Underground Space最新文献

This paper focuses on the performance of a braced deep excavation in soft soil based on field monitoring and numerical modeling. Laboratory tests were conducted to determine the soil parameters used in the modified Cam–Clay (MCC) model. Intelligent field monitoring means were adopted and a three-dimensional model was established. Spatial and temporal effects induced by the excavation are investigated for the deep-large foundation pit in soft soil. Deformation characteristics of the enclosure structure and the surrounding environment throughout the excavation process are presented. The behaviors of diaphragm walls, columns, the maximum wall deflection rate, ground surface settlement, and utility pipelines were focused on and investigated during the whole excavation process. Besides, the axial forces of the internal supports are analyzed. Based on the measured and simulated data, the following main conclusions were obtained: the numerical simulation results are in good agreement with the measured values, which proves the accuracy of the model parameters; the wall and the ground surface showed the maximum displacement increment at stage 9, which was a coupled product of the “creep effect” of the soft soil in Nanjing, China and the “depth effect” of the excavation; as the excavation progressed, the ground settlement changed from a “rising” to a “spoon-shaped” trend, δ_vm was measured between δ_vm = 0.0686%H and δ_vm = 0.1488%H; the rebound deformation curve of the pit bottom was corrugated, and the depth of disturbance of the pit bottom after the completion of soil unloading was 2–3 times the excavation depth; the closer the pipeline is to the corner of the pit, the less the excavation process will affect the settlement of the pipeline and the less the obvious pit corner effect will occur; the support strength of the buttress and the longest corner brace should be strengthened during the actual construction process to ensure the stability of the foundation deformation.

Large deformation of sand due to soil liquefaction is a major cause for seismic damage. In this study, the mechanisms and modeling of large post-liquefaction deformation of sand considering the significant influence of water absorption in shearing and seismic wave conditions. Assessment of case histories from past earthquakes and review of existing studies highlight the importance of the two factors. Based on the micro and macro scale mechanisms for post-liquefaction shear deformation, the mechanism for water absorption in shearing after initial liquefaction is revealed. This is aided by novel designed constant water-absorption-rate shear tests. Water absorption in shearing can be classified into three types, including partial water absorption, complete water absorption, and compulsory water absorption. Under the influence of water absorption in shearing, even a strongly dilative sand under naturally drained conditions could experience instability and large shear deformation. The mechanism for amplification of post-liquefaction deformation under surface wave load is also explained via element tests and theoretical analysis. This shows that surface wave–shear wave coupling can induce asymmetrical force and resistance in sand, resulting in asymmetrical accumulation of deformation, which is amplified by liquefaction. A constitutive model, referred to as CycLiq, is formulated to capture the large deformation of sand considering water absorption in shearing and seismic wave conditions, along with its numerical implementation algorithm. The model is comprehensively calibrated based on various types of element tests and validated against centrifuge shaking table tests in the liquefaction experiments and analysis projects (LEAP). The model, along with various numerical analysis methods, is adopted in the successful simulation of water absorption in shearing and Rayleigh wave-shear wave coupling induced large liquefaction deformation. Furthermore, the model is applied to high-performance simulation for large-scale soil-structure interaction in liquefiable ground, including underground structures, dams, quay walls, and offshore wind turbines.

The application of steel strut force servo systems in deep excavation engineering is not widespread, and there is a notable scarcity of in-situ measured datasets. This presents a significant research gap in the field. Addressing this, our study introduces a valuable dataset and application scenarios, serving as a reference point for future research. The main objective of this study is to use machine learning (ML) methods for accurately predicting strut forces in steel supporting structures, a crucial aspect for the safety and stability of deep excavation projects. We employed five different ML methods: radial basis function neural network (RBFNN), back propagation neural network (BPNN), K-Nearest Neighbor (KNN), support vector machine (SVM), and random forest (RF), utilizing a dataset of 2208 measured points. These points included one output parameter (strut forces) and seven input parameters (vertical position of strut, plane position of strut, time, temperature, unit weight, cohesion, and internal frictional angle). The effectiveness of these methods was assessed using root mean square error (RMSE), correlation coefficient (R), and mean absolute error (MAE). Our findings indicate that the BPNN method outperforms others, with RMSE, R, and MAE values of 72.1 kN, 0.9931, and 57.4 kN, respectively, on the testing dataset. This study underscores the potential of ML methods in precisely predicting strut forces in deep excavation engineering, contributing to enhanced safety measures and project planning.

High-speed railway tunnels in various countries have continuously reported accidents of vault falling concrete blocks. Once the concrete block falling occurs, serious consequences follow, and traffic safety may be endangered. The aerodynamic shockwave evolves from the initial compression wave may be an important inducement causing the tunnel lining cracks to grow and form falling concrete blocks. A joint calculation framework is established based on ANSYS Fluent, ABAQUS, and FRANC3D for calculating the crack tip field under the aerodynamic shockwave. The intensification effect of aerodynamic shockwaves in the crack is revealed, and the evolution characteristics of the crack tip field and the influence factors of stress intensity factor (SIF) are analyzed. Results show that (1) the aerodynamic shockwave intensifies after entering the crack, resulting in more significant pressure in the crack than the input pressure. The maximum pressure of the inclined and longitudinal cracks is higher than the corresponding values of the circumferential crack, respectively. (2) The maximum SIF of the circumferential, inclined, and longitudinal crack appears at 0.5, 0.68, and 0.78 times the crack front length. The maximum SIF of the circumferential crack is higher than that of the inclined and longitudinal crack. The possibility of crack growth of the circumferential crack is the highest under aerodynamic shockwaves. (3) The influence of train speed on the SIF of the circumferential crack is more than 40%. When the train speed, crack depth, and crack length change, the change of pressure in the crack is the direct cause of the change of SIF.

The evaluation of urban underground space (UUS) suitability involves multiple indicators. Assigning weight to these indicators is crucial for accurate assessment. This paper presents a method for spatially variable weight assignment of indicators using the order relation analysis method (G₁-method), the entropy weight method, an improved grey relational analysis (GRA) and a set of spatial weight adjustment coefficients. First, the subjective and objective weights of indicators for engineering geological and hydrogeological conditions were determined by the G₁-method and entropy weight method, respectively, and their combined weights were then obtained using the principle of minimum discriminatory information. This study highlighted the impact of surface restrictions, such as buildings, on UUS, and the degree of the influence of these buildings gradually decreased with the increase in depth of the rock and soil mass in UUS, which resulted in changes in weights of indicators with depth. To address this issue, a coefficient was defined as the standardized value of the ratio of additional stress applied by restrictions to the self-weight stress of soil at the same depth to modify the combined weights so that all weights of indicators could vary in space. Finally, an improved GRA was used to determine the suitability level of each evaluation cell using the maximum correlation criterion. This method was applied to the 3D suitability evaluation of UUS in Sanlong Bay, Foshan City, Guangdong Province, China, including 16 evaluation indexes. This study comprehensively considered the influence of multiple factors, thereby providing reference for evaluating the suitability of UUS in big cities.

The pipe curtain structure method (PSM) is a novel construction method to control ground deformation strictly. Compared with the traditional pipe-roofing and pipe jacking method, the connection between pipes in large spacings using PSM is widely acknowledged as a unique construction procedure. Further study on this connection procedure is needed to resolve similar cases in that the pipes are inevitably constructed on both sides of existing piles. Cutting the steel plate during the connection procedure is the first step, which is crucial to control the safety and stability of the surrounding environment and existing structures. The deformation mechanism and limit support pressure of the cutting steel plate during the connection between pipes in large spacings are studied in this paper, relying on the undercrossing Yifeng gate tower project of Jianning West Road River Crossing Channel in Nanjing, China. A modified 3D wedge-prism failure model is proposed using the 3D discrete element method. Combined with Terzaghi loose earth pressure theory and the limit equilibrium theory, the analytical solutions for the limit support pressure of the excavation face of the cutting steel plate are derived. The modified 3D wedge-prism failure model and corresponding analytical solutions are categorised into two cases: (a) unilateral cutting scheme, and (b) bilateral cutting scheme. The analytical solutions for the two cases are verified from the numerical simulation and in-situ data and compared with the previous solutions. The comparative analysis between the unilateral and bilateral cutting schemes indicates that the bilateral cutting scheme can be adopted as a priority. The bilateral cutting scheme saves more time and induces less ground deformation than the unilateral one due to the resistance generated from the superimposed wedge. In addition, the parametric sensitivity analysis is carried out using an orthogonal experimental design. The main influencing factors arranged from high to low are the pipe spacing, the cutting size, and the pipe burial depth. The ground deformation increases with the increased cutting size and pipe spacing. The pipe burial depth slightly affects the ground deformation if the other two factors are minor. Cutting steel plates in small sizes, excavating soil under low disturbance, and supporting pipes for high frequency can effectively reduce the ground surface subsidence.

This paper presents a regional 3D geological modeling method based on the stacking ensemble technique to overcome the challenges of sparse borehole data in large-scale linear underground projects. The proposed method transforms the 3D geological modeling problem into a stratigraphic property classification problem within a subsurface space grid cell framework. Borehole data is pre-processed and trained using stacking method with five different machine learning algorithms. The resulting modelled regional cells are then classified, forming a regional 3D grid geological model. A case study for an area of 324 km² along Xuzhou metro lines is presented to demonstrate the effectiveness of the proposed model. The study shows an overall prediction accuracy of 85.4%. However, the accuracy for key stratigraphy layers influencing the construction risk, such as karst carve strata, is only 4.3% due to the limited borehole data. To address this issue, an oversampling technique based on the synthetic minority oversampling technique (SMOTE) algorithm is proposed. This technique effectively increases the number of sparse stratigraphic samples and significantly improves the prediction accuracy for karst caves to 65.4%. Additionally, this study analyzes the impact of sampling distance on model accuracy. It is found that a lower sampling interval results in higher prediction accuracy, but also increases computational resources and time costs. Therefore, in this study, an optimal sampling distance of 1 m is chosen to balance prediction accuracy and computation cost. Furthermore, the number of geological strata is found to have a negative effect on prediction accuracy. To mitigate this, it is recommended to merge less significant stratigraphy layers, reducing computation time. For key strata layers, such as karst caves, which have a significant impact on construction risk, further on-site sampling or oversampling using the SMOTE technique is recommended.

When tunnelling in difficult ground conditions, shield machine would inevitably produce significant ground loss and vibration, which may disturb the ground ahead of the tunnel face. In this paper, discrete element models calibrated by model tests were established to investigate the response of tunnel face under the coupling effects of unloading and cutterhead vibrations. The results show that the friction angle reduction under cyclic loading and vibration attenuation in the sandy ground are significant and can be estimated by the fitted exponential functions. Under cutterhead vibration, the tunnel face stability is undermined and the limit support pressure (LSP) increases to 1.4 times as that in the static case with the growth of frequency and amplitude. Meanwhile, the loosening zone becomes wider and the arching effect is weakened with the reduction of peak horizontal stress and the increase of vertical stress above the tunnel. Based on the numerical results, a pseudo-static method was introduced into the limit equilibrium analysis of the wedge-prism model for calculating the LSP under vibration. With an error rate less than 5.2%, the proposed analytical method is well validated. Further analytical calculation reveals that the LSP would increase with the growth of vibration amplitude, vibration frequency and covered depth but decrease with the increase of friction angle. This study can not only lay a solid foundation for the further investigation of ground loss, ground water and soft-hard heterogeneous ground under cutterhead vibration, but also provide meaningful references for the control of environmental disturbance in practice.

This paper concentrates on the sensitivity and dynamic simulation of randomly distributed karst cave groups on tunnel stability and connectivity extended ratio based on water–rock interaction using a novel contact dynamic method (CDM). The concept of karst cave group connectivity extended ratio during tunneling and water inrush is proposed. The effects of cave shape and spatial distribution on Qiyueshan tunnel are investigated. Tunnel deformation and damage index, and connectivity extended ratio with uniform random karst cave groups are evaluated. The results demonstrate that the connectivity extended ratio is verified as a crucial judgment in predicting the safe distance and assessing the stability of the tunnel with the karst cave group. CDM model captures the fracture propagation and contact behavior of rock mass, surface flow, as well as the bidirectional water–rock interaction during the water inrush of Qiyueshan tunnel with multiple caves. A larger cave radius and smaller minimum distance between the cave and tunnel increase the deformation and damage index of the surrounding rock. When the cave radius and cave area ratio increase, the failure pattern shifts from overall to local failure. These findings potentially have broad applications in various surface and subsurface scenarios involving water–rock interactions.

Discontinuity is critical for strength, deformability, and permeability of rock mass. Set information is one of the essential discontinuity characteristics and is usually accessed by orientation grouping. Traditional methods of identifying optimal discontinuity set numbers are usually achieved by clustering validity indexes, which mainly relies on the aggregation and dispersion of clusters and leads to the inaccuracy and instability of evaluation. This paper proposes a new method of Fisher mixed evaluation (FME) to identify optimal group numbers of rock mass discontinuity orientation. In FME, orientation distribution is regarded as the superposition of Fisher mixed distributions. Optimal grouping results are identified by considering the fitting accuracy of Fisher mixed distributions, the probability monopoly and central location significance of independent Fisher centers. A Halley-Expectation-Maximization (EM) algorithm is derived to achieve an automatic fitting of Fisher mixed distribution. Three real rock discontinuity models combined with three orientation clustering algorithms are adopted for discontinuity grouping. Four clustering validity indexes are used to automatically identify optimal group numbers for comparison. The results show that FME is more accurate and robust than the other clustering validity indexes in optimal discontinuity group number identification for different rock models and orientation clustering algorithms.