Stope Stability Research Articles

Study on Crushed-Stone Cementation Properties and Bottom Stope Stability of Goaf by Open Stope Mining in Inclined Ore Bodies

The mining of the part of the inclined ore body below a goaf is crucial for improving resource extraction and safe production. In this study, the cementation properties of crushed stone during the mining of the inclined ore body were investigated by means of laboratory experiments, theoretical analysis, and numerical simulation. Additionally, orthogonal experiments were performed to assess how factors like water–cement ratio, crushed-stone particle size, and cement–sand ratio affect the strength of the grouting concretion body (GCB). Furthermore, the fluidity of the slurry under different ratios was also measured. Considering both the fluidity of the slurry and the strength of the GCB, the optimal ratios of the slurry were determined to be a water–cement ratio of 2.5:1 and a cement–sand ratio of 1:4. This ratio was then used for crushed-stone cementing under the poorest crushed-stone particle size conditions, based on which mechanical parameters were obtained from experiments. Theoretical analysis equated the problem of the grouting range to the width of the plastic zone of surrounding rock, and a conclusion was reached that the width of the GCB should be at least 29 m. The numerical simulation results reveal that among 30 mining rooms formed below the GCB, 24 mining rooms are in a stable state and 6 mining rooms are partially damaged on a small scale. As a whole, the GCB formed by grout filling into the goaf manages to effectively support the stope below, and it is verified that the theoretical calculation method of the width of the GCB is feasible.

Exploring Machine Learning Techniques for Open Stope Stability Prediction: A Comparative Study and Feature Importance Analysis

The stability of underground excavations is essential for ensuring the safety of mining operations. Classical stability assessment methods, established in empirical formulas and rock mass classification systems, have long been employed for evaluating stope stability in underground mining. Stability graphs, a popular empirical approach, utilize factors like rock stress, joint orientation, and surface orientation to calculate stability numbers critical for stope design. However, modern advancements in machine learning present new opportunities for enhancing predictive capabilities and understanding complex relationships influencing stope stability. Building upon research demonstrating the feasibility of using machine learning for stability prediction, our study investigates and compares several machine learning algorithms. By analyzing a dataset comprising stope dimensions and geomechanical properties, we explore the potential of machine learning models such as Random Forest, Support Vector Machine, AdaBoost, XGBoost, LightGBM, and Artificial Neural Network in predicting stope stability. Evaluation metrics including accuracy, precision, recall, and F1 score are employed to assess model performance, with the Artificial Neural Network emerging as the most effective. Furthermore, SHapley Additive exPlanations (SHAP) analysis enhances interpretability by explaining the contribution of individual features to model predictions.

Refined Approaches for Open Stope Stability Analysis in Mining Environments: Hybrid SVM Model with Multi-optimization Strategies and GP Technique

Refined Approaches for Open Stope Stability Analysis in Mining Environments: Hybrid SVM Model with Multi-optimization Strategies and GP Technique

A New CRITIC-GRA Model for Stope Dimension Optimization Considering Open Stoping Stability, Mining Capacity and Costs

In the long-hole stage open stoping with subsequent backfill mining of underground metal mines, the selection or optimization of stope dimension parameters is significant for safe and economic mining operations. To analyze the optimal stope sizes, the Mathews empirical graph method and FLAC3D numerical method can be used, but the analyzed safety results of the two methods are generally independent from each other. More importantly, economic indicators including production capacity and mining costs should be considered simultaneously to optimize the stope dimension which was mostly ignored in previous reports. In this paper, a new CRITIC-GRA model was proposed for the first time to build up a multi-factor quantitative optimization for stope dimension, which allows for a comprehensive analysis with preset influential safety and economic indicators. The indicators considered include the safety indicators such as stability probability for the side walls and roof of the open stope via the updated Mathews graph method, maximum displacement, plastic zones volume and maximum principal stress via FLAC3D simulations, as well as economic indicators such as mining costs and stope production capacity in mine operations. The model was then illustrated in an underground iron mine. With the given rockmass quality in the mine, the overall stability of the open stope can be improved instead of reduced to enlarge the single stage stope height (60 m) to a double stage height (120 m) by reducing the stope width from 20 m to 15 m, thereby significantly increasing the mineable ore amount and improving the stope safety. An integrated evaluation of open stope stability, mining capacity and costs objectively determined that scheme No. 10, with a slope length of 50 m, a width of 15 m and a height of 120 m, was the optimum out of the 20 preset schemes. The new CRITIC-GRA model offers a dependable reference tool for determining the optimal stope dimensions in similar underground mines.

Enhancing open stope stability prediction in mining engineering: Optimal configuration of an artificial neural network model

Ensuring the stability of underground excavations is a crucial concern in mining engineering, directly impacting operational safety and efficiency. Given the dynamic nature of the subsurface environment, innovative methods are essential to enhance stability in open stopes and mitigate potential risks. This study focuses on refining predictions of underground excavation stability in mining engineering through the optimization of an artificial neural network (ANN) model. Analyzing Potvin’s database, which includes 175 historical cases, we examined the impact of various ANN model configurations. Our findings indicate that normalizing data using Standard Scaler and employing Swish as the activation function across all layers yielded the most accurate predictions for this specific scenario. Additionally, employing the SHAP (Shapley Additive exPlanations) tool enabled us to assess feature importance and identify the most influential factors. Our results underscore the significant impact of the shape factor on underground opening stability, closely followed by the Q value. This research contributes to enhancing predictive models for underground mining excavation stability, emphasizing the critical role of specific parameters affecting open stope stability.

The Impact of Temperature on the Triaxial Compression Characteristics of Cemented Paste Backfill

In deep well mining, due to the influence of the surrounding environmental temperature, the mechanical properties of the cemented paste backfill (CPB) will change. Therefore, studying the effect of temperature on the mechanical characteristics of CPB is of great research significance for the safety and stability of the mining stope. This article conducted triaxial compression tests on CPB at different temperatures, studied the effect of temperature on the shear strength characteristics of CPB specimens, and investigated the failure mechanisms and characteristics of CPB. The results show that: (1) The cohesion and internal friction angle of CPB specimens increase with increasing temperature. (2) As the temperature increases, the failure mode of CPB specimens changes from single oblique section shear failure to Y-type failure.

Iron ore grade's impact on uniaxial compression behavior and acoustic emission characteristics

The mechanical properties of iron ore are influenced by various factors, including its grade, which consequently impacts stope stability and equipment efficiency in the mining process. In order to explore the influence and mechanism of grade on these properties, handheld XRF testing was conducted to determine the grade of iron ore samples ranging from 28% to 40%. Subsequently, the acoustic emission method was employed to acquire signals during the uniaxial compression tests. Additionally, scanning electron microscopy was utilized to examine the fracture surface, for performing a microscopic analysis of the influence mechanism of grade on the mechanical properties of iron ore. The results revealed that lower-grade iron ore exhibited larger transverse deformation, with a corresponding dominance of tensile failure. This observation aligned with the AF-RA value (Parameters of reaction crack type), which depicted a shift in the types of microcracks generated during the compression process from tensile cracks to shear cracks with the increasing grade. The content of gangue minerals diminishing as the grade increased. Consequently, the location of the cracks transitioned from the primary failure Through the gangue minerals to the primary microcracks in metallic minerals, resulting in a higher occurrence of acoustic emission events during the early loading stage and the development speed of microcracks accelerates during the loading process. The dominant frequency (Parameters of reaction crack size) of the acoustic emission signal increased from 150 kHz at a grade of 28% to 264 kHz at a grade of 40%, accompanied by a linear decrease in the proportion of low-frequency signals. The b value (indicator for quantifying the degree of damage) demonstrates a decrease with increasing grade. Overall, the content of metal minerals in the iron ore increased with the grade, resulting in polymerization. However, the influence of crack propagation on the overall strength of iron ore remained relatively minor. Macroscopically, the uniaxial compressive strength increased almost linearly with the iron ore grade.

Dynamic multifractal characteristics of acoustic emission about composite samples with different stress loading and unloading conditions

Studying the failure characteristics of the common composite strata structure in western China is essential for evaluating stope stability and predicting coal mine dynamic disasters. To investigate the influence of different stress loading and unloading conditions on the instability characteristics of composite samples, three triaxial loading and unloading test schemes simulating different in-situ mining depths were designed. Complex triaxial tests were conducted on 12 sets of composite samples, and the bearing capacity, acoustic emission (AE) parameters and dynamic multifractal characteristics of the samples under different stress loading or unloading conditions were analyzed. The results indicate that samples tested by stress schemes simulating greater mining depths exhibit less damage, and the failure mode is a tensile-shear mixed failure, but the tensile failure is the main failure mode. The multifractal spectral parameters Δα\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Delta \\alpha$$\\end{document} of AE time series during the failure of composite samples tested with triaxial loading and unloading schemes simulating different mining depths show a decreasing trend in Δα\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Delta \\alpha$$\\end{document} values with increasing mining depth, while the change rules of Δfα\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Delta f\\left( \\alpha \\right)$$\\end{document} values are the opposite. The multifractal parameter changes degree in four-layer rock structure composite samples under different stress conditions are lower than those in three-layer rock structure composite samples, indicating that the microcrack propagation process in the three-layer composite sample is more complex, resulting in higher levels of damage. The dynamic change of multifractal parameters Δα\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Delta \\alpha$$\\end{document} and Δfα\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\Delta f\\left( \\alpha \\right)$$\\end{document} during different stress loading and unloading stages reflects the influence of axial pressure or confining pressure changes on crack propagation in composite samples. Compared to the initial stress stage, the non-uniformity of AE signals increases in the residual stress stage, and the proportion of large signals becomes more prominent, signifying a complex micro-fracture process in the composite samples.

Application of supervised random forest paradigms based on optimization and post-hoc explanation in underground stope stability prediction

This study applies a supervised random forest (SRF) paradigm to predict the underground stope stability. To improve the model prediction accuracy, 400 actual stopes with three main features (the optimized stability number (N), the hydraulic radius (HR), and a rock mass quality factor (Q)) are used to train the model, and nine meta-heuristic (MH) optimization algorithms are utilized to select the optimal hyperparameters of the SRF model. The prediction results show that the tiki taka algorithm-based SRF (TTA-SRF) model obtains the most satisfactory classification performance, with the smallest variance in the overfitting evaluation (Precision of 0.0201, Recall of 0.0257, Specificity of 0.0061, Accuracy of 0.0125, and F1-measure of 0.0246). Furthermore, four post-hoc explainable techniques (i.e., model-independent) including the feature importance (FI), the Shapley additive explanations (SHAP), the partial dependence plot (PDP), and the individual conditional expectation (ICE) are adopted to explain the best prediction model. The results of the model interpretation show that all features are essential for predicting the stope stability and they have an opposite tendency on the stability prediction of stable and caved stopes. In particular, the limits at which HR, Q, and N do not contribute to the stope stability prediction are 18 m, 40, and 100, respectively. The results of optimization designs for a specific case stope based on the visualization program showed that the suggestions given by the prediction model are desirable. In conclusion, a high-performance and strongly explanatory prediction model is proposed in this study to facilitate the refinement of stope stability assessment in underground space.

Analysis of influence of filling body with different filling intervals on stope stability.

The stratified backfill will lead to the reduction of the strength of the filling body, thus increasing the safety risks of the stope. By means of experimental research and numerical simulation, the stability of stope is studied. Based on the physical parameters of filling body measured by triaxial compression test, the stability of filling stope is numerically simulated by FLAC 3D software. By comparing the stress distribution and displacement of stope with filling body at different intervals, the filling process parameters of Bianjiadayuan lead-zn-silver mine can be optimized.The experimental results show that: When the filling interval is 12h, the roof stress, filling body pressure stress and roof displacement are small, and the stope stability is better. When it exceeds 12h, the change is large and the stope stability is poor. The interval time in the stratified backfill process of Bianjiadayuan lead-zinc-silver mine should not exceed 12h.The research results have significant reference value for improving the stope stability and selecting a reasonable interval time for stratified backfill.

Macro-meso fatigue fracture and instability of rock-backfill composite structure under increasing-amplitude cyclic loading

The rock-backfill composite structure (RBCS) material in mine stopes is often subjected to stress disturbance. In order to reveal the fracture and instability mechanism of the RBCS exposed to disturbed stresses, a series of multi-stage cyclic loading tests were conducted on RBCS specimens with various cement-tailing ratios (c/t). The results indicate that deformation characteristics, stiffness degradation, damage propagation and failure mode of the RBCS were greatly influenced by the c/t. The volume dilatancy increases as well as the secant modulus (Es) increases and then decreases with decreasing c/t, i.e., from 1:4 to 1:12. For a sample with c/t of 1:4 and 1:8, the damage displays two-phase increasing pattern. However, for a sample with c/t of 1:10 and 1:12, inverted S-shaped damage accumulation pattern is found. As the c/t decreased, failure mode of RBCS specimens transformed from mixed tensile-shear failure to dominant tensile failure. Post-test CT imaging reveals obvious fracture evolution pattern that was characterized by shear fracture within the backfill, a circular tensile fracture along the rock-backfill interface, and tensile-shear fracture within the surrounding rock. It is noteworthy that complicated crack network is prone to forming for RBCS specimens with the c/t of 1:4 and 1:8. It is found that the use of "flexible CTB" with relatively low c/t is beneficial to improve the overall stability of the mine stopes.

Numerical modeling of the underground mining stope stability considering time-dependent deformations via finite element method

Numerical modeling of the underground mining stope stability considering time-dependent deformations via finite element method

Analyzing the Energy and Damage Constitutive of Cemented Backfill with Different Water Content under Dynamic Load.

The dynamic characteristics of the filling body are the key parameters for designing the filling ratio and evaluating the stability of an underground stope. The different environment (water-bearing state) of the filling body in the underground stope exerts a complex impact on the mechanical behavior of the filling body. Therefore, six groups of cemented filling body specimens with different states were formed and subjected to dynamic uniaxial impact tests. The effects of water content on the mechanical properties, fractal dimension, and deformation damage characteristics of the cemented backfill under dynamic load were analyzed in depth, and a dynamic damage constitutive model that considers water damage and the compaction stage was established. The results indicate the following: (1) Due to the change of the specimen from the dry state to the water saturation state, the dynamic compressive strength of the cemented filling body decreases from 5.03 Mpa to 1.79 Mpa; however, the ductility of the specimen generally increases, and the filling body specimens with different water contents mainly exhibit tensile failure. (2) There is a significant nonlinear relationship between the water content and the fractal dimension Db of the cemented backfill specimen, and the growth rate of the fractal dimension Db tends to slow down with the increase in the water content. (3) From the energy evolution perspective, the water content of the specimen exerts a significant effect on the elastic deformation and failure stage of the stress-strain curve, and the slope of the dissipated energy-strain curve decreases with the increase in water content. (4) Based on the Weibull distribution and damage theory, a statistical damage constitutive model of cemented backfill was established, and it was compared with the experimental curve to verify the rationality of the model. Therefore, the relationship between stress and damage and the strain curves is discussed, and it is inferred that the damage evolution curve of cemented backfill is a typical S-shaped curve that exhibits a stable development-rapid increase-tending to be gentle. This study can provide a theoretical reference for further understanding the dynamic behavior and stability of backfill under different water conditions.

Stability analysis of crown pillar under the zone of relaxation around sub-level open stopes using numerical modelling

The stability of stopes and pillars is a critical concern in deep underground metal mining due to the potential for stress concentration and relaxation that can cause the dynamic failure of pillars. This study employs a finite element approach to investigate the behaviour of crown pillars to various stress and geo-mining parameters. The analysis includes examining stresses, deformations, and yielding zones around the crown pillars using variations in rock mass parameters. The study involves 240 non-linear numerical models with the Mohr–Coulomb elastoplastic failure criteria under plane strain conditions. The results indicate that increasing the crown pillar thickness from 5 to 8 m reduces maximum vertical deformation by 55.8% and the maximum extent of yielding zones from 2.2 to 0 m. The study suggests a 6 m crown pillar for depths up to 670.56 m and thicker pillars of 7 m or more for greater depths.

A 2D roughness method for irregular interface of rock-backfill

A simple and reasonable roughness method for irregular interface of rock-backfill is significant for estimating the long-term stability of mine stopes in underground engineering. In this paper, two new concepts, contribution height difference (CHD) and average contribution height difference (ACHD), were presented through analyzing the influences of whole movement process of asperity and properties of contact material on the shear strength properties of interface. Occupying the presented concepts and combining with the fractal theory, a 2D roughness method for irregular interface of rock-backfill was created, which depends on fractal dimension Dp and direction-correlated parameter ACHD0. The roughness index Iif was introduced to quantitatively characterize the roughness of irregular interface. The results of scanning experiment and shear strength experiment about granite and cement backfill were used to verify the proposed 2D roughness method. The application analysis shows that the proposed roughness method has very outstanding advantage for irregular interface of rock-backfill, which provides the evolution of roughness method by involving the directionality of roughness and resolving the effect of sampling interval. The roughness index Iif can predict the shear strength of interface between rock and backfill. The parameters described in this work are easy to measure in field and also they are very convenient in usage.

Safety analysis of Sormeh underground mine to improve sublevel stoping stability

AbstractIn underground mines, sublevel stoping is used among a variety of different methods for mining an orebody, which creates large underground openings. In this case, the stability of these openings is affected by a number of factors, including the geometrical characteristics of the rock and mining‐induced stresses. In this study, a sensitivity analysis was conducted with the numerical, squat pillar, and Mathews stability methods using the Taguchi technique to properly understand the influence of geometric parameters and stress on stope stability according to Sormeh underground mine data. The results show a full factorial analysis is more reliable since stope stability is a complex process. Furthermore, the numerical results indicate that overburden stress has the most impact on stope stability, followed by stope height. However, the results obtained with Mathews and squat pillar methods show that stope height has the greatest impact, followed by overburden stress and span. It appears that these methods overestimate the impact of stope height. Therefore, it is highly recommended that Mathews and squat pillar methods should not be used in high stope that is divided with several sill pillars. Nonetheless, Mathews method cannot accurately predict how the sill pillar impacts the stope stability. In addition, numerical analysis shows that all geometric parameters affect the roof safety factor, whereas the sill pillar has no significant influence on the safety factor of the hanging wall, which is primarily determined by the stope height–span ratio.

Comprehensive evaluation method of stope stability and its application in deep metal mine.

The problem of high stress conditions is a critical challenge for mining activity in deep metal mines, and the difficulty and economic cost of maintaining stope stability also increases. In order to ensure stope stability in the mining process, it is necessary to evaluate stope stability for a more stable stope structure. However, there are many kinds of methods for rock stability assessment, and most of them are based on empirical and analytical methods, which lead to uncertain results. In this paper, a comprehensive evaluation method including factors of stope stability, self-stabilization time, maximum safety span, and support measure is determined, which is more likely to provide a comprehensive result. Finally, it was verified by the field application in Jiaojia Gold Mine. Results show that it can accurately evaluate the stope stability from different aspects compared with the traditional single evaluation method, and it leads to a more comprehensive and reliable result.

Predicting the stability of open stopes using Machine Learning

The Mathews stability graph method was presented for the first time in 1980. This method was developed to assess the stability of open stopes in different underground conditions, and it has an impact on evaluating the safety of underground excavations. With the development of technology and growing experience in applying computer sciences in various research disciplines, mining engineering could significantly benefit by using Machine Learning. Applying those ML algorithms to predict the stability of open stopes in underground excavations is a new approach that could replace the original graph method and should be investigated. In this research, a Potvin database that consisted of 176 historical case studies was passed to the two most popular Machine Learning algorithms: Logistic Regression and Random Forest, to compare their predicting capabilities. The results obtained showed that those algorithms can indicate the stability of underground openings, especially Random Forest, which, in examined data, performed slightly better than Logistic Regression.

Quantifying the Influence of Variations in Rock Mass Properties on Stope Stability

Variations in rock mass properties are well-established in rock mechanics and underground mining. The literature is replete with methods of assessing them and determining values that are used in design or numerical analysis. In this paper, a simplified 3D model is constructed for a tabular orebody in the Canadian Shield and instability is quantified using the ”brittle shear ratio” criterion to calculate the volume at risk. A 1-4-7 stope pillar sequence is implemented on four active levels, and three variations in the properties of the host formation are assessed. It is observed that the locations of ore at risk follow the formations of stope pillars and are then transferred to the sill pillars above and below. Instability in the footwall and the hanging wall is observed to be lesser in volume but remains persistent. With the allocation of weak properties to the host rock, at-risk volumes increase in the orebody, footwall, and hanging wall, and the reverse trend occurs with strong greenstone properties. It is concluded that the stress increase in the orebody is due to transfers from the weaker host rock, while that in the greenstone formation is due to the use of a lower compressive strength value.

Design and Stope Stability Analysis of Multiple Concurrent Excavated Veins in Underground Mine; Case Study of Hermyingyi Tin-Tungsten (W-Sn) Mine

Design and Stope Stability Analysis of Multiple Concurrent Excavated Veins in Underground Mine; Case Study of Hermyingyi Tin-Tungsten (W-Sn) Mine