCD camera system, which are composed of advanced micro-electronics devices based on IT technology, have been gamma irradiated at the dose rate of about 4.2kGy/h during an hour UP to a total dose of 4kGy. The degradation performance of the gamma irradiated CCD camera system is explained.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.55
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• pp.25-31
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• 2000

To make a better decision about when to shutdown a nuclear power plant, we build a decision model using influence diagrams. We proceed the analysis adopting a bayesian approach. Firstly, an accident arrival rate is assumed to be known and this assumption is relaxed later. We perform our analysis on the cases of exponential time to accidents, and gamma distribution for the arrival rate. An optimal shutdown time is obtained considering the trade-off between the costs incurred by an accident due to late shutdown and the possible loss of revenues due to the early shutdown. We also derive the upper bound of the failure rate where we may operate the plant.

• Nuclear Engineering and Technology
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• v.48 no.4
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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.

• Proceedings of the Korean Nuclear Society Conference
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• 2001.05a
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• pp.234.1-234
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• 2001

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.05a
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• pp.151-152
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• 2018

In the domestic nuclear power industry, concern about safety of nuclear power plants is continuously increased with the Fukushima nuclear power plant accident. In order to enhance the safety of nuclear power plants, it is important to ensure that the power plants are operating with proper margin within the original design bases. Margin management is the process of ensuring that the NPP designer and operator are aware of the physical and operating limits, and potential and probability of failure, for each component in the plant. All components are subject to margin considerations, but the most important components by scope and attention are those related to safety-related systems and NPP safe shutdown.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.351-353
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• 2022

There have been several nuclear accidents at home and abroad so far, and there have been major and small damages. Overseas, in order to reduce such accidents, the safety and reliability of nuclear power plant operations have been improved by introducing a technology called Configuration Management. Through basic information on Configuration Management and successful cases of introducing Configuration Management from overseas nuclear power plants, this paper checks the technical parts applicable to Korea and examines whether they can be newly applied by supplementing them for domestic nuclear power plants.