• Tunnel and Underground Space
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• v.26 no.1
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• pp.32-45
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• 2016

For effective utilization of downtown area, many studies about underground have been performed around the world, and double-deck tunnel have being operated in USA, Europe and China, etc. (A86 East Duplex in France, M30 tunnel project in Spain, SR-99 in seattle, USA, Yangtze river tunnel in China) In Korea, the research about network type double-deck tunnel in deep underground space is in progress to solve the traffic jam and secure the ground space. In this study, a number of factors required for double-deck tunnel in deep underground are analyzed through the existing ventilation design outline and unique ventilation design factors for network type double-deck tunnel are established by reviewing design cases of overseas double-deck tunnel.

• Journal of Korean Tunnelling and Underground Space Association
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• v.16 no.6
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• pp.553-560
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• 2014

The road tunnel install a vent for the purpose of ventilation and smoke control. Ventilation equipment capacity(number of jet fans) depends on from the condition that of the pressure and ventilation resistance. Pressure and the resistance under operating vehicle have affected on the drag coefficient. The drag coefficient of the tunnel have affected by the blockage effect and slipstream effects. However, when calculating the ventilation fan, are not properly consider taking into account such effects. Therefore, ventilation force may have been slightly overestimated. This paper describes the drag coefficient through a numerical analysis to calculate the equivalent resistance area that reflects the vehicle distance, and examined the equivalent resistance area. The ventilation coefficient corresponding to the result heavy vehicle mixing ratio of the present study was not clear. Equivalent resistance area had reduced by about 86% compared to the road design handbook current standards. Also it had analyzed and reduced to 62.2% compared to Korea Highway Corporation ventilation design criteria ratio, which is the old standard.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.17 no.10
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• pp.922-929
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• 2005

This paper compared ventilation performance between the sound roof tunnel with flat roof and the sound roof tunnel with gable roof. The ventilation rate of the sound roof tunnel is calculated by natural ventilation rate plus ventilation by vehicle. The roof type is divided by the shape of the roof and the ventilator location on the roof. The results between calculation and CFD on the ventilation rate are almost alike. The ventilation rate on the flat roof is $558.4\;m^3/s$ with mid-ventilator and $496.8\;m^3/s$ with left-right ventilator. The ventilation rate on the gable roof is $653.2\;m^3/s$ with mid-ventilator and $611.6\;m^3/s$ with left-right ventilator. The ventilation rate of soundproof with gable roof is higher than that with flat roof. The ventilation rate and with mid-ventilator is higher than that with left-right ventilator the soundproof roof. Therefore, the ventilation performance of soundproof roof depends on the roof shape and ventilator location on the roof.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.1
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• pp.173-185
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• 2015

This study aims to investigate the characteristics and types of car accidents and establish a prediction model by analyzing 456 car accidents having occurred in the 11 tunnels in Busan, through statistical analysis techniques. The results of this study can be summarized as below. As a result of analyzing the characteristics of car accidents, it was found that 64.9% of all the car accidents took place in the tunnels between 08:00 and 18:00, which was higher than 45.8 to 46.1% of the car accidents in common roads. As a result of analyzing the types of car accidents, the car-to-car accident type was the majority, and the sole-car accident type in the tunnels was relatively high, compared to that in common roads. Besides, people at the age between 21 and 40 were most involved in car accidents, and in the vehicle type of the first party to car accidents, trucks showed a high proportion, and in the cloud cover, rainy days or cloudy days showed a high proportion unlike clear days. As a result of analyzing the principal components of car accident influence factors, it was found that the first principal components were road, tunnel structure and traffic flow-related factors, the second principal components lighting facility and road structure-related factors, the third principal factors stand-by and lighting facility-related factors, the fourth principal components human and time series-related factors, the fifth principal components human-related factors, the sixth principal components vehicle and traffic flow-related factors, and the seventh principal components meteorological factors. As a result of classifying car accident spots, there were 5 optimized groups classified, and as a result of analyzing each group based on Quantification Theory Type I, it was found that the first group showed low explanation power for the prediction model, while the fourth group showed a middle explanation power and the second, third and fifth groups showed high explanation power for the prediction model. Out of all the items(principal components) over 0.2(a weak correlation) in the partial correlation coefficient absolute value of the prediction model, this study analyzed variables including road environment variables. As a result, main examination items were summarized as proper traffic flow processing, cross-section composition(the width of a road), tunnel structure(the length of a tunnel), the lineal of a road, ventilation facilities and lighting facilities.