• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.3
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• pp.277-285
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• 2020

Survivability in a battle field is the most important aspect to the warriors. To analyze the survival effectiveness of warrior platform, the simulation via war-game model is an essential step in advance to the development of platform. In this study, Army Weapon effectiveness Analysis Model(AWAM) was utilized for analysis. Several weapon parameters were adjusted to apply the characteristics of warrior platform in some cases of the defense and survival system. Especially, adjusted triage possibility, probability of kill, fatality and accuracy were employed as parameters in the simulation program to evaluate the survival effectiveness of intelligent system based on the previous researches. In the future battle field or virtual space in the AWAM, the warrior platform intelligent system could react emergency treatment on time by expoiting the bio-information of man at arms. Considering the order of supply priority, special force was selected as operating troops and battle scenario without engagement was selected to measure accurate survival effectiveness. In conclusion, the survivability of defence and survival system of the warrior platform was about 1.47 times higher than that of current system.

• Journal of the Korean Society of Safety
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• v.26 no.3
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• pp.91-97
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• 2011

The weight of elderly people in Korea has been increasing. Statistics show that the percentage of the elderly people in Korea was 3.1% in 1970; 3.8% in 1980; 5.1% in 1990, and 7.2% in 2000. Based on this trend, thus, the number of elderly people could be estimated to be 14% of the whole Korean population in 2018. This reveals that Korea is entering a super-aging society with remarkable fast pace. In such a change, the statistics related to elderly people driving license and the occurrence of traffic accidents are showing a noticeable numerical value. The number of traffic accident fatality in Korea ranks the highest value in OECD Countries. However, the research on old drivers in the nation is going on partially centering on system improvement and management scheme. Thus, first of all, researches about the linkage & characteristics between the driving behavior of old drivers and traffic accident should be implemented, in order properly to draw system improvement and management scheme for the old drivers. Therefore, the focus of this study is the influence model for discerning the severity of the age-old-caused traffic accidents by inquiring into the relation between the Driving Aptitude Test items that make it possible to measure their behavioral characteristics and influential factors by age group on the basis of the data on traffic accidents. The analysis results can be used as basic data for suggesting the behavioral research and countermeasure for traffic safety and its management for old driver in preparation for the aging society.

• Journal of Korean Tunnelling and Underground Space Association
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• v.12 no.4
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• pp.307-319
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• 2010

As we learned in Daegu subway fire accident, fire in the railway tunnel is prone to develop to large disaster due to the limitation of smoke control and smoke exhaust. In railway tunnel, in order to ensure fire safety, fire prevention and fighting systems are installed by quantitative risk assessment results. Therefore, in this research, developed the program to establish quantitative risk assessment and suggested quantitative safety assessment method including fire scenarios in railway tunnel, fire and evacuation analysis model, fatality estimate model and societal risk criteria. Moreover, this method applys to plan preventing disaster for Honam high speed railway tunnel. As results, we presented the proper distance of escape route and societal risk criteria.

• Journal of Korean Society of Steel Construction
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• v.17 no.2 s.75
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• pp.227-241
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• 2005

This paper presents a practical and realistic Life-Cycle Cost (LCC) optimum design methodology for steel bridges considering the long-term effect of environmental stressors such as corrosion and heavy truck traffics on bridge reliability. The LCC functions considered in the LCC optimization consist of initial cost, expected life-cycle maintenance cost, and expected life-cycle rehabilitation costs including repair/replacement costs, loss of contents or fatality and injury losses, road user costs, and indirect socio-economic losses. For the assessment of the life-cycle rehabilitation costs, the annual probability of failure, which depends upon the prior and updated load and resistance histories, should be accounted for. For the purpose, Nowak live load model and a modified corrosion propagation model, which takes into consideration corrosion initiation, corrosion rate, and repainting effect, are adopted in this study. The proposed methodology is applied to the LCC optimum design problem of an actual steel box girder bridge with 3 continuous spans (40m+50m+40m=130m). Various sensitivity analyses are performed to investigate the effects of various design parameters and conditions on the LCC-effectiveness. From the numerical investigation, it has been observed that local corrosion environments and the volume of truck traffic significantly influence the LCC-effective optimum design of steel bridges. Thus, these conditions should be considered as crucial parameters for the optimum LCC-effective design.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1A
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• pp.75-89
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• 2006

This paper presents a practical and realistic Life-Cycle Cost (LCC) optimum design methodology of steel bridges considering time effect of bridge reliability under environmental stressors such as corrosion and heavy truck traffics. The LCC functions considered in the LCC optimization consist of initial cost, expected life-cycle maintenance cost and expected life-cycle rehabilitation costs including repair/replacement costs, loss of contents or fatality and injury losses, road user costs, and indirect socio-economic losses. For the assessment of the life-cycle rehabilitation costs, the annual probability of failure which depends upon the prior and updated load and resistance histories should be accounted for. For the purpose, Nowak live load model and a modified corrosion propagation model considering corrosion initiation, corrosion rate, and repainting effect are adopted in this study. The proposed methodology is applied to the LCC optimum design problem of an actual steel box girder bridge with 3 continuous spans (40 m+50 m+40 m=130 m), and various sensitivity analyses of types of steel, local corrosion environments, average daily traffic volume, and discount rates are performed to investigate the effects of various design parameters and conditions on the LCC-effectiveness. From the numerical investigation, it has been observed that local corrosion environments and the number of truck traffics significantly influence the LCC-effective optimum design of steel bridges, and thus realized that these conditions should be considered as crucial parameters for the optimum LCC-effective design.

• Journal of Ocean Engineering and Technology
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• v.26 no.1
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• pp.60-63
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• 2012

The accident risks in the marine environment are increasing because of the tendency to build faster and larger ships. To secure ship safety, risk-based ship design (RBSD) was recently suggested based on a formal safety assessment (FSA). In the process of RBSD, a ship designer decides which risk reduction option is most cost-effective in the design stage using a cost-benefit analysis (CBA). There are three dimensions of risk in this CBA: fatality, environment, and asset. In this paper, we present an approach to estimate the environmental costs based on the size of an oil tanker involved in an accident using a neural network. An appropriate neural network model is suggested for the estimation,and the neural network is trained using IOPCF data. Finally,the learned neural network is compared with the cost regression equation by IMO MEPC 62/WP.13 (2011).

• Safety and Health at Work
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• v.8 no.2
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• pp.175-182
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• 2017

Background: With the recent rapid industrialization, occupational safety and health (OSH) has become an important issue in all industrial and human activities. However, incidents of injuries and fatality rates in the Ghanaian industry sector continue to increase. Despite this increase, there is no evidence regarding the element of OSH management in transport activities in Ghanaian industries. Thus, this study aims to examine the perceptions regarding the importance of safety and health in work-related transport activities in Ghanaian industries. Methods: A survey data collection technique was used to gather information on best safety practices over a 5-month period. We randomly selected 298 respondents from industries to answer structured questionnaires. The respondents included drivers, transport managers, and safety engineers. Standard multiple regression model and Pearson product-movement correlation were used to performed the analysis. Results: The result shows that for interventions to improve safety and health, concentration has been on drivers' safety practice with less attention to safe driving environments and vehicle usage. Additionally, the respondents are aware of the importance of OSH in transport activities, but the level of integration does not measure up to the standard to reduce operational accidents and injuries. Finally, strong commitment to changing unsafe practices at all levels of operations appears to be the effective way to improve safety situations. Conclusion: OSH culture is not fully complied in industries transport activities. This study, therefore, supports the use of safety seminars and training sessions for industry workers responsible for transport operations for better integration of safety standards.

• Journal of the Korean Institute of Gas
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• v.7 no.1 s.18
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• pp.33-40
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• 2003

In this work, a novel approach was introduced to assess cost of loss resulting from risk as well as to help deciding inspection period through quantifying risk. In order to quantifying risk of city gas pipeline, frequency and consequence analysis were required. The main causes of city gas accident were analyzed to be digging, external corrosion, ground movement, and equipment failure. Tools to evaluate frequency of each cause was also suggested. Among city gas accidents, fire damage is the dominant one and mainly discussed; fatality, burning injury, and damage to building were estimated using the consequence model suggested. By combining frequency and consequence analysis, evaluating cost of risk management together with calculating example. This work could be applicable for city gas companies to plan how to manage risk most effectively.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.87-95
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• 2020

Generally, occupational safety and particularly construction safety is an intricate phenomenon. Industry professionals have devoted vital attention to enforcing Occupational Safety and Health (OHS) from the last three decades to enhance safety management in construction. Despite the efforts of the safety professionals and government agencies, current safety management still relies on manual inspections which are infrequent, time-consuming and prone to error. Extensive research has been carried out to deal with high fatality rates confronting by the construction industry. Sensor systems, visualization-based technologies, and tracking techniques have been deployed by researchers in the last decade. Recently in the construction industry, computer vision has attracted significant attention worldwide. However, the literature revealed the narrow scope of the computer vision technology for safety management, hence, broad scope research for safety monitoring is desired to attain a complete automatic job site monitoring. With this regard, the development of a broader scope computer vision-based risk recognition system for correlation detection between the construction entities is inevitable. For this purpose, a detailed analysis has been conducted and related rules which depict the correlations (positive and negative) between the construction entities were extracted. Deep learning supported Mask R-CNN algorithm is applied to train the model. As proof of concept, a prototype is developed based on real scenarios. The proposed approach is expected to enhance the effectiveness of safety inspection and reduce the encountered burden on safety managers. It is anticipated that this approach may enable a reduction in injuries and fatalities by implementing the exact relevant safety rules and will contribute to enhance the overall safety management and monitoring performance.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.6
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• pp.1017-1023
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• 2017

Duration induced by freeway crashes has a critical influence on traffic congestion. In general, crash duration composes detection and verification, response, and clearance time. Of these, the crash clearance time determined by a crash clearance team has attracted considerable attention in the freeway congestion management since the interest of the first two time stages faded away with increasing ubiquitous mobile phone users. The objective of this study is to identify the critical factors that affect freeway crash clearance time using a Cox's proportional hazard model. In total, 6,870 crash duration data collected from 30 major Korean freeways in 2013 were used. As a result, it was found that crashes during the night, with trailer or larger size truck, and in tunnel section contribute to increasing clearance time. Crashes associated with fatality, completed damage of crashed vehicle (s), and vehicles' fire or rollover after crash also lead to increasing clearance time. Additionally, an increase in the number of vehicles involved resulted in longer clearance time. On the other hand, crashes in the vicinity of tollgate, by passenger car, during spring, on flat section, and of car-facility type had longer clearance time. On the basis of the results, this paper suggested some strategic plans and mitigation measures to reduce crash clearance time on Korean freeway systems.