The precast composite reinforced concrete wall with the advantages of fewer joints, superior impermeability and rapid construction provides an efficient and environmental friendly alternative in the construction of underground utility tunnels in the last few years. To investigate the seismic performance of precast concrete composite walls of utility tunnels with grouting-sleeve connection under out-of-plane loads, a series of quasi-static cyclic tests were performed on the full-scale sidewall specimens with different axial compression ratios in this study. The experimental results including the failure modes, crack distributions, and the influence of different connections on the out-of-plane seismic performance of precast concrete composite wall were carefully examined and compared with those from the cyclic tests of the cast-in-place sidewalls of the utility tunnel. The test results show that the seismic performance of the precast concrete composite sidewall specimen, such as the hysteresis curves, the ultimate bearing capacity, stiffness degradation pattern and the ductility ratio, is basically the same as that of the cast-in-place specimen, indicating that the seismic performance of the prefabricated structure is equivalent to that of the cast-in-place structure. Moreover, the grouting-sleeves of the joints can effectively transfer the reinforcement stress until the failure of the precast concrete composite sidewall specimens, which exhibits excellent out-of-plane ductility and serviceability.

The long and large diameter uncharged hole boring (LLB) method is a cut blasting method that minimizes blast-induced vibrations by creating long and large diameter uncharged holes at the excavation face of tunnels prior to tunnel excavation. Drilling in this method typically uses a 50 m long with a 382 mm diameter hammer bit in the horizontal direction at the tunnel face. However, the significant weight and uni-directional rotation of the rod head, as well as variables such as geological characteristics, machine conditions, and inexperienced operators result in significant deviation from the target borehole alignment that hinders the vibration-dampening effect of the uncharged holes. Furthermore, since there is no method to verify the alignment of the boreholes until main tunnel construction, borehole misalignment is often not discovered until weeks after construction, which requires tunnel construction to cease until the equipment can be remobilized and an additional borehole be created, causing significant delays and increased costs for the entire tunnel project. In this study, the borehole alignment tracking and ground exploration system (BGS) is developed to predict and monitor the quality and alignment of boreholes for cut blasting methods such as the LLB methods immediately after boring. The BGS was subsequently tested at a subway construction site to evaluate its performance in the field. The measurements yielded by the BGS were compared with manually measured boring positions at every 5 m along the borehole. Although the BGS showed a maximum deviation of approximately 12% at a local point where the hole surface was relatively rough, the accuracy for the final boring position was approximately 97%, demonstrating excellent precision of the alignment tracking system. The BGS demonstrates excellent performance in predicting ground conditions and the boring quality of a cut hole immediately after drilling, and shows promise in various other applications for monitoring borehole alignment.

This paper conducts a theoretical analysis of ground settlements due to shield tunneling in multi-layered soils which are usually encountered in urban areas. The proposed theoretical solution which is based on the general form of the Mindlin's solution and Loganathan-Poulos formula can comprehensively consider the in-process tunneling parameters including: unbalanced face pressure, shield-soil friction, unbalanced tail grouting pressure, unbalanced secondary grouting pressure, overloading during tunneling and the ground volume loss. The method is verified by comparing with the field data from the Qinghuayuan Tunnel Project in terms of the ground surface settlements along the longitudinal and transverse direction. Due to the local settlement or heave caused by the certain tunneling parameters, the ground surface settlements calculated using current solution along the longitudinal direction presents an irregular S-shaped curve instead of the traditional S-shaped curve. Results also find that the effect of the unbalanced secondary grouting pressure and the overloading during tunneling cannot be ignored.

The probability analysis of ground deformation is becoming a trend to estimate and control the risk brought by shield tunnelling. The gap parameter is regarded as an effective tool to estimate the ground loss of tunnelling in soft soil. More specifically, ω, which is a gap parameter component defined as the over (or insufficient) excavation due to the change in the posture of the shield machine, may contribute more to the uncertainty of the ground loss. However, the existing uncertainty characterization methods for ω have several limitations and cannot explain the uncertain correlations between the relevant parameters. Along these lines, to better characterize the uncertainty of ω, the multivariate probability distribution was developed in this work and a dynamic prediction was proposed for it. To attain this goal, 1 523 rings of the field data coming from the shield tunnel between Longqing Road and Baiyun Road in Kunming Metro Line 5 were utilized and 44 parameters including the construction, stratigraphic, and posture parameters were collected to form the database. According to the variance filter method, the mutual information method, and the value of the correlation coefficients, the original 44 parameters were reduced to 10 main parameters, which were unit weight, the stoke of the jacks (A, B, C, and D groups), the pressure of the pushing jacks (A, C groups), the chamber pressure, the rotation speed, and the total force. The multivariate probability distribution was constructed based on the Johnson system of distributions. Moreover, the distribution was satisfactorily verified in explaining the pairwise correlation between ω and other parameters through 2 million simulation cases. At last, the distribution was used as a prior distribution to update the marginal distribution of ω with any group of the relevant parameters known. The performance of the dynamic prediction was further validated by the field data of 3 shield tunnel cases.

The design of universal segments and deviation control of segment assembly are essential for robust and low-risk tunnel construction. A building information modeling (BIM)-based framework was proposed for parametric modeling, automatic assembly, and deviation control of universal segments. First, segment models of different levels of detail (LoDs) were built based on BIM visual programming language (VPL) for different project life cycles. Then, the geometric constraints, requirements, and procedures for parametric segment assembly were distilled to develop a program that combines a novel typesetting algorithm with a 3D path replanning algorithm. Typesetting is implemented by introducing a point indication matrix, characterizing segments by sides, and manipulating geometries in a VPL. Simultaneously, 3D path replanning, with non-uniform rational B-splines (NURBS) and arcs as basic shapes, was used to resolve unacceptable deviation situations after typesetting. Finally, the proposed framework was validated on a water diversion line and was found to be more effective and accurate than the previous method.

Numerous analytical models have been developed to predict ground deformations induced by tunneling, which is a critical issue in tunnel engineering. However, the accuracy of these predictions is often limited by errors and uncertainties resulting from model selection and parameter fittings, given the paucity of monitoring data in field settings. This paper proposes a novel approach to estimate tunnelling-induced ground deformations by applying Bayesian model averaging to several representative prediction models. By accounting for both model and parameter uncertainties, this approach enables more realistic predictions of ground deformations than individual models. Specifically, our results indicate that the Gonzalez-Sagaseta model outperforms other models in predicting ground surface settlements, while the Loganathan-Poulos model is most suitable for predicting subsurface vertical and horizontal deformations. Importantly, our analysis reveals that when monitoring data are sparse, model uncertainties may contribute up to 78.7% of the total uncertainties. Thus, obtaining sufficient data for parameter fitting is crucial for accurate predictions. The proposed method in this study offers a more realistic and efficient prediction of tunnelling-induced ground deformations.

This paper proposes an efficient method for quantifying the stratigraphic uncertainties and modeling the geological formations based on boreholes. Two Markov chains are used to describe the soil transitions along different directions, and the transition probability matrices (TPMs) of the Markov chains are analytically expressed by copulas. This copula expression is efficient since it can represent a large TPM by a few unknown parameters. Due to the analytical expression of the TPMs, the likelihood function of the Markov chain model is given in an explicit form. The estimation of the TPMs is then re-casted as a multi-objective constrained optimization problem that aims to maximize the likelihoods of two independent Markov chains subject to a set of parameter constraints. Unlike the method which determines the TPMs by counting the number of transitions between soil types, the proposed method is more statistically sound. Moreover, a random path sampling method is presented to avoid the directional effect problem in simulations. The soil type at a location is inferred from its nearest known neighbors along the cardinal directions. A general form of the conditional probability, based on Pickard's theorem and Bayes rule, is presented for the soil type generation. The proposed stratigraphic characterization and simulation method is applied to real borehole data collected from a construction site in Wuhan, China. It is illustrated that the proposed method is accurate in prediction and does not show an inclination during simulation.

With the rapid development of urban underground space, the construction of shield-driven cross-river twin tunnels is increasing, and the complex hydro-mechanical coupling effects and twin-tunnel interactions bring huge construction risks to such projects, which have attracted more and more attention. This study aims to understand the excavation effects induced by shield driving of cross-river twin tunnels through numerical simulation. A refined three-dimensional numerical model based on the fully coupled hydro-mechanical theory is established. The model considers the main components of the slurry pressure balance shield (SPBS) machine, including support force, jacking thrust, grouting pressure, shield-rock interaction and lining-grouting interaction, as well as the detailed construction process. The purpose is to examine the excavation effects during construction, including rock deformation around tunnels, the change in pore pressure, and the response of the lining. The results show the influence range of twin-tunnel excavation on rock deformation and pore pressure, as well as the modes of lining response. In addition, this study also systematically investigates the effects of water level fluctuation and burial depth on twin-tunnel excavation. The results indicate that the increase of water level or burial depth will enhance the excavation effects and strengthen the twin-tunnel interactions. These results provide useful insights for estimating the construction impact range and degree of twin tunnels, and serve as basic references for the design of cross-river twin tunnels.

Using fiberglass bolts to reinforce a tunnel face is a practical auxiliary technology for ensuring tunnel face stability in soft ground. The reinforcing effect and the economics of this technology are significantly affected by bolt length. However, to date, the failure mechanism of bolt-reinforced tunnel faces with different bolt lengths has rarely been investigated. To reveal the failure mechanism of bolt-reinforced shallow tunnel faces, in this study, the stability of bolt-reinforced tunnel faces with different bolt lengths was investigated by using laboratory tests and numerical simulations, and a simplified theoretical model for practical engineering was proposed. The face support pressure and failure pattern for different bolt lengths during the face collapse process were obtained, and the influence of bolt length on face stability was clearly revealed. More specifically, the results show that face stability increases with increasing bolt length, and the reinforcing effect of face bolts is governed by the shear failure at the soil-grout interface first in the stable zone of the tunnel face and then in the failure zone. Once the bolt length in the stable zone is larger than that in the failure zone, face stability will not be improved with increasing bolt length; thus, this bolt length is referred to as the optimal bolt length L_opt. The L_opt value is slightly larger than the initial failure range (in the unreinforced condition) and can be approximately calculated by L_opt = (1 − 0.0133ϕ)D (ϕ is the friction angle of the soil, and D is the tunnel diameter) in practical engineering. Finally, a simplified theoretical model was established to analyse the stability of reinforced tunnel faces, and the results are in good agreement with both laboratory tests and numerical simulations. The proposed model can be used as an efficient tool for the design of face bolts.

The accurate understanding of rockburst mechanism poses a global challenge in the field of rock mechanics. Particularly for strain rockburst, achieving self-initiated static-dynamic state transition is a crucial step in the formation of catastrophic events. However, the state transition behavior and its impact on rockburst have not received sufficient attention, and are still poorly understood. Therefore, this study specifically focuses on the state transition behavior, aiming to investigate its abrupt transition process and formation mechanism, and triggering effects on rockburst. To facilitate the study, a novel burst rock-surrounding rock combined laboratory test model is proposed and its effectiveness is validated through experiment verification. Subsequently, corresponding numerical models are established using the three-dimensional (3D) discrete element method (DEM), enabling successful simulation of static brittle failure and rockbursts of varying intensities under quasi-static displacement loading conditions. Moreover, through secondary development, comprehensive recording of the mechanical and energy information pertaining to the combined specimen system and its subsystems is achieved. As a result of numerical investigation studies, the elastic rebound dynamic behavior of the surrounding rock was discovered and identified as the key factor triggering rockburst and controlling its intensity. The impact loading on the burst rock, induced by elastic rebound, directly initiates the dynamic processes of rockburst, serving as the direct cause. Additionally, the transient work and energy convergence towards the burst rock resulting from elastic rebound are recognized as the inherent cause of rockburst. Moreover, it has been observed that a larger extent of surrounding rock leads to a stronger elastic rebound, thereby directly contributing to a more intense rockburst. The findings can provide novel theoretical insights for the exploring of rockburst mechanism and the development of monitoring and prevention techniques.

The collapse of the tunnel face is a prevalent geological disaster in tunnelling. This study employs a three-dimensional (3D) material point method (MPM) to simulate the dynamic collapse process and post-failure mechanisms of the tunnel face. The specific focus is on the scenario where the auxiliary air pressure balanced shield with a partially filled chamber is shut down. To assess the suitability of the 3D MPM, numerical solutions are compared with the results from small-scale experimental tests. Subsequently, a series of large-scale numerical simulations is conducted to explore the dynamic collapse characteristics of the tunnel face induced by the shutdown of the EPB shield under various support air pressures and cutter head conditions. The temporal evolution of the accumulated soil masses in the soil chamber and ground responses under different support air pressures, cutter head types and opening ratios are discussed. In particular, the associated surface subsidence due to the tunnel face collapse is determined and compared with empirical solutions. Numerical results confirm the applicability of the 3D MPM for simulating the large-scale tunnel face collapse scenarios, spanning from small to large deformation analysis.

Local failures (loss of concrete or reinforcement) can severely compromise the bearing capacity of shield segments, damaging the tunnel structures. To investigate the effects of local openings on the bearing behavior and failure mechanism, four full-scale bending tests were conducted on specimens with different opening positions and diameters; monitoring of load, displacement, and concrete strain was performed during loading. The test results reveal that both the opening position and diameter significantly influence the bearing characteristics of the segment. The failure process includes four sequential stages distinguished by three critical loads, namely the cracking, failure, and ultimate loads. Subsequently, the numerical model of the local failure segment was established using the elastoplastic damage constitutive relation of the concrete and verified by inversing the full-scale test results. Based on the numerical model, parametric analyses were performed to comprehensively investigate the influences of the opening position, concrete loss, and reinforcement loss on the bending capacity. Furthermore, an analytical model was proposed, indicating that the opening position is the primary factor decreasing the bearing capacity, followed by the opening diameter and reinforcement loss. The results of this study can provide a theoretical basis for the safety assessment and remedial design of subway shield tunnels under extreme breakthrough conditions.

This paper presents a surrogate modeling approach for predicting ground surface settlement caused by synchronous grouting during shield tunneling process. The proposed method combines finite element simulations with machine learning algorithms and introduces an intelligent optimization algorithm to invert geological parameters and synchronous grouting variables, thereby predicting ground surface settlement without conducting numerous finite element analyses. Two surrogate models based on the random forest algorithm are established. The first is a parameter inversion surrogate model that combines an artificial fish swarm algorithm with random forest, taking into account the actual number and distribution of complex soil layers. The second model predicts surface settlement during synchronous grouting by employing actual cover-diameter ratio, inverted soil parameters, and grouting variables. To avoid changes to input parameters caused by the number of overlying soil layers, the dataset of this model is generated by the finite element model of the homogeneous soil layer. The surrogate modeling approach is validated by the case history of a large-diameter shield tunnel in Beijing, providing an alternative to numerical computation that can efficiently predict surface settlement with acceptable accuracy.

The immersed tunnel is considered an effective solution for traffic problems across rivers and seas. The sand filling layer, as an important part of immersed tunnel foundation treatments, directly affects segment attitude stability. Due to difficulties in quality control of concealed construction and the complex hydrodynamic environment, the sand filling layer is prone to compaction defects, further leading to changes in segment attitude. However, limited by structural concealment and state complexity, most studies consider the sand filling layer part of the foundation to study its impact on settlement while neglecting its influence on segment attitude. This research proposes an evaluation method for the sand filling layer state based on elastic wave testing and the elastic wave characteristic parameters selected come from analysis of the time domain, frequency domain and time-frequency domain. By classifying the elastic wave characteristic parameters through the K-means clustering method, the relationship between the state of the sand filling layer and the elastic wave characteristic parameters is established. The state of the sand filling layer is divided into dense, incompact, and void. A numerical model is established based on the Guangzhou BI-UT immersed tunnel with incompact and void sand filling layer states to simulate deformation and torsion. The results indicate that the settlement of the tunnel segment is low in the eastern region and high in the western region due to the presence of a less dense sand filling layer, with a maximum differential settlement of 0.04 m. The evaluation method plays a crucial role in guiding the construction of immersed tube tunnels.

A circular shaft is often used to access a working well for deep underground space utilization. As the depth of underground space increases, the excavation depth of the shaft increases. In this study, the deformation characteristics of a circular shaft with a depth of 56.3 m were presented and analysed. The main monitoring contents included: (1) wall deflection; (2) vertical wall movement; (3) horizontal soil movement; (4) vertical surface movement; and (5) basal heave. Horizontally, the maximum wall deflection was only 7.7 mm. Compared with the wall deflection data collected for another 29 circular excavations, the ratio of maximum wall deflection to excavation depth of this shaft was smaller due to a smaller ratio of diameter to excavation depth. The wall deflection underwent two stages of deformation: the first stage was mainly circumferential compression caused by the mutual extrusion of joints between walls, and the second stage was typical vertical deflection deformation. The horizontal soil movement outside the shaft was greater than the wall deflection and the deep soil caused great horizontal movement because of dewatering at confined water layers. Vertically, a basal heave of 203.8 mm occurred in the pit centre near the bottom. Meanwhile, the shaft was uplifted over time and showed 3 stages of vertical movement. The surface outside the shaft exhibited settlement and uplift deformation at different locations due to different effects. The basal heave caused by excavation was the dominant factor, driving the vertical movement of the shaft as well as the surrounding surface. The correlation between the wall deflection and the surface settlement outside the shaft was weak.

This paper presents the development of a framework for the parametric design of tunnels using geographic information system (GIS) mapping and building information modelling (BIM). According to the framework, a parametric representation of each system component (e.g., layers of rock mass, size of excavation, topography, fault geometry, primary lining, secondary lining, rock bolts, etc.) can be incorporated in the GIS model with high levels of detail and used for the automatic generation of numerical models for the design of tunnel construction. This parametric evaluation allows the designer to consider several levels of detail for each component, for the efficient design and process optimization in conventional tunneling. Information between parametric analysis and numerical simulations can be freely exchanged with significantly reduced computational effort while results can be exported into BIM. It is anticipated that the proposed framework could lead to a comprehensive, yet efficient analysis of complex conventional tunneling project using parametric evaluations at the early design stages.

Multiform fractures have a direct impact on the mechanical performance of rock masses. To accurately identify multiform fractures, the distribution patterns of grayscale and the differential features of fractures in their neighborhoods are summarized. Based on this, a multiscale processing algorithm is proposed. The multiscale process is as follows. On the neighborhood of pixels, a grayscale continuous function is constructed using bilinear interpolation, the smoothing of the grayscale function is realized by Gaussian local filtering, and the grayscale gradient and Hessian matrix are calculated with high accuracy. On small-scale blocks, the pixels are classified by adaptively setting the grayscale threshold to identify potential line segments and mini-fillings. On the global image, potential line segments and mini-fillings are spliced together by progressing the block frontier layer-by-layer to identify and mark multiform fractures. The accuracy of identifying multiform fractures is improved by constructing a grayscale continuous function and adaptively setting the grayscale thresholds on small-scale blocks. And the layer-by-layer splicing algorithm is performed only on the domain of the 2-layer small-scale blocks, reducing the complexity. By using rock mass images with different fracture types as examples, the identification results show that the proposed algorithm can accurately identify the multiform fractures, which lays the foundation for calculating the mechanical parameters of rock masses.

One of the common excavation methods in the construction of urban infrastructures as well as water and wastewater facilities is the excavation through soldier pile walls. The maximum lateral displacement of pile wall is one of the important variables in controlling the stability of the excavation and its adjacent structures. Nowadays, the application of machine learning methods is widely used in engineering sciences due to its low cost and high speed of calculation. This paper utilized three intelligent machine learning algorithms based on the excavation method through soldier pile walls, namely eXtreme gradient boosting (XGBoost), least square support vector regressor (LS-SVR), and random forest (RF), to predict maximum lateral displacement of pile walls. The results showed that the implemented XGBoost model performed excellently and could make predictions for maximum lateral displacement of pile walls with the mean absolute error of 0.1669, the highest coefficient of determination 0.9991, and the lowest root mean square error 0.3544. Although the LS-SVR, and RF models were less accurate than the XGBoost model, they provided good prediction results of maximum lateral displacement of pile walls for numerical outcomes. Furthermore, a sensitivity analysis was performed to determine the most effective parameters in the XGBoost model. This analysis showed that soil elastic modulus and excavation height had a strong influence on of maximum lateral displacement of pile wall prediction.

This study presents a detailed investigation into the soil arching effects within deep foundation pits (DFPs), focusing on their mechanical behavior and implications for structural design. Through rigorous 3D finite element modeling and parameter sensitivity analyses, the research explores the formation, geometric characteristics, and spatial distribution of soil arching phenomena. The investigation encompasses the influence of key parameters such as elastic modulus, cohesion, and internal friction angle on the soil arching effect. The findings reveal that soil arching within DFPs exhibits distinct spatial characteristics, with the prominent arch axis shifting as excavation depth progresses. Optimal soil arching is observed when the pile spacing approximates three times the pile diameter, enhancing soil retention and minimizing deformation risks. Sensitivity analyses highlight the significant impact of soil parameters on soil arching behavior, underscoring the critical role of cohesive forces and internal friction angles in shaping arching characteristics. By elucidating the interplay between soil parameters and soil arching effects, the research provides insights for optimizing pile spacing and structural stability.