• Journal of the Korean Society for Railway
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• v.20 no.4
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• pp.482-490
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• 2017

This study is a railway accident investigation statistic study with the purpose of prediction and classification of accident severity. Linear regression models have some difficulties in classifying accident severity, but a logistic regression model can be used to overcome the weaknesses of linear regression models. The logistic regression model is applied to escalator (E/S) accidents in all stations on 5~8 lines of the Seoul Metro, using data mining techniques such as logistic regression analysis. The forecasting variables of E/S accidents in urban railway stations are considered, such as passenger age, drinking, overall situation, behavior, and handrail grip. In the overall accuracy analysis, the logistic regression accuracy is explained 76.7%. According to the results of this analysis, it has been confirmed that the accuracy and the level of significance of the logistic regression analysis make it a useful data mining technique to establish an accident severity prediction model for urban railway casualty accidents.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.2
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• pp.197-217
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• 2020

Shield TBM tunneling, used in the construction of Seoul subway line 7 and line 9, has been well known as a very efficient, as well as safe, tunneling method. Although the Shield TBM method has been known to be effectively used in poor ground conditions, a number of troubles have occurred during the use of the shield TBM, due to inappropriate machine selection, machine breakdown, and unpredicted ground conditions etc. In this study, several accidents and trouble cases occurred during excavation by Shield TBM, reported from Japan, were investigated. A series of numerical analysis was then performed to compare with the trouble cases and back-analysis results for the cause analysis. The lessons learned from the case studies are presented at the end.

• Journal of Korean Tunnelling and Underground Space Association
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• v.7 no.3
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• pp.219-226
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• 2005

The result that analyze for 6 years a groundwater influx quantity of total 60 catch-pit established in subway line 5 appeared with $0.77m^3/min$. When comparing design approaches of the catch-pit with design approaches of the box structure $2m^3/min$ and the tunnel structure $3m^3/min$, it is found that it has a surplus. Red sedimentation substance contains large portion of Fe. The earth retaining structure of a tunnel and groundwater containing more portion of Fe than other area rue the major factor of this substance. In case of white sedimentation substance, the most frequently founded ingredient is CaO, which is occurred in case grouting injection materials for ground reinforcement is transmitted into a tunnel system by ground water. This substance is doesn't affect safety of a tunnel.

• Tunnel and Underground Space
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• v.19 no.3
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• pp.236-247
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• 2009

Overpopulation has significantly increased the use of underground spaces in urban areas, and led to the developments of shallow-depth underground space. Due to unexpected rock fall, however, it is very necessary to understand and categorize the rock mass behaviors prior to the tunnel excavation, by which unnecessary casualties and economic loss could be prevented. In case of cave-in, special attention should be drawn since it occurs faster and greater in magnitude compared to rock fall and plastic deformation. Types of cave-in behavior are explained and categorized using seven parameters - Uniaxial Compressive Strength (UCS), Rock Quality Designation (RQD), joint surface condition, in-situ stress condition, ground water condition, earthquake & ground vibration, tunnel span. This study eventually introduces a new index called Cave-in Behavior Index (CBI) which explains the behavior of cave-in under given in-situ conditions expressed by the seven parameters. In order to assess the mutual interactions of the seven parameters and to evaluate the weighting factors for all the interactions, survey data of the experts' opinions and Rock Engineering Systems (RES) were used due to lack of field observations. CBI was applied to the tunnel site of Seoul Metro Line No. 9. UDEC analyses on 288 cases were done and occurrences of cave-in in every simulation were examined. Analyses on the results of 288 cases of simulations revealed that the average CBI for the cases when cave-in for different patterns of tunnel support was estimated by a logistic regression analysis.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.2
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• pp.216-232
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• 2016

In present, the Seoul City is undergoing traffic congestion problems caused by rapid urbanization and population growth. Thus the City government has reorganized the mass transportation system since 2004 and the subway has become a very important means for public transit. Since the subway system is typically a closed environment, the indoor air quality issues have often raised by the public. Especially since a huge amount of PM (particulate matter) is emitted from ground tunnels passing through the subway train, it is now necessary to assess the characteristics and behaviors of fine PM inside the tunnel. In this study, the concentration patterns of $PM_1$, $PM_{2.5}$, and $PM_{10}$ in the Seoul subway line-2 were analyzed by real-time measurement during winter (Jan 13, 2015) and summer (Aug 7, 2015). The line-2 consisting of 51 stations is the most busy circular line in Seoul having the railway of 60.2 km length. The the one-day average $PM_{10}$ concentrations were $148{\mu}g/m^3$ in winter and $66.3{\mu}g/m^3$ in summer and $PM_{2.5}$ concentrations were $118{\mu}g/m^3$ and $58.5{\mu}g/m^3$, respectively. The $PM_{2.5}/PM_{10}$ ratio in the underground tunnel was lower than the outdoor ratio and also the ratio in summer is higher than in winter. Further the study examined structural types of underground subsections to explain the patterns of elevated PM concentrations in the line-2. The subsections showing high PM concentration have longer track, shorter curvature radius, and farther from the outdoor stations. We also estimated the outdoor PM concentrations near each station by a spatial statistical analysis using the $PM_{10}$ data obtained from the 40 Seoul Monitoring Sites, and further we calculated $PM_{2.5}/PM_{10}$ and $PM_1/PM_{10}$ mass ratios near the outdoor subway stations by using our observed outdoor $PM_1$, $PM_{2.5}$, and $PM_{10}$ data. Finally, we could develop pollution maps for outdoor $PM_1$ and $PM_{2.5}$ near the line-2 by using the kriging method in spatial analysis. This methodology may help to utilize existing $PM_{10}$ database when managing and control fine particle problems in Korea.

• Journal of the Korean Society for Railway
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• v.17 no.5
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• pp.328-335
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• 2014

Numerical prediction methods were applied to investigate the turbulent air currents and air-conditioning efficiency in an underground subway station, and the results compared to experimental data. The Shin-gumho Station($8^{th}$ floor underground and 43.6m in depth) in Seoul was selected for the analysis. The entire station was covered for simulation and the ventilation mode was ordinary. The ventilation diffusers were modeled as 95 square shapes of $0.6m{\times}0.6m$ in the lobby and as 222 square shapes in the platform. Cooling air of $47,316m^3/h$ was supplied and the returned air of $33,980m^3/h$ is exhausted in the lobby and the cooling air of $33,968m^3/h$ is supplied and the returned air of $76,190m^3/h$ was exhausted in the platform which is the same as the experimental data. The cases of the screen-door-closed and open were respectively investigated. A total of 7.5million grids were generated and the whole domain divided into 22 blocks for MPI efficiency of calculation. Large eddy simulation (LES) was applied to solve the momentum and energy equation.