• Journal of the Korean Institute of Gas
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• v.23 no.5
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• pp.35-43
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• 2019

The safety of industrial valves, which are the core parts of plant facilities, are managed by manpower and there are difficulties because of side area for inspection and limited accessibility due to the nature of facilities. The industrial valves used in plant facilities cause problems such as interrupted production; a loss of life due to leak or explosion of poisonous material and flammable gases, and difficulty in locating accident positions in the event of leakage or failure. Therefore, safety management and control systems based on IoT technology are needed. This study is about the development of risk factor prediction technique among the safety management of industrial valves through IoT- based wireless communication and the development of actuator control system. We have developed IoT-based industrial valve safety management techniques to prevent accidents caused by main risk factors by conducting an analysis of the structural characteristics of valves and an analysis of the causes of main risk factors through review of failure data and literature and an analysis of accident scenarios.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.1-12
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• 2021

Emergence of the COVID 19 pandemic has resulted in a sharp increase in the number of two-wheeler vehicular traffic accidents, prompting the introduction of numerous efforts for their prevention. This study applied XGBoost to determine the factors that affect severity of two-wheeled vehicular traffic accidents, by examining data collected over the past 10 years and analyzing the influence of each factor. Among the total factors assessed, variables affecting the severity of traffic accidents were overwhelmingly high in cases of signal violations, followed by the age group of drivers (60s or older), factors pertaining only to the car, and cases of centerline infringement. Based on the research results, a reasonable legal reform plan was proposed to prevent serious traffic accidents and strengthen safety management of two-wheeled vehicles. Based on the research results, we propose a reasonable legal reform plan to prevent serious traffic accidents and strengthen safety management of two-wheeled vehicles.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.324-330
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• 2023

Aids to navigation, which provide information about a ship's position, direction, and the location of obstacles, are crucial for uninterrupted maritime services. This study aimed to analyze accidents involving aids to navigation that resulted in service disruptions and identify the key factors associated with these accidents. Aids to navigation accident data from 2000 to 2022 were utilized to achieve this. We categorized accidents by accident type, cause, region, season, and type of navigation aid and established a network through correlation analysis. Bayesian networks based on aids to navigation accidents were assigned prior probabilities, and the factors that increased the probability of accidents for different types of aids to navigation were identified. The findings can be used to infer the causes of unreported aids to navigation accidents and serve as foundational data for the prevention of such accidents.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.3
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• pp.259-267
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• 2016

The study performs a risk analysis on container ship accidents using accident data collected over the six years from 2006 to 2011, presents the resulting risk level, and suggests three risk mitigation measures to reduce the overall risk, for the safer operation of container ships. More specifically, starting from the initial accident of collision, we developed 13 different accident scenarios using event tree analysis based on which the overall risk level was obtained and presented as a FN curve. Since diverse human factors are the main cause of most of the ship accidents, our study focuses on the effect of reducing human causes on the resulting risk level. For the research we considered the injuries for the calculation of fatality with the help of MAIS. The results show that collision was the main type of accident, accounting for 62 % of all accidents, and the measures employed were proven to be effective in the sense that the risk level was much lowered and the average number of fatalities was also reduced. With more data accumulated, more precise risk level will be calculated with which the practical risk mitigating measures will be also developed. For future study, economic loss and environmental damage as consequences need to be considered.

• Journal of the Korean Society of Safety
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• v.24 no.5
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• pp.69-76
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• 2009

The estimation of costs from industrial accidents is very important because they have a serious effect on individuals, companies, and nation. The department of labor estimates the cost of accidents by using the "Heinrich" method. From that method, the scale of accident cost can be approximately computed, but accurate calculation of uninsured cost is not easy. Therefore, a better method of calculating uninsured cost caused by industrial accident is necessary. This study aimed to construct an estimation method of uninsured cost according to domestic circumstances. The results of this study are as follows: (1) This study derived applicable factors for quantitative estimation of industrial accident cost (2) This study made the equation that the calculation of each item of uninsured cost was possible (3) This study applied the uninsured cost by degrees of disaster to individual items (4) The subjects and types of occurrence in uninsured cost were analyzed and presented. Theses results will provide a basis for further researchers of uninsured cost.

• 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.47 no.4
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• pp.461-471
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• 2015

Recently, the estimation of the social cost of energy sources has been emphasized as various novel energy options become feasible in addition to conventional ones. In particular, the social cost of introducing measures to protect power-distribution systems from power-source instability and the cost of accident-risk response for various power sources must be investigated. To account for these risk factors, an integrated societal risk assessment framework, based on power-uncertainty analysis and accident-consequence analysis, is proposed. In this study, we applied the proposed framework to nuclear power plants, solar photovoltaic systems, and wind-turbine generators. The required capacity of gas-turbine power plants to be used as backup power facilities to compensate for fluctuations in the power output from the main power source was estimated based on the performance indicators of each power source. The average individual health risk per terawatt-hours (TWh) of electricity produced by each power source was quantitatively estimated by assessing accident frequency and the consequences of specific accident scenarios based on the probabilistic risk assessment methodology. This study is expected to provide insight into integrated societal risk analysis, and can be used to estimate the social cost of various power sources.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.2
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• pp.457-463
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• 2012

Changing the environment around detecting areas may lower the performance of a video-based accident detection system. Region of interest(ROI) and background information changing constantly on account of the car headlights at night and a sudden changes in the weather are the biggest factors to increase the ratio of wrong results. Thus, we proposed and implemented the integrated accident detection system combined the video-based system and the laser-based imaging system. In this paper, we were able to overcome the majority problem of video-based system and it was a meaningful results that it can improve the reliability for the system.

• Proceedings of the Safety Management and Science Conference
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• 2010.04a
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• pp.141-147
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• 2010

Risk level for each construction work can be very important factors to establish advanced preventionmeasures. But it is important how to produce it. There are three different methods to set it up for consturuction situation. They are as follows; 1) occurrence frequency = the number of accident workers of each work kind / yearly accident workers 2) occurrence frequency = the number of accident workers of each work kind / yearly workers 3) occurrence frequency = the number of accident workers of each work kind / the total workers All these three concepts(=averaged concept)are analyzed. Additionally frequency based on discrete curve, and severity based on continuous curve are also combined for producing risk level with more scientific approach. This risk level can be very useful to make prevention plan or take measures at construction sites. This is study result can change existing risk level concept to new concept of it, namely rail way work and in-water work showed be high risk level and RC work be low risk level, different from the situation which we have thought commonly, so far.

• Journal of the Ergonomics Society of Korea
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• v.22 no.1
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• pp.81-94
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• 2003

The British railway safety research group has developed a risk assessment model for the railway infrastructure and major railway accidents. The major hazardous factors of the railway infrastructure were identified and classified in the model. The frequency rates of critical top events were predicted by the fault tree analysis method using failure data of the railway system components and ratings of railway maintenance experts, The consequences of critical top events were predicted by the event tree analysis method. They classified the Joss of accident due to railway system into personal. commercial and environmental damages. They also classified 110 hazardous event due to railway system into three categories. train accident. movement accident and non-movement accident. The risk assessment model of the British railway system has been designed to take full account of both the high frequency low consequence type events (events occurring routinely for which there is significant quantity of recorded data) and the low frequency high consequence events (events occurring rarely for which there is little recorded data). The results for each hazardous event were presented in terms of the frequency of occurrence (number of events/year) and the risk (number of equivalent fatalities per year).