• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.9-15
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• 2023

The Severe Disaster Punishment Act had recently been established in order to promote safety and health (OSH) management system for severe accident prevention. OSH management system is primarily designed based on risk assessments; however, companies in industries have been experiencing difficulties in hazard identification and selecting proper measures for risk assessments and accident prevention. This study intended to introduce an accident analysis method based on epidemiological model in finding hazard and preventive measures. The accident analysis method employed in this study was proposed by the U.S. Department of Energy. To demonstrate the effectiveness of the accident analysis method, this study applied it to two accident cases occurred in construction and manufacturing industries. The application process and results of this study can be utilized in improving OSH management system and preventing severe accidents.

• Journal of the Korean Society of Safety
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• v.32 no.5
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• pp.179-185
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• 2017

Accident analysis is an essential process to make basic data for accident prevention. Most researches depend on survey data and accident statistics to analyze accidents, but these kinds of data are not sufficient for systematic and detailed analysis. We, in this paper, propose an accident classification model that extracts task type, original cause materials, accident type, and the number of deaths from accident reports. The classification model is a support vector machine (SVM) with word occurrence features, and these features are selected based on mutual information. Experiment shows that the proposed model can extract task type, original cause materials, accident type, and the number of deaths with almost 100% accuracy. We also develop an accident ontology to express the information extracted by the classification model. Finally, we illustrate how the proposed classification model and ontology effectively works for the accident analysis. The classification model and ontology are expected to effectively analyze various accidents.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.246-251
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• 2005

Accident scenarios analysis is a course to understand, analyze, and describe a process of an accident and behavior pattern of the parties to an accident. The method of accident scenarios is that we described patterns represented between accidents and hazardous conditions, and then provide data to prevent the accident. We have carried out scenarios analysis in various fields so far, but it was not taking account of system. In this research, we made a study on technology of accident scenarios analysis using QFD (Quality Function Deployment) to analyze systematically and evaluate quantitatively types of hazards and scenarios of railway accident. And we analyses accident scenarios of a subject of work-related fatality accident to railway employee and conducted risk assessment for different scenarios. Also we defined relation between unsafe events and hazardous conditions caused to work-related fatality accident, and attempted to quantitatively assess work-related fatality accident and the parties to accidents. The results of this research will be used in analyzing for important causes and contributing factors of work-related fatality accidents at the step of risk assessment of railway system, and quantitatively assessing frequency of work-related accidents and risk.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.1
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• pp.87-94
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• 2017

Many industrial accidents have occurred continuously in the manufacturing industries, construction industries, and service industries of Korea. Fatal accidents have occurred most frequently in the construction industries of Korea. Especially, the trend analysis of the accident rate and fatal accident rate is very important in order to prevent industrial accidents in the construction industries systematically. This paper considers forecasting of the accident rate and fatal accident rate with static and dynamic time series analysis methods in the construction industries. Therefore, this paper describes the optimal accident rate and fatal accident rate by minimization of the sum of square errors (SSE) among regression analysis method (RAM), exponential smoothing method (ESM), double exponential smoothing method (DESM), auto-regressive integrated moving average (ARIMA) model, proposed analytic function model (PAFM), and kalman filtering model (KFM) with existing accident data in construction industries. In this paper, microsoft foundation class (MFC) soft of Visual Studio 2008 was used to predict the accident rate and fatal accident rate. Zero Accident Program developed in this paper is defined as the predicted accident rate and fatal accident rate, the zero accident target time, and the zero accident time based on the achievement probability calculated rationally and practically. The minimum value for minimizing SSE in the construction industries was found in 0.1666 and 1.4579 in the accident rate and fatal accident rate, respectively. Accordingly, RAM and ARIMA model are ideally applied in the accident rate and fatal accident rate, respectively. Finally, the trend analysis of this paper provides decisive information in order to prevent industrial accidents in construction industries very systematically.

• Journal of the Korean Society of Safety
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• v.17 no.1
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• pp.94-98
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• 2002

This study aimed to search for the fundamental accident causes using a categorical analysis, a kind of statistical methods. As the analysis methods, correlation analysis, independence test and logistic regression analysis were used. And the SPSS package, a general-purpose mathematical library, was used to obtain statistical characteristics. As the result of this study, the accident causes associated with factor of 'lost working days' were factors such as 'employed periods', 'sex', 'type of accident', 'month'. In case of applying independence test method, the most important cause was the factor of 'month'. In case that logistic regression analysis method was applied, the cause contributed to the increase structure'. 'less than 6 month'. On the basis of these results, the plan for accident prevention and the proper investment for accident prevention expenditure could be carried out in each workshop.

• Journal of Multimedia Information System
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• v.5 no.2
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• pp.111-114
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• 2018

Traffic accident analysis is important to reduce the occurrence of the accidents. In this paper, we analyze the traffic accident with Apriori algorithm to find out an association rule of traffic accident in Korea. We first design the traffic accident analysis model, and then collect the traffic accidents data. We preprocessed the collected data and derived some new variables and attributes for analyzing. Next, we analyze based on statistical method and Apriori algorithm. The result shows that many large-scale accident has occurred by vans in daytime. Medium-scale accident has occurred more in day than nighttime, and by cars more than vans. Small-scale accident has occurred more in night time than day time, however, the numbers were similar. Also, car-human accident is more occurred than car-car accident in small-scale accident.

• Journal of the Korean Society of Safety
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• v.36 no.3
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• pp.50-59
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• 2021

The main purpose of accident analysis is to identify the causal factors and the mechanisms of those factors leading to the accident. However, current accident analysis techniques focus only on finding the factors related to the accident without providing more insightful results, such as structures or mechanisms. For this reason, preventive actions for safety management are concentrated on the elimination of causal factors rather than blocking the connection or chain of accident processes. This greatly reduces the effectiveness of safety management in practice. In the present study, a technique to model the correlational structure of accident risk factors is proposed by using the co-occurrence keyword network analysis technique. To investigate the effectiveness of the proposed technique, a case study involving a portable ladder fall accident is conducted. The results indicate that the proposed technique can construct the correlational structure model of the risk factors of a portable ladder fall accident. This proves the effectiveness of the proposed technique in modeling the correlational structure of accident risk factors.

• Journal of the Korean Society of Safety
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• v.33 no.5
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• pp.28-34
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• 2018

Recently, various engineering approaches have been widely used in the accident investigation field to identify the cause of the accident and to predict damage by accident. Computational analysis is the most commonly used method of accident investigation technique. This technique is mainly used to identify the mechanism of the accident generation and to determine the cause when it is difficult to reproduce the situation at the time of the accident or when it is impossible to perform a reproduction experiment. In this study, The computational fluid dynamics analysis for nitrogen asphyxiation accident generated by defect of building structural between diffusion outlet and cooling tower was performed to determine the inflow path of the suffocation gas, death possibility by concentration of suffocation gas and predicted the time of death due to the accident using 3D modeling and FLACS program. We can quantify diffusion concentration of asphyxiation gas and predict mechanism of death occurrence by accident and evaluate the consequence Analysis through this study. In the future, This method can be widely used in the field of gas safety by improving the reliability and validity of the analysis.

• Nuclear Engineering and Technology
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• v.44 no.3
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• pp.311-322
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• 2012

Since the crisis at the Fukushima plants, severe accident progression during a station blackout accident in nuclear power plants is recognized as a very important area for accident management and emergency planning. The purpose of this study is to investigate the comparative characteristics of anticipated severe accident progression among the three typical types of nuclear reactors. A station blackout scenario, where all off-site power is lost and the diesel generators fail, is simulated as an initiating event of a severe accident sequence. In this study a comparative analysis was performed for typical pressurized water reactor (PWR), boiling water reactor (BWR), and pressurized heavy water reactor (PHWR). The study includes the summarization of design differences that would impact severe accident progressions, thermal hydraulic/severe accident phenomenological analysis during a station blackout initiated-severe accident; and an investigation of the core damage process, both within the reactor vessel before it fails and in the containment afterwards, and the resultant impact on the containment.

• Journal of the Korean Society of Safety
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• v.33 no.3
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• pp.1-7
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• 2018

Recently, various engineering approaches have been widely used in the accident investigation field to identify the cause of the accident and to predict damage by accident. Computational analysis is the most commonly used method of accident investigation technique. This technique is mainly used to identify the mechanism of the accident generation and to determine the cause when it is difficult to reproduce the situation at the time of the accident or when it is impossible to perform a reproduction experiment. In this study, The gas explosion analysis for LPG explosion accident generated by defect of the blocking action was performed to determine the accident object, gas leakage amount and predicted the damage caused by the accident using 3D laser scanner and FLACS program. We can quantify the explosive power by LPG gas accident and predict the gas leakage amount, damage by accident and evaluate the stability of the structure through this study. In the future, This method can be widely used in the field of gas safety by improving the reliability and validity of the analysis.