• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.2
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• pp.283-299
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• 2017

The leakage of tunnel causes the long-term durability of the structures such as concrete lining to deteriorate. The cause of durability degradation can be various substances contained in groundwater such as chloride, sulphate, water, and gas. In this study, a series of test were carried out to determine the watertightness performance and the resistance to salt water of the spray-applied membrane used as non-structural rock support or as a waterproof material for tunnels. As a result, it was found that the penetration of water could occur in a specimen, and the reason was that the internal pores generated by the mixing of the liquid polymer and the powder material and the internal pores were connected by the water pressure. The tensile strength of the test specimens immersed in distilled water and saline water was found to be reduced to less than half of the tensile strength in normal condition. In addition, The elongation was measured to be higher in distilled water than in salt water. However, this result will require further investigation.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.6
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• pp.1177-1192
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• 2018

The objective of this study is to develop the existing drainage system for catching the partial leakage of tunnel structures operating in cold region. The drainage system consists of drainage board, Hotty-gel as a waterproofing material, cover for preventing protrusion of Hotty-gel, air nailer, fixed nail, pipe for collecting ground leak, pipe for conveying ground leak, wire-mesh, and sprayed cement mortar. The drainage systems were installed in conventional concrete lining tunnels to evaluate the site applicability and constructability. The performances of waterproof and the drainage in the drainage system were evaluated by injecting 1,000 ml of red water in the back of the drainage system at 7 days, 14 days, 21 days, 28 days, 2 months, 3 months, 4 months, 5 months, 6 months, 7 months and 8 months. During 8 months of field test, the average daily temperature of the tunnel site was measured from $-16.0^{\circ}C$ to $25.6^{\circ}C$. The daily minimum temperature was $-21.3^{\circ}C$ and the daily maximum temperature was $30.8^{\circ}C$. There was no problem in waterproof and drainage performance of the drainage board in the drainage system. However, the pipe for conveying ground leak had the leakage problem from 14 days. It is considered that the leakage of the pipe for conveying ground leak was caused by the deformation of the pipe of the flexible plastic material having a thickness of 0.2 cm by using the high pressure air nailer and the fixing pin and the insufficient thickness and width of the hotty-gel for preventing the leakage.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.1
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• pp.1-9
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• 2009

When a rock slope is excavated adjacent to a existing tunnel, the behavior of the existing tunnel in the jointed rock masses is greatly influenced by the joint conditions and slope status. In this study, the effects of joint dip and slope angle close to a tunnel are investigated through a large scale model using a biaxial test equipment ($3.1\;m\;{\times}\;3.1\;m\;{\times}\;0.50\;m$ (width $\times$ height $\times$ length)). The jointed rock masses were built by concrete blocks. The diameter of the modeled tunnel is 0.6 m and the dip angles of joint vary in the range of $0-90^{\circ}$. In addition, the excavated slope angle varies within $30{\sim}90^{\circ}$. Deformational behaviors of the tunnel were analyzed in consideration of joint dip and slope angle. With increase of the joint dip and slope angle, the magnitude of tunnel distortion and the moment of tunnel lining were increased. Rock mass displacement in horizontal was also dependent on the joint dip and the excavated slope angle, which indicated the optimal slope reinforcement for a specific rock mass conditions.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.617-628
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• 2022

A ground support pattern should be designed by properly integrating various support materials in accordance with the rock mass grade when constructing a tunnel, and a technical decision must be made in this process by professionals with vast construction experiences. However, designing supports at the early stage of tunnel design, such as feasibility study or basic design, may be very challenging due to the short timeline, insufficient budget, and deficiency of field data. Meanwhile, the design of the support pattern can be performed more quickly and reliably by utilizing the machine learning technique and the accumulated design data with the rapid increase in tunnel construction in South Korea. Therefore, in this study, the design data and ground exploration data of 48 road tunnels in South Korea were inspected, and data about 19 items, including eight input items (rock type, resistivity, depth, tunnel length, safety index by tunnel length, safety index by rick index, tunnel type, tunnel area) and 11 output items (rock mass grade, two items for shotcrete, three items for rock bolt, three items for steel support, two items for concrete lining), were collected to automatically determine the rock mass class and the support pattern. Three machine learning models (S1, A1, A2) were developed using two machine learning algorithms (SVR, ANN) and organized data. As a result, the A2 model, which applied different loss functions according to the output data format, showed the best performance. This study confirms the potential of support pattern design using machine learning, and it is expected that it will be able to improve the design model by continuously using the model in the actual design, compensating for its shortcomings, and improving its usability.