Bulletin of Engineering Geology and the Environment最新文献

Dynamic loads due to blasting will affect the mechanical properties of rock masses and form an excavation damage zone (EDZ). The rock mass properties within the EDZ are obtained by the geological strength index (GSI) and disturbance factor (D) in the Hoek-Brown criterion. In order to avoid the subjectivity of GSI evaluation, a stochastic-deterministic 3D discrete fracture network (DFN) is constructed to quantify the GSI. The D value is considered to be a value that varies with depth within the EDZ, rather than a fixed value. Quantitative blasting vibration data is used to determine the disturbance factor rather than qualitatively estimated values. When the disturbance factor decreases linearly within the EDZ, the mechanical properties of the rock mass increase linearly to the undamaged value. Numerical simulation is used to analyze the influence of linear decrease of the rock mass properties on the stability evaluation of the tunnel. The results show that different rock mass parameters have a great influence on tunnel convergence and settlement values. The method described in this paper helps to evaluate the stability of surrounding rock more objectively and accurately.

Hydraulically filled coral sand foundations are susceptible to various challenges within intricate marine environment. The friability of coral sand results in the production of large amounts of sub-graded fine particles under external stress. Meanwhile, the continual influence of oceanic forces leads to a gradual erosion of these fine particles from soil. The interaction between these two long-term effects plays a crucial role in particle breakage and soil mechanics of coral sand. To address this issue, consolidated drained triaxial tests and sieving analysis were conducted on the gap-graded coral sand with various fine contents. Three unique test methodologies are devised to alter the fine content, including hydraulic scouring, particle removal and particle replacement. The experimental results revealed that a specific amount of fine particle loss can significantly deteriorate the mechanical properties of dense coral sand. By replacing coarse particles with fine particles, larger strength parameters and less dilation were observed, yet there existed a critical threshold of 60% fine content, beyond which further substitution did not yield additional improvement in soil strength. Particle crushing was primarily concentrated in the middle layer of the specimen, influenced by the development of the shear band. Furthermore, the amount of newly generated finer particles exhibited a positive correlation with the increase in fine content in the initial gap-graded soil. These findings could enhance the understanding of the role that fines plays in determining the mechanical characteristics and particle breakage behavior of coral sand, and thus aid in more accurate assessments and designs of engineering applications involving coral sand.

China’s extensive permafrost regions necessitate studying strength changes in frozen soil to ensure structural stability and safety. To quantitatively assess soil mechanics under varying conditions, this paper investigates the silty soil in Northeast China using piezoelectric ceramic testing and triaxial testing of freeze-thaw cycles and freezing conditions. The study explores strength variation patterns and structural change mechanisms of silty soil during these processes and establishes soil strength evaluation indices based on piezoelectric signal energy. The principal findings are: (1) Strength of silty soil decreases parabolically with increasing freeze-thaw cycles, with the initial cycle having the most significant impact, particularly for soil with optimal water content. (2) Lower freezing temperature can effectively improve silty soil’s elasticity modulus, failure strength, and cohesion, with more pronounced improvements observed between − 2 °C and − 5 °C compared to -5 °C to -10 °C, while the internal friction angle shows no clear change pattern. (3) Monitoring signals of smart aggregate are related to the properties of smart aggregate and the tested soil. The strength deterioration index ((:SDI)) defined by signal energy correlates greater than 98% with the failure strength of soil at room temperature. Low water content samples exhibit higher energy vectors under the same conditions. (4) The strength enhancement index (:left(SEIright)) defined by signal energy correlates greater than 90% with failure strength of frozen soil. High-frequency signals are more responsive to temperature fluctuations. The aforementioned indices provide invaluable insights with regard to the implementation of piezoelectric ceramic testing technology within the field of geotechnical engineering.

The selection of landslide and non-landslide samples significantly influences the performance of machine learning (ML)-based landslide susceptibility assessment (LSA). The commonly used buffer-controlled sampling (BCS) strategy for selecting non-landslide samples overlooks the spatial heterogeneity of the geological environment and lacks a standardized method for determining buffer radius. As a result, the sampling process introduces significant uncertainty to ML models. This paper proposes an improved BCS strategy that incorporates the spatial heterogeneity of conditioning factors to address this issue. The proposed strategy generates a buffer zone for each landslide by merging all neighboring areas with the same attributes as the landslide and then calculates the average equivalent radius of those zones for comparative analysis. The random forest (RF) and the support vector machine (SVM) models are employed to predict the landslide susceptibility of Taojiang County, China, using both the improved and the traditional BCS strategy. Furthermore, the impact of different buffer radii on the model prediction is thoroughly investigated to provide guidance for the selection of buffer radius. The results demonstrate that a buffer radius of less than 3,000 m is optimal in Taojiang County. Compared with the traditional RF and SVM model, the corresponding improved models exhibit superior performance, with higher AUC values and increased peak frequency ratios in areas of very high susceptibility. These findings confirm the effectiveness of the proposed strategy, offering valuable guidance for buffer radius selection and improving the ML-based LSA.

The geological conditions in the dam area of Baihetan Hydropower Station are very complex, with columnar joints accounting for up to 39.9% of the base area. None of the existing methodologies for rock mass classification are fully suitable for the purposes of quality classification of columnar jointed basalt rock masses. This article addresses the challenges in evaluating and classifying the quality of the columnar jointed basalt rock mass at the dam foundation of the Baihetan Hydropower Station on the Jinsha River. Considering the engineering geological conditions, rock mass characteristics, and environmental context of the Baihetan dam area, evaluation indicators were selected for engineering rock mass quality classification. It also introduces a new rock mass classification model that combines the Gaussian function with the K-nearest neighbor (KNN) classification algorithm. Different weight coefficients were assigned based on the similarity of the samples. Thus, the proposed model was used for the evaluation and classification of the rock mass at the dam foundation in the key area. Ultimately, a new classification tool is proposed for assessing engineering properties of the rock mass at Baihetan dam foundation, providing a viable solution for quality classification in this particular area.

Due to the elevation of tunnel-type anchorages (TTAs) is close to or even much lower than the reservoir water level in the Three Gorges Reservoir area of China, some TTAs are in a water-soaked state due to the high groundwater level. Nevertheless, the influence of the water content of soft rock on the bearing performance of a TTA has not been fully explored. Hence, two large-scale field models buried in soft rock with different water contents were developed to investigate the effects of water on the deformation evolution, ultimate bearing capacity, load transfer efficiency, and progressive failure characteristics of TTAs. The model tests show that the water content of the rock mass increases from 5.36 to 7.39%, and the ultimate bearing capacity of the TTA decreases by approximately 22.8%. The load transfer efficiency of TTAs decreases with increasing rock mass water content. There will be great relative slip along the interface between the floor of the plug body and the surrounding rock during the bearing of TTAs with different rock mass water content; the TTA preferentially fails along this interface. Additionally, the ground surface cracks are mainly tensile and shear cracks. Although an increase in water content significantly reduces the ability of a rock mass to resist deformation, a change in water content does not affect its movement mode or failure characteristics. The influence of water is mainly manifested in the increase in rock mass deformation and decrease in the ultimate load-carrying capability, crack initiation load, and load transfer efficiency of TTAs.

The digital representation, representative elementary volume (REV), and mechanical parameters of broken rock masses are essential foundations for simulating and studying the mechanical properties and behaviors of broken rock masses. Taking the broken surrounding rock of the main powerhouse of the Liyang pumped storage power station as the research subject, an equivalent rock mass model was constructed using equivalent rock mass techniques. Through a series of numerical tests, the REV size and equivalent mechanical parameters of the broken rock mass under various factors were investigated. The results indicate that the REV size of the broken surrounding rock of the main powerhouse, determined based on the equivalent cylindrical rock mass model, is 5 m × 10 m. The broken rock mass with a friction angle of structural planes lower than 30° exhibits brittle failure after reaching the uniaxial peak stress. As the number of fractures within the rock mass increases, the equivalent mechanical parameters of the rock mass show a decreasing trend, and the degree of dispersion of the mechanical parameters increases. Furthermore, the ratio of structural surface trace length to spacing was proposed as a classification criterion for broken surrounding rock, and a range of mechanical parameters for different types of broken rock masses was provided. This study offers important references for the numerical calculations of the mechanical behavior of broken rock masses.

The displacement prediction of step-like landslides is the simplest and most reasonable method for assessing their potential destructiveness. Over the years, machine learning methods have been progressively developed and optimized, and are now extensively used by researchers for predicting the displacement of step-like landslides. However, these methods, often referred to as “black box” models, fall short of explaining the physical processes that lead to landslide displacement, resulting in a lack of interpretability in the prediction of results. Here, we propose the use of the Trend Speed Ratio (TSR) as a novel method to identify step points in step-like landslides. A step in the landslide is observed when TSR > 1.0 and ΔTSR > 0. When TSR > 2.0, the landslide is deemed to have experienced failure. Additionally, TSR is employed to predict the displacement of secondary steps following landslide deformation. In the application cases of the Baishuihe and Baijiabao landslides in the Three Gorges Reservoir area, the accuracy of the step point identification method based on TSR reached 100%, and the mean absolute errors (MAEs) of the step post-displacement prediction method based on TSR were 31.60333 mm and 25.68056 mm, respectively, and the coefficient of determination values were 0.91043 and 0.99378, respectively. Compared to traditional methods, this approach provides practical physical insights and is more straightforward, sensitive, and stable, thus providing new technical support for onsite engineers to assess the potential risks of step-like landslides.

Masjed Soleyman rockfill dam, with a height of 177 m, has experienced significant settlement during its construction, impoundment and operation stages. A possible contributing factor in the excessive deformation is the weak conglomerate rockfill material used in building the dam shells. This research work focuses on the experimental study of the mechanical behavior of the conglomerate rockfill material of the dam shells, including the point load, Brazilian, oedometer, and direct shear tests. The results of the point load and Brazilian tensile tests showed moisture and size effects, and suggested that the strength of the rockfill made of this rock falls within the medium to weak range. The oedometer test results demonstrated that the specimen moisture, density, gradation and applied stress impact the particle breakage, strain, and saturation collapse of the rockfill material. Our findings suggest that the excessive dam settlement and saturation collapse (wetting deformation) could have been substantially decreased and controlled by wet compacting the rockfill layers during the dam construction. It was shown that particle breakage in the direct shear tests is greater than that in the oedometer tests, suggesting that for dams with excessive shear deformation (like Masjed Soleyman Dam), a more realistic estimate of particle breakage can be obtained using either direct shear test or triaxial tests. The ratio of strain to particle breakage index was revealed to be independent of the applied stress and moisture content of the specimen, but it was affected by the material gradation and density.

Complex fault modeling is one of the key technologies in 3D geological modeling. Fault data are sparse, especially where the faults intersect. To solve this problem, this paper proposes a deductive approach for 3D complex fault model. Firstly, based on multi-source data, such as exploration and attribute data, the hanging wall and footwall of marker strata of each fault are modeled as a ring composed of a series of three-dimensional coordinate of the discrete points. And then, the fault throws on each non-marker stratum are calculated. Secondly, by dividing the priority of faults, the discrete points of the hanging wall and footwall on each non-marker stratum are calculated by intersecting the fault plane with the non-marker strata under the priority of faults. The calculation increases the number of point data on the fault. Based on the intersection points formed by the plane of higher-level fault and the fault line of lower-level fault, the intersections of faults are deduced. Fault lines on each stratum are obtained by intersecting faults with collapse columns and special geological bodies such as lenses. The discrete points on each fault plane are processed through Delaunay triangulation to generate the fault plane model. The proposed method is applied to build a 3D geological modeling of a mine in real case. The model represents the morphology, key locations, and spatial relationships of faults, improving the accuracy of fault models.