This study demonstrates a three-dimensional numerical simulation of earth pressure balance (EPB) shield tunnelling using a coupled discrete element method (DEM) and a finite difference method (FDM). The analysis adopted the actual size of a spoke-type EPB shield tunnel boring machine (TBM) consisting of a cutter head with cutting tools, working chamber, screw conveyor, and shield. For the coupled model to reproduce the in situ ground condition, the ground formation was generated partially using the DEM (for the limited domain influenced by excavation), with the rest of the domain being composed of FDM grids. In the DEM domain, contact parameters of particles were calibrated via a series of large-scale triaxial test analyses. The model simulated tunnelling as the TBM operational conditions were controlled. The penetration rate and the rotational speed of the screw conveyor were automatically adjusted as the TBM advanced to prevent the generation of excessive or insufficient torque, thrust force, or chamber pressure. Accordingly, these parameters were maintained consistently around their set operational ranges during excavation. The simulation results show that the proposed numerical model based on DEM–FDM coupling could reasonably simulate EPB driving while considering the TBM operational conditions.

This study predicted soil classification using data gathered during the operation of an earth-pressure-balance-type tunnel boring machine (TBM). The prediction methodology used machine learning to find relationships between the TBM’s operating parameters which are monitored continuously during excavation, and the engineering characteristics of the ground which are only available from prior geotechnical investigation. Classification criteria were set using the No. 200 sieve pass rate and N-value and employed classification algorithms that used data for six operating parameters (penetration rate, thrust force, cutterhead torque, screw torque, screw revolution speed, and earth pressure). The results of the ensemble model (i.e., AdaBoost, gradient boosting, XG boosting, and Light GBM), decision tree, and SVM model were examined. As a result, the decision tree and AdaBoost models showed accuracy values of 0.759 to 0.879 in the first and second classification steps, but with poor precision and recall values of around 0.6. In contrast, the gradient boosting, XG boosting, Light GBM, and support vector models all showed excellent performance, with accuracy values over 0.90, and strong precision and recall values. Comparing the performance and the speed of learning using the same PC found Light GBM which showed both excellent learning performance and speed to be a suitable model for predicting soil classification using TBM operating data. The classification model developed here is expected to help guide excavation in sections of ground that lack prior geotechnical information.

This study used a discrete-element analysis to predict the excavation performance of a 7.73 m-diameter earth pressure balance (EPB) shield tunnel boring machine (TBM). The simulation mainly predicted several excavation performance indicators for the machine, under different operating conditions. The number of particles in the chamber and the chamber pressure varied, as the operating conditions changed during the simulated TBM excavation. The results showed that the compressive force, torque, and driving power acting on the TBM cutterhead varied with its rotation speed, increasing as the cutterhead rotation speed rose. The overall compressive force acting on all of the disc cutters and their impact wear increased linearly as the cutterhead rotation accelerated. The position of a disc cutter on the cutterhead had a particularly strong influence, with higher compressive forces experienced by the cutters closer to the center. In contrast, the gauge disc cutters at the transition zone of the cutterhead showed more wear than those elsewhere. The muck discharge rate and the driving power of the screw conveyor rose with increasing screw conveyor and cutterhead rotation speeds. Finally, this study suggests optimal operation conditions, based on pressure balance and operational management of the TBM.

Waterproof membranes have higher initial strength, faster construction, and better waterproofing than conventional sheet membranes. In addition, their polymer constituents have much higher interfacial adhesion and tensile strength than those of conventional materials. However, despite their advantages, waterproof membranes are not widely used in civil construction. This study evaluates the material properties and interface parameters of a waterproof membrane by considering the results of laboratory experiments and numerical analysis. Since the contact behavior of a membrane at its interface with shotcrete is important for understanding the mechanism of the support it offers known as a shotcrete tunnel lining, modeling should adopt appropriate contact conditions. The numerical analysis identifies the suitability and contact conditions of the waterproof membrane in various conditions.

This study reports on the development of an operating model for an EPB Shield TBM simulator by the correlation between operating parameters. First, four main operating parameters required for excavation are analyzed, then multiple regression analysis estimates their requirements depending on the ground conditions and the TBM’s specifications. Further multiple regression analysis then determines the interactions between six operational actions and ten mechanical responses. Operating procedures are established, and interlock and warning alarm systems are designed for use in the operating model. Lastly, several simulations were tested for the operating model of the TBM simulator under various conditions.