Bulletin of Engineering Geology and the Environment最新文献

The challenge faced by roadway excavation methods lies in minimizing disturbance to the surrounding rock while maintaining driving speed. To minimize damage to the surrounding rock during roadway excavation, this study proposes a method of unloading the roadway contour to sever the connection between the excavated target rock mass and the retained surrounding rock mass. This approach initiates the propagation of cracks within the targeted rock mass, thereby releasing internal energy to facilitate rapid excavation. Through laboratory testing of contour excavation and coupled numerical testing of PFC3D-FLAC3D, the fracture mechanism of surrounding rock in roadway contour excavation is elucidated, and the impact of geometric parameters of contour excavation on surrounding rock disturbance is examined. The findings indicate that contour excavation does not result in structural impairment to the entire coal body, but instead leads to the formation of internal macroscopic fractures. The AE parameters (RA-AF total statistics, cumulative ringing count, cumulative energy), the range of high strain field, and the degree of internal fracture of the sample all exhibit a significant decrease as the length of cyclic excavation (LCE). This is evidenced by a decrease in development depth of roof cracks from 0.43 m to 0.20 m and a 33% reduction in the number of cracks. Selecting a lower LCE has the potential to substantially mitigate the adverse effects of contour excavation on the surrounding rock mass. The inner rock mass of the excavation target exhibits a reduced contact field, leading to a noticeable deterioration in the strength of the rock mass, thereby creating favorable conditions for subsequent cutting operations. The contour excavation method has the potential to mitigate the severe damage caused by traditional roadway excavation, transforming it into a more controlled and shallow cracking process. This allows for the implementation of precise local support design.

Entrainment is crucial in shaping debris flow deposits, influencing their morphology and dynamics. Understanding deposition driven by entrainment is vital for improving hazard mitigation and sediment management strategies. This study employs a small-scale flume setup to examine the interplay between water content (w/c), sediment composition, and bed morphology on granular flow behavior. Sixteen experiments were conducted, varying w/c (20–50%) and erodible bed configurations, with deposit morphology analyzed for width, thickness, and runout length. The findings revealed distinct patterns in deposit morphology across w/c levels. At lower w/c (20–24%), deposits exhibited broad, shorter lobes with minimal scouring, forming cone-shaped structures. Moderate w/c (~ 28%) enhanced flow mobility, producing thicker deposits near the flume bed due to reduced entrainment. At higher w/c (30–50%), deposits shifted further downstream, driven by greater entrainment volumes and longer runout distances. While higher w/c levels decreased deposit thickness, they significantly widened the runout deposits, demonstrating the dual influence of w/c and entrainment. A clear relationship emerged between entrainment and flow mobility, as increased entrainment volumes widened and flattened deposits. Additionally, water content dominated entrainment in controlling deposit thickness, underscoring its critical role in sediment transport dynamics. The deposits were poorly sorted, with a distinct bedding structure akin to natural debris flows, validating the experimental setup. This study provides an efficient and scalable methodology for analyzing granular flow behavior in erodible beds. The results offer insights into sediment transport processes, bridging the gap between mesoscale experiments and real-world applications in natural hazard mitigation and geotechnical engineering.

Many early highway tunnels are no longer adequate for current traffic demands and require renovation. For short tunnels, in-situ expansion is a proposed solution. However, most research on tunnel construction mechanics and load calculations has focused on new tunnels, with limited studies on in-situ expansion, particularly in tunnels with fractured surrounding rock. This paper presents research using similar material models, field pressure and deformation monitoring, and surrounding rock pressure theory. Key findings indicate that removing the upper bench lining and excavating the surrounding rock on the expansion side reduces surrounding rock stress, with a more significant pressure decrease on the expansion side. The shallow surrounding rock experiences greater stress reduction than deeper strata. Field monitoring shows similar three-stage patterns (rapid change, slow change, and stability) in anchor shaft force, steel arch stress, and contact stress between the initial support and surrounding rock, stabilizing after 15 h. Stress concentrations occurred at the left and right arch shoulders, with higher stress at the left. The removal of upper bench lining and surrounding rock expansion had a significant impact on stress changes, while lower bench excavation had minimal effect on arch shoulder stress. Physical and field data showed severe damage and stress reduction at the right arch shoulder on the expansion side, causing asymmetric stress and damage distribution. The rates of perimeter rock pressure change during tunnel expansion were significantly higher than during sub-conductor excavation, indicating the substantial influence of construction steps and expansion width.

Karst-related geological disasters pose great threats to public safety. Geophysical methods for detecting geological hazards, such as electrical resistivity tomography (ERT), seismic tomography, ground penetrating radar (GPR), and borehole radar methods, have flourished in the past decades. However, the application of a single method among them has limitations in terms of probing depth, imaging resolution, and data interpretability. Therefore, to enhance detection accuracy and improve imaging resolution, selecting and combining multiple geophysical methods is indispensable before conducting a survey in a karst-affected area. In this paper, the location, boundary, and infill of a karst cave in an urban area are explored using surface and borehole geophysical methods. The experimental results demonstrate that ERT is appropriate for roughly detecting the location of the karst. The results indicate the presence of a U-shaped low-resistivity anomaly corresponds to a karst cave filled with water-bearing sand. Accordingly, locations of boreholes are determined. To further characterize the boundary and infill of a karst cave, cross-hole computer tomography (CT) of radar and seismic method is employed. The results show that the cross-hole radar CT yields superior results over the cross-hole seismic CT in characterizing a shallow soil layer and delineating the karst cave boundary. The geology of the test area is characterized by combining these geophysical findings and the drilling results. These findings provide useful information for planning underground engineering projects in urban areas.

Rock mass strength is one of the key factors related to rock mechanics research and rock engineering design. In this paper, rock mass failure is simulated using a discrete Bonded Block Model, BBM, and the rock mass strength is characterized accordingly. A set of optimization algorithms is initially developed to relocate key fractures in the Discrete Fracture Network, DFN, where the distance or intersection angle between two fractures are inappropriate to accommodate regularly sized block elements. The rock mass failure and strength are then simulated using BBM models with varied fracture orientations. Higher strength is generally captured when fractures in the rock mass are less favorable to shear sliding. Since the strength of intact rocks is mechanically stronger than the strength of the initial fractures, the higher rock mass strength results from additional failures of intact rocks. Inherent numerical uncertainties are also characterized when the BBM model is selected for characterizations of the rock mass failure and strength. The strength uncertainty is captured through calibration BBM models, and are attributed to the variations of the block distributions related to fracture accommodations. This strength uncertainty is further increased considering the weakening effects of the fractures. The research addresses several key aspects of using the BBM models for simulations of the rock mass failure, and is expected to characterize the rock mass strength in a more reliable manner.

Slow-moving landslides are typically characterised by pre-existing shear zones composed of thick, clay-rich, and mechanically weak soil layers that exhibit heightened sensitivity to changes in moisture content and hydrological conditions. These zones, often governed by variations in suction and degree of saturation, play a critical role in the stability and long-term behaviour of slow-moving landslides. In this study, we investigate the influence of the degree of saturation on the mechanical properties of shear-zone soils from a reactivated slow-moving landslide in the Three Gorges Reservoir area, China. A series of laboratory experiments, including consolidation, reversal direct shear, and ring-shear tests, were conducted on reconstituted shear-zone soil samples at varying degrees of saturation. The test results indicate that increasing the degree of saturation has a marked impact on the compressibility of the soils, with saturated samples exhibiting greater compressibility and unsaturated samples demonstrating reduced compressibility. Both shear tests indicate that higher saturation leads to a reduction in peak and residual shear strength, likely due to elevated pore water pressures and a decrease in inter-particle bonding forces. These insights emphasise the need to account for varying degrees of saturation when analysing the mechanical behaviour of slow-moving landslides, contributing to an improved understanding of their deformation patterns and failure mechanisms.

Discontinuities in rock masses significantly influence their mechanical properties and are critical for engineering applications, making it essential to thoroughly understand their geometric parameters. 3D point clouds serve as fundamental data for efficiently and accurately analyzing discontinuity orientations. In this context, a novel semi-automated method that employs a Nutcracker Optimization Algorithm-improved Probabilistic Neural Network (NOA-PNN) is proposed. The NOA enables the PNN to quickly identify the optimal smoothing factor, balancing both accuracy and efficiency. This method utilizes not only normal vectors, but also point coordinates, curvature, and density, incorporating a broader set of features to accurately identify points on discontinuities. The NOA-PNN model, trained on manually selected samples, swiftly identifies discontinuity sets while efficiently filtering out noise. Density-Based Spatial Clustering of Applications with Noise (DBSCAN) is then used to extract single discontinuities within each set. Each discontinuity is fitted to a plane using a Principal Component Analysis (PCA)-based least squares method, facilitating the measurement of their spatial geometric parameters. Validation through two cases demonstrated that the proposed method achieved an average deviation of less than 5° in both dip direction and dip angle, exhibiting potential advantages in terms of accuracy and efficiency when compared to other important studies or software. This method significantly improves computational efficiency and achieves satisfactory results with only a small number of randomly selected samples. Its low requirements for sample quality and operator expertise make it highly operable and easily adaptable for practical engineering applications.

The coupled effects of heterogeneous composition and block structure make it challenging to establish a generalized mechanical model for block-in-matrix (bim) geomaterials. In this study, the bim cell is introduced as a new unit to investigate the mechanical coupling behaviors of cohesive bim geomaterials. First, the structural features and experimental preparation of the bim cell are outlined, and the shear mechanical properties and failure surface of the bim cell were obtained through direct shear tests and laser scanning experiments. Additionally, a three-dimensional discrete element model of the bim cell was precisely constructed and calibrated to replicate the meso-failure process, and was applied in numerical tests of bim cells with varying block sizes. Based on experimental and numerical results, it was demonstrated that the mechanical behavior of the rock block is akin to the existence of a structural interface within the matrix, which significantly controll both the peak and residual strength mechanism. In the peak state, the mechanical effects of the block are primarily controlled by the block-matrix interface properties. Whereas in the residual state, the structural effects of the block gradually become prominent in the irregularity of shear-induced slip. Finally, the strength coupling law of the components has been discussed based on the construction of a mechanical unit. The core contribution of this paper lies in emphasizing the differences in the failure mechanisms of the bim geomaterials under different shear deformations, providing a solid meso-mechanical basis for the development of peak and residual strength models.

The diversity of topographic and geological conditions significantly affects the kinematics and failure mechanisms of reservoir-induced landslides, especially those with rear reservoirs, which remain understudied. Taking the Shuiyunshan slow-moving landslide as a case study, this study investigates its failure mechanisms through a combination of field investigations, InSAR monitoring, and numerical simulations. The results reveal that the landslide is primarily driven by effective rainfall accumulation in a rear concave catchment area and sustained infiltration and erosion from rear reservoirs. The rear concave catchment area, which is 1.04 times the volume of the landslide body, alters the infiltration process of atmospheric rainfall. Approximately 61.9% of the rainfall generates surface runoff that accumulates in the rear reservoirs rather than discharging during rainstorms (100 mm/d). Furthermore, the distinctive geological structure featuring limestone interfacing with shale prolongs the infiltration process, while the rear reservoirs intensify groundwater recharge and weaken shale through prolonged immersion. The hydrostatic pressure and substantial hydraulic gradient exerted by the rear reservoirs significantly increase groundwater recharge within the landslide. Numerical simulations indicate that increasing the reservoir water level from 0 m to 3 m results in a decrease of approximately 16.3% in the safety factor of the most dangerous sliding surface of the landslide, highlighting the adverse impact of rear reservoirs on landslide stability. This study enhances the understanding of rear reservoir-induced landslides in mountainous regions, with implications for rural hydraulic infrastructure.

Rainfall is a critical factor in triggering landslides globally, with slope failure probability serving as a key metric for assessing landslide risks. While the spatial variability of soil properties and rainfall uncertainty significantly influence slope failure probability, limited studies have addressed these factors concurrently. Most existing research either emphasizes the spatial variability of soil properties or rainfall uncertainty, often neglecting their combined effects. To address this gap, this study introduces an integrated probabilistic framework that incorporates soil spatial variability and rainfall uncertainty into a slope model for the probabilistic slope seepage analysis based on Monte Carlo simulations. Multivariate soil random fields are employed to represent spatial variability, while rainfall uncertainty is modeled using a bivariate distribution of intensity and duration. This approach allows for the derivation of critical metrics, including the probability of slope failure under single rainfall events, annual failure probabilities, and failure probabilities over multiple years. The proposed framework was applied to a soil slope from the Sawala Laska road project in Ethiopia to demonstrate its effectiveness. Compared to traditional methods that consider only rainfall uncertainty or treat soil properties as deterministic, the framework provides a broader range of safety factor values and more precise estimates of critical rainfall durations. It also reveals that the probability of failure during a single rainfall event decreases, while annual failure probability increases gradually with more frequent rainfall events. By integrating spatial soil variability and rainfall uncertainty within a unified framework, this study advances landslide risk assessments and provides practical tools for slope stability analysis under real-world conditions.