• Tunnel and Underground Space
• /
• v.32 no.6
• /
• pp.502-517
• /
• 2022

As the use of TBM increases, research has recently increased to to analyze TBM data with machine learning techniques to predict the exchange cycle of disc cutters, and predict the advance rate of TBM. In this study, a regression prediction of disc cutte wear of slurry shield TBM site was made by combining machine learning based on the machine data and the geotechnical data obtained during the excavation. The data were divided into 7:3 for training and testing the prediction of disc cutter wear, and the hyper-parameters are optimized by cross-validated grid-search over a parameter grid. As a result, gradient boosting based on the ensemble model showed good performance with a determination coefficient of 0.852 and a root-mean-square-error of 3.111 and especially excellent results in fit times along with learning performance. Based on the results, it is judged that the suitability of the prediction model using data including mechanical data and geotechnical information is high. In addition, research is needed to increase the diversity of ground conditions and the amount of disc cutter data.

• Journal of the Korean Geotechnical Society
• /
• v.22 no.11
• /
• pp.55-64
• /
• 2006

It is very Important to predict the damage zone of a rock mass induced by blasting for the excavation of an underground cavity such as a tunnel, as the damage zones incur mechanical and hydraulic instability of the rock mass potentially. Complicated blasting processes that can hinder the proper characterization of the damage zone can be effectively represented by two loading mechanisms. The first mechanism is the dynamic impulsive load-generating stress waves that radiate outwards immediately after detonation. This load creates a crushed annulus along with cracks around the blasthole. The second is the gas pressure that remains for an extended time after detonation. As the gas pressure reopens some arrested cracks and extends these, it contributes to the final structure of the damage zone induced by the blasting. This paper presents a simple method to evaluate the damage zone induced by gas pressure during rock blasting. The damage zone is characterized by analyzing crack propagations from the blasthole. To do this, a model of a blasthole with a number of radial cracks that are equal in length in a homogeneous infinite elastic plane is considered. In this model, crack propagation is simulated through the use of only two conditions: a crack propagation criterion and the mass conservation of the gas. The results show that the stress intensity factor of a crack decreases as the crack propagates from the blasthole, which determines the crack length. In addition, it was found that the blasthole pressure continues to decrease during crack propagation.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.29 no.6D
• /
• pp.737-743
• /
• 2009

Shield TBM, since it was employed for Suyoungman Bay riverbed tunnel of Busan Subway in 2000,has been increasingly adopted in Korea, and in line with growing popularity, the study on Shield TBM has been expanded. However the studies mostly focus on ground condition in a bid to estimate the advancement rate and develop the model for calculating the excavation efficiency, whereas the efforts to analyze the cause of delay and to develop the improvement measures have been neglected. Thus the studies were mostly intended to analyze the schedule slippage focusing on ground conditions, while the study on schedule behind due to equipment itself and related facilities have yet to be attempted in earnest. This study hence was aimed at evaluating the troubles and schedule slippage caused by mechanical elements such as shield TBM equipment and tools and ground conditions, making use of FMEA approach so as to analyze the risk of schedule delay by such elements, thereby proposing the preventive measures to deal with high-risk factors. So, this study suggest the solution to highly ranked trouble factor for the purpose of enhance the efficiency on Shield TBM.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.1C
• /
• pp.45-51
• /
• 2010

In urban area, design and construction of civil engineering structures such as subway tunnel, underground space and deep excavation is impeded by unreliable site investigation. Variety of embedded objects, electric noises and traffic vibrations degrades the quality of site investigation, whatever the site-investigation technique would be. In this research, a preliminary research was performed to develop a dedicated site investigation technique for urban geotechnical sites, which can overcome the limitations of urban sites. HiRAS (Hybrid Integration of Surface Waves and Resistivity) technique which is the first outcome of the preliminary research was proposed in this paper. The technique combines surface wave as well as electrical resistivity. CapSASW method for surface-wave technique and PDC-R technique for electrical resistivity survey were incorporated to develop HiRAS technique. CapSASW method is a good method for evaluating material stiffness and PDC-R technique is a reliable method for determination of underground stratification even in a site with electrical noise. For the inversion analysis of HiRAS techniuqe, a site-specific relationship between stress-wave velocity and resistivity was employed. As for outgrowth of this research, the 2-D distribution of Poisson's ratio could be also determined.

• Tunnel and Underground Space
• /
• v.33 no.6
• /
• pp.547-560
• /
• 2023

Recently, research on predicting ground classification using machine learning techniques, TBM excavation data, and ground data is increasing. In this study, a multi-classification prediction study for uniaxial compressive strength (UCS) was conducted by applying random forest model based on a decision tree among machine learning techniques widely used in various fields to machine data and ground data acquired at three slurry shield TBM sites. For the classification prediction, the training and test data were divided into 7:3, and a grid search including 5-fold cross-validation was used to select the optimal parameter. As a result of classification learning for UCS using a random forest, the accuracy of the multi-classification prediction model was found to be high at both 0.983 and 0.982 in the training set and the test set, respectively. However, due to the imbalance in data distribution between classes, the recall was evaluated low in class 4. It is judged that additional research is needed to increase the amount of measured data of UCS acquired in various sites.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.18 no.5
• /
• pp.453-467
• /
• 2016

Overall risks that can occur in a shield TBM tunnelling are studied in this paper. Both the potential risk events that may occur during tunnel construction and their causes are identified, and the causal relationship between causes and events is obtained in a systematic way. Risk impact analysis is performed for the potential risk events and ways to mitigate the risks are summarized. Literature surveys as well as interviews with experts were made for this purpose. The potential risk events are classified into eight categories: cuttability reduction, collapse of a tunnel face, ground surface settlement and upheaval, spurts of slurry on the ground, incapability of mucking and excavation, and water leakage. The causes of these risks are categorized into three areas: geological, design and construction management factors. Bayesian Networks (BN) were established to systematically assess a causal relationship between causes and events. The risk impact analysis was performed to evaluate a risk response level by adopting an Analytic Hierarchy Process (AHP) with the consideration of the downtime and cost of measures. Based on the result of the risk impact analysis, the risk events are divided into four risk response levels and these levels are verified by comparing with the actual occurrences of risk events. Measures to mitigate the potential risk events during the design and/or construction stages are also proposed. Result of this research will be of the help to the designers and contractors of TBM tunnelling projects in identifying the potential risks and for preparing a systematic risk management through the evaluation of the risk response level and the migration methods in the design and construction stage.