• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.364-367
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• 2007

According to increase of construction projects which is accomplished in the town, diaphragm wall method was proposed. This method diminished noise and vibration. And it is able to excavate deeper than other methods. But excavation work is difficult to maintain vertical and requires much time to work. Also the work result depends on know-how, experience and intuition of excavating machine operator. We interviewed technical experts related with slurry wall method and find equipment's characteristics. We used cost-concern matrix to investigate the propriety for the introduction of trench cutter automation. Through the research, it is proper to apply trench cutter automation.

• Geomechanics and Engineering
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• v.11 no.1
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• pp.117-139
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• 2016

Previous studies for soil movements induced by tunneling have primarily focused on the free soil displacements. However, the stiffness of existing structures is expected to alter tunneling-induced ground movements, the sheltering influences for underground structures should be included. Furthermore, minimal attention has been given to the settings for the shield machine's operation parameters during the process of tunnels crossing above and below existing tunnels. Based on the Shanghai railway project, the soil movements induced by an earth pressure balance (EPB) shield considering the sheltering effects of existing tunnels are presented by the simplified theoretical method, the three-dimensional finite element (3D FE) simulation method, and the in-situ monitoring method. The deformation prediction of existing tunnels during complex traversing process is also presented. In addition, the deformation controlling safety measurements are carried out simultaneously to obtain the settings for the shield propulsion parameters, including earth pressure for cutting open, synchronized grouting, propulsion speed, and cutter head torque. It appears that the sheltering effects of underground structures have a great influence on ground movements caused by tunneling. The error obtained by the previous simplified methods based on the free soil displacements cannot be dismissed when encountering many existing structures.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.03a
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• pp.562-570
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• 2010

This study was conducted to estimate the number of disc cutter consumption and to predict amount of disc cutters when a shield TBM(Tunnel Boring Machine) of the Han Riverbed Tunnel was applied. In fact, it is almost impossible to change the machine after starting the excavation using the shield TBM method. Therefore, it is important to design an appropriate equipment in the shield method - an efficiency choice of the operation equipment plays a key role in the shield tunnel processing. For the above reason, the disc cutter consumption prediction is quite important so that the detailed analysis is required. A number of disc cutter consumption was predicted by the three methods, viz. KOMATSU, MITSUBISHI and NTNU. In addition, the predicted results were compared with field data. The prediction of disc cutter consumption showed that 237 for KOMATSU, 501 for MITSUBISHI, and 634 for NTNU, respectively. However, a total number of 1,263 disc cutter consumption were investigated during the tunnel construction. It was found that there was a huge difference between the predicted and real values of the disc cutter consumption. The more detailed investigation showed that the disc cutter was worn out bluntly in the northbound tunnel, meanwhile it was worn out sharply in the southbound tunnel. In particular, the disc cutter consumption in the southbound tunnel was increased rapidly because of rear abrasion for remaining mucks in the chamber.

• 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.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.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.463-481
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• 2020

Cutter suction dredgers (CSDs) are widely used in various dredging constructions such as channel excavation, wharf construction, and reef construction. During a CSD construction, the main operation is to control the swing speed of cutter to keep the slurry concentration in a proper range. However, the slurry concentration cannot be monitored in real-time, i.e., there is a "time-lag effect" in the log of slurry concentration, making it difficult for operators to make the optimal decision on controlling. Concerning this issue, a solution scheme that using real-time monitored indicators to predict current slurry concentration is proposed in this research. The characteristics of the CSD monitoring data are first studied, and a set of preprocessing methods are presented. Then we put forward the concept of "index class" to select the important indices. Finally, an ensemble learning algorithm is set up to fit the relationship between the slurry concentration and the indices of the index classes. In the experiment, log data over seven days of a practical dredging construction is collected. For comparison, the Deep Neural Network (DNN), Long Short Time Memory (LSTM), Support Vector Machine (SVM), Random Forest (RF), Gradient Boosting Decision Tree (GBDT), and the Bayesian Ridge algorithm are tried. The results show that our method has the best performance with an R² of 0.886 and a mean square error (MSE) of 5.538. This research provides an effective way for real-time predicting the slurry concentration of CSDs and can help to improve the stationarity and production efficiency of dredging construction.

• Journal of the Korean GEO-environmental Society
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• v.19 no.3
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• pp.35-45
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• 2018

It is essential to predict ground conditions ahead of the tunnel face during tunnel excavation. Various studies on tunnel prediction method of the ground condition ahead of the tunnel face have already been done and applied to in mechanized tunnelling job sites. So, all the methods used in mechanized tunnelling to predict ground conditions ahead of the tunnel face were reviewed. A questionnaire surveying Tunnel Boring Machine (TBM) operators with at least 10 years' experience in TBM operation was used to determine the requirements for prediction methods as well as the distance from the tunnel face that must be assessed. Based on the result of questionnaire survey, the most feasible prediction methods applicable to mechanized tunnelling job-sites are suggested. One of the prediction methods applicable to mechanized tunnelling job-sites might be the electrical resistivity survey by utilizing the disk cutter on the cutterhead as electrode. So, in this study, laboratory tests were performed to evaluate the feasibility of prediction method utilizing electrical resistivity survey at mechanized tunnelling job-sites. It was found that geological condition ahead of 0.3 times of TBM's diameter from tunnel face could be predicted.

• Journal of the Korean Geotechnical Society
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• v.19 no.6
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• pp.39-47
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• 2003

Rockbursts are mainly caused by a sudden release or the stored strain energy in the rock mass. They have been the major hazard in deep hard rock mines but rarely occur in tunnels. Due to the short history and limited information on rockbursts, the topic has rarely been studied in Korea. Some cases of rockbursts, however, have been reported during construction of a mountain tunnel for waterway. This study focuses on analyzing data on rockbursts obtained from a TBM (Tunnel Boring Machine) tunnel and suggests methods for a comprehensive understanding on rockbursts. From the analysis of the field data of rockbursts, it was found that most rockbursts mainly occurred at the section between the tunnel face and the TBM operating room, and the rock bursting phenomena lasted up to 20 days after excavation in certain areas. The data also show that the bursting spots are located all around the tunnel surface including the face, the wall, and the roof, The maximum size of bursting spots is usually less than 100cm. This study also suggests new scale systems of brittleness and uniaxial compressive strength to evaluate the possible tendency for a rockburst. These systems are scaled based on the scale system of strain energy density. In addition, with these scale systems, this research shows that there are potentially higher tendencies for rockbursts in this specific tunnel. Moreover this research suggests that properties of rock and rock mass, RMR (Rock Mass Rating) value, tunneling method, excavating speed, and depth of tunnel have a strong correlation with rockbursts.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.1
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• pp.1-12
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• 2016

When utilizing a Tunnel Boring Machine (TBM) for tunnelling work, unexpected ground conditions can be encountered that are not predicted in the design stage. These include fractured zones or mixed ground conditions that are likely to reduce the stability of TBM excavation, and result in considerable economic losses such as construction delays or increases in costs. Minimizing these potential risks during tunnel construction is therefore a crucial issue in any mechanized tunneling project. This paper proposed the potential risk events that may occur due to risky ground conditions. A resistivity survey is utilized to predict the risky ground conditions ahead of the tunnel face during construction. The potential risk events are then evaluated based on their occurrence probability and impact. A TBM risk management system that can suggest proper solution methods (measures) for potential risk events is also developed. Multi-Criterion Decision Making (MCDM) is utilized to determine the optimal solution method (optimal measure) to handle risk events. Lastly, an actual construction site, at which there was a risk event during Earth Pressure-Balance (EPB) Shield TBM construction, is analyzed to verify the efficacy of the proposed system.