• Geomechanics and Engineering
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• v.29 no.3
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• pp.301-310
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• 2022

Accurate prediction of mixed ground conditions ahead of a tunnel face is of vital importance for safe excavation using tunnel boring machines (TBMs). Previous studies have primarily focused on electrical resistivity surveys from the ground surface for geotechnical investigation. In this study, an FE (finite element) numerical model was developed to simulate electrical resistivity surveys for the prediction of risky mixed ground conditions in front of a tunnel face. The proposed FE model is validated by comparing with the apparent electrical resistivity values obtained from the analytical solution corresponding to a vertical fault on the ground surface (i.e., a simplified model). A series of parametric studies was performed with the FE model to analyze the effect of geological and sensor geometric conditions on the electrical resistivity survey. The parametric study revealed that the interface slope between two different ground formations affects the electrical resistivity measurements during TBM excavation. In addition, a large difference in electrical resistivity between two different ground formations represented the dramatic effect of the mixed ground conditions on the electrical resistivity values. The parametric studies of the electrode array showed that the proper selection of the electrode spacing and the location of the electrode array on the tunnel face of TBM is very important. Thus, it is concluded that the developed FE numerical model can successfully predict the presence of a mixed ground zone, which enables optimal management of potential risks.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.03a
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• pp.157-164
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• 2002

Based on the results of prototype air-shaft construction, penetration capacity of RBM(Raise Boring Machine) was analyzed and compared with TBM(Tunnel Boring Machine) performance in this study. Utilization, down time, net penetration rate and advance rate were evaluated and compared. By conducting the laboratory tests for rock properties with the analysis of penetration capacity, relation of penetration capacity and geotechnical parameters was studied. The results showed that much more higher value of utilization, however lower value of net penetration rate for RBM was obtained compared to those of TBM. In addition, as the strength of rock penetrated increased, higher value of net penetration rate was obtained contrarily to the results of TBM performance. Finally, new relationship between total hardness and net penetration rate for weak and weathered rock was derived from these results.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.803-812
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• 2008

Along with the increasing demand for automatic and mechanical tunnel excavation methods in Korea, the Tunnel Boring Machine (TBM) method of tunnel excavation has become increasingly popular. However, in spite of this rising demand, few studies have been performed on the TBM method, in Korea. For this reason, this study focused on evaluation of the applicability of TBM performance prediction models based on field data in order to contribute to the basic and essential parts of TBM designation and the TBM method of tunnel excavation in Korea. These rock properties can be defined as the mechanical and physical factors of rock that have an influence on a disc cutter's ability to cut rock, and provide information for the evaluation of the applicability of field data. Based on outcomes from these tests, applicability of the prediction model was evaluated and the predicted performance of a TBM was compared with real field data obtained from four different TBM construction sites in Korea.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.3
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• pp.257-272
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• 2016

It is usually not an easy task to counter-measure on time and appropriately when confronting with troubles in mechanized tunnelling job-sites because of the limitation of available spaces to perform those actions with the existence of disk cutter, cutter head, chamber and other various apparatus in Tunnel Boring Machine (TBM). So, it is important to predict the ground condition ahead of a tunnel face during tunnel excavation. Efforts have been made to utilize geophysical methods such as elastic wave survey, electromagnetic wave survey, electrical resistivity survey, etc for predicting the ground condition ahead of the TBM tunnel face. Each prediction method among these geophysical methods has its own advantage and disadvantage. Therefore, it might be needed to apply several geophysical methods rather than just one to predict the ground condition ahead of the tunnel face in the complex and/or mixed grounds since those methods will compensate among others. The problem is that each prediction method will give us different answer on the predicted ground condition; how to combine different solutions into a most reasonable and representative predicted value might be important. Therefore, in this study, we proposed a methodology how to systematically combine each prediction method utilizing probabilistic analysis as well as analytic hierarchy process. The proposed methods is applied to a virtual job site to confirm the applicability of the model to predict the ground condition ahead of the tunnel face in the mechanized tunnelling.

• 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.

• Proceedings of the KSR Conference
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• 2003.10b
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• pp.569-578
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• 2003

In this paper a determination of the optimal excavation method and machine type for a tunnel under the Han river between the Sungsoo-dong, Sungdong-Gu and the Chungdaw-dong, Kangnam-Gu in the Bundang railway. The geological investigation results show that some fractured zones exist locally under the northern boundary of the Han river bed, but the other regions consist mostly of hard rocks of good quality in the tunnel excavation level. Also, a hign water pressure of $5kgf/cm^2$ and a flash inflow of river water due to old boring holes are expected during tunnel excavation. A EPB shield TBM is selected as a optimal excavation machine for the Han river tunnel considering the geological and ,site conditions.

• Geomechanics and Engineering
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• v.20 no.6
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• pp.475-484
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• 2020

The prediction of the ground conditions ahead of a tunnel face is very important, especially for tunnel boring machine (TBM) tunneling, because encountering unexpected anomalies during tunnel excavation can cause a considerable loss of time and money. Several prediction techniques, such as BEAM, TSP, and GPR, have been suggested. However, these methods have various shortcomings, such as low accuracy and low resolution. Most studies on electrical resistivity tomography surveys have been conducted using numerical simulation programs, but laboratory experiments were just a few. Furthermore, most studies of scaled model tests on electrical resistivity tomography were conducted only on the ground surface, which is a different environment as compared to that of mechanized tunneling. This study performed a laboratory experimental test to extend and verify a prediction method proposed by Lee et al., which used electrical resistivity tomography to predict the ground conditions ahead of a tunnel face in TBM tunneling environments. The results showed that the modified dipole-dipole array is better than the other arrays in terms of predicting the location and shape of the anomalies ahead of the tunnel face. Having longer upper and lower borehole lengths led to better accuracy of the survey. However, the number and length of boreholes should be properly controlled according to the field environments in practice. Finally, a modified and verified technique to predict the ground conditions ahead of a tunnel face during TBM tunneling is proposed.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.553-581
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• 2022

Shortly after tunnel boring machine (TBM) was introduced in the tunneling industry, the use of TBM has surprisingly increased worldwide due to its performance together with the benefit of being safely and environmentally friendly. One of the main cost items in the TBM tunneling in rock and soil is changing damaged or worn cutters. It is because that the cutter change is a time-consuming and costly activity that can significantly reduce the TBM utilization and advance rate and has a major effect on the total time and cost of TBM tunneling projects. Therefore, the importance of accurately evaluating the cutter life can never be overemphasized. However, the prediction of cutter wear in soil, rock including mixed face is very complex and not yet fully clarified, subsequently keeping engineers busy around the world. Various prediction models for cutter wear have been developed and introduced, but these models almost usually produce highly variable results due to inherent uncertainties in the models. In this study, a case study of design and construction of disc cutter change is introduced and analyzed, rather than proposing a prediction model of cutter wear. As the disc cutter is strongly affected by the geological condition, TBM machine characteristic and operation, authors believe it is very hard to suggest a generalized prediction model given the uncertainties and limitations therefore it would be more practical to analyze a real case and provide a detailed discussion of the difference between prediction and result for the cutter change. By doing so, up-to-date idea about planning and execution of cutter change in practice can be promoted.

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.403-421
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• 2023

As the number of underground structures has increased in recent decades, it has become crucial to predict geological hazards ahead of a tunnel face during tunnel construction. Consequently, this study developed a finite element (FE) numerical model to simulate electrical resistivity surveys in tunnel boring machine (TBM) operations for predicting mixed ground conditions in front of tunnel faces. The accuracy of the developed model was verified by comparing the numerical results not only with an analytical solution but also with experimental results. Using the developed model, a series of parametric studies were carried out to estimate the effect of geological conditions and sensor geometric configurations on electrical resistivity measurements. The results of these studies showed that both the interface slope and the difference in electrical resistivity between two different ground formations affect the patterns and variations in electrical resistivity observed during TBM excavation. Furthermore, it was revealed that selecting appropriate sensor spacing and optimizing the location of the electrode array were essential for enhancing the efficiency and accuracy of predictions related to mixed ground conditions. In conclusion, the developed model can serve as a powerful and reliable tool for predicting mixed ground conditions during TBM tunneling.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.1
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• pp.1-17
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• 2024

Analyzing the tunnel excavation behavior and its effect on the surrounding ground involves large deformation behavior. Therefore, in order to properly simulate the tunnel excavation process and rigorously investigate the actual effect of excavation on surrounding ground and tunnel structure large deformation analysis method is required. In this study, two major numerical approaches capable of considering large deformations behavior were applied to investigate the effect of tunnel boring machine excavation on the surrounding ground: coupled Eulerian-Lagrangian (CEL) and the automatic remeshing (AR) method. Relative performance of both approaches was evaluated through the ground response due to TBM excavation. The ground response will be quantified by estimating the range of the excavation damaged zone (EDZ). By comparing the results, the range of the EDZ will be suggested on the vertical and horizontal direction along the TBM excavation surface. Based on the computed results, it was found that the size of EDZ around the excavation surface and the tendencies was in good agreement among the two approaches. Numerical results clearly show that the size of the EDZ around the tunnel tends to be larger for rock with higher RMR rating. The size of the EDZ is found to be direct proportional to the tunnel diameter, whereas the depth of the tunnel is inversely proportional due to higher confinement stress around the excavation surface.