Realization of Super-Large-Diameter Slurry Shield Passing through Settlement-Sensitive Area Based on Unreinforced Disturbance Control Technology

Due to the complex construction conditions of shield tunnels, ground disturbance is inevitable during the construction process, which leads to surface settlement and, in serious cases, damage to surrounding buildings (structures). Therefore, it is especially important to effectively control the constructive settlement of subway tunnels when crossing settlement-sensitive areas such as high-density shantytowns. Based on the project of Wuhan Metro Line 8 Phase I, the shield of Huangpu Road Station-Xujiapang Road Station interval crossing high-density shantytowns, we study the disturbance control technology of oversized diameter mud and water shield crossing unreinforced settlement-sensitive areas during the construction process. By optimizing the excavation parameters and evaluating the ground buildings, the excavation process can be monitored at the same time, and the water pressure, speed, and tool torque required during the excavation during the construction process can be finely adjusted; the control of tunneling process parameters can provide reference and basis for analyzing the construction control of large-diameter shield through old shantytowns.

Chloride Transport Behaviour and Service Performance of Cracked Concrete Linings in Coastal Subway Tunnels

The concrete lining in subway tunnels often undergoes cracking damage in coastal cities. The combination of cracked tunnel lining structures and high concentrations of corrosive ions in the groundwater (e.g., chlorine) can accelerate concrete erosion, reduce the mechanical performance of the lining structures and shorten the tunnel service life. This paper investigates the chloride ion concentration in the groundwater of several subway tunnels in the coastal city of Qingdao, China. Indoor experiments and numerical simulations are conducted to investigate the chloride ion transport behaviour and service performance of cracked concrete linings. The results are applied to predict the service life of lining structures. The crack depth in concrete linings is found to have the most significant effect on the transport rate of chloride ions, followed by the crack width. The numerical simulations are carried out using COMSOL software to study the chloride transport behaviour in cracked specimens and predict the service lifetimes of lining structures of different thicknesses, and the results correspond well with the experimental data. The durability of a concrete lining can be enhanced by increasing the thickness of the protective concrete layer. Additional measures are proposed for treating cracked concrete linings to resist chloride ion attack in subway tunnels.

An Analytical Solution for 2D Dynamic Structure-Soil-Structure Interaction for Twin Flexible Tunnels Embedded in a Homogeneous Half-Space

The interaction between subway tunnels is investigated by using a 2D analytic model of a twin tunnels system embedded in a homogenous half-space. The closed-form analytical solution for tunnel displacement response is derived through the wave function expansion method and the mirror method, and the correctness of the solution is verified through residuals convergence and comparison with the published results. The analysis focuses on the effects of tunnel relative stiffness on tunnel–soil–tunnel interaction. Tunnel relative stiffness has a great influence on tunnel displacement response. For small tunnel relative stiffness, tunnel displacement amplitude can be enlarged by 3.3 times that of single rigid tunnel model. The response of the tunnel–soil–tunnel interaction system depends not only on the distances between tunnels but also on the frequency of the incident wave and the incident angle. The strength of the interaction between the tunnels is highly related to the tunnel spacing distance. The smaller the distance between tunnels, the stronger the interaction between them. When the distance between tunnels reaches s/a = 20, the interaction between tunnels can be ignored. It is worth pointing out that the seismic design of underground tunnels should consider the interaction between tunnels when the tunnel distance is small.

Theoretical, Numerical, and Experimental Study on the Identification of Subway Tunnel Structural Damage Based on the Moving Train Dynamic Response

As an important part of urban rail transit, subway tunnels play an important role in alleviating traffic pressure in mega-cities. Identifying and locating damage to the tunnel structure as early as possible has important practical significance for maintaining the long-term safe operation of subway tunnels. Summarizing the current status and shortcomings of the structural health monitoring of subway tunnels, a very economical and effective monitoring program is proposed, which is to use the train vibration response to identify and locate the damage of the tunnel structure. Firstly, the control equation of vehicle–tunnel coupling vibration is established and its analytical solution is given as the theoretical basis of this paper. Then, a damage index based on the cumulative sum of wavelet packet energy change rate (TDISC) is proposed, and its process algorithm is given. Through the joint simulation of VI-Rail and ANSYS, a refined 3D train-tunnel coupled vibration model is established. In this model, different combined conditions of single damage and double damage verify the validity of the damage index. The effectiveness of this damage index was further verified through model tests, and the influence of vehicle speed and load on the algorithm was discussed. Numerical simulation and experimental results show that the TDISC can effectively locate the damage of the tunnel structure and has good robustness.

Research on and Application of Tunnel Structure Defects Prediction Using Machine Learning Methods

With the rapid development of underground engineering in China, more metro tunnels are being constructed, the mileage of subway tunnels is increasing, and the corresponding problems of tunnel structure diseases are becoming more prominent. At present, the treatment of tunnel structural diseases mainly relies on manual inspection and identification, and research on defects prediction is still lacking. Because of the complexity of the factors affecting tunnel structure diseases, it is difficult to analyze the causes and development trend of the diseases comprehensively by manual analysis. Fortunately, machine learning methods have gained popularity in classification and regression tasks in recent decades. Many algorithms, such as decision tree algorithms, the random forest algorithm, and XGBoost, have been applied in fields including finance, engineering, and transportation. This study aimed to analyze the prediction effect of machine learning models by feeding 68055 segment lining rings of six subway lines in a city. According to the disease records from 2014 to 2016 and the corresponding convergence and characteristic data, defect conditions in 2017 were predicted and compared with real defect conditions in 2017. The accuracy rates and F1 values of the predicted results were all above 80%. The prediction results can help tunnel maintenance departments and relevant government regulators make auxiliary decisions to control tunnel structure diseases, and can help them focus on the tunnel interval of severe diseases to clarify the development trend of tunnel disease.