Design Method and Application of Stope Structure Parameters in Deep Metal Mines Based on an Improved Stability Graph

This research aims to develop a methodology of selecting and validating support system designs for different purpose roadways by means of synthesizing the rock mass quality index Q and the stability categories which are in application in mines in Russia. The existing approaches to rock mass quality evaluation based on different combinations of complementary classification criteria are reviewed and generalized. It is found that the stability categories in use in Russian mines comply with the Q-index, which enables their flexible adaptation to specific features of a deposit and allows revealing of average mining conditions for different mines. The multi-factor rock mass quality rating and classification made it possible to justify mine designs per different categories. On this basis, the safe shapes and cross-section sizes are determined for the face entries for the prevalent geological conditions of ore mining under equicomponent (hydrostatic) stress state. The analysis and generalization of actual data from operating mines in the ore provinces in Yakutia, Russian Far East, Krasnoyarsk Krai and Eastern Kazakhstan allowed correlating the maximum permissible widths and cross-section shapes of roadways, as well as the roadway purpose and the rock mass quality by the Q-system by Barton. The revealed patterns of rock mass stability effect on the roadway roof span size made it possible to define rockbolting design variables for the face entries of operating mines in rock masses characterized by the widely ranging Q-index. The implementation of the integrated approach to rock mass stability estimation can improve reliability of the pre-project and project design solutions aimed to enhance safety and efficiency of roadways in different geological and geomechanical conditions of mineral mining.

There is currently a need for better understanding of backfill design requirements at depth or under highstress conditions, or in rock mass with poor quality. It is generally acknowledged that rock mass closure affects backfill performance but there is currently negligible practical guidance for a design engineer. Understanding how mining conditions induce closure onto backfill is essential, as is predicting the reaction of the backfill to passively supporting the rock mass. This paper introduces a new framework for backfill design incorporating closure conditions. Rock mass-backfill interaction is considered using parametric studies that consider the backfill’s ‘loading system’ as a combination of field stress, rock mass stiffness and the evolving geometry associated with ongoing mining. Parameterisation is used so that the extent of potential rock mass closure can be estimated for different mining conditions. Then, stiffness contrasts between backfill and the rock mass are considered. Load transfer from rock mass to backfill must be understood, neglecting initial closure occurring before the open stope is backfilled. The resulting analysis framework predicts the extent to which backfill distress may be an issue and enables assessment of the efficiency of increasing backfill strength and stiffness for a particular design scenario. A critical determination is that opportunities to engineer the backfill’s strength and stiffness to resist initial rock mass closure on the backfill when the adjacent stope is mined is limited to cases where stresses are relatively low and rock mass quality (evaluated using the geological strength index [GSI] or equivalent) is moderate to high. Conversely, in high-stress conditions the initial closure on the backfill may have negligible consequences if the rock mass quality is sufficiently high. These extremes are quantified for a particular mining method and geometry. However, the analysis approach is equally applicable to other mining methods and geometries, and the framework to tackle these different mining problems is provided.

With the development of shallow surface mineral resources in metal mines, it is gradually turning to the stage of deep mining. According to the current mining depth and the average annual depth, during the period of “14th Five‐Year Plan,” one‐third of the underground metal mines will reach or exceed the mining depth of 1,000 m, with the deepest being 2,000 m. In the stage of deep mining, mines will face the conditions of high stress, high temperature, high well depth, and strong mining disturbance, which will greatly increase the difficulty of large‐scale deep mining. Among them, the high ground stress environment is the principal problem of many technical problems in deep mining. The selection of mining method has become a prerequisite for solving the problem of efficient and safe mining of deep deposits. In this paper, the vague set theory was introduced into the selection of mining methods and a vague set model for deep unloading mining schemes was established. Taking the Jinchuan No. 2 mining area as the engineering background, four unloading schemes for deep mining were proposed, and the Vague set model was used for optimization. It is concluded that the mining approach with large‐section unloading is the optimal unloading mining plan. The application shows that it has the advantages of high unloading efficiency, large production capacity, and low loss index. It has been fully promoted in the deep mining of the mining area. It is feasible and effective to use the vague set theory in the selection of deep unloading mining schemes, which provides a proper approach in the selection of deep unloading mining schemes.

The hydro-electrical power station is planned to be built on the Jinsha River. The regional geologic structure is complex. On the basis of the geological engineering conditions and rock mass quality classification, the change of wave velocity of rock mass is used to analyze systematically the control function of corrosion of calcareous sandstone over rock mass quality. The modificatory standard of rock mass quality classification and the system of rock mass quality classification in the hydroelectric station have been carried out. The main results can be taken as the basic data and the theoretical proofs to evaluate the engineering rock mass stability.

In the field of deep mining engineering, it poses a challenge to promptly determine the mechanical properties of rocks under poor geological conditions through in-situ tests. However, the indirect determination of uniaxial compressive strength (UCS) of rocks can be achieved through the point load strength index (PLSI) test on irregular samples. In the present study, laboratory uniaxial compressive and field PLSI tests were carried out on irregular ore and rock blocks extracted through mechanical mining methods from a stope at a lead–zinc mine in Yunnan Province, China, with a depth of approximately 1000 m. The effects of mechanical excavation and drilling-blasting methods on the PLSI of rocks and ores are compared. It is found that there are significant differences in the point load strength indexes obtained by different excavation methods, and the Is(50) obtained after the mechanical excavation method approximates the actual value of ore and surrounding rocks. Two correction methods were utilized to obtain the point load strength indexes Is(50)-1 and Is(50)-2 of irregular rock samples. The correlation factors (k) linking Is(50) to UCS and Brazilian splitting strength are derived based on testing results. The findings indicate that using the conversion factor (k) recommended by ISRM to predict the UCS of rocks may significantly underestimate the actual strength of rocks in intricate mining environments. This study can serve as a benchmark for analogous deep mining projects.

Purpose. Development of an adequate model of steel arch support for underground workings of deep coal mines to assess its stress-strain state. Methodology. The study of the deformation of steel arch supports in main workings of deep coal mines, comparing them with the results of analytical studies, considering the peculiarities of the time-dependent geomechanical processes in the rock mass near the face, and development a new mechanical model of the deformation of steel arch support during its loading based on this. The research employed methods of structural mechanics, field studies, and statistical processing of field measurement results. Results. Considering the development of geomechanical processes during the advance of the face, a new two-stage deformation model of steel arch support has been proposed, which operates in the first stage under a regime of specified deformations due to the movement of the contour of the workings, and in the second stage under a regime of specified loading after the loss of stability of the rock at the bottom, which will allow for a reasoned approach to the design of support, justification of its rational form, and ensuring the stability of underground workings in deep mines and quarries. Scientific novelty. Based on the patterns of deformation of steel support in capital workings, a new two-stage deformation model of steel arch support for capital underground workings in coal mines and quarries has been proposed, which corresponds to the conditions of its operation in real conditions. By analyzing the stress-strain state of the arch support, its possible forms have been justified, which have reduced material consumption and are adapted to specific mining and geological conditions. Practical significance. The new model of deformation of steel arch support in coal mines will allow for a reduction in the consumption of steel rolled special profiles used for support production, which is scarce under conditions where the main producers of special profiles – metallurgical plants named after Illich and Azovstal, both located in temporarily occupied Mariupol – have been destroyed. This will also reduce the cost of the extracted mineral resources and increase production efficiency.

Alternate Room-Pillar Mining Method with Ascending Backfill is now used in deep mining of Sanshandao Gold Mine. In mining practice of the metal mines, the widths of the room and pillar vary from 6m to 15m. In order to improve the production capacity and solve the deep mining safety problems, a fuzzy optimization model containing 11 evaluation indexes was built to choose the optimal structural parameters among 8m×8m, 8m×10m, 10m×10m, 10m×12m and 12m×12m. The fuzzy comprehensive evaluation results prove that the optimal stope structural parameter is 10m×10m for safety and high efficiency mine operation.

Analysis of microseismic activity in rock mass controlled by fault in deep metal mine

With the coal mines in western China entering the field of deep mining, the problem of coal burst is becoming more and more serious. According to the characteristics of deep mining, it is an urgent problem that requires the development of an efficient and reasonable coal burst prevention and control plan to guide project practices. This study takes the typical deep mining area in Ordos as the research background, according to the stress state of the coal mining area and the load form of induced coal burst, which, in Ordos deep mining, is divided into the typical and atypical type. The former is caused by the superposition of high in situ stress and strong mining-induced stress, while the latter is due to the combination of high in situ stress, strong mining-induced stress, and external stress disturbances. Combined with theoretical analysis, numerical simulation, and field measurement, it is shown that the stress level of the Ordos deep mining area is higher than that of the shallow original rock, and the difference of the three-dimensional stress between coal and rock mass is greater. The concentration degree and influence range of mining-induced stress obviously increase. Coal and rock mass are more prone to instability and failure due to external disturbances. Based on the stress control theory, the prevention and control strategies of coal burst in different types of deep mining are put forward. In addition, the prevention and control technology system of coal burst in the Ordos deep mining area is established. The field engineering practice has been carried out to realize the efficient prevention and control of coal burst.

Comprehensive heat extraction performance and fractured reservoir cooling effect analysis of a novel mine enhanced geothermal system

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.

During the construction of tunnel, the observational classification of rock mass quality is the most direct method to evaluate the quality of the tunnel face surrounding rock. It is also an important basis for preventing geological disasters in tunnel construction, deciding construction excavation method and supporting measures. The traditional Q method and BQ method of national standard rock mass quality grading evaluation method require on-site and indoor laboratory tests and analysis, which results in the lag time of rock mass quality evaluation, often reduces the construction efficiency, or misses the window time to prevent sudden construction geological disasters. Rapidly and accurately to rock mass quality classification of tunnel face is the primary problem to be solved in observational rock mass classification of highway tunnel during construction period. The artificial intelligence algorithm provides a method to solve the real-time and accurate evaluation of the rock mass of the tunnel. Taking Yanqing-Chongli highway for Beijing Winter Olympic Games as an example, we adopt a method of using photogrammetry and artificial intelligence rock structure parameter to identify working face. In this method, seven index parameters system are established. We use the KNN intelligent algorithm to evaluate the quality of the tunnel rock and select 150 samples from 40 working faces in 8 tunnels for the training and learning. Another 50 samples are selected for rock mass quality evaluation and verification. Compared with the rock mass quality evaluation results of BQ, the accuracy reachs 90%. Conclusions are as follows. (1)KNN method for observational classification of rock mass quality of highway tunnel is a fast and efficient method for observational classification of rock mass quality by using artificial intelligence technology, which can obtain real-time rock mass evaluation results on site. (2)KNN classification method selects seven discriminant indicators, considering the occurrence of rock environment, geological structure, rock structure and other characteristics, and reflecting the operability and applicability of these indicators in the actual engineering. (3)KNN classification method misjudgment rate is very low. It has strong discriminant ability when marking discriminant classification by excluding the influence of artificial factors. This method provides a new way to solve the rock mass grade determination and classification.

In order to optimize the stope structure parameters in broken rock conditions, a novel method for the optimization of stope structure parameters is described. The method is based on the field investigation, laboratory tests and numerical simulation. The grey relational analysis (GRA) is applied to the optimization of the stope structure parameters in broken rock conditions with multiple performance characteristics. The influencing factors include stope height, pillar diameter, pillar spacing and pillar array pitch, the performance characteristics include maximum tensile strength, maximum compressive strength and ore recovery rate. The setting of influencing factors is accomplished using the four factors four levels Taguchi experiment design method, and 16 experiments are done by numerical simulation. Analysis of the grey relational grade indicates the first effect value of 0.219 is the pillar array pitch. In addition, the optimal stope structure parameters are as follows: the height of the stope is 3.5 m, the pillar diameter is 3.5 m, the pillar spacing is 3 m and the pillar array pitch is 5 m. In-situ measurement shows that all of the pillars can basically remain stable, ore recovery rate can be ensured to be more than 82%. This study indicates that the GRA method can efficiently applied to the optimization of stope structure parameters.

Mining deeper is needed in order to sustain production in many established camps worldwide, but this comes with elevated risk due to, among other things, high stresses. In these conditions, the interactions between stress and structure become critical, as does the state of the rock mass itself and how it’s impacted by the process of mining. Research leading to optimised mine designs and an improved geomechanics outcome is needed. Specifically, rock mass system stiffness and its effect on the stability of structures, the performance of our ground support, and thereby the vulnerability of our excavations is critical to consider, but is not easily measured or understood. This is despite its fundamental importance. At a strategic level, work needs to focus on an integrated approach comprised of enhanced early site characterisation techniques/procedures coupled with rock mass behaviour monitoring in response to the mining process itself. Recognition of the inherently dynamic, rather than static, conditions which prevail in deep mines is essential to ensuring that strategic goals are met through employment of appropriate tactics. This paper will discuss the difficulties and hazards associated with unpredictable rock mass behaviour in deep mines and examine in some detail various tactical research and tool development approaches being undertaken to lower the risk associated with them.

Приведены результаты исследования геомеханического состояния прибортового массива пород в окрестности крупной карьерной выемки с использованием сейсмического метода. С помощью натурных определений скоростей прохождения упругих волн в массиве устанавлены его упругие характеристики, на основе которых сделан вывод об устойчивости участка. Показано, что сейсмическим методом можно получать достаточно надежные данные о динамике изменения геомеханического состояния приконтурного массива на большой площади и осуществлять контроль геомеханической ситуации и устойчивости участков борта карьера. На примере карьера “Железный“ АО “Ковдорский ГОК” представлен многолетний опыт применения сейсмического метода для решения задач обеспечения устойчивости участков борта карьера. Изложенный подход применим для предприятий горной промышленности, разрабатывающих месторождения полезных ископаемых с формированием глубоких карьерных выемок. The article describes the studies on the geomechanical behavior of the large pitwall rock mass using the seismic method. The on-site measurements of elastic wave velocities in rock mass enabled determining the elastic characteristics of rocks, which allowed an inference on the rock mass stability. It is shown that the seismic method provides sufficiently reliable data on the time history of the geomechanical behavior of the large-area pitwall rock mass, and enables the geomechanics and stability control. The long-term experience of using the seismic method to ensure pitwall rock mass stability is presented as a case-study of Zhelezny Open Pit Mine, Kovdor Mining and Processing Plant. The proposed approach is applicable at deep open pit mines.