Search Results (19)

The spatial variability in rock mass mechanical parameters critically affects slope stability assessments. This study investigated the southern slope of the Bayan Obo open-pit mine. A representative elementary volume (REV) with a side length of 14 m was determined through discrete fracture network (DFN) simulations. Based on the rock quality designation (RQD) data from 40 boreholes, a three-dimensional spatial distribution model of the RQD was constructed using Ordinary Kriging interpolation. The RQD values were converted into geological strength index (GSI) values through an empirical correlation, and the generalized Hoek–Brown criterion was applied to develop a spatially heterogeneous equivalent mechanical parameter field. Numerical simulations were performed using FLAC3D, with the slope stability evaluated using the point safety factor (PSF) method. For comparison, three homogeneous benchmark models based on the 5th, 25th, and 50th percentiles produced profile-scale safety factors of 0.96–1.92 and failed to replicate the observed failure geometry. By contrast, the heterogeneous model yielded safety factors of approximately 1.03–1.08 and accurately reproduced the mapped sliding surface. These findings demonstrate that incorporating spatial heterogeneity significantly improves the accuracy of slope stability assessments, providing a robust theoretical basis for targeted monitoring and reinforcement design. Full article

The geometry of rock mass fractures is typically characterized through geological and geotechnical investigations. Detailed descriptions of granitic host rock can yield valuable data for constructing fracture network models. However, significant discrepancies often arise between data representing the mechanical and hydraulic properties of rocks. At the study site, fracture geometry data were gathered through surface and underground surveying, borehole logging, and underground mapping. Three-dimensional photogrammetry was utilized alongside traditional rock mass classification methods (Q-system, RMR, GSI) to derive key parameters of fracture networks, such as orientation, size, and intensity. This study focuses on Rock Quality Designation (RQD), a measure of fracture density derived from tunnel face mapping. Findings indicate that variations in fracture frequency are significantly affected by how fracture sets are defined and by the orientation distribution of fractures. Furthermore, using the D parameter (the 2D fractal dimension of fracture frequency) as a validation measure for RQD may lead to misleading interpretations if it aggregates fracture sets on the tunnel scale. Full article

This article presents a comparative analysis of rock mass fracturing at the Karasu gold deposit, located approximately 400 km northwest of Karaganda, Kazakhstan. The analysis is based on core drilling data and measurements from underground workings, including an old mine that was explored and investigated to gather missing information. The spatial characteristics of fractures and their relationship with tectonic faults are identified. The feasibility of using the Rock Quality Designation (RQD) index for classifying fracture systems is assessed. Engineering and geological studies include the identification of major fracture systems and their characteristics using Leapfrog and Rocscience software, chosen for their ease of use and extensive functionality. The stability parameters of open-pit slopes are calculated, considering the physical and mechanical properties of rocks, the degree of fracturing, and the influence of groundwater. Key engineering and geological elements of the rock mass are identified, emphasizing the necessity of integrating fracture data from various sources to improve the accuracy of mine design and ensure the safe operation of open pits. These studies are part of the exploration phase to assess the geological situation and the physico-mechanical properties of these rocks for further quarry design. Full article

Metallic ore deposits are generally formed through magmatic intrusions, followed by metamorphism. The geological structures in such regions are often complex, with mechanical parameters exhibiting significant variability. These characteristics dictate the need for refined geological modeling and heterogeneous mechanical parameters for rock mass stability analysis to ensure reliability. Therefore, this paper proposes a novel method for rock mass stability analysis. The method fully leverages high-density drilling data from the mine and introduces an intelligent rock quality designation (RQD) identification technique, facilitating characterization of the spatial heterogeneity of rock mass RQD. Building on this, laboratory experiment data and in situ measurements are integrated, and the Hoek–Brown criterion is employed to achieve a refined characterization of heterogeneous rock mass mechanical parameters. This method allows for a realistic inversion of in situ rock mass mechanical conditions, overcoming the limitations inherent in assigning uniform parameters. Finally, the computed rock mass mechanical parameters are assigned to the refined computational model to conduct rock mass stability analysis. Taking the Jiangfeng Iron Mine, with its complex geological conditions, as an example, this method enables the accurate evaluation of the rock mass stability, determines the feasibility of joint mining, and calculates the appropriate thickness of the isolation pillars, effectively mitigating safety risks in mining operations. This method provides a valuable reference for the rock mass stability analysis of underground joint mining operations for similar mines. Full article

The accurate analysis of rock cores is of primary importance for designing in and on the rock mass environment. There are several methods for analyzing boreholes, but the most accepted and widely used method is the rock quality designation (RQD) value, which has been a core rating metric for six decades. The RQD value serves as: (1) an important input parameter for rock mass classifications such as RMR and Q; (2) a basis for calculating the Geological Strength Index (GSI) of boreholes; and (3) a key indicator in assessing rock mass quality, particularly in highly fractured or weak rock masses. The original RQD method has several drawbacks and shortcomings, which have led to numerous proposed amendments. This review paper aims to: (1) summarize alternative methods of calculating the RQD value; (2) analyze the sensitivity of different rock mass classifications to the accuracy of this value; and (3) present a systematic analysis of the practical implications of modified RQD methods, emphasizing advancements such as DFN modeling, seismic RQD techniques, and machine learning-based approaches. The findings provide a comprehensive framework for more robust and versatile assessments of rock mass quality. Full article

Rock quality designation (RQD) is a parameter that describes rock mass quality in terms of percentage recovery of core pieces greater than 10 cm. The RQD represents a basic element of several classification systems. This paper studies scale effects for RQD measurements using synthetic rock masses generated using discrete fracture network (DFN) models. RQD measurements are performed for rock masses with varying fracture intensities and by changing the orientation of the simulated boreholes to account for orientation bias. The objective is to demonstrate the existence of a representative elementary length (REL, 1D analogue of a 3D representative elementary volume, or REV) above which RQD measurements would represent an average indicator of rock mass quality. For the synthetic rock masses, RQD measurements were calculated using the relationship proposed by Priest and Hudson and compared to the simulated RQD measurements along the boreholes. DFN models generated for a room-and-pillar mine using mapped field data were then used as an initial validation, and the conclusion of the study was further validated using the RQD calculation results directly obtained from the depth data collected at an iron cap deposit. The relationship between rock mass scale and assumed threshold length used to calculate RQD is also studied. Full article

Accurate rock mass quality classification is crucial for the design and construction of underground projects. Traditional methods often rely on expert experience, introducing subjectivity, and struggle with complex geological conditions. Machine learning algorithms have improved this issue, but obtaining complete rock mass quality datasets is often difficult due to high cost and complex procedures. This study proposed a hybrid XGBoost model for predicting rock mass quality using incomplete datasets. The zebra optimization algorithm (ZOA) and Bayesian optimization (BO) were used to optimize the hyperparameters of the model. Data from various regions and types of underground engineering projects were utilized. Adaptive synthetic (ADASYN) oversampling addressed class imbalance. The model was evaluated using metrics including accuracy, Kappa, precision, recall, and F1-score. The ZOA-XGBoost model achieved an accuracy of 0.923 on the test set, demonstrating the best overall performance. Feature importance analysis and individual conditional expectation (ICE) plots highlighted the roles of RQD and UCS in predicting rock mass quality. The model’s robustness with incomplete data was verified by comparing its performance with other machine learning models on a dataset with missing values. The ZOA-XGBoost model outperformed other models, proving its reliability and effectiveness. This study provides an efficient and objective method for rock mass quality classification, offering significant value for engineering applications. Full article

Reliably assessing the quality and mechanical properties of rock masses is crucial in underground engineering. However, existing methods have significant limitations in terms of applicability and accuracy. Therefore, a field measurement method that meets the real-time monitoring and safety requirements for the quality of engineering rock masses is needed. Firstly, the research findings of domestic and international scholars on the application of drilling process monitoring technology are comprehensively analyzed. Rotary cutting penetration tests are conducted on tuff rock masses containing fractures and joints. Various rock mass classification and evaluation standards are integrated with rotary penetration tests. Rotary cutting penetration tests are used to determine the residual strength of rock, based on this review. The rationality of the calculated m_i parameter values is validated. The peak strength, residual strength, and errors of the rock are obtained based on the penetration method. The rock quality index rock quality designation from drilling (RQD_d) is redefined, based on the drilling process monitoring apparatus (DPMA). Rock mass classification is conducted, based on the correlation between the standard deviation of rotary drilling energy and the rock quality designation (RQD). Additionally, a new relational formula is introduced to determine the RQD from variations in drilling energy, based on discontinuity frequency. This field measurement method undoubtedly provides a crucial scientific basis for rock design and construction, ensuring long-term safety in engineering applications. Full article

At the initial phases of tunnel design, information on rock properties is often limited. In such instances, the engineering classification of the rock is recommended as a primary assessment of its geotechnical condition. This paper reviews different rock mass classification methods in the tunnel industry. First, some important considerations for the classification of rock are discussed, such as rock quality designation (RQD), uniaxial compressive strength (UCS) and groundwater condition. Traditional rock classification methods are then assessed, including the rock structure rating (RSR), rock mass rating (RMR), rock mass index (RMI), geological strength index (GSI) and tunnelling quality index (Q system). As RMR and the Q system are two commonly used methods, the relationships between them are summarized and explored. Subsequently, we introduce the detailed application of artificial intelligence (AI) method on rock classification. The advantages and limitations of traditional methods and artificial intelligence (AI) methods are indicated, and their application scopes are clarified. Finally, we provide suggestions for the selection of rock classification methods and prospect the possible future research trends. Full article

Rock Quality Designation (RQD) is among the widely used measures of the quality of rock masses and can be derived through Monte Carlo stochastic process-based fracture network simulations. However, repeated simulations can yield variable RQD results. Here, we introduce a four-step approach that incorporates class ratio analysis to estimate the representative RQD, which includes (1) extracting the mean and confidence interval of the RQD sample, in terms of the Confidence Neutrosophic Number Cubic Value (CNNCV), (2) employing class ratio analysis to determine the thresholds of the number of virtual boreholes and that of the number of models for a given size D, beyond which the CNNCV remains substantially unchanged, (3) accepting the CNNCV at the thresholds of the number of models as the representative RQD for the model of size D (RQD(D)) and (4) determining the representative RQD (rRQD), defined as the specific value which, once D exceeds, the RQD(D) does not change significantly. The introduced approach is illustrated with a case study of an open-pit slope in China, and it was tested for its performance. The RQD calculation results of the proposed method and the traditional single-model approach exhibit differences, which diminish with increasing model sizes. At the 95% confidence level, the stable size of the RQD determined by the proposed method is 13 m, compared to 25 m for the single-model approach. This method enhances the accuracy of representative elementary volume predictions by accounting for the diversity in the simulation results of RQDs for the same size. Overall, the introduced approach offers a reliable method for obtaining RQD estimates. Full article

The most common classification method of drill cores is the Rock Quality Designation (RQD) value, which indicates the percentage of rock cores longer than 10 cm in a given core section. This core logging procedure is the basic parameter in the most useful rock mass classification methods like Rock Mass Rate (RMR) and Rock Mass Quality (Q). It is also used to determine the Geological Strength Index (GSI), which has become widely used in the last 20 years. One of the basic problems of the RQD value is that it does not distinguish different rock cores longer than 10 cm (100% is obtained for one piece of 1 m length and 10 pieces of 10 cm length) and a uniform result is obtained for shorter units. In this paper, the so-called Integrated RQD (Int_RQD) factor is introduced to eliminate these problems and to provide a better description of fracture density in the core logging procedure. As it uses the original core logging procedure, historical RQD data can also be reevaluated. Considering that RQD is an input parameter for most rock engineering classifications, these systems such as GSI can be reviewed based on the new RQD definition proposed herein. Full article

In this study, the K-means algorithm based on particle swarm optimization (K-PSO) and game theory are introduced to establish the quality evaluation model of a rock mass. Five evaluation factors were considered, i.e., uniaxial saturated compressive strength of rock, discontinuity spacing, acoustic velocity, rock quality designation (RQD), and integrity coefficient. The rock mass of an elevation adit at the abutment of Maji hydropower station was taken as a case study. The subjective weight of the evaluation factor was determined by the weighted least squares method, and the objective weight of the evaluation factor was determined by the entropy method. The combined weights of each influencing factor were determined by game theory to be 0.142, 0.179, 0.035, 0.116, and 0.108. The rock mass quality evaluation in the study area was analyzed by K-PSO algorithm. The results indicate that the K-PSO clustering results are almost the same as the evaluation results of the traditional basic quality (BQ) classification method and the widely used extension evaluation method and are consistent with the preliminary judgment of the expert field. The results are consistent with the field observation law. It is considered that the K-PSO clustering theory can reflect the engineering geological characteristics of the rock mass of the hydropower project in the rock mass quality evaluation. Full article

Rock quality designation (RQD) and permeability coefficient are important reference indexes for grouting application. Based on the readily available RQD, RQD is found to have no relationship with the depth of rock stratum, and a method for calculating the mean RQD (RQD_m) of long stratum is proposed, which is applied to the calculation of RQD of grouting sections. Through Lugeon and grouting tests on the grouting sections, RQD_m of the grouting sections is found to be directly related to the average permeability coefficient, permeability, and units of grouting per amount of rock mass. It is found that RQD_m has a symmetrical relationship with permeability and grouting volume as well as a negative exponential correlation with unit grouting volume and average permeability coefficient. According to the curve of RQD varying with depth, the grouting amount at different depths can be obtained by using the fitting formula of unit grouting amount and RQD_m. Full article

The determination of rock seepage characteristics is a complex phenomenon due to the variability, discontinuities, and formation age of rocks. The available literature on rock mechanics covers empirical relationships and approaches for the estimation of seepage characteristics from the rock mass parameters. In this study, an area comprising of infrastructure such as a water reservoir, embankments, roads, etc., constructed on mix rock mass formations was selected. The field and laboratory tests’ geo-mechanical data for the study area were evaluated. The data obtained from the field geo-mechanical engineering tests like Rock Quality Designation (RQD), Rock Core Recovery, Lugeon, etc., were analyzed. The data retrieved from the geological and geotechnical laboratory tests such as petrography, uniaxial compression, Hoek shear, elastic modulus, etc., were also evaluated. Rock mass was characterized based on petrographic and RQD, and was found in the hybrid formation of igneous, metamorphic, and sedimentary deposits. Seepage analysis in the study area was also carried out based on adit and piezometric data (installed in accordance with the mining technology guidelines), using Seep W Finite Element Method (FEM). The seepage observed in adits were compared with seepage calculated from Seep W. The trend of simulated flux was also presented against K ratio. Seepage quantities for different ranges of K ratio were plotted to evaluate interdependency between seepage and K ratio. Correlations of RQD were developed with hydraulic conductivity “k” for igneous, metamorphic, and sedimentary rocks for quick assessment of seepage characteristics of rock mass by RQD. These correlations and seepage related evaluations will be beneficial for the characterization of rock mass in relation to seepage for sustainable infrastructure development. Full article

The traditional method of obtaining rock quality designation (RQD) cannot fully reflect the anisotropy of the rock mass and thus cannot accurately reflect its quality. In the method of calculating RQD based on three-dimensional network simulation of discontinuities, due to the limited number of samples and low accuracy of discontinuity data obtained by manual contact measurement, a certain deviation in the network is generated based on the data, which has an impact on the calculation result. Taking a typical slope in Dongsheng quarry in Changchun City as an example, in this study, we obtained the discontinuity data of the slope based on digital close-range photogrammetry, which greatly enlarged the sample size of discontinuity data and improved the data quality. Based on the heterogeneity of the rock mass, the optimum threshold of discontinuity spacing was determined when surveying lines were laid parallel to different coordinate axes to calculate the generalized RQD, and the influence of measuring blank areas on the slope caused by vegetation coverage or gravel accumulation was eliminated. The real generalized RQD of the rock mass after eliminating the influence of blank areas was obtained. Experiments showed that, after eliminating the influence of blank areas, the generalized RQD of the slope rock mass more truly represented the complete quality of rock mass and offers a new idea for the quality evaluation of engineering rock mass. Full article