• Journal of the Korean Society of Safety
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• v.24 no.3
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• pp.79-87
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• 2009

The objective of this study is to develop accident scenario models for the risk assessment of railway casualty accidents. To develop these scenario models, hazardous events and hazardous factors were identified by gathering various accident reports and information. Then, the accident scenario models were built up. Each accident scenario model consists of an occurrence scenario model and a progress scenario model. The occurrence scenario refers to the occurrence process of the event before the hazardous event. The progress scenario means the progress process of the event after the hazardous event. To manage a large amount of accident/incident data and scenarios, a railway accident analysis information system was developed using railway accident scenario models. To test the feasibility of the developed scenario models, more than 800 domestic railway casualty accidents that occurred in 2004 and 2005 were investigated and quantitative and qualitative analyses were performed using the developed information system.

• Journal of the Korean Society of Safety
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• v.32 no.6
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• pp.137-142
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• 2017

This study deals with the relation between traffic accident and urban decline. The purpose of this study is to develop the regional accident models of elderly drivers. In order to develop the count data models, 2009-2015 traffic accident data from TAAS(traffic accident analysis system) and urban decline data from urban regeneration information system are collected. The main results are as follows. First, the null hypothesis that there is no difference in the accident number between elderly and non-elderly drivers is rejected. Second, 8 accident models which are all statistically significant have been developed. Finally, common variables between elderly and non-elderly are ratio of elderly people, elderly person living alone/1,000 persons and wholesale/retail employments/1,000 persons. This study could be expected to give many implications to making regional accident reduction policy.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.836-842
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• 2016

When an accident occurs in the nuclear power plant, the faulted information might mislead to the high possibility of aggravating the accident. At the Fukushima accident, the operators misunderstood that there was no core exposure despite in the processing of core damage, because the instrument information of the reactor water level was provided to the operators optimistically other than the actual situation. Thus, this misunderstanding actually caused to much confusions on the rapid countermeasure on the accident, and then resulted in multiplying the accident propagation. It is necessary to be equipped with the function that informs operators the status of instrument integrity in real time. If plant operators verify that the instruments are working properly during accident conditions, they are able to make a decision more safely. In this study, we have performed various tests for the fault detection sensitivity of an data-driven empirical model to review the usability of the model in the accident conditions. The test was performed by using simulation data from the compact nuclear simulator that is numerically simulated to PWR type nuclear power plant. As a result of the test, the proposed model has shown good performance for detecting the specified instrument faults during normal plant conditions. Although the instrument fault detection sensitivity during plant accident conditions is lower than that during normal condition, the data-drive empirical model can be detected an instrument fault during early stage of plant accidents.

• Journal of the Korean Society of Safety
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• v.25 no.6
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• pp.47-52
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• 2010

Many industrial accidents have occurred over the years in the manufacturing and construction industries in Korea. However, as the service industry has increased continuously, the share of the accident rate in the service industry was 39.07% in 2009, while the manufacturing industry share was 33.73%. The service industry share overtook the manufacturing industry share for the first time. Therefore, this research considers prevention of industrial accidents in the service industry as well as manufacturing and construction industries. This paper describes a procedure and a method to estimate efficient accident rate forecasting and estimated zero accident time in the service industry in order to prevent industrial accidents in the transportation, storage, and telecommunication divisions. This paper proposes a model using an analytical function for the sake of very efficient accident rate forecasting. Accordingly, this paper has develops a program for accident rate forecasting, zero accident time estimating, and calculation of achievement probability through MFC (Microsoft Foundation Class) software Visual Studio 2008 in the transportation, storage, and telecommunication divisions. In results of this paper, ARIMA (Auto Regressive Integrating Moving Average) is regarded as a very efficient forecasting model for the transportation, storage, and telecommunication division. In testing this model, value minimizing the Sum of Square Errors (SSE) was calculated as 0.2532. Finally the results of this paper are sure to help establish easy accident rate forecasting and strategy or method of zero accident time in the service industry for prevention of industrial accidents.

• International Journal of Highway Engineering
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• v.18 no.6
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• pp.153-160
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• 2016

OBJECTIVES : The objective of this study is to develop a traffic accident model of a roundabout based on the type of land use. METHODS : The traffic accident data from 2010 to 2014 were collected from the "traffic accident analysis system (TAAS)" data set of the Road Traffic Authority. A multiple linear regression model was utilized in this study to analyze the accidents based on the type of land use. Variables such as geometry and traffic volume were used to develop the accident models based on the type of land use. RESULTS : The main results are as follows. First, the null hypothesis that the type of land use does not affect the number of accidents is rejected. Second, four accident models based on the type of land use have been developed, which are statistically significant (high $R^2$ values). Finally, the total entering and circulating volumes, area of the central island, number of speed breakers, mean number of entry lanes, diameter of the inscribed circle, mean width of the entry lane, area of the roundabout, bus stops, and number of circulatory roadways are analyzed to see how they affect the accident for each type of land use. CONCLUSIONS : The development of the accident models based on the type of land use has revealed that the accident factors at a roundabout are different for each case. Thus, more speed breakers in commercial areas and an inscribed circle of proper diameter in commercial and residential areas are determined to be important for reducing the number of accidents. Additionally, expanding the width of the entry lanes, decreasing the area of the roundabouts in residential areas, and reducing the conflict factors such as bus stops in green spaces are determined to be important.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.10a
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• pp.73-74
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• 2016

Although various research is being carried out to prevent the construction accidents, the number of victims of construction site is increasing continuously. Therefore, the purpose of this study is construction accidents prediction applying the boosting algorithm to the construction domains. Boosting algorithm was applied to construct construction accident prediction model and application of the model was examined using actual accident cases. It is possible to support safety manager to manage and prevent accidents in priority using the model.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.91-98
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• 2011

We develop a model to predict traffic accidents in Korea. In contrast to the classical approach that mainly uses regression analysis, Bayesian approach is adopted. A dependent model that incorporates the data from different kinds of accidents is introduced. The rate of severe accident can be updated even with no data of the same kind. The data of minor accident that can be obtained frequently is efficiently used to predict the severe accident.

• Journal of Korean Port Research
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• v.13 no.1
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• pp.101-112
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• 1999

Traffic accidents increase with the increase of the vehicles in operation on the street. Especially big traffic accidents composed of over 3 killed or 20 injured accidents with the property damage become one of the serious problems to be solved in most of the cities. The purpose of this study is to build the discrimination model on big traffic accidents using the Quantification II theory for establishing the countermeasures to reduce the big traffic accidents. The results are summarized as follows. 1)The existing traffic accident related model could not explain the phenomena of the current traffic accident appropriately. 2) Based on the big traffic accident types vehicle-vehicle, vehicle-alone, vehicle-pedestrian and vehicle-train accident rates 73%, 20.5% 5.6% and two cases respectively. Based on the law violation types safety driving non-fulfillment center line invasion excess speed and signal disobedience were 48.8%, 38.1% 2.8% and 2.8% respectively. 3) Based on the law violation types major factors in big traffic accidents were road and environment, human, and vehicle in order. Those factors were vehicle, road and environment, and human in order based on types of injured driver’s death. 4) Based on the law violation types total hitting and correlation rates of the model were 53.57% and 0.97853. Based on the types of injured driver’s death total hitting and correlation rates of the model were also 71.4% and 0.59583.

• Fire Science and Engineering
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• v.33 no.6
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• pp.72-79
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• 2019

Through this study, we developed a model for predicting chemical accidents lead to casualties. The model was derived from the logistic regression analysis model and applied to the variables affecting the accident. The accident data used in the model was analyzed by studying the statistics of past chemical accidents, and applying independent variables that were statistically significant through data analysis, such as the type of accident, cause, place of occurrence, status of casualties, and type of chemical accident that caused the casualties. A significance of p < 0.05 was applied. The model developed in this study is meaningful for the prevention of casualties caused by chemical accidents and the establishment of safety systems in the workplace. The analysis using the model found that the most influential factor in the occurrence of casualty in accidents was chemical explosions. Therefore, there is an urgent need to prepare countermeasures to prevent chemical accidents, specifically explosions, from occurring in the workplace.

• 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.