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The rock slope stability analysis can be performed using deterministic and probabilistic approaches. The deterministic analysis based on the safety concept factor uses fixed representative values for each input parameter involved without considering the variability and uncertainty of the rock mass properties. Probabilistic analysis with the calculation of probability of failure instead of the factor of safety against failure is emerging in practice. Such analyses offer a more rational approach to quantify risk by incorporating uncertainty in the input variables and evaluating the probability of the failure of a system. In rock slope engineering, uncertainty and variability involve a large scatter of geo-structural data and varied geomechanical test results. There has been extensive reliability analysis of rock slope stability in the literature, and different methods of reliability are being employed for assessment of the probability of failure and the reliability of a slope. Probabilistic approaches include Monte Carlo simulation (MCS), the point estimate method (PEM), the response surface method (RSM), first- and second-order reliability methods (FORMs and SORMs), and the first-order second-moment method (FOSM). Although these methods may be complicated, they provide a more complete definition of risk. Probabilistic slope stability analysis is an option in most commercial software; however, the use of this method is not common in practice. This paper provides an overview of the literature on some of the main probabilistic reliability-based methods available for the design of the rock slope in open pit mining. To demonstrate its applicability, the paper investigates the stability of a rock slope in an open pit mine in the Goldfields region, Western Australia. Two different approaches were adopted: deterministic stability analysis using two-dimensional limit equilibrium and finite element shear strength reduction methods using SLIDE and RS2 software, respectively, and probabilistic analysis by applying the MCS and RSM methods in the limit equilibrium method. In this example, the slope stability analysis was performed using the Spencer method with Cuckoo search optimization to locate the critical slip surface. The results obtained were compared and commented on.

Quantitative descriptions of geochemical patterns and providing geochemical anomaly map are important in applied geochemistry. Several statistical methodologies are presented in order to identify and separate geochemical anomalies. The U-statistic method is one of the most important structural methods and is a kind of weighted mean that surrounding points of samples are considered in U value determination. However, it is able to separate the different anomalies based on only one variable. The main aim of the presented study is development of this method in a multivariate mode. For this purpose, U-statistic method should be combined with a multivariate method which devotes a new value to each sample based on several variables. Therefore, at the first step, the optimum p is calculated in p-norm distance and then U-statistic method is applied on p-norm distance values of the samples because p-norm distance is calculated based on several variables. This method is a combination of efficient U-statistic method and p-norm distance and is used for the first time in this research. Results show that p-norm distance of p=2 (Euclidean distance) in the case of a fact that Au and As can be considered optimized p-norm distance with the lowest error. The samples indicated by the combination of these methods as anomalous are more regular, less dispersed and more accurate than using just the U-statistic or other nonstructural methods such as Mahalanobis distance. Also it was observed that the combination results are closely associated with the defined Au ore indication within the studied area. Finally, univariate and bivariate geochemical anomaly maps are provided for Au and As, which have been respectively prepared using U-statistic and its combination with Euclidean distance method.

Energy principles, which can favorably explain the complete rock failure process, are one of the most reliable analysis approaches in rock mechanics and engineering. In this study, a strain energy approach under true triaxial compression (TTC) is proposed. On this basis, the energy evolution characteristics and variations of different failure behavior types (Class I, Class II and ductile failure) under TTC are analyzed. The variations of the strain energy characteristics of Beishan granite with σ2 and σ3 under TTC are studied. The results indicate that the total strain energy U and the elastic strain energy \\[U^e\\] of Beishan granite increase with the increasing σ2 or σ3. The dissipated strain energy \\[U^d\\] rapidly increases when the value of ε1/ε1peak is approximately 0.6–0.8. The influence of σ3 on the rock failure mode and energy evolution characteristics is greater than that of σ2. In highly brittle rocks, the tensile cracking of the rock microstructure is dominant, and the rock has a high strain energy storage capacity and a low strain energy dissipation capacity. The cumulative acoustic emission (AE) count rate curve shows the same trend as the total dissipated strain energy \\[U^d\\] curve. The research results show that the proposed strain energy analysis method for TTC can explain the macroscopic failure behaviors, microscopic failure mechanism and AE characteristics of Beishan granite under TTC, thereby providing new ideas and methods for investigating the behaviors of deep underground hard rock.

Understanding the variation patterns of tunnel boring machine (TBM) operational parameters is crucial for assessing engineering geological conditions and quality grades of surrounding rock within tunnels. Studying the multifractal characteristics of the TBM operational parameters can help identify the patterns, but the relevant research has not yet been explored. This paper proposed a novel classification model for quality grades of surrounding rock in TBM tunnels based on multifractal analysis theory. Initially, the statistical characteristics of eight TBM cycle data with different grades of surrounding rock were explored. Subsequently, the method of calculating and analyzing the multifractal characteristic parameters of the TBM operational data was deduced and summarized. The research results showed that the TBM operational parameters of cutterhead torque, total thrust, advance rate, and cutterhead rotation speed have significant multifractal characteristics. Its multifractal dimension, midpoint slope of the generalized fractal spectrum, and singularity strength range can be used to evaluate the surrounding rock grades of the tunnel. Finally, a novel classification model for the tunnel surrounding rocks based on the multifractal characteristic parameters was proposed using the multiple linear regression method, and the model was verified through four TBM cycle data containing different surrounding rock grades. The results showed that the proposed multifractal-based classification model for tunnel surrounding rocks has high accuracy and applicability. This study not only achieves multifractal feature representation and surrounding rock classification for TBM operational parameters but also holds the potential for adaptive adjustment of TBM operational parameters and automated tunneling applications.

Pillars play a critical role in an underground mine, as an inadequate pillar design could lead to pillar failure, which may result in catastrophic damage, while an over-designed pillar would lead to ore loss, causing economic loss. Pillar design is dictated by the inclination of the ore body. Depending on the orientation of the pillars, loading can be axial (compression) in horizontal pillars and oblique (compression as well as shear loading) in inclined pillars. Empirical and numerical approaches are the two most commonly used methods for pillar design. Current empirical approaches are mostly based on horizontal pillars, and the inclination of the pillars in the dataset is not taken into consideration. Laboratory and numerical studies were conducted with different width-to-height ratios and at different inclinations to understand the reduction in strength due to inclined loading and to observe the failure mechanisms. The specimens’ strength reduced consistently over all the width-to-height ratios at a given inclination. The strength reduction factors for gypsum were found to be 0.78 and 0.56, and for sandstone were 0.71 and 0.43 at 10° and 20° inclinations, respectively. The strength reduction factors from numerical models were found to be 0.94 for 10° inclination, 0.87 for 20° inclination, 0.78 for 30° inclination, and 0.67 for 40° inclination, and a fitting equation was proposed for the strength reduction factor with respect to inclination. The achieved results could be used at preliminary design stages and can be verified during real mining practice.

The degree of rock mass discontinuity is crucial for evaluating surrounding rock quality, yet its accurate and rapid measurement at construction sites remains challenging. This study utilizes fractal dimension to characterize the geometric characteristics of rock mass discontinuity and develops a data-driven surrounding rock classification (SRC) model integrating machine learning algorithms. Initially, the box-counting method was introduced to calculate the fractal dimension of discontinuity from the excavation face image. Subsequently, crucial parameters affecting surrounding rock quality were analyzed and selected, including rock strength, the fractal dimension of discontinuity, the discontinuity condition, the in-situ stress condition, the groundwater condition, and excavation orientation. This study compiled a database containing 246 railway and highway tunnel cases based on these parameters. Then, four SRC models were constructed, integrating Bayesian optimization (BO) with support vector machine (SVM), random forest (RF), adaptive boosting (AdaBoost), and gradient boosting decision tree (GBDT) algorithms. Evaluation indicators, including 5-fold cross-validation, precision, recall, F1-score, micro-F1-score, macro-F1-score, accuracy, and the receiver operating characteristic curve, demonstrated the GBDT-BO model’s superior robustness in learning and generalization compared to other models. Furthermore, four additional excavation face cases validated the intelligent SRC approach’s practicality. Finally, the synthetic minority over-sampling technique was employed to balance the training set. Subsequent retraining and evaluation confirmed that the imbalanced dataset does not adversely affect SRC model performance. The proposed GBDT-BO model shows promise for predicting surrounding rock quality and guiding dynamic tunnel excavation and support.

As mining depth extends continuously, complex geological environment and strong mining stress pose serious challenges against excavation safety and higher demand for bolt support. To meet the challenges, a new type of flexible bolt is developed that is free from the limitation of excavation height and can be installed quickly. The flexible bolts have a tail structure which is squeezed together by the locking casing and the steel-strand rod. The tail structure forms the thread through the rolling process, and then can be quickly installed by the nut rotation type, which avoids the disadvantages of the cable tension installation. Through the flexible long bolts, the thick anchoring layer of the roof can be constructed, and the safety control of the roadway is realized. To obtain the optimal specifications, locking casings of three diameters and lengths were used to prepare bolt samples for static tensile test. Test results show that when the diameter of locking casing is fixed, the peak resistance increases as the length of locking casing increases, but the increased amplitude tends to reduce gradually. When the length of locking casing is fixed, too large a diameter makes the mechanical property unstable. Finally, the optimal length and diameter of locking casing are set at 120 and 30 mm, respectively. In addition, cyclic loading tests were conducted, the results of which indicate that cyclic loading does not change the stress state within the bolts and that flexible bolts display a stable mechanical property. Field results indicate that flexible bolts achieve low damage of the surrounding rock and control the maximum roof fracture depth within 2.1 m, thus guaranteeing the roadway safety.

Pillar stability is an important factor for safe working and from an economic standpoint in underground mines. This paper discusses the effect of blast damage on the strength of hard rock pillars using numerical models through a parametric study. The results indicate that blast damage has a significant impact on the strength of pillars with larger width-to-height (W/H) ratios. The blast damage causes softening of the rock at the pillar boundaries leading to the yielding of the pillars in brittle fashion beyond the blast damage zones. The models show that the decrease in pillar strength as a consequence of blasting is inversely correlated with increasing pillar height at a constant W/H ratio. Inclined pillars are less susceptible to blast damage, and the damage on the inclined sides has a greater impact on pillar strength than on the normal sides. A methodology to analyze the blast damage on hard rock pillars using FLAC3D is presented herein.

The design of landfill liners of waste disposal to reduce migration of leachate containment, low swelling, and shrinkage and ensure sufficient shear strength to resist bearing capacity and instability of the landfill has been a major challenging task to landfill engineers. Over the last decade, there has been an increase in research on the stability of substitute materials as liners that are environmentally friendly, cost-effective, and socially beneficial due to the growing cost of traditional landfill liners. In this regard, geotechnical tests were conducted on shale samples treated with 0–12% (increment of 2%) of palm kernel shell ash (PKSA) and pulverized palm kernel shell (PPKS) to evaluate their suitability as alternative landfill liners using West African Standard (WAS) and Modified AASHTO Standard (MAS) for compactive energy. The shale has more percentage of finer fractions, thus classified as poorly graded soil (A-7-5). The Atterberg limit tests show that liquid and plastic limits decrease with an increase in plasticity index as the percentage of addition of PKSA and PPKS content increases. The results also established that the maximum dry density (MDD), volumetric shrinkage strain (VSS), and hydraulic conductivity significantly decrease, while the optimum moisture content (OMC) increases as the content of PKSA and PPKS increases at both compactive efforts. The maximum strengths of 380.30 and 448.70 kPa were obtained at 4% of both stabilizers. From the results, it can therefore be concluded that the treated compacted shale meets the condition of the suitability of landfill liners. Furthermore, with the use of industrial and agricultural wastes such as palm kernel shells as replacement materials with natural soils used as liners, significant social, economic, and environmental impact of landfills and reduction in wastes can be achieved. The research results can provide a reference for similar conditions of landfill liners worldwide.

The Higashi-Shikagoe limestone quarry is an open-pit mine situated in Hokkaido Prefecture, Japan, that has experienced four slope failure incidents since 1996. The rock slope behaviour has been monitored since the first failure event by measuring the rock slope surface displacement using an automated polar system. Recent measurements have revealed a gradual decrease of the distance between the beam generator and mirrors over time; however, the displacements and decrease rate differs between the centre and left- and right-hand sides of the quarry. This implies that the deformation characteristics of the rock slope and factors influencing the slope deformation differ at the centre and left- and right-hand sides of the quarry. In this study, the two-dimensional finite element method was used to identify the causes of slope deformation by investigating the effects of limestone excavation at the foot of the rock slope, the deterioration of a ∼70 m-thick clay layer at the rock slope foot wall, and shear failure owing to rainfall infiltration. The numerical results show that slope deformation on the left-hand side and centre of the quarry are induced by clay deterioration, whereas the right-hand side of the quarry is deformed owing to floor excavation and/or shear sliding. The rock slope is presently stable because the magnitude of the rate of displacement decrease is small and no acceleration is observed.