• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.403-421
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• 2021

Most of the urban tunnels in Korea, which are represented by the 1st to 3rd subways, use the drainage tunnel by NATM. Recently, when a construction project that actively utilizes large-scale urban space is promoted, negative effects that do not conform to the existing empirical rules of urban tunnels may occur. In particular, there is a high possibility that groundwater fluctuations and hydrodynamic behavior will occur owing to the practice of tunnel technology in Korea, which has mainly applied the drainage tunnel. In order to solve the problem of the drainage tunnel, attempts are being made to control groundwater fluctuations. For this, the establishment of tunnel groundwater management standard concept and the analysis of the tunnel hydraulic behavior were performed. To prevent the problem of groundwater fluctuations caused by the construction of large-scale tunnels in urban areas, it was suggested that the conceptual transformation of the empirical technical practice, which is applied only in the underground safety impact assessment stage, to the direction of controlling the inflow in the tunnel, is required. And the relationship between the groundwater level and the inflow of the tunnel required for setting the allowable inflow when planning the tunnel was derived. The introduction of a tunnel groundwater management concept is expected to help solve problems such as groundwater fluctuations, ground settlement, depletion of groundwater resources, and decline of maintenance performance in various urban deep tunnel construction projects to be promoted in the future.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.5
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• pp.431-449
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• 2022

As many tunnels generally have been constructed, various experiences and techniques have been accumulated for tunnel design as well as tunnel construction. Hence, there are not a few cases that, for some usual tunnel design works, it is sufficient to perform the design by only modifying or supplementing previous similar design cases unless a tunnel has a unique structure or in geological conditions. In particular, for a tunnel blast design, it is reasonable to refer to previous similar design cases because the blast design in the stage of design is a preliminary design, considering that it is general to perform additional blast design through test blasts prior to the start of tunnel excavation. Meanwhile, entering the industry 4.0 era, artificial intelligence (AI) of which availability is surging across whole industry sector is broadly utilized to tunnel and blasting. For a drill and blast tunnel, AI is mainly applied for the estimation of blast vibration and rock mass classification, etc. however, there are few cases where it is applied to blast pattern design. Thus, this study attempts to automate tunnel blast design by means of machine learning, a branch of artificial intelligence. For this, the data related to a blast design was collected from 25 tunnel design reports for learning as well as 2 additional reports for the test, and from which 4 design parameters, i.e., rock mass class, road type and cross sectional area of upper section as well as bench section as input data as well as16 design elements, i.e., blast cut type, specific charge, the number of drill holes, and spacing and burden for each blast hole group, etc. as output. Based on this design data, three machine learning models, i.e., XGBoost, ANN, SVM, were tested and XGBoost was chosen as the best model and the results show a generally similar trend to an actual design when assumed design parameters were input. It is not enough yet to perform the whole blast design using the results from this study, however, it is planned that additional studies will be carried out to make it possible to put it to practical use after collecting more sufficient blast design data and supplementing detailed machine learning processes.

• Journal of the Korean Geotechnical Society
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• v.22 no.6
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• pp.71-82
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• 2006

One of the most popular pre-reinforcement methods of tunnel heading in cohesionless soils would be the fore-polling of grouted pipes, known as RPUM (reinforced protective umbrella method) or UAM (umbrella arch method). This technique allows safe excavation even in poor ground conditions by creating longitudinal arch parallel to the tunnel axis as the tunnel advances. Some previous studies on the reinforcing effects have been performed using numerical methods and/or laboratory-based small scale model tests. The complexity of boundary conditions imposes difficulties in representing the tunnelling procedure in laboratory tests and theoretical approaches. Full-scale study to identify reinforcing effects of the tunnel heading has rarely been carried out so far. In this study, a large scale model testing for a tunnel in granular soils was performed. Reinforcing patterns considered are four cases, Non-Reinforced, Crown-Reinforced, Crown & Face-Reinforced, and Face-Reinforced. The behavior of ground and pipes as reinforcing member were fully measured as the surcharge pressure applied. The influences of reinforcing pattern, pipe length, and face reinforcement were investigated in terms of stress and displacement. It is revealed that only the Face-Reinforced has decreased sufficiently both vertical settlement in tunnel heading and horizontal displacement on the face. Vertical stresses along the tunnel axis were concentrated in tunnel heading from the test results, so the heading should be reinforced before tunnel advancing. Most of maximum axial forces and bending moments for Crown-reinforced were measured at 0.75D from the face. Also it should be recommended that the minimum length of the pipe is more than l.0D for crown reinforcement.