Tunnelling and Underground Space Technology最新文献

Tunnel construction in karst areas presents significant risks due to the complex geological environment and inherent uncertainties. Existing risk assessment methods often struggle to adequately capture and quantify these uncertainties, leading to potentially inaccurate evaluations. This study addresses this gap by developing a novel risk assessment system specifically for shield tunnel engineering in karst areas. This system combines a risk index, considering both frequency and consequence dimensions, with four probabilistic models for quantifying risk levels. These models, based on the spatial geometric characteristics of the two-dimensional cloud model, simulate a large number of outcomes of risky decisions under the influence of uncertainties. Applied to the Guiyang Metro Line 3 construction project, the models effectively determined risk levels, with the Comprehensive Cloud Envelope Model (CCEM) demonstrating high precision and the Comprehensive Cloud Oval Model (CCOM) excelling in computational efficiency. Comparative analysis with existing 2D and 1D cloud models highlights the advantages and wider applicability of the proposed methodology for risk evaluation and control in complex geological environments.

The use of flexible buried corrugated metal culverts (CMCs) for traffic and watercourses has recently expanded as a promising technique for shallow underground tunnelling. However, in the design of such structures it is challenging to mimic the performance of the mobilized soil-structure interaction. The backfilling process, with the use of compaction forces, can be considered the major loading mode that develops the predominant deformations and internal forces in the culvert body. Therefore, a thorough understanding of the backfilling process and its effects can contribute to improving CMC design methodology. In this study, a laboratory experiment was used to investigate a flexible buried corrugated metal open-bottom arch culvert, where the compaction impact was monitored during each backfill stage. Following the installation of the culvert in a rigid steel tank, seven sequenced backfill layers were added and compacted, until the target cover depth was reached. Culvert deformations and internal forces were recorded during each backfilling stage. Moreover, the variations in vertical soil stresses developed due to backfilling were measured at two locations: the surface of the bedding soil, and just above the culvert crown. In addition, the lateral perpendicular stresses induced at the exterior circumference of the culvert body near the midpoint of each side backfill layer were measured during backfilling. Finally, a numerical analysis using 3D finite element modelling was performed to simulate the construction sequence of the laboratory test during the backfilling process. The numerical modelling results for the culvert deformations and internal forces were then validated against the recorded measurements obtained in the laboratory experiment and a numerical procedure to simulate the induced backfilling efforts was recommended.

The experimental approach is crucial for investigating the seismic performance and damage process of underground structures. Considering the shortcomings of the 1-g, centrifuge shaking table and monotonic displacement pushover tests, a large-scale cyclic displacement pushover test method is proposed based on the soil-underground structure dynamic interaction and seismic performance quantification system. Taking a two-story three-span subway station structure as the prototype, the cyclic displacement pushover test device was designed for a 1/7-scale multi-story subway station based on the seismic response characteristics of underground structures. The corresponding numerical simulations and experiments were conducted. Typical numerical results (including the seismic damage process, capacity curves of the structural columns, and strain response) and test results (the macroscopic phenomenon of structural damage development, strain response, and deformation response) are interpreted. The results show that the proposed cyclic displacement pushover test is better than the monotonic displacement pushover test, the damage process of the tested station structure conforms to the description of the inter-story drift ratio (IDR) quantification system of seismic performance. Meanwhile, the column has greater strain amplitudes than other components, and the column strain curves reach their peaks before other components. Furthermore, the tested station structure has a similar damage pattern to the Daikai subway station. The reliability and feasibility of the proposed cyclic displacement pushover test method are verified.

It is widely recognized that the improvement effects of the foam on the soil properties during earth pressure balance shield (EPBS) tunnelling can be well characterized by some conditioning evaluation indices such as shear strength, flowability, and compressibility. The number of EPBS has increased significantly worldwide in the past few decades. Consequently, recycling the EPBS muck wastes for other applications becomes important, and in this context, estimating the recycling potential of foam-conditioned soils is of great practical significance. Although numerous studies have proved dewaterability to be one of the most important indices to assess the reusability of clay muck wastes, the dewatering behaviors of foam-conditioned clay soils and their quantitative interrelations with common conditioning evaluation indices are still not properly understood. To understand the comprehensive effects of foams on high-saturation clay soil that is comparable to natural clays of real tunnels, a series of laboratory experiments were carried out, including undrained shear tests, flowability tests, and vacuum filtration tests. The concept of specific resistance was introduced to characterize the dewaterability, taking the effects of filtration time and pressure into consideration. The moisture migration mechanisms at both the conditioning and dewatering stages were analyzed using low-field nuclear magnetic resonance tests. It was found that increasing the degree of saturation and the foam injection ratio could lead to a significant enhancement in the flowability (vertical and horizontal slumps), compressibility, and dewaterability, but a reduction in the undrained shear strength. The injected foams caused the moisture to migrate from micropores to mesopores during conditioning, but from mesopores to micropores and macropores during dewatering. Accordingly, quantitative expressions were established to determine the interrelations between conditioning and dewatering indices. The specific resistance was also demonstrated to be an effective alternative variable to characterize the conditioning performance of foams for high-saturation clay soils. Finally, a new application diagram of different evaluation indices, which can assist engineers in effectively assessing the foam’s effects on clay soils, was provided to contribute valuable knowledge to EPBS tunnelling practices.

Thin spray-on liners (TSLs) have been widely adopted in underground mining as rock support materials owing to their notable tensile strength, elongation capability, and bond strength with rock surfaces. In this study, to evaluate the reinforcing capacity of a high-tensile-strength polyurea-based TSL on rock pillars subjected to dynamic loads, a series of compression, impact, and compression-after-impact tests were conducted on polyurea-coated coal and limestone samples, which represent soft and hard rock pillars in underground coal mining and stone mining, respectively. The strength, deformative modulus, energy evolution, and failure modes of the rock samples with coating thicknesses of 1, 2.5, 5, and 10 mm were examined. The results indicated that there is a critical thickness above which additional coating does not improve the reinforcing performance. Coated coal samples exhibited a residual stress plateau in the post-peak stage, which was not observed in uncoated samples. The failure mode of polyurea-coated rock pillars depends on the energy absorption threshold of polyurea, causing the coating to fracture and leading to the overall failure of the structure. During the impact, the polyurea coating absorbed excessive energy, thereby enhancing the dynamic strength of rock pillars. Surprisingly, moderate impact loading converted the effect of polyurea coating from passive to active confinement, resulting in a residual strength that surpassed the inherent strength of the rock. Based on laboratory observations, this study concludes that ductile TSLs such as polyurea are particularly advantageous for reinforcing soft rock pillars.

A strategy to optimize relief hole positions is proposed to enhance the effectiveness of tunnel blasting in rock breaking. This study employed two predefined arithmetic progressions to coordinate the distribution of rock-breaking areas and hole-bottom minimum burdens allocated to each row of holes. Iterative calculations were performed to determine the final position of each row of holes. To determine the optimal drilling scheme, modeling and simulation were conducted using a finite element method-smoothed particle hydrodynamics (FEM-SPH) coupling algorithm. This approach allowed for a comparison of the rock-breaking effects of relief holes under different constraint combinations. This study indicates that the displacement of rock particles varies in different depth zones. The largest displacements of the rock particles were observed in the middle of the charge section. For a conventional working face with a width of 12.2 m and a designed advance of 3 m, the rock-breaking efficiency is optimal when the two control ratios, r_A and r_W, are 1.5 and 1.4, respectively. This study advances the underground blasting design technology and contributes to energy reduction and efficiency improvements in blasting engineering.

In water conservancy, transportation, and mining projects, the timely acquisition of geological structural information from tunnels is critical in the analysis of engineering geological problems during the investigation and construction stages. The acquisition of comprehensive and accurate geological information from a tunnel surface remains challenging. This study provides an automatic extraction method for geological discontinuities on a tunnel surface by integrating 2D textural semantic features and 3D geological semantic features. A dense point cloud is generated using multiline parallel sequence images, after which the 3D geological semantic features, including the local geological attitude, are calculated. Through a virtual projection from 3D to 2D, the red, green, and blue (RGB) images and geological semantic images based on views of the interior umbrella arch and the sidewalls of the tunnel surface are obtained. The feature mapping between the 2D textural semantic features and the 3D geological semantic features is determined accordingly. The virtual RGB images and geological semantic images serve as dual inputs for ensemble learning for pixel block segmentation, and the output is a similarity probability tensor that describes the probability that each pixel will belong to its surrounding pixel blocks. The pixel blocks are clustered on the basis of pole and contour plots of their geological attitudes to extract geological discontinuities. Experiments were conducted to confirm and evaluate the feasibility and veracity of the proposed method. The developed method automatically extracts geological discontinuities of a tunnel surface and extends the scope of surveying and mapping through geological remote sensing.

The increasing frequency of structural damage and reinforcement repairs in long-term highway tunnels necessitates an understanding of their effects on drivers. This study examines drivers’ physiological responses to visible structural changes in highway tunnels. Using a vehicle static in-the-loop platform, we created various models of apparent tunnel structure changes for simulated driving experiments. These experiments enabled a detailed analysis of the effects of such changes on driver safety, utilizing metrics such as eye movements, regions of interest, heart rate, and vehicle speed. The results show that visible alterations in tunnel structures significantly affect drivers’ physiological responses. Structural spalling and fire residues within tunnel structures notably increased drivers’ vigilance and psychological stress, resulting in a 14.7% increase in the average number of fixations, a 26.35% increase in the average duration of fixations, and a 36.05% increase in heart rate variability. Additionally, tunnel spalling tends to cause drivers to accelerate or exceed the speed limit, with maximum speeds reaching 17.87% above the designed speed. In contrast, repairs involving cover arch erection had minimal impact on drivers, with eye movement and heart rate data similar to those in ordinary tunnels. However, reinforcement with steel strips and corrugated steel in tunnels has attracted significant attention, with the area of interest exceeding 50% of the tunnel area, potentially leading to distracted driving. This study clarifies the extent of the influence of visible tunnel structure changes on drivers, providing a reference for damage assessment, reinforcement, and repair measures for long-term operated tunnels.

Concealment of filling constructions poses significant challenges for quality assurance in filling engineering. Direct surveillance of fill dispersal currently remains infeasible, while conventional detection techniques suffer deficiencies in efficiency. This research proposes a framework integrating elastic wave monitoring and hybrid deep learning for predictive modelling of filling state transitions and diffusion range. During the sand filling of the immersed tunnel, elastic wave data is collected via elastic wave testing, and the response energy characteristic is derived through time-domain analysis. The trends in elastic wave response energy are correlated with three filling states: free diffusion, accumulation, and filled state, using Seasonal and Trend decomposition using Loess (STL) for seasonal trend analysis. Convolutional Neural Networks (CNN) and Long Short-Term Memory Networks (LSTM) are utilized to extract spatiotemporal features from the response energy trends, facilitating accurate prediction of the trends’ development and the sand filling state over time. The performances of the proposed strategy are illustrated through an application to the case study of the sand filling construction of the Chebeilu immersed tunnel. The CNN + LSTM model with the proposed strategy gave excellent results (MAE 0.0663, MSE 0.0071, RMSE 0.0845). The model can predict fill state changes and quantify diffusion radii to optimize and guide the construction process.

This study introduces an innovative Roughness-CANUPO-Dip-Facet (R-C-D-F) methodology for the measurement of dip angle and direction in geological rock facets. The R-C-D-F method is distinguished by its comprehensive four-step approach, encompassing filtration through roughness analysis, CANUPO analysis, and dip angle filtration, followed by facet segmentation as the measurement step. To achieve precise and efficient results, the method specifically focuses on isolating joint embedment, achieved by systematically filtering out joint bands. This selective filtration process ensures that measurements are conducted exclusively on relevant joint embedment points. The novelty of this methodology lies in its capability to automatically eliminate joint bands while retaining the joint embedment points, facilitating precise measurements without manual intervention. Three site models were evaluated using the R-C-D-F method, alongside four different techniques for measuring dip angle and direction: plane fitting, normal vector conversion, facet segmentation, and compass measurements. The results demonstrated that all methods accurately calculated the dip angle, with an accuracy ranging from 97 % to 99.4 %. The facet segmentation method was selected as the optimal measurement tool due to its automatic nature and capacity to provide accurate results without manual intervention. Furthermore, the optimal local neighbour radius (LNR) for calculating normal vectors was determined, with findings indicating that a larger LNR value enhances accuracy but also increases computational time. A verification was conducted to estimate the dip angle used for filtering and discarding additional points representing joint rock bands, with the optimal value being 45, 30, and 45 degrees for the respective sites.

The R-C-D-F method effectively detected and eliminated 100 % of joint band points while retaining 81 % of joint embedment points, and the facet segmentation method provided accurate dip angle and direction measurements for each joint embedment segment. These outcomes underscore the robustness and precision of the R-C-D-F method in geological engineering and rock stability studies.