• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.5
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• pp.1135-1146
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• 2015

This thesis aims to improve the safety of bicycle traffic for activating the use of bicycle, main means of non-powered and non-carbon transportation in order to cope with worldwide crisis such as climate change and energy depletion and to implement sustainable traffic system. In this regard, I analyzed the problem of bicycle roads currently installed and operated, and developed the bicycle accident forecasting model. Following are the processes for this. First, this study presented the current status of bicycle road in Korea as well as accident data, collect the data on bicycle traffic accidents generated throughout the country for recent 3 years (2009~2011) and analyzed the features of bicycle traffic accidents based on the data. Second, this study selected the variable affecting the number of bicycle accidents through accident feature analysis of bicycle accidents at Jeollanam-do, and developed accident forecast model using the multiple regression analysis of 'SPSS Statistics 21'. At this time, the number of accidents due to extension per road types (crossing, crosswalk, other single road) was used. To verify the accident forecast model deduced, this study used the data on bicycle accident generated in Gwangju, 2011, and compared the prediction value with actual number of accidents. As a result, it was found out that reliability of accident forecast model was secured through reconciling with actual number of cases except certain data. Third, this study carried out field survey on the bicycle road as well as questionnaire on satisfaction of bicycle road and use of bicycle for analysis of bicycle road problems, and presented safety improvement measures for the problems deduced as well as bicycle activation plans. This study is considered to serve as the fundamental data for planning and reorganizing of bicycle road in the future, and expected to improve safety of bicycle users and to promote activation of bicycle use as the means of transportation.

• Safety and Health at Work
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• v.8 no.3
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• pp.267-275
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• 2017

Background: The mining industry is known worldwide for its highly risky and hazardous working environment. Technological advancement in ore extraction techniques for proliferation of production levels has caused further concern for safety in this industry. Research so far in the area of safety has revealed that the majority of incidents in hazardous industry take place because of human error, the control of which would enhance safety levels in working sites to a considerable extent. Methods: The present work focuses upon the analysis of human factors such as unsafe acts, preconditions for unsafe acts, unsafe leadership, and organizational influences. A modified human factor analysis and classification system (HFACS) was adopted and an accident predictive fuzzy reasoning approach (FRA)-based system was developed to predict the likelihood of accidents for manganese mines in India, using analysis of factors such as age, experience of worker, shift of work, etc. Results: The outcome of the analysis indicated that skill-based errors are most critical and require immediate attention for mitigation. The FRA-based accident prediction system developed gives an outcome as an indicative risk score associated with the identified accident-prone situation, based upon which a suitable plan for mitigation can be developed. Conclusion: Unsafe acts of the worker are the most critical human factors identified to be controlled on priority basis. A significant association of factors (namely age, experience of the worker, and shift of work) with unsafe acts performed by the operator is identified based upon which the FRA-based accident prediction model is proposed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.2
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• pp.118-127
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• 2009

This study tries to develop model in order to assess personal factors of senior traffic accidents that are widely recognized as one of the social problems. For the current practice. it gathers data (Simulation & Questionnaire Survey) of KOTSA and conducts Poisson and Negative Binomial Regression Analysis to develop traffic accident severity model. The results show that elderly drivers' accidents are mainly affected by attentiveness selection, velocity prediction ability and attentiveness distribution ability in a positive(+) way. Second, non-senior drivers' accidents are also positively(+) influenced by attentiveness selection, velocity prediction, distance perception, attentiveness distribution ability and attentiveness diversion ability. Therefore, influencing factors of senior and non-senior drivers to vehicle accidents are different. This eventually poses a indication that preliminary education for car accident prevention should be implemented based up[n the distinction between senior drivers and non-senior drivers.

• Journal of the Korea Institute of Building Construction
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• v.23 no.6
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• pp.831-839
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• 2023

This study aims to develop a framework for an accident prediction model leveraging a deep neural network algorithm, specifically tailored for small-scale construction sites. Notably, the incidence of accidents in the construction sector is markedly higher compared to other industries, with a significant contribution from small-scale sites. The challenging nature of construction in urban settings, coupled with the increasing frequency of adverse weather conditions, is likely to escalate accident risks at these sites. Anticipating and mitigating accidents at small-scale construction sites is therefore crucial to decrease the overall industry accident rate. Consequently, this research introduces a Deep Neural Network-based model for forecasting accidents at small-scale construction sites. The framework and findings of this study are poised to serve as a guideline for the safety management of small-scale construction projects, ultimately aiding in the realization of safer, more sustainable construction practices at these sites.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2017.11a
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• pp.195-196
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• 2017

The number of human accidents in the construction industry is increasing every year, and it constitute the highest percentage among industry. This means that activities performed to prevent safety accidents in the country are not efficient to reduce the rate of accidents in the construction industry. In order to solve this issue, research has been conducted from various perspectives. But, research regarding to quantification model of human accidents is insufficient. the objective of this study is to conduct a basic study on quantification model development of human accidents. To achieve the objective, first, Cause of accident is defined the through literature review. Second, a basic statistic analysis is conducted to determine the characteristics of the accident causes. Third, the analysis is conducted after dividing into four categories : accumulate rate, season, total construction cost, and location. In the future, this study can be used as a reference for developing the safety management checklist for safety management in construction site and development of prediction models of human accident.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.3D
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• pp.343-353
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• 2011

The unsignalized intersections in a community road in the city of Seoul have 3,753 traffic accidents(9%) of total 41,702 cases in 2008, not high in the occurrence rate of traffic accidents, but seem to have a quite high potential of accidents due to the unreasonable and insufficient operation of systems and facilities in the part of traffic foundations. In particular, the un-signalized intersections in a community road have an insufficient measure for safety as compared to the crossroads with signals, and there are few analysis of traffic accidents and domestic researches on the model of affecting factors. Our country also has no concept of passing priority in operating a crossroad without signals, differently from foreign countries, so the researches and safety measures for improving the safety of a crossroad without signals in a community road are urgent. Therefore, This study set out to analyze the road conditions, traffic conditions, and traffic environment conditions on unsignalized intersection, to identify the elements that would impose obstructions in safety, and develop a traffic accident prediction model to evaluate the safety of an unsignalized intersection using the correlation between the elements and an accident. In addition, the focus was made on suggesting appropriate traffic safety policies by dealing with the danger elements in advance and on enhancing the safety on intersection in developing a traffic accident prediction model for an unsignalized intersection.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.15 no.2
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• pp.64-70
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• 2019

In recent years, attention has been paid to the integrity of steam generator (SG) tubes due to severe accident and beyond design basis accident conditions. In these transient conditions, steam generator tubes may be damaged by high temperature and pressure, which might result in a risk of fission products being released to the environment due to the failure. Alloy 690 which has increased the Cr content has been replaced for the SG tube due to its high corrosion resistance against stress corrosion cracking (SCC). However, there is lack of research on the high temperature creep rupture and life prediction model of Alloy 690. In this study, creep test was performed to estimate the high temperature creep rupture life of Alloy 690 using tube specimens. Based on manufacturer's creep data and creep test results performed in this study, creep life prediction was carried out using the Larson-Miller (LM) Parameter, Orr-Sherby-Dorn (OSD) parameter, Manson-Haford (MH) parameter, and Wilshire's approach. And a hyperbolic sine (sinh) function to determine master curves in LM, OSD and MH parameter methods was used for improving the creep life estimation of Alloy 690 material.

• Journal of the Korea Safety Management & Science
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• v.11 no.4
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• pp.119-125
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• 2009

We predict the earthquake rate in Korea following Bayesian approach. We make a model that can utilize the data to predict other levels of earthquake. An event tree model which is a frequently used graphical tool in describing accident initiation and escalation to more severe accident is transformed into an influence diagram model. Prior distributions for earthquake occurrence rate and probabilities to escalating to more severe earthquakes are assumed and likelihood of number of earthquake in a given period of time is assessed. And then posterior distributions are obtained based on observed data. We find that the minor level of earthquake is increasing while major level of earthquake is less likely.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.663-668
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• 1996

A two-dimensional continuum model for the prediction of the hydrogen mixing phenomena in the containment compartment under the severe accident conditions is developed. The model could predict well the distribution of time-dependent hydrogen concentration for selected HEDL Experiment. For a simulation of these experiments, the hydrogen is mixed uniform over the test compartment. To predict the extent of non-uniform distribution, the dominant factors such as the geometrical shape of obstacle and velocity of source injection in mixing phenomena are investigated. If the obstacle disturbing the flow of gas mixture exists in the compartment, the uniform distribution of hydrogen may be not guaranteed. The convective circulation of gas flow is separately formed up and down of the obstacle position, which makes a difference of hydrogen concentration between the upper and lower region of the compartment. The recirculation flow must have a considerable mass flow rate relative to velocity of the source injection to sustain the well-mixed conditions of hydrogen.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.3
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• pp.152-160
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• 2024

In the event of a maritime accident, search plans have traditionally been planned using experiential methods. However, these approaches cannot guarantee safety when the scale of a maritime accident increases. Therefore, this study proposes a model utilizing discrete event simulation (DES) to predict the diving time for compartment searches of a ship located on the seabed. The discrete event simulation model was created by applying the DEVS formalism. The M/V Sewol sinking was used as an example to simulate how to effectively navigate compartments of different sizes. The simulation results showed the optimal dive time with the number of decompression chambers needed to navigate the compartment as a variable. Based on this, we propose a methodology for efficient navigation planning while ensuring diver safety.