• Tunnel and Underground Space
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• v.34 no.2
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• pp.154-168
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• 2024

The Tunnel Boring Machine (TBM) disc cutter is subjected to wear and damage during the rock excavation process, and the worn disc cutter should be replaced on time. The manual inspection by workers is generally required to determine the disc cutter replacement. In this case, the workers are exposed to dangerous environments, and the measurements are sometimes inaccurate. In this study, we developed a technology that measures the disc cutter wear in real time. From a series of laboratory tests, a magnetic sensor was selected as the wear sensor, and the real-time disc cutter measurement system was developed integrating wireless communication modules, power supply and data processing board. In addition, the measurement system was verified in actual TBM excavation circumstances. As a result, it was confirmed that the accuracy and stability of the system.

• Tunnel and Underground Space
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• v.34 no.2
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• pp.143-153
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• 2024

Tunnel Boring Machine (TBM) method is a tunnel excavation method that produces lower levels of noise and vibration during excavation compared to drilling and blasting methods, and it offers higher stability. It is increasingly being applied to tunnel projects worldwide. The disc cutter is an excavation tool mounted on the cutterhead of a TBM, which constantly interacts with the ground at the tunnel face, inevitably leading to wear. In this study quantitatively predicted disc cutter wear using geological conditions, TBM operational parameters, and machine learning algorithms. Among the input variables for predicting disc cutter wear, the Uniaxial Compressive Strength (UCS) is considerably limited compared to machine and wear data, so the UCS estimation for the entire section was first conducted using TBM machine data, and then the prediction of the Coefficient of Wearing rate(CW) was performed with the completed data. Comparing the performance of CW prediction models, the XGBoost model showed the highest performance, and SHapley Additive exPlanation (SHAP) analysis was conducted to interpret the complex prediction model.

• Journal of Korean Tunnelling and Underground Space Association
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• v.26 no.1
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• pp.39-58
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• 2024

Tunnel Boring Machines (TBM) use multiple disc cutters to excavate tunnels through rock. These cutters wear out due to continuous contact and friction with the rock, leading to decreased cutting efficiency and reduced excavation performance. The rock's abrasivity significantly affects cutter wear, with highly abrasive rocks causing more wear and reducing the cutter's lifespan. The Cerchar Abrasivity Index (CAI) is a key indicator for assessing rock abrasivity, essential for predicting disc cutter life and performance. This study aims to develop a new method for effectively estimating CAI using rock strength, petrological characteristics, linear regression, and machine learning. A database including CAI, uniaxial compressive strength, Brazilian tensile strength, and equivalent quartz content was created, with additional derived variables. Variables for multiple linear regression were selected considering statistical significance and multicollinearity, while machine learning model inputs were chosen based on variable importance. Among the machine learning prediction models, the Gradient Boosting model showed the highest predictive performance. Finally, the predictive performance of the multiple linear regression analysis and the Gradient Boosting model derived in this study were compared with the CAI prediction models of previous studies to validate the results of this research.

• Journal of the Korean GEO-environmental Society
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• v.11 no.2
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• pp.43-52
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• 2010

Shield method is the tunnel boring method that propels a steel cylinder in the ground and excavates tunnels at once. After Marc Isambard Brunel started using the method for the Thames Riverbed Tunnel excavation in London, many kinds of TBM (Tunnel Boring Machine) developed and applied for the construction of road, railway, electricity channel, pipeline, etc. In comparison with NATM concept that allows to observe ground condition and copes with difficulty. The machine selected before starting construction is not able to be changed during construction in shield TBM. Therefore the machine should be designed based on the ground survey result and experiment, so that the tunnel might be excavated effectively by controlling penetration speed, excavation depth and cutter head speed according to the ground condition change. This research was conducted to estimate penetration depth, excavate speed, wear of disc cutter on Boondang Railway of the Han Riverbed Tunnel ground condition by TBM performance prediction models such as NTNU, $Q_{TBM}$, Total Hardness, KICT-SNU and compare the estimated value with the field data. The estimation method is also used to analyze the reason of poor excavation efficiency at south bound tunnel.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.6D
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• pp.839-848
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• 2011

TBM (Tunnel Boring Machine) tunnel should be carry out with the adopted machine until the end of excavation because of impossibility of replacement or modification of machine. Observation of the face of the tunnel is difficult, especially in EPB(Earth Pressure Balance) shield TBM, predict changes in the ground condition with analyzing data, collected during the excavation, and it should be reflected in construction. Until recently, subjects of studies on TBM are mainly the determination of machine and the development of advance rate prediction model, according to the characteristics of ground which is the target of excavation. However, study focused on the estimation of ground conditions and the improvement in operational methods using excavation data of TBM equipment, the principal of the excavation, has been done not so much. This study examine the variances in advance rate depending on changes in operating conditions and evaluate the optimal operating conditions of adopt machine, using working data obtained from EPB shield TBM project. The result of this study is suggested as follows. First, cutter head RPM and total thrust force are biggest influences on advance rate, Second, it is recommended for proper advance rate that total thrust force is controlled while optimum cutter head RPM is kept, Third, according to the increasing trend of total thrust force, the changes in ground conditions can be predicted, the appropriate operating conditions can be determined.

• Tunnel and Underground Space
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• v.21 no.6
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• pp.508-517
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• 2011

The linear cutting test is the most reliable and accurate approach to measuring cutting forces and cutting efficiency using full-size disc cutter in various rock types. The result of linear cutting tests can be used to obtain the key parameters of cutter-head design (i.e. optimum cutter spacing, cutter forces). In Korea, LCM (Linear Cutting Machine) tests have been performed for typical Korean rock types, but these studies focused on the isotropic rocktypes. For prediction of TBM (Tunnel Boring Machine) performances in complex geological conditions including a bedded and schistose rockmass, it is important to consider the effects of anisotropy of rockmass on cutting performances and cutting efficiency. This study discusses a series of LCM tests that were performed for Asan Gneiss having two types of anisotropy angles to assess the effect of the anisotropy angle on rock-cutting performances of TBM. The result shows that the rock-cutting performances and optimum cutting conditions are affected by anisotropy angle and the effect of anisotropy on rock strength should be considered in a prediction of the cutting performances and efficiency of TBM.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.594-609
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• 2023

TBM (Tunnel Boring Machine) method is gaining popularity in urban and underwater tunneling projects due to its ability to ensure excavation face stability and minimize environmental impact. Among the prominent models for predicting disc cutter life, the NTNU model uses the Cutter Life Index(CLI) as a key parameter, but the complexity of testing procedures and rarity of equipment make measurement challenging. In this study, CLI was predicted using multiple linear regression analysis and tree-based machine learning techniques, utilizing rock properties. Through literature review, a database including rock uniaxial compressive strength, Brazilian tensile strength, equivalent quartz content, and Cerchar abrasivity index was built, and derived variables were added. The multiple linear regression analysis selected input variables based on statistical significance and multicollinearity, while the machine learning prediction model chose variables based on their importance. Dividing the data into 80% for training and 20% for testing, a comparative analysis of the predictive performance was conducted, and XGBoost was identified as the optimal model. The validity of the multiple linear regression and XGBoost models derived in this study was confirmed by comparing their predictive performance with prior research.

• Tunnel and Underground Space
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• v.22 no.2
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• pp.144-156
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• 2012

This paper discusses the methods of estimating the punch penetration indices and data analysis punch penetration test to estimate the TBM normal force and penetration rate. In punch penetration test is known as a useful test to estimate penetration rates and normal force of TBMs directly with several slope indices indicated drill-ability and brittleness of rocks. However, the standard methods and indices for punch penetration test are not suggested yet. The main purpose of punch penetration test which is prediction of normal force of TBM disc cutter when cutters excavate rock mass. In this study, the punch penetration tests were performed for 6 representative Korean rock types and variety length and diameter of rock core specimens. Among slope indices were obtained from punch penetration test, PLI and MLI which is suggested in this study show high correlation with cutter force measured by full-scale cutting test. The results show that the predicted normal force of a single disc cutter and the experimental error was 10%. Based on these results, it is concluded that punch penetration test is reliable laboratory test for estimating thrust and penetration rates of TBM.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.5
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• pp.281-302
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• 2021

Railway projects have been consistently increasing in Korea. In relation to this trend, the mechanized tunneling using Tunnel Boring Machine (TBM) is preferably applied for mining urban areas and passing under rivers. The TBM tunneling under difficult grounds like mixed faces with high water pressure could require ground improvements for stable TBM advance or safe cutter head intervention (CHI). In this study, pre-grouting works for CHI in Daegok-Sosa railway project are presented in terms of the grouting zone design, the executions and the results, the lessons learned from the experience. It should be mentioned that the grouting from inside TBM was carried out several times and turned out to be inefficient in the project. Therefore, grouting experiences from the surface are highlighted in this study. Jet grouting was implemented on CHI points on land, while permeation grouting off shore in the Han River, which mostly allow to access the cutter head of TBM in free air with stable faces. The results of CHI works have been analyzed and the lesson learned are suggested.

• 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.