• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.1
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• pp.61-77
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• 2019

If a new utility tunnel is planned for high density existing urban areas in Korea, a rational decision-making process such as the determination of optimum design capacity by using the feasibility evaluation system based on quantitative evaluation indexes and the economic evaluation is needed. Thus, the previous study presented the important weight of individual higher-level indexes (3 items) and sub-indexes (16 items) through a hierarchy analysis (AHP) for quantitative evaluation index items, considering the characteristics of each urban type. In addition, an economic evaluation method was proposed considering 10 benefit items and 8 cost items by adding 3 new items, including the effects of traffic accidents, noise reduction and socio-economic losses, to the existing items for the benefit cost analysis suitable for urban utility tunnels. This study presented a quantitative feasibility evaluation method using the important weight of 16 sub-index items such as the road management sector, public facilities sector and urban environment sector. Afterwards, the results of quantitative feasibility and economic evaluation were compared and analyzed in 123 main road sections of the Seoul. In addition, a comprehensive evaluation method was proposed by the combination of the two evaluation results. The design capacity optimization program, which will be developed by programming the logic of the quantitative feasibility and economic evaluation system presented in this study, will be utilized in the planning and design phases of urban community zones and will ultimately contribute to the vitalization of urban utility tunnels.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.1
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• pp.95-107
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• 2017

In this study, a preliminary study was undertaken for development of a tunnel incident automatic detection system based on a machine learning algorithm which is to detect a number of incidents taking place in tunnel in real time and also to be able to identify the type of incident. Two road sites where CCTVs are operating have been selected and a part of CCTV images are treated to produce sets of training data. The data sets are composed of position and time information of moving objects on CCTV screen which are extracted by initially detecting and tracking of incoming objects into CCTV screen by using a conventional image processing technique available in this study. And the data sets are matched with 6 categories of events such as lane change, stoping, etc which are also involved in the training data sets. The training data are learnt by a resilience neural network where two hidden layers are applied and 9 architectural models are set up for parametric studies, from which the architectural model, 300(first hidden layer)-150(second hidden layer) is found to be optimum in highest accuracy with respect to training data as well as testing data not used for training. From this study, it was shown that the highly variable and complex traffic and incident features could be well identified without any definition of feature regulation by using a concept of machine learning. In addition, detection capability and accuracy of the machine learning based system will be automatically enhanced as much as big data of CCTV images in tunnel becomes rich.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.517-534
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• 2021

Hydrogen fuel is emerging as an new energy source to replace fossil fuels in that it can solve environmental pollution problems and reduce energy imbalance and cost. Since hydrogen is eco-friendly but highly explosive, there is a high concern about fire and explosion accidents of hydrogen fueled vehicles. In particular, in semi-enclosed spaces such as tunnels, the risk is predicted to increase. Therefore, this study was conducted on the applicability of the equivalent TNT model and the numerical analysis method to evaluate the hydrogen explosion pressure in the tunnel. In comparison and review of the explosion pressure of 6 equivalent TNT models and Weyandt's experimental results, the Henrych equation was found to be the closest with a deviation of 13.6%. As a result of examining the effect of hydrogen tank capacity (52, 72, 156 L) and tunnel cross-section (40.5, 54, 72, 95 m²) on the explosion pressure using numerical analysis, the explosion pressure wave in the tunnel initially it propagates in a hemispherical shape as in open space. Furthermore, when it passes the certain distance it is transformed a plane wave and propagates at a very gradual decay rate. The Henrych equation agrees well with the numerical analysis results in the section where the explosion pressure is rapidly decreasing, but it is significantly underestimated after the explosion pressure wave is transformed into a plane wave. In case of same hydrogen tank capacity, an explosion pressure decreases as the tunnel cross-sectional area increases, and in case of the same cross-sectional area, the explosion pressure increases by about 2.5 times if the hydrogen tank capacity increases from 52 L to 156 L. As a result of the evaluation of the limiting distance affecting the human body, when a 52 L hydrogen tank explodes, the limiting distance to death was estimated to be about 3 m, and the limiting distance to serious injury was estimated to be 28.5~35.8 m.

• Journal of Korean Society for Atmospheric Environment
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• v.26 no.5
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• pp.543-553
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• 2010

Almost five million citizens a day are using subways as a means of traffic communication in the Seoul metropolitan. As the subway system is typically a closed environment, indoor air pollution problems frequently occurs and passengers complain of mal-health impact. Especially $PM_{10}$ is well known as one of the major pollutants in subway indoor environments. The purpose of this study was to compare the indoor air quality in terms of $PM_{10}$ and to quantitatively compare its source contributions in a Seoul subway platform before and after installing platform screen doors (PSD). $PM_{10}$ samples were collected on the J station platform of Subway Line 7 in Seoul metropolitan area from Jun. 12, 2008 to Jan. 12, 2009. The samples collected on membrane filters using $PM_{10}$ mini-volume portable samplers were then analyzed for trace metals and soluble ions. A total of 18 chemical species (Ba, Mn, Cr, Cd, Si, Fe, Ni, Al, Cu, Pb, Ti, $Na^+$, $NH_4^+$, $K^+$, $Mg^{2+}$, $Ca^{2+}$, $Cl^-$, and ${SO_4}^{2-}$) were analyzed by using an ICP-AES and an IC after performing proper pre-treatments of each sample filter. Based on the chemical information, positive matrix factorization (PMF) model was applied to identify the source of particulate matters. $PM_{10}$ for the station was characterized by three sources such as ferrous related source, soil and road dust related source, and fine secondary aerosol source. After installing PSD, the average $PM_{10}$ concentration was decreased by 20.5% during the study periods. Especially the contribution of the ferrous related source emitted during train service in a tunnel route was decreased from 59.1% to 43.8% since both platform and tunnel areas were completely blocked by screen doors. However, the contribution of the fine secondary aerosol source emitted from various outside combustion activities was increased from 14.8% to 29.9% presumably due to ill-managed ventilation system and confined platform space.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.1
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• pp.107-120
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• 2020

In a performance-based evaluation of structures in use, the current performance is assessed by summing up the weighting of the evaluation indices for each performance. In this study, to suggest a performance-based evaluation technique for NATM tunnels in use, the performance evaluation indices were derived by examining the characteristics and similarities of each index developed from previous study. The weighting of the evaluation indices was derived by calculating the relative importance of each evaluation indices from the AHP analysis. In order to develop a quantitative evaluation model, grading criteria for each performance index was derived through literature review, and performance evaluation tables for road and railway tunnels were presented. In order to verify the significance of the proposed performance evaluation model, the correlation analysis was performed between each evaluation index and the final evaluation result. In the correlation analysis, the survey data measured through precision safety diagnosis in the tunnel in use was applied. It may be said that the proposed evaluation indices, weighting, criteria and evaluation models for tunnels in use can be applied to the performance-based maintenance system of tunnels.

• Journal of the Mineralogical Society of Korea
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• v.22 no.1
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• pp.13-22
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• 2009

The study area is a tunnelling section passing through the Yangsan Fault zone. Kyungbu express highway and national road 35 are located above the tunnel. Previous study showed that fault gouge and fault breccia were widely distributed in the tunnelling section with a maximum width of 100 m. From the present study, it is found that sedimentary rocks consisting mainly of shale are distributed at the eastern block of the Yangsan Fault and these rocks are not subject to mechanical fracturing and hydrothermal alteration. On the other hand, dacitic tuff distributed at the western block of the Yangsan Fault is largely affected by mechanical fracturing and hydrothermal alteration. The large fault zone of $50{\sim}130m$ width was formed by complex processes of mechanical fracturing and hydrothermal alterations such as chloritization, sericitization, and kaolinization. Based on the characteristics of mechanical fracturing and hydrothermal alterations, the Yangsan fault zone in the study area is geotechnically classified as four zones: unaltered zone, altered zone, altered fractured zone, and fault gouge zone. These zones show different degrees and aspects in mechanical fracturing and hydrothermal alterations, resulting in different engineering properties.

• Tunnel and Underground Space
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• v.17 no.5
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• pp.411-427
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• 2007

Reliability in tunnel analysis is necessary to accomplish technically sound design and economical construction. For this, a thorough understanding of the construction procedure including the ground-support interaction has to be obtained. This paper describes a proper modelling technique to simulate the behavior of the steel fiber reinforced shotcrete (SFRS) which maintain the supporting capability in post-failure regime. The additional supporting effect of the steel support was also verified by 3-D analyses and a new load distribution factor were proposed. The use of the plastic moment limit (PML) alone can eliminate the occurrence of the awkwardly high tensile stress in the shotcrete and can successfully model the post-peak ductile behavior of the SFRS. But with this method, moment is limited whenever the stress caused by moment reaches tensile strength of the shotcrete irrespective of the stress by axial force. Therefore, it was necessary to find a more comprehensive method which can reflect the influence of the moment and axial force. This can be accomplished by the proper use of "liner element" which is the built-in model in FLAC. In this model, the peak and residual strength as well as the uniaxial compressive strength of the SFRS can be specified. Analyses were conducted with these two models on the 2-lane road tunnels excavated in class IV and V rock mass and results were compared with the conventional elastic beam model. Results showed that both models can reflect the fracture toughness of the SFRS which could not be accomplished by the elastic beam model.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.1 no.1
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• pp.41-51
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• 2002

As Advanced Traveler Information System(ATIS) is the kernel of the Intelligent Transportation System, it is very important how to manage data from traffic information collectors on a road and have at borough grip of the travel time's change quickly and exactly for doing its part. Link travel time can be obtained by two method. One is measured by area detection systems and the other is estimated by point detection systems. Measured travel time by area detection systems has the limitation for real time information because it Is calculated by the probe which has already passed through the link. Estimated travel time by point detection systems is calculated by the data on the same time of each. section, this is, it use the characteristic of the various cars of each section to estimate travel time. For this reason, it has the difference with real travel time. In this study, Artificial Neural Networks is used for estimating link travel time concerned about the relationship with vehicle detector data and link travel time. The method of estimating link travel time are classified according to the kind of input data and the Absolute value of error between the estimated and the real are distributed within 5$\~$15minute over 90 percent with the result of testing the method using the vehicle detector data and AVI data of Namsan Tunnel $\#$1. It also reduces Time lag of the information offered time and draws late delay generation and dissolution.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.699-714
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• 2022

The objective of this study is to suggest a safe and economical pillar reinforcement method when very near-twin tunnels with a minimum interval of 1 m passes through a soft zone such as weathered soil or weathered rock. A standard cross-sectional view of a two-lane road tunnel was applied to suggest a pillar reinforcement method for the very near-twin tunnels. The thickness of the pillar was 1 m. The ground condition around the tunnel was weathered soil or weathered rock. There were four reinforcement methods for pillar stability evaluation. These were rock bolt reinforcement, pre-stressed steel strand reinforcement, horizontal steel pipe grouting reinforcement, horizontal steel pipe grouting + prestressed steel strand reinforcement. When the ground condition was weathered soil, only the pillar reinforced the horizontal steel pipe grouting + prestressed steel strand did not failed. When the ground condition was weathered rock, there were no failure of the pillar reinforced the horizontal steel pipe grouting or the horizontal steel pipe grouting + prestressed steel strand. It is considered that the horizontal steel pipe grouting reinforcement played a role in increasing the stability of the upper part of the pillar by supporting the upper load applied to the upper part of the pillar.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.1161-1175
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• 2018

An unexpected event could be easily followed by a large secondary accident due to the limitation in sight of drivers in road tunnels. Therefore, a series of automated incident detection systems have been under operation, which, however, appear in very low detection rates due to very low image qualities on CCTVs in tunnels. In order to overcome that limit, deep learning based tunnel incident detection system was developed, which already showed high detection rates in November of 2017. However, since the object detection process could deal with only still images, moving direction and speed of moving vehicles could not be identified. Furthermore it was hard to detect stopping and reverse the status of moving vehicles. Therefore, apart from the object detection, an object tracking method has been introduced and combined with the detection algorithm to track the moving vehicles. Also, stopping-reverse discrimination algorithm was proposed, thereby implementing into the combined incident detection processes. Each performance on detection of stopping, reverse driving and fire incident state were evaluated with showing 100% detection rate. But the detection for 'person' object appears relatively low success rate to 78.5%. Nevertheless, it is believed that the enlarged richness of image big-data could dramatically enhance the detection capacity of the automatic incident detection system.