Rock is a typical brittle material, and the evaluation of its brittleness index has important guiding significance for hard rock resource exploitation, unconventional oil and gas resource exploitation, mechanical driving efficiency, rock burst prediction, and dynamic disaster prevention and control. At present, brittleness index often measures the brittleness of rock under static load; thus, whether it is applicable to dynamic load is worth exploring. In this study, static and dynamic uniaxial compression tests and Brazilian splitting tests were carried out on five kinds of rocks, including fine granite, coarse granite, shale, marble, and sandstone, using the INSTRON−1346 test system and split−Hopkinson pressure bar (SHPB), respectively. The brittleness index values of different rocks under static and dynamic load were determined, and the changes in the brittleness of rocks under different loading methods and different strain rates were studied. The definition of brittleness and the applicability of existing brittleness indices were also discussed. It was found that the loading rate amplified the variation of the brittleness characteristics of rock. When static load changes to dynamic load, the brittleness of rocks increases, and the brittleness relationship between different rocks remains unchanged. The more brittle the rock is under static load, the greater the range of brittleness enhancement is under dynamic load. It was also found that the brittleness of sandstone had an obvious effect on the strain rate. The brittleness of rock increases with the increase in strain rate, and the greater the strain rate, the greater the brittleness enhancement degree. These research results can provide reference values for dynamic disaster prevention and safe construction of deep rock projects such as mines and tunnels.
Abstract Rock masses around fluid injection projects are usually subject to complex stress states, including hydraulic pressure, in situ stresses, and fatigue loads. Thus, a series of hydraulic fracturing experiments were performed on granite to simulate such stress states using the true triaxial dynamic testing system. Computed tomographic (CT) imaging was performed to identify the fatigue effects on hydraulic fractures. The results indicate that the increasing amplitudes of cyclic load applied on the minimum principal stress direction will change fracture initiation pressure and generate nonplanar and narrow fractures. When the disturbance direction was changed to the intermediate principal stress, the higher amplitude corresponds to the lower breakdown pressure and the shorter pressurize duration and leads to wider fractures. With the increasing disturbance frequency, complex fatigue cracks were generated, which might weaken the rock strength. The present experiments can enhance the understanding of the hazard of fatigue loads on hydraulic fracturing.
Taking the “11.28” rockburst occurred in the Jinping II Hydropower Station as the engineering background, the evolution mechanism of structure-type rockburst was studied in detail based on the particle flow code. The results indicate that the failure mechanism of structure-type rockburst includes a tensile fracture induced by tangential compressive stress and a shear fracture caused by shear stress due to overburdened loadings and shear slip on the structural plane. In addition, it is found that the differences between structure-type rockburst and strainburst mainly include (a) the distribution of the local concentrated stress zone after excavation, (b) the evolution mechanism, and (c) the failure locations. Finally, the influence of four factors on the structure-type rockburst are explored. The results show that (1) when the friction coefficient is greater than 0.5, the effect of structural plane is weakened, and the rock near excavation tends to be intact, the structural-type rockburst intensity decreases; (2) the dissipated and radiated energy in structural-type rockburst reduces with rockmass heterogeneity m; (3) the lateral pressure coefficient has a significant effect on the intensity of deep rock failure, specifically in the form of the rapid growth in dissipative energy; (4) and the structural-type rockburst is more pronounced at a structural plane length near 90 mm.
Accurate and efficient rock mass quality classification is a prerequisite for assessing slope stability, designing support schemes, and ensuring mining safety in open-pit mines. However, traditional empirical classification methods rely heavily on expert judgment and often struggle to capture the complex, nonlinear relationships among factors influencing slope stability. Existing intelligent classification models also suffer from limitations, including sensitivity to incomplete data, insufficient feature interaction learning, and unstable performance on small-scale datasets. To address these issues, this study develops a deep forest (DeepForest) model optimized by three metaheuristic algorithms—brown bear optimizer (BBO), tuna swarm optimizer (TSO), and sparrow search algorithm (SSA)—to intelligently classify slope rock mass quality. A rock mass quality dataset containing 204 groups of slope and non-slope cases was established to train and evaluate the classification performance of the DeepForest models. Six influencing factors were set as input parameters: uniaxial compressive strength (UCS) of rock, rock quality designation (RQD), spacing of discontinuities (Sd), rock mass integrity coefficient (Kv), groundwater conditions (W), and site type (St). Multivariate imputation by chained equations (MICE), isolation forest (IsoForest), and synthetic minority over-sampling technique (SMOTE) were used to handle missing values, outliers, and imbalance in the dataset, respectively. The performance of the proposed models was evaluated using five metrics: accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC). The experimental results indicate that the BBO-DeepForest model performed best on the independent test set, with accuracy, precision, recall, F1-score, and average AUC values of 0.878, 0.682, 0.678, 0.678, and 0.961, respectively. A comparison with seven well-known imputation algorithms revealed the superiority of the selected imputation algorithm in recovering incomplete rock mass quality datasets. Model interpretation results showed that RQD and UCS are critical feature parameters for classifying slope rock mass quality. At last, the proposed BBO-DeepForest model was employed to verify the rock mass quality of three slopes at the Luming molybdenum mine, resulting in classifications consistent with on-site observations. It demonstrates that combining DeepForest with metaheuristic optimization algorithms is a feasible and accurate approach for intelligently classifying the rock mass quality of slopes.
Abstract Chongqing is a mountain city in western China, with complex geological environment, which brings many difficulties to the construction of large section underground projects. The construction experience of a large number of underground projects shows that ordinary engineering geological survey is difficult to meet the requirement of engineering design and construction. Therefore, on the basis of the initial survey, intensive drilling and coring work were carried out for the engineering area of the Guobo underground station with large cross-section to be built, and the basic mechanical, softening properties of the surrounding rock and in-situ stress field of the project area are obtained by laboratory tests. Based on the present experimental results and engineering experiences, it is proposed that the potential risks of Guobo station excavation include: ①bias pressure;②High in-situ stress;③Surrounding rock deterioration. The present study has practical significance for the design and construction of Guobo underground station, and it has certain reference value for the construction of underground projects in similar geological areas.
Dynamic fatigue of rocks under repeated cyclic impact is a nonconservative property, as surrounding rocks in real environments subjects them to variable impact disturbances, and the degree of damage varies under different energy level loads. To evaluate the dynamic response and fatigue damage characteristics of rocks under multi-level cyclic impacts, uniaxial cyclic impact tests were carried out on granite with various stress paths and energy levels using a modified split Hopkinson pressure bar. Dynamic deformation characteristics of specimens under different loading modes were investigated by introducing the deformation modulus of the loading stage. Evolution of macroscopic cracks during the impact process was investigated based on high-speed camera images, and the microscopic structure of damaged specimens was examined using SEM. In addition, cumulative energy dissipation was used to assess the damage of rocks. Results show that the deformation modulus of the loading stage, dynamic peak stress and strain of specimens increase with the impact energy, and the deformation modulus of the loading stage decreases as the damage level increases. Propagation rate of tensile cracks in rock was correlated with participation time of the higher energy level, which observed the following sequence: linearly decreasing > same > linearly increasing energy level, and cyclic loading of nonlinear energy level produced more tensile cracks and rock spalling than the same energy level. Compared with cyclic impacts of the same energy level, multi-level impacts form more microcracks and fatigue striations. The cumulative rate of specimen damage under the same energy change rate is as follows: linear decreasing > same > linear increasing loading. This provides a new case study for evaluating the dynamic damage, crushing efficiency and load-bearing capacity of rocks in real engineering environments.
