Bulletin of Engineering Geology and the Environment最新文献

Natural stones used as construction materials in outdoor applications and the rock environment in rock engineering applications are subject to weakening such as freeze-thaw (F-T) and thermal shock (TS) due to weather conditions. Predicting the mechanical effects of F-T and TS weathering is important for the design on rock engineering. While the change in mechanical properties can be determined by F-T and TS simulating with experimental studies, it can also be predicted with simple models in the literature and determining initial conditions. While the properties of weakened rock are determined from the models proposed in the literature, a rock-specific experimental study is needed and precise results cannot be obtained. Instead, the predicting of F-T and TS weathering on rocks by using deep learning-based algorithms enables better data for design. In this study, the effects of deterioration on physical and mechanical properties of natural stones after F-T and TS weathering was investigated with experimental simulation. The samples of 15 different rock type were subjected to F-T and TS process for 15, 30 and 45 cycles following standard methods in experimental study. The changes of apparent porosity, water absorption by weight, P-wave velocity, uniaxial compressive strength and elastic module of rocks after each process were investigated and analysed with different deep learning algorithms to predict these properties. It has been determined that AdaBoost is the best algorithm for predicting the properties of natural stone after F-T and TS weathering. Additionally, the stress distribution was modelled numerically to investigate the effect of F-T and TS weathering on rock samples. The study shows that deep learning-based algorithms can be used as an auxiliary tool in prediction in order to perform more precise studies.

The rapid movement and extensive displacement of gravel-silty clay landslides result in significant property damage and loss. Following the destabilization of the Shaziba landslide in Enshi City, it transformed into a debris flow, ultimately obstructing the Qingjiang River and creating a barrier dam. This study delves into the failure mechanism, leap dynamics, and motion processes of this specific landslide by employing a blend of ring shear testing and the discrete element method. Initially, the residual shear strength of the sliding soil was assessed through ring shear tests conducted under various coaxial stresses and shear rates within the sliding region, using field surveys and aerial imagery. Building upon this foundation, the entire progression of the landslide-from sliding to settlement-was replicated using PFC3D, allowing for an examination of the landslide's movement characteristics such as speed, displacement, and trajectory. The findings indicate that the shear displacement and residual friction coefficients are higher at elevated shear rates compared to lower rates. The landslide commences with an initial acceleration phase, with the silty clay material's movement lasting approximately 757 s, reaching a maximum velocity of 32.5 m/s and a displacement exceeding 1000 m. The simulated settlement volume of the landslide (9.31 × 10⁵m³) closely aligns with the results obtained from field investigations (1.5 × 10⁶m³). This research offers comprehensive insights into recent Shaziba landslides, serving as a valuable resource for enhancing our understanding of the dynamics involved and mitigating the potential risks associated with such events.

Predictions of cutting and bead consumption rates of diamond wire cutting machines are major subjects in determining the economics of natural stone quarrying. The main aim of this study is to develop empirical models to predict areal net cutting rate and bead consumption rate of diamond wire cutting machines based on statistical analyses using different physical and mechanical properties of natural stones at macro and micro scales. Firstly, twenty different natural stone quarries in Turkey were visited to collect natural stone samples and record field performance (areal net cutting rate and bead consumption rate) of diamond wire cutting machines. Macro and micro scale tests were applied in the laboratory on twenty-five different natural stone samples of metamorphic and sedimentary origins obtained from the fields. Macro-scale physical and mechanical property tests include density, uniaxial compressive strength, Brazilian tensile strength, Shore scleroscope hardness, and Schmidt hammer hardness. Micro-scale tests include texture coefficient, Knoop microhardness, and mean grain size. Then, simple, multiple linear, and multiple non-linear regression analyses were carried out using the macro and micro scale stone properties and the areal net cutting rate and bead consumption rate. An important feature distinguishing this study from previous ones is the use of micro and macro properties of stones separately and together, as well as the use of a very large number of data with high diversity. Results indicate that the models suggested in this study may be very useful and reliable tools for predicting the areal net cutting rate and bead consumption rate of diamond wire cutting machines.

Frequent disaster chains from landslides and debris flows in the tectonically active southwest of the Loess Plateau significantly impact local settlement safety and economic development. This paper proposes a method that integrates a hydrological stability model for landslides with FLO-2D numerical simulation to predict the reservoir type landslide-debris flow disaster chain under various rainfall conditions, based on the amplifying effects of landslides on debris flow disasters during extreme rainfall events. The results indicate that the construction of reservoir is a key factor triggering landslides. The calculated rainfall threshold for landslide reactivation ranges from 0.0–122.1 mm/d, meaning that under a 20-year return period, 98.5% (1750.0 × 10⁴ m³) of landslides will reactivate and become material sources of debris flow. Therefore, under the influence of heavy rainfall, landslides slide into the reservoir, forming debris flows, which serve as a model for the landslide-debris flow disaster chain evolution. Simulation results for the Yuling Gully debris flow under different return periods indicate that the volume of debris flow under a 100-year return period is equivalent to the sum of volumes under both 20-year and 50-year return periods, while the area of high-hazard areas is 2.7 times greater than that under a 20-year return period. Therefore, it is crucial to emphasize the investigation of debris flow disaster chains in small watersheds that contain reservoirs, as well as to enhance disaster prevention and early warning systems to ensure public safety.

In this study, an analytical model for the three-dimensional (3D) dynamic stability analysis of vegetation-rooted slopes is first developed under steady-state unsaturated flow conditions. Root reinforcement, defined as the increase in the soil shear strength produced by the mechanical and hydrological effects of vegetation roots, is included in the proposed analytical model. By combining the modified pseudo-dynamic approach (MPDA) and the kinematic theory of limit analysis to the 3D discretized failure model, the most critical failure surface and the corresponding factor of safety (FS) are derived to examine the stability of vegetation-rooted slopes with the aid of the optimization algorithm of particle swarm. The proposed approach is verified by comparing with published analytical solutions and numerical results. A series of parametric analysis are then conducted to examine the influence of seismic-related parameters, vegetation properties, possible surcharge and slope geometry parameters on the slope stability. Finally, a comparison between the slope stability under different root architectures is provided and discussed. The results show that, for these selected cases, the stability of vegetation-rooted slopes is significantly improved by approximately 45% compared to bare soil slopes, and the divergences of reinforcement effects between different root architectures can be negligible.

Mining landslides in southwestern China pose a serious threat to people's property and safety. In order to study the destabilisation and damage mechanism of karst mountains under the combined action of mining and rainfall, based on the landslides in the mountainous area of the Maidi Coal Mine in Guizhou Province, and combining with field investigations, we have analysed the characteristics of the landslides, investigated the stability of the bearing structure of the bedrock of the mountain, the composition of the mineral components, and the microscopic characteristics of the rocks, and simulated the excavation of the coal seams as well as the infiltration of the rainfall. The destabilisation mechanism of the karst mountain under the coupling of mining stress and rainfall infiltration was investigated. The obtained destabilisation and destruction mechanism of karst mountain destabilisation under the coupled action of mining and rainfall lays the foundation for the control of karst landslides.

Uncompacted saturated loess retains its residual pore structure without artificial compaction, making it highly sensitive to environmental changes such as dehydration-rehydration cycles. This study investigates the dynamic characteristics of uncompacted saturated loess in the Xi'an area, where infrastructure projects are commonly affected by the soil's instability. Dynamic triaxial tests were conducted under varying confining pressures and dehydration-rehydration cycles to examine the dynamic stress–strain relationship, dynamic modulus, and damping ratio variation. The methodology involved multi-stage loading using dynamic triaxial equipment, with cycles of drying and rehydration applied to replicate field conditions. A hyperbolic tangent function was used to model the dynamic stress–strain behavior, and structural parameters m1​ and m2​ were introduced to quantify the soil's stability and variability. Key findings show that dynamic stress increases with dehydration-rehydration cycles, while dynamic modulus and damping ratio decrease, especially during the initial cycles. The results provide critical insights into the behavior of uncompacted saturated loess under dynamic conditions, offering practical guidelines for managing soil stability in infrastructure projects across the Xi'an region.

Debris flow blocking river is a common mountain disaster chain, and however, there is a scarcity of quantitative approaches for assessing this particular disaster chain. To tackle this issue, we have developed a mathematical model using the framework of depth-averaged theory and its associated computational method. The model effectively captures the multistage process of debris flow blocking river at a catchment scale. It encompasses the dynamics of runoff, debris flow, and the river, ensuring the transfer of mass and momentum throughout the entire chain. To facilitate a more intuitive transition between the various secondary induced disasters associated with debris flow blocking river, two additional state variables are introduced. The presented computing method solves the model equations by integrating an HLLC Riemann solver into a second-order accurate finite volume method. To validate the effectiveness of this approach, two laboratory experiments and the 2020 Meilong debris flow blocking river event are simulated, and the obtained results are consistent with the available data. Moreover, this approach is employed to estimate the impact of scission on the chain process of debris flow blocking river. The simulated results showcase whether the transition between the various sub-disasters can successfully transpire under the influence of chain scission. This study can provide a basis for quantitatively assessing the chain process of debris flow blocking river as well as finding the optimization scheme to prevent this disaster chain.

The investigation of crack initiation and expansion is vital for the stability of structures. The Mode I fracture toughness (K_Ic) of rocks is a key property used to predict crack propagation in tension and hydraulic fracturing. Various methods have been introduced to determine K_Ic, but results differ due to factors like sample dimensions, crack geometry, groove type, and loading conditions. The cracked chevron notched Brazilian disc (CCNBD) sample is commonly used in laboratory tests for its easy preparation. This study employs the rock engineering system (RES) technique to overcome the challenges of time-consuming and costly laboratory tests and the uncertainty in traditional methods (analytical, numerical, experimental, laboratory, regression). Using 88 CCNBD rock samples proposed by ISRM, input parameters include thickness of the disc specimen (B), uniaxial tensile strength (σ_t), initial crack length (α₀), radius of the disc specimen (R), crack length (α_B), and the length of the final crack (α₁). The RES-based model used 70 data points (80% of the dataset) for development, and 18 data points (20%) for evaluation. Regression analysis compared the performance of the RES method, using statistical indicators such as squared correlation coefficient (R²), mean square error (MSE), and root mean square error (RMSE) to measure accuracy. The RES-based method outperformed other regression techniques, demonstrating significantly enhanced accuracy. This highlights the effectiveness and superior performance of the RES method in estimating fracture toughness, particularly for CCNBD samples, showcasing its potential as a robust analytical tool.

The mountainous region of southwest China is rich in mineral resources; however, its complex topography and geological conditions make underground mining susceptible to triggering geological hazards. To comprehensively understand the mechanisms of mining-induced slope instability, generalized models of linear, concave, and concave-convex slopes were developed. The progression from the formation of mining-induced fissure networks to slope failure was analyzed using base friction tests, digital photogrammetry for deformation measurement (DPDM) technology, and fractal theory. The results indicate that an increase in mining area, number of layers, and depth leads to continuous adjustments in fissure networks and formation dislocations, resulting in diverse interactions and developmental trajectories. Fissures propagate toward the surface, increasing the fractured rock mass and decreasing slope stability. The maximum displacement occurring in the direct roof and the upper-middle part of the slope, and the maximum shear strain concentrated in the direct roof, the leading and trailing edges of the slope, and the shear failure zones. Slope shape influences deformation and failure modes: linear and concave slopes undergo creepsliding and fracturing, whereas concave-convex slopes are more prone to bending and fracturing. The fractal dimension is directly proportional to mining depth, while the probability distribution index is inversely proportional to mining depth, indicating that the fissure development mechanism evolves from micro-fissure formation to large-scale fissure. The increasing complexity in the boundaries of fissure networks is accompanied by expansion, compaction, and penetration. These findings provide a foundation for the accurate assessment of mining-induced geological hazards in slopes with similar geometric configurations.