Underground Space最新文献

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.

Ground penetrating radar (GPR) is a vital non-destructive testing (NDT) technology that can be employed for detecting the backfill grouting of shield tunnels. To achieve intelligent analysis of GPR data and overcome the subjectivity of traditional data processing methods, the CatBoost & BO-TPE model was constructed for regressing the grouting thickness based on GPR waveforms. A full-scale model test and corresponding numerical simulations were carried out to collect GPR data at 400 and 900 MHz, with known backfill grouting thickness. The model test helps address the limitation of not knowing the grout body condition in actual field detection. The data were then used to create machine learning datasets. The method of feature selection was proposed based on the analysis of feature importance and the electromagnetic (EM) propagation law in mediums. The research shows that: (1) the CatBoost & BO-TPE model exhibited outstanding performance in both experimental and numerical data, achieving R² values of 0.9760, 0.8971, 0.8808, and 0.5437 for numerical data and test data at 400 and 900 MHz. It outperformed extreme gradient boosting (XGBoost) and random forest (RF) in terms of performance in the backfill grouting thickness regression; (2) compared with the full-waveform GPR data, the feature selection method proposed in this paper can promote the performance of the model. The selected features within the 5–30 ns of the A-scan can yield the best performance for the model; (3) compared to GPR data at 900 MHz, GPR data at 400 MHz exhibited better performance in the CatBoost & BO-TPE model. This indicates that the results of the machine learning model can provide feedback for the selection of GPR parameters; (4) the application results of the trained CatBoost & BO-TPE model in engineering are in line with the patterns observed through traditional processing methods, yet they demonstrate a more quantitative and objective nature compared to the traditional method.

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.

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 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 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.

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 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.

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 issue of significant floor heave deformation in gob-side entry retaining has long been a challenging problem in the context of longwall mining. This paper studies the floor heave failure mechanism and control method for gob-side entry retaining with concrete blocks in Guizhou Faer Coal Mine in China. Based on Rankine’s earth pressure theory, the effective shear stress equation for the plastic slip of roadway floor is established. The deformation mechanism of floor heave in a retaining roadway with a block wall is revealed in this study. The new comprehensive control method is proposed, encompassing roof pre-splitting blasting for pressure relief, reinforcing cables for roof control, double directions control bolts for concrete block, and pliability cushion yielding pressure. FLAC^3D numerical calculation model is established, which shows that the new method can effectively reduce the average vertical stress peak value of the entity coal floor by 34.6% and significantly reduce the pressure source causing the roadway floor heave. Besides, a multi-parameter real-time online monitoring system for mine pressure was designed, and field tests were carried out. The results show that the maximum value of roadway floor heave under the new method is 163 mm, reduced by 66.9%, and the roadway floor heave is effectively controlled. These research findings offer a fresh perspective and new ideas for controlling floor heave in mining operations.