• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.3
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• pp.201-220
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• 2023

Power cable tunnels is one of the underground structures meant for electricity transmission and are constructed using shield TBM method when transitting across urban and subsea regions. With the increasing shaft depth for tunnels excavation when the shield TBM excavated the rock mass, the review of selecting closed-type shield TBM in rocks becomes necessary. A simplified shield TBM design method is also necessary based on conventional geotechnical survey results. In this respect, design method and related design program are developed based on combined results of full-scale tests, considerable amount of accumulated TBM data, and numerical simulation results. In order to validate the program results, excavation data of a completed power cable tunnel project are utilized. Thrust force, torque, and power of shield TBM specification are validated using Kernel density concept which estimates the population data. The robustness of design expertise is established through this research which will help in stable provision of electricity supply.

• Tunnel and Underground Space
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• v.29 no.6
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• pp.394-406
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• 2019

Difficult ground conditions (e.g., fault zone and mixed grounds) are highly probable to appear in subsea and urban tunnels because of the shallow working depth and alluvial characteristics. TBM usually experienced decrease of penetration rate and increase of downtime when it meets these difficult ground conditions. The problems are usually caused by the adverse geological conditions, and it is preferable to determine the optimal operational parameters of TBM based on the previous operational data obtained while excavating a preceding tunnel. This study carried out for efficient TBM excavation in fault zone and mixed grounds. TBM excavation data from the tunnel site in Singapore and the characteristics of the TBM excavation data was analyzed. The key operational parameters (i.e., thrust, torque, and RPM), penetration rate, and downtime were highly influenced by the presence of fault zones and mixed grounds, and the features was discussed. It is expected that the results and main discussions will be useful information for future tunneling projects in similar geological conditions.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.5
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• pp.575-589
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• 2020

In recent years, Shield TBM construction has been continuously increasing in domestic tunnels. The main excavation tool in the shield TBM construction is a disc cutter which naturally wears during the excavation process and significantly degrades the excavation efficiency. Therefore, it is important to know the appropriate time of the disc cutter replacement. In this study, it is proposed a predictive model that can determine yes/no of disc cutter replacement using machine learning algorithm. To do this, the shield TBM machine data which is highly correlated to the disc cutter wears and the disc cutter replacement from the shield TBM field which is already constructed are used as the input data in the model. Also, the algorithms used in the study were the support vector machine, k-nearest neighbor algorithm, and decision tree algorithm are all classification methods used in machine learning. In order to construct an optimal predictive model and to evaluate the performance of the model, the classification performance evaluation index was compared and analyzed.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.4
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• pp.519-534
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• 2019

Mechanized tunneling methods, including shield TBM, have been increasingly used for tunnel construction because of their relatively low vibration and noise levels as well as low risk of rock-falling accidents. In the excavation using the shield TBM, it is important to design penetration rate appropriately. In present study, both subsurface investigation data and shield TBM excavation data, produced for and during ${\bigcirc}{\bigcirc}{\sim}{\bigcirc}{\bigcirc}$ high-speed railway construction, were analyzed and used to compare with shield TBM penetration rates calculated using existing penetrating rate prediction models proposed by several foreign researchers. The correlation between thrust force per disk cutter and uniaxial compressive strength was also examined and, based on the correlation analysis, a simple prediction model for penetration rate was derived. The prediction results using the existing prediction models showed approximately error rates of 50~500%, whereas the results from the simple model proposed from this study showed an error rate of 15% in average. It may be said, therefore, that the proposed model has higher applicability for shield TBM construction in similar ground conditions.

• Tunnel and Underground Space
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• v.25 no.5
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• pp.397-407
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• 2015

Estimation of shield TBM tunnelling-induced volume loss is of great importance for ground settlement control. This study proposed a simple method for evaluation of volume loss during TBM tunnlling, which is able to take into account of shield machine configurations and main driving data in calculation. The method was applied to analyze the tunnelling cases with earth pressure balanced and slurry pressure balanced shiled TBM, and mostly, reasonable agreements with monitoring results were found. Additional discussions were made for some disagreements.

• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.3
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• pp.347-362
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• 2019

Underground excavation using TBM machines has been increasing to reduce complaints caused by noise, vibration, and traffic congestion resulted from the urban underground construction in Korea. However, TBM excavation design and construction still need improvement because those are based on standards of the technologically advanced countries (e.g., Japan, Germany) that do not consider geological environment in Korea at all. Above all, although TBM performance is a main factor determining the TBM machine type, duration and cost of the construction, it is estimated by only using UCS (uniaxial compressive strength) as the ground parameters and it often does not match the actual field conditions. This study was carried out as part of efforts to predict penetration rate suitable for Korean ground conditions. The effective parameters were defined through the correlation analysis between the penetration rate and the geotechnical parameters or TBM performance parameters. The effective parameters were then used as variables of the multiple regression analysis to derive a regression model for predicting TBM penetration rate. As a result, the regression model was estimated by UCS and joint spacing and showed a good agreement with field penetration rate measured during TBM excavation. However, when this model was applied to another site in Korea, the prediction accuracy was slightly reduced. Therefore, in order to overcome the limitation of the regression model, further studies are required to obtain a generalized prediction model which is not restricted by the field conditions.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.393-402
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• 2021

The first TBM introduced in Korea was the gripper TBM, which was applied to the Gudeok Waterway Tunnel in 1985. In the initial stage of the introduction of the gripper TBM, many applications were mainly focused on waterway tunnels (Tunnel Mechanized Construction Design, 2008). Currently, the construction range of gripper TBM in Korea is widely applied to not only waterway tunnels, but also subways, railway tunnels, and TBM+NATM expansion. Overseas, gripper TBM is generally applied, and even when NATM tunnel is applied, it is applied as an exploration tunnel because of the excellent advance rate of gripper TBM and used as an evacuation tunnel after completion. Due to the fast excavation speed, the application of the gripper TBM in the rock section of weathered rock or higher can minimize the environmental and civil complaints caused by creating a large number of work areas when planning long tunnels or mountain tunnels. In this study, the work process of the general gripper TBM was analyzed by analyzing the construction cycle and the gripper TBM with a diameter of 2.6~5.0 m, which was applied the most in Korea. Downtime was investigated and analyzed.

• Tunnel and Underground Space
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• v.30 no.3
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• pp.214-225
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• 2020

Uniaxial compressive strength (UCS) of rock is one of the important factors to determine the advance speed during shield TBM tunnel excavation. UCS can be obtained through the Geotechnical Data Report (GDR), and it is difficult to measure UCS for all tunneling alignment. Therefore, the purpose of this study is to predict UCS by utilizing TBM machine driving data and machine learning technique. Several machine learning techniques were compared to predict UCS, and it was confirmed the stacking model has the most successful prediction performance. TBM machine data and UCS used in the analysis were obtained from the excavation of rock strata with slurry shield TBMs. The data were divided into 8:2 for training and test and pre-processed including feature selection, scaling, and outlier removal. After completing the hyper-parameter tuning, the stacking model was evaluated with the root-mean-square error (RMSE) and the determination coefficient (R²), and it was found to be 5.556 and 0.943, respectively. Based on the results, the sacking models are considered useful in predicting rock strength with TBM excavation data.

• Tunnel and Underground Space
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• v.30 no.6
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• pp.540-550
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• 2020

Machine learning has been actively used in the field of automation due to the development and establishment of AI technology. The important thing in utilizing machine learning is that appropriate algorithms exist depending on data characteristics, and it is needed to analysis the datasets for applying machine learning techniques. In this study, advance rate is predicted using geotechnical and machine data of TBM tunnel section passing through the soil ground below the stream. Although there were no problems of application of statistical technology in the linear regression model, the coefficient of determination was 0.76. While, the ensemble model and support vector machine showed the predicted performance of 0.88 or higher. it is indicating that the model suitable for predicting advance rate of the EPB Shield TBM was the support vector machine in the analyzed dataset. As a result, it is judged that the suitability of the prediction model using data including mechanical data and ground information is high. In addition, research is needed to increase the diversity of ground conditions and the amount of data.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.1
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• pp.61-74
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• 2016

This paper presents a case study on the ground settlement and volume loss estimation for slurry pressure balanced shield TBM tunnelling in weathered zone of granite rock. Settlement at each stage of shield tunnelling was analyzed and the volume losses and settlement trough factors were estimated from observations. In addition, using the existing volume loss evaluation method in literature, volume losses were estimated considering ground properties and actual driving parameters. Most of ground settlement occurred during passage of shield skin passage and after backfill grouting, and the measured total volume loss and trough curves appeared to coincide with literature. Shield and tail loss obtained from field measurement were found to be around 90% and 60% of the predictions, where tail loss indicated larger deviation than shield loss.