• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.2
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• pp.61-76
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• 2021

As the number of existing road tunnels increases every year, collapse and floor heaving accidents occur frequently during construction. The collapse among tunnel accidents dominates, so that studies related to the floor heaving are relatively insufficient. Accordingly, many studies to reinforce the lower part of the tunnel have been conducted, but the analysis on the effect of the curvature of the tunnel floor is insufficient. Therefore, in this study, the effects of the upper analysis area height and the coefficient of lateral earth pressure of the tunnel located on a tuff deterioration zone with a large rock cover, as well as the floor curvature, were examined through sensitivity analysis. As a result of the analysis, it turned out that the overall stability of the tunnel increases as the floor curvature increases, the coefficient of lateral earth pressure decreases, and the upper analysis region increases.

• Geotechnical Engineering
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• v.9 no.3
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• pp.61-66
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• 1993

In this paper, the incorporation of qualitative(or soft) data, such as outputs of geophysical tests or construction experience which has so far been cumulated, was discussed for rock classsification. Geostatistics wart used for this research since the parameters for the design of tunnels are spatially correlated. In particular, indicator kriging technique, which is one of non -parametric approaches, was used. As a selection criteria for an optimal classification, the cost of errors was adopted and the binary classes were only considered for rock classification. In future, incorporating an appreciable amount of available qualitative data will be necessary in tunnelling projects in which quantitative data are scarce. In this respect, this research is of great significance.

• Journal of Korean Tunnelling and Underground Space Association
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• v.2 no.2
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• pp.50-61
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• 2000

The ground around the portal of a tunnel is the most typical part showing the 3-dimensional mechanical behavior in the tunnel. The portal slope is constructed at the weathered soft rock-mass, and remains as a potential sliding mass. The slope failure around the tunnel portal may happen drastically and induce the great disaster; hence, for the permanent stability several special techniques are required. To solve this problem, the ground around the tunnel portal may be excavated in the arch shape to develop the arching effect in horizontal direction. With the arch-type portal slope, one can reduce considerably the excavation mass and the damage of environments. This approach has not been attempted yet due to the lack of understanding and the well-defined analyzing method, so the retaining wall type portal is more universal. The 3-dimensional finite element analyses were carried out to prove that the arch type is more advantageous in safety and cost than the right angle type. The influence of the tunnel construction sequence and the strength of the rock-mass on the slope stability was investigated by focusing on the maximum shear strain in the slope, and the yield zone at the tunnel face.

• Geotechnical Engineering
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• v.13 no.3
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• pp.101-122
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• 1997

A spiting reinforcement system is composed of a series of radially installed reinforcing spites along the perimeter of the tunnel opening ahead of excavation. The reinforcing spill network is extended into the in-situ soil mass both radially and longitudinally The sailing reinforcement system has been successfully used for the construction of underground openings to reinforce weak rock formations on several occasions. The application of this spiting reinforcement system is currently extended to soft ground tunneling in limited occasions because of lack of reliable analysis and design methods. A method of threetimensional limit equilibrium stability analysis of the smile-reinforced shallow tunnel in soft ground is presented. The shape of the potential failure wedge for the case of smile-reinforced shallow tunnel is assumed on the basis of the results of three dimensional finite element analyses. A criterion to differentiate the spill-reinforced shallow tunnel from the smile-reinforced deep tunnel is also formulated, where the tunnel depth, soil type, geometry of the tunnel and reinforcing spites, together with soil arching effects, are considered. To examine the suitability of the proposed method of threedimensional stability analysis in practice, overall stability of the spill-reinforced shallow tunnel at facing is evaluated, and the predicted safety factors are compared with results from twotimensional analyses. Using the proposed method of threetimensional limit equilibrium stability analysis of the smile-reinforced shallow tunnel in soft ground, a parametric study is also made to investigate the effects of various design parameters such as tunnel depth, smile length and wadial spill spacing. With slight modifications the analytical method of threeiimensional stability analysis proposed may also be extended for the analysis and design of steel pipe reinforced multi -step grouting technique frequently used as a supplementary reinforcing method in soft ground tunnel construction.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.1
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• pp.13-24
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• 2021

Tunnel boring machine (TBM) is widely used for tunnel excavation in hard rock and soft ground. In the perspective of TBM-based tunneling, one of the main challenges is to drive the machine optimally according to varying geological conditions, which could significantly lead to saving highly expensive costs by reducing the total operation time. Generally, drilling investigations are conducted to survey the geological ground before the TBM tunneling. However, it is difficult to provide the precise ground information over the whole tunnel path to operators because it acquires insufficient samples around the path sparsely and irregularly. To overcome this issue, in this study, we proposed a geological type classification system using the TBM operating data recorded in a 5 s sampling rate. We first categorized the various geological conditions (here, we limit to granite) as three geological types (i.e., rock, soil, and mixed type). Then, we applied the preprocessing methods including outlier rejection, normalization, and extracting input features, etc. We adopted a deep neural network (DNN), which has 6 hidden layers, to classify the geological types based on TBM operating data. We evaluated the classification system using the 10-fold cross-validation. Average classification accuracy presents the 75.4% (here, the total number of data were 388,639 samples). Our experimental results still need to improve accuracy but show that geology information classification technique based on TBM operating data could be utilized in the real environment to complement the sparse ground information.

• Journal of Korean Tunnelling and Underground Space Association
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• v.5 no.4
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• pp.323-336
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• 2003

Recently, the development of tunnel reinforcement method has been required relating to the shallow tunnelling in soft ground. In this study, the improvement method on tunnel stability is proposed by evaluating the efficiency of face reinforcement which enables to control extrusion of advance core, however, it is often neglected in urban tunnelling under the poor ground conditions. Systematic pre-confinement ahead of the face improves the tunnel stability, subsequently, displacement of the crown and surface settlement can be restrained by proper method. 3-dimensional numerical analysis including horizontal reinforcement modelling on a face is applied to estimate the behaviour of a tunnel in relation to the ground and reinforcement conditions. Consequently, extrusion at the face decreases significantly after using the horizontal reinforcement and the effect of reinforcement is much increased in case of applying the supplemental reinforcement ahead of the face together. Especially, confinement effect around the tunnel and the core is proved by means of the core reinforcement in poor ground conditions.

• Geomechanics and Engineering
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• v.31 no.6
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• pp.545-556
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• 2022

Evaluation and optimization of tunnel wall convergence (TWC) plays a vital role in preventing potential problems during tunnel construction and utilization stage. When convergence occurs at a high rate, it can lead to significant problems such as reducing the advance rate and safety, which in turn increases operating costs. In order to design an effective solution, it is important to accurately predict the degree of TWC; this can reduce the level of concern and have a positive effect on the design. With the development of soft computing methods, the use of deep learning algorithms and neural networks in tunnel construction has expanded in recent years. The current study aims to employ the long-short-term memory (LSTM) deep neural network predictor model to predict the TWC, based on 550 data points of observed parameters developed by collecting required data from different tunnelling projects. Among the data collected during the pre-construction and construction phases of the project, 80% is randomly used to train the model and the rest is used to test the model. Several loss functions including root mean square error (RMSE) and coefficient of determination (R²) were used to assess the performance and precision of the applied method. The results of the proposed models indicate an acceptable and reliable accuracy. In fact, the results show that the predicted values are in good agreement with the observed actual data. The proposed model can be considered for use in similar ground and tunneling conditions. It is important to note that this work has the potential to reduce the tunneling uncertainties significantly and make deep learning a valuable tool for planning tunnels.

• Journal of the Korean Geotechnical Society
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• v.19 no.4
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• pp.201-209
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• 2003

For the purpose of research study, a vertical shaft of 98m in length and 3.05m in diameter was constructed in the layer of conglomerate by using the Raise Boring Machine (RBM). In order to estimate the net penetration rate of the RBM, which can be used in the stage of design, the in-situ test results were analysed and correlated to data from the boring log in situ and laboratory testing. Its average net penetration rate is 2.233mm/rev while its average advance rate is 0.382m/hr, which is lower than that of TBM(Tunnel Boving Machine). It turns out that the net penetration rate increases with the increase of strength characteristics in rock mass (e.g., uniaxial compression strength, tensile strength, etc.). Similarly, the net penetration rate increases linearly with the hardness of rock mass. These results are contrary to the results of the previous construction sites where the TBM was generally used in the layer of hard rock. However, the trend obtained in this study is in accordance with the findings of Barton suggesting the relationship between Q$_TBM$ and penetration rate in the layer of soft rock. Thus, the trend is valid in soft and/or weathered rocks.

• Tunnel and Underground Space
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• v.25 no.5
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• pp.417-422
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• 2015

This paper introduces the design and operational considerations for TBM tunneling in boulder bed which poses significant problems in terms of advance rate and machine wear. Managing these problems is difficult since normal soil investigation techniques do not accurately predict the presence and frequency of boulders. This has leads to considerable extra costs and delays during construction. In this paper, EPBM design and operational parameters, cutter wear characteristics and soil conditioning method in soft ground condition were studied and key successes were highlighted for future projects in similar ground condition.

• Tunnel and Underground Space
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• v.28 no.3
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• pp.232-246
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• 2018

In this study, the relationship between in situ seismic wave velocities and RMR (rock mass rating) was investigated in a test bed for the examination of the basis of rock classification (RMR) based on seismic wave velocity. The seismic wave velocity showed a monotonous increase with depth. It was also found that there was no systematic correlation between the seismic wave velocity (Vp) and other parameters (RQD, joint spacing, UCS, rock core Vp, and RMR) collected at the same depth of the same borehole. However, correlative relation was observed among RMR, RQD, and joint spacing. On the other hand, when all the data in the borehole (three holes) are examined without considering the depth, Vp still shows no correlation with RMR parameters (e.g., correlative coefficient for uniaxial compressive strength and joint spacing are 0.039 and 0.091, respectively), but Vp shows weak correlative relation with RMR and RQD (correlative coefficient for RQD and RMR are 0.193 and 0.211, respectively). Thus, it is found that it is difficult to deduce physical properties of rock mass directly from seismic wave velocities, but the seismic wave velocity can be used as a tool to approximate rock mass properties because of weaker correlation between Vp and RMR with RQD. In addition, the velocity value of for soft and moderate rocks suggested by widely used construction standards is slower than that of the observed velocity, implying that the standards need to be examined and revised.