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Coal mining often causes periodic disruption in the rock mass around the stope. The study of the deformation and failure characteristics of cyclic loading and unloading sandstone is very critical for gaining a thorough understanding of the mechanisms of rock damage, degradation, and failure. This kind of investigation is very helpful in determining the precursors of rock failure and the instability of engineering structures. In this research study, the properties of acoustic emission and infrared radiation of cyclic loading and unloading sandstone are explored using a cyclic loading and unloading sandstone experiment. Based on acoustic emission and infrared radiation, the loading–unloading response ratio of rock is established. It is found that the response variables of sandstone during the loading stage based on acoustic emission (AE) counts and the loading–unloading response ratio based on average infrared radiation temperature (AIRT) both rise suddenly in the last cycle, which may be a precursor of “acoustic-thermal” approaching rock failure. On this basis, the quantitative analysis index of infrared radiation of differential infrared energy change rate (DIECR) is proposed, that is, the change of square of ΔAIRT in unit time, and based on AE counts and DIECR, the loading–unloading response ratio of “acoustic-thermal” is defined. It is found that the “acoustic-thermal” loading–unloading response ratio suddenly increases during the penultimate cycle of loading and unloading. This feature can be taken as the initial precursor of rock failure. Together with the “acoustic-thermal” imminent failure precursor of rock, it constitutes the “initial precursor-imminent failure precursor” combined with the internal fracture and surface infrared radiation temperature field during the cyclic loading and unloading process of rock, realizing the hierarchical monitoring and early warning of cyclic loading and unloading rock failure. The research results lay a theoretical and practical foundation for using infrared radiation to monitor engineering disasters caused by rock fracture and failure in mining engineering.

The dynamic contact behavior between multi-component droplets and the surface of iron ore dust was taken as the research object, analysis of the maximum spreading coefficient, maximum acting diameter, maximum acting area, and maximum bouncing height of solid-liquid contact, from a microscopic perspective, using high-speed photography and image analysis and processing technology. The experimental results indicate that (1) with the particle size of dust particles decreases, the solid-liquid contact behavior sequentially manifests as spread immediately after broken, retraction, negative bounce, primary bounce, and secondary bounce. (2) When the surface tension of the droplets decreases from 55.5 to 34.8 mN/m, the maximum spreading diameter of the droplet has increased by 30% to 40%, the maximum bounce heights (coefficients) decreased by 100%, 57.14%, and 53.57%, respectively, the maximum spreading coefficient of the droplet exhibits no obvious pattern. (3) With decreasing droplet surface tension, the unidirectional acting diameter and the maximum acting area increase when the dust surface size is over 100 μm. When the surface particle size is less than 100 μm, there is no significant change in the unidirectional acting diameter and maximum acting area despite decreasing surface tension. Thus, droplet diffusion is mainly influenced by particle size. These findings contribute to enhancing the theory of water mist dust removal and improving dust removal efficiency.

Rock strength, specifically the uniaxial compressive strength (UCS), is a critical parameter mostly used in the effective and sustainable design of tunnels and other engineering structures. This parameter is determined using direct and indirect methods. The direct methods involve acquiring an NX core sample and using sophisticated laboratory procedures to determine UCS. However, the direct methods are time-consuming, expensive, and can yield uncertain results due to the presence of any flaws or discontinuities in the core sample. Therefore, most researchers prefer indirect methods for predicting rock strength. In this study, UCS was predicted using seven different artificial intelligence techniques: Artificial Neural Networks (ANNs), XG Boost Algorithm, Random Forest (RF), Support Vector Machine (SVM), Elastic Net (EN), Lasso, and Ridge models. The input variables used for rock strength prediction were moisture content (MC), P-waves, and rebound number (R). Four performance indicators were used to assess the efficacy of the models: coefficient of determination (R2), Root Mean Square Error (RMSE), Mean Square Error (MSE), and Mean Absolute Error (MAE). The results show that the ANN model had the best performance indicators, with values of 0.9995, 0.2634, 0.0694, and 0.1642 for R2, RMSE, MSE, and MAE, respectively. However, the XG Boost algorithm model performance was also excellent and comparable to the ANN model. Therefore, these two models were proposed for predicting UCS effectively. The outcomes of this research provide a theoretical foundation for field professionals in predicting the strength parameters of rock for the effective and sustainable design of engineering structures

The working face blasting dust of Dexing Copper Mine was taken as the research object, and hydrophilic dust (HD, sinking quickly to the bottom) and hydrophobic dust (HCD, floating on the surface for a long time) were separated. The wettability was quantitatively characterized by measuring the wetting contact angle of the two, and the physicochemical properties of the dust particles were comprehensively characterized by measuring the particle size distribution, surface properties, elemental composition, and phase composition of the dust particles. Finally, by comparing the differences in physicochemical properties between HCD and HD, the key factors affecting the wettability of dust were investigated. The results indicate that the wetting angle of HCD is much smaller than that of HD at any given time. When the wetting contact angle of HCD reaches 20° and is in a relative equilibrium state, HD tends to 0°. In terms of wetting properties, the average particle size of HCD is 21.97% smaller compared with HD, which makes HCD have a larger mass-specific surface area, surface energy, and surface activity. Additionally, the true density of HCD is 4.54% lower than that of HD. HCD is less affected by gravity and has a more complex surface pore structure, resulting in a more pronounced air film effect on the surface of dust particles. The formation of an air film greatly weakens the dust’s wettability. Therefore, particle size and surface structure are the main factors affecting the dust’s wettability. Organic substances cannot be detected in the HCD and HD spectra, indicating that both HCD and HD are hydrophilic phases, which determines the overall wettability of blasting dust. The phase composition of HCD and HD is similar, and the difference in the content of hydrophobic groups (C-C, C-H) between them is less than 3%, so the surface groups are not the main factors affecting the wettability of dust.

Overburden collapse and water inrush in mines are primarily caused by rock fractures. Mining safety can be enhanced by monitoring and identifying early signs of coal failure in the mines. This article collected acoustic emission data synchronously throughout a series of uniaxial compression (UC) experiments on natural and water-saturated coal. The influence mechanisms of water, mechanical properties, and acoustic emission signals on the stress–strain curve and the SEM results of water-saturated and dry samples are investigated. As a result, the mechanical properties of coal are not only weakened by water saturation, such as elastic modulus, strain, stress, and compressive strength but also reduced acoustic emissions. In comparison with saturated coal, natural coal has a uniaxial stress of 13.55 MPa and an elastic modulus of 1.245 GPa, while saturated coal has a stress of 8.21 MPa and an elastic modulus of 0.813 GPa. Intergranular fractures are more likely to occur in coal with a high water content, whereas transgranular fractures are less likely to occur in coal with a high water content. An innovative and unique statistical model of coal damage under uniaxial loading has been developed by analyzing the acoustic emission data. Since this technique takes into account the compaction stage, models based on this technique were found to be superior to those based on lognormal or Weibull distributions. A correlation coefficient of greater than 0.956 exists between the piecewise constitutive model and the experimental curve. Statistical damage constitutive models for coal are compatible with this model. Additionally, the model can precisely forecast the stress associated with both natural and saturated coal and can be useful in the prevention of rock-coal disasters in water conditions.

To investigate the effect of water on the mechanical properties and acoustic emission (AE) characteristics of coal in the failure and deformation processes. Coal samples of different content were subjected to uniaxial compression tests and AE signals were monitored. The characteristics of the AE signals were further analyzed using fractal analysis. The results show that saturated coal samples have substantially reduced mechanical properties such as uniaxial compressive strength (UCS), dissipation energy, peak stress, and elastic modulus. Under loading, stress–strain curves are characterized by five distinct stages: (1) compaction; (2) linear elastic; (3) crack stable propagation; (4) crack accelerating propagation; and (5) post-peak and residual stages. Using phase-space theory, a novel Grassberger Procaccia (GP) algorithm was utilized to find the AE fractal characteristics of coal samples in different stages. It is significant to note that AE energy does not exhibit fractal characteristics in either the first or second stages. Contrary to the first two stages, the third stage showed obvious fractal characteristics. Fractal analysis of AE time sequences indicates that fractal dimension values change as stress increases, indicating the initiation of complex microcracks in coal. In the fourth stage, the fractal dimension rapidly declines as the strength reaches its limit, indicating the occurrence of macrocracks. However, fractal dimensions continued to decrease further or increased slightly in the fifth stage. Consequently, the coal begins to collapse, potentially resulting in a disaster and failure. It is, therefore, possible to accurately predict coal and rock dynamic failures and microcrack mechanisms by observing the subsequent sudden drop in the correlation dimension of the AE signals in response to different stages of loading.

Effective monitoring of rock fracture and seepage is an important information means to ensure the safety of geotechnical engineering. Therefore, sandstone samples were subject to uniaxial compression under different hydraulic conditions in the presence of infrared radiation and observation. This study uses the multiple infrared radiation indexes (ΔAIRT, IRV, VDIIT) and image data to analyze the influence of coupled stress-hydro effect of infrared radiation change on sandstone surface. The main findings are: (1) The surface temperature of sandstone samples rises in the compaction and linear elastic stages, keeps stable or decreases in the fracture development stage, and rapidly decreases in the post-peak failure stage. (2) The samples with internal water pressure not more than 0.30 MPa, surface temperature and load curve at the compaction and linear elastic stage have a strong power function relationship, which a coefficient of determination is 0.8900. (3) The IRV curve appears as a pulse jump at the time of water seepage. After that, both the fracture development and the post-peak failure stages have stepped up. The VDIIT curve also appears to be a pulse jump at the time of water seepage, and obvious up and down fluctuations exist before water seepage and fracture. (4) Based on the Pauta Criterion, by analyzing the values of VDIIT during the experiment, the early warning threshold of sandstone fracture seepage is determined to be 0.00559. The research finding can provide an experimental and theoretical basis for the early warning of flood accidents in underground rock engineering.

Water is one of the most effective agents that weaken the physio-mechanical properties of rock, trigger significant construction delays, endanger the construction operation, and lead to rock failure. Therefore, an early failure point (EFP) prediction of rock under such conditions is imperative for the robust and reliable implementation of underground engineering. In this research, an EFP of sandstone with different water contents was predicted based on infrared radiation and complex energy evolution during loading. The ratios of elastic to dissipation energy (KED) and elastic to total energy (KET) were proposed to predict EFP. The results show that KED and KET give EFP at the same time for sandstone with water contents 0%, 0.991%, 2.136%, and 3.109%, and the average time of EFP ahead 208 s, 250 s, 265.8 s, and 276.9 s than rock failure, respectively. Furthermore, the proposed KED and KET were predicted using an artificial neural network (ANN). The ANN models’ efficacy was evaluated using the performance coefficient (R2) and root-means-square error (RMSE). The findings revealed high R2 and low RMSE for KED and KET of sandstone with different water contents. The research findings can be used effectively to monitor disasters for the safe and efficient execution of engineering projects.

Rock failure is the root cause of geological disasters such as slope failure, civil tunnel collapse, and water inrush in roadways and mines. Accurate and effective monitoring of the loaded rock failure process can provide reliable precursor information for water inrushes in underground engineering structures such as in mines, civil tunnels, and subways. The water inrush may affect the safe and efficient execution of these engineering structures. Therefore, it is essential to predict the water inrush effectively. In this paper, the water inrush process of the roadway was simulated by laboratory experiments. The multiparameters such as strain energy field and infrared radiation temperature field were normalized based on the normalization algorithm of linear function transformation. On the basis of analyzing the variation characteristics of the original parameters, the evolution characteristics after the parameters normalization algorithm were studied, and the precursor of roadway water inrush was predicted comprehensively. The results show that the dissipation energy ratio, the infrared radiation variation coefficient (IRVC), the average infrared radiation temperature (AIRT), and the variance of successful minor infrared image temperature (VSMIT) are all suitable for the prediction of roadway water inrushes in the developing face of an excavation. The intermediate mutation of the IRVC can be used as an early precursor of roadway water inrush in the face of an excavation that is being developed. The inflection of the dissipation energy ratio from a declining amount to a level value and the mutation of VSMIT during rock failure can be used as the middle precursor of roadway water inrush. The mutation of AIRT and VSMIT after rock failure can be used as the precursor of roadway imminent water inrush. Combining with the early precursor and middle precursor of roadway water inrush, the graded warning of “early precursor–middle precursor–final precursor” of roadway water inrush can be obtained. The research results provide a theoretical basis for water inrush monitoring and early warning in the sustainable development of mine, tunnel, shaft, and foundation pit excavations.

Purpose. To analyze the coupling effect between composite slope geometrical parameters. Methods. The slope angle and excavation depth are coupled with load which is waste dump in this case. Several models were created and analyzed to capture their coupling effect and interactions using FLAC/Slope. Findings. When the slope angle and excavation depth are coupled with a load such as that of a waste dump, the factor of safety decreases. But a suitable dumping position can prove vital to enhancing stability. The primary cause of this phenomenon is that the stresses induced by the waste dump decrease as the dump is moved away from the crest of the slope and the stress induced within the zone of active wedge beneath the dump reduces on the reference slip plane. Hence, it can be said that the position of the waste dump in the formation of a composite slope plays a key role in enhancing stability. Factor of safety have the same influence pattern for all parameters induced by stress as that of influence rule. The results obtained from the finite element stress analysis are the same with those obtained for the slope stability analysis. Originality. The current research presents for the first time the coupling effect of the composite slope geometrical parameters and the results of finite element stress analysis, which are similar to those of slope stability analysis. Practical implications. The current research results can be used to effectively analyze and design the composite slopes in soft rocks specially in surface mines.

Mineral exploitation contributes to the economic growth of developing countries. Managing mineral production brought a more disturbing environment linked to workers' causalities due to scarcities in the safety management system. One of the barriers to attaining an adequate safety management system is the unavailability of future information relating to accidents causing fatalities. Policymakers always try to manage the safety system after each accident. Therefore, a precise forecast of the number of workersfatalities can provide significant observation to strengthen the safety management system. This study involves forecasting the number of mining workers fatalities in Cherat coal mines by using Auto-Regressive Integrating Moving Average Method (ARIMA) model. Workers'fatalities information was collected over the period of 1994 to 2018 from Mine Workers Federation, Inspectorate of Mines and Minerals and company recordsto evaluate the long-term forecast. Various diagnostic tests wereused to obtain an optimistic model. The results show that ARIMA (0, 1, 2) wasthe most appropriate model for workers fatalities. Based on this model, casualties from2019 to 2025 have been forecasted. The results suggest that policymakers should take systematic consideration by evaluating possible risks associated with an increased number of fatalities and develop a safe and effective working platform.

In this paper, the dilatancy stress and mechanical characterization of sandstone were evaluated under uniaxial loading at different elastic modulus and porosity conditions. The prediction model of dilatancy stress was established using a regression equation and an artificial neural network based on a multilayer perceptron (ANN–MLP). The results indicate that: (1) The rock crack initiation stress, dilatancy stress and its elastic modulus are a power function relationship, while porosity is linearly negatively correlated. (2) σci/σmax hardly changes with the change of elastic modulus (E) and porosity (n); its value is about 0.443. σcd/σmax increase with the increase in the elastic modulus, but decrease with the increase in the porosity. (3) Most of the rock samples are observed as a tensile failure when the porosity is low, while they are a shear failure at medium porosity and tensile shear composite failure at high porosity. (4) The optimum value from the ANN–MLP model for dilatancy stress with architecture 6-5-1 having coefficient correlation (R2, 0.96%) was obtained at mean absolute error (MAE, 0.18981) and root mean square error (RMSE, 0.17016). It is worth mentioning that the research results will help and provide a reference for the related to rock mechanics test, rock engineering deformation and failure mechanism, and will also give specific guidelines significance for the efficient design of excavation and support in deep rock engineering.

In order to better understand the failure process of water-bearing rocks, samples of water-bearing sandstone were tested uniaxially. The failure process and the development of internal cracks were studied through the evolution characteristics of dissipated strain energy and particle flow simulation. In this study, we found that: (1) The presence of water in sandstone results in a reduction in energy storage capacity as well as strength. (2) The dissipated energy ratio curve of sandstone samples and simulated samples’ internal fracture development curve has obvious stages. The dissipated energy ratio turning point and the rapid fracture development point are defined as the failure precursor points of sandstone samples and simulated samples, respectively. In both sandstone samples and simulated samples, the ratio between failure precursor stress and peak strength remains almost unchanged under various water conditions. (3) The ratio of fracture to dissipated energy (RFDE) of sandstone is proposed, and interpreted as the increased number of cracks in the rock under the unit dissipated. On this basis, the fracture initiation dissipated energy (FIDE) of sandstone under different water cut conditions is determined, that is, the dissipation threshold corresponding to the start of the development of sandstone internal cracks. (4) The analysis shows that RFDE increases exponentially and FIDE decreases negatively with the scale-up in moisture content. Further, high moisture content sandstone consumes the same dissipative strain energy, which will lead to more fractures in its interior. The research in this paper can lay a theoretical and experimental foundation for monitoring and early warning of rock engineering disasters such as coal mining, tunnel excavation, slope sliding, and instability.

It is significant to monitor the leakage at the joints of the diaphragm walls of subway station foundation pits to check the weak links in the waterproof quality of the diaphragm wall structure. It is essential to take effective waterproof measurements timely to improve the overall waterproof quality of the diaphragm wall in the foundation pit to prevent accidents and reduce the operation and maintenance costs. This paper used ground penetrating radar (GPR) to detect the Lishan North Road Station section of Jinan Rail Transit Line R2 during construction. The abnormal waveform image is obtained after processing radar detection data with Reflexw software. This abnormal waveform image is used to identify the abnormal area. In order to accurately predict the location of leakage at the joint of diaphragm wall, MATLAB is used to calculate the average wave velocity amplitude and single channel signal of the electromagnetic wave velocity of geological radar at different mileages and draw the trend chart of average wave velocity amplitude with mileage and the corresponding relationship curve of electromagnetic wave amplitude and depth of radar. It is proposed that sudden changes in the area of the average wave velocity amplitude cause a change in the trend chart. Furthermore, the radar electromagnetic wave velocity amplitude curve is taken as the area where seepage may occur at the joints of the diaphragm wall, so as to determine the corresponding mileage and depth of the leakage area. On this basis, the grey correlation analysis for the analysis of the source of the water leakage at the joints of the diaphragm wall of the subway foundation pit is proposed. The research results show that the leakage water at the joints of the diaphragm wall of the subway foundation pit is not connected to the rivers around the foundation pit, which confirms that the construction of the subway station has not affected the groundwater resources around the station. The proposed approach has successfully predicted the location of the foundation pit leakage disaster and has been verified on the project site. The research results provide a reference for the monitoring and early warning of leakage at the joints of diaphragm walls in foundation pits with similar geological conditions.

The rock mass deformation modulus (Em) is an essential input parameter in numerical modeling for assessing the rock mass behavior required for the sustainable design of engineering structures. The in situ methods for determining this parameter are costly and time consuming. Their results may not be reliable due to the presence of various natures of joints and following difficult field testing procedures. Therefore, it is imperative to predict the rock mass deformation modulus using alternate methods. In this research, four different predictive models were developed, i.e., one statistical model (Muti Linear Regression (MLR)) and three Artificial Intelligence models (Artificial Neural Network (ANN), Random Forest Regression (RFR), and K-Neighbor Network (KNN)) by employing Rock Mass Rating (RMR89) and Point load index (I50) as appropriate input variables selected through correlation matrix analysis among eight different variables to propose an appropriate model for the prediction of Em. The efficacy of each predictive model was evaluated by using four different performance indicators: performance coefficient R2, Mean Absolute Error (MAE), Mean Squared Error (MSE), and Median Absolute Error (MEAE). The results show that the R2, MAE, MSE, and MEAE for the ANN model are 0.999, 0.2343, 0.2873, and 0.0814, respectively, which are better than MLR, KNN, and RFR. Therefore, the ANN model is proposed as the most appropriate model for the prediction of Em. The findings of this research will provide a better understanding and foundation for the professionals working in fields during the prediction of various engineering parameters, especially Em for sustainable engineering design in the rock engineering field.

Uniaxial compressive strength (UCS) and the static Young’s modulus (Es) are fundamental parameters for the effective design of engineering structures in a rock mass environment. Determining these two parameters in the laboratory is time-consuming and costly, and the results may be inappropriate if the testing process is not properly executed. Therefore, most researchers prefer alternative methods to estimate these two parameters. This work evaluates the thermal effect on the physical, chemical, and mechanical properties of marble rock, and proposes a prediction model for UCS and ES using multi-linear regression (MLR), artificial neural networks (ANNs), random forest (RF), and k-nearest neighbor. The temperature (T), P-wave velocity (PV), porosity (η), density (ρ), and dynamic Young’s modulus (Ed) were taken as input variables for the development of predictive models based on MLR, ANN, RF, and KNN. Moreover, the performance of the developed models was evaluated using the coefficient of determination (R2) and mean square error (MSE). The thermal effect results unveiled that, with increasing temperature, the UCS, ES, PV, and density decrease while the porosity increases. Furthermore, ES and UCS prediction models have an R2 of 0.81 and 0.90 for MLR, respectively, and 0.85 and 0.95 for ANNs, respectively, while KNN and RF have given the R2 value of 0.94 and 0.97 for both ES and UCS. It is observed from the statistical analysis that P-waves and temperature show a strong correlation under the thermal effect in the prediction model of UCS and ES. Based on predictive performance, the RF model is proposed as the best model for predicting UCS and ES under thermal conditions.

The deformation and failure of rock materials are closely related to the strain energy characteristics during the loading process. These strain energy characteristics and rock properties are greatly affected when the rock is subjected to the acidic solution. To study the effects of chemical solutions with different pH on the mechanical properties and strain energy mechanism of mudstone, the chemical corrosion mudstone samples are subjected to a uniaxial loading testing machine (CN64 electro-hydraulic servo). The corrosive effects of the acidic solution on the porosity, strain energy characteristics, and failure mode of mudstone samples were thoroughly investigated. The findings of this research indicate that: (1) The rate of change in the porosity and chemical damage coefficient of rock samples after chemical corrosion decreases, which is closely linear with the increase of solution pH, (2) The total strain energy, elastic strain energy, and dissipative strain energy decrease with the increase of pH, and, as a result, it is proposed that the observed turning point of the proportion curve of dissipated strain energy from decline to rise is used as a precursor point of the rock failure, (3) The stress value of the failure precursor point increases and the strain value decreases with the increase in pH value. However, the ratio of the stress value of the failure precursor point to the peak stress hardly changes with pH value, and its value is about 0.883, and (4) Rock samples soaked in a weak acidic chemical solution (pH 7.3 and 5.3) are damaged by tensile crack, while rock samples soaked in a strong acidic chemical solution (pH 3.3 and 1.3) are mainly damaged by the combination of tensile and shear. The findings of this study can be used to provide an experimental and theoretical foundation for monitoring rock engineering disasters such as slope, tunnel, and coal mine failures.

In this study, a uniaxial impact compression test was performed on coal samples with length-to-diameter L / D ratios of 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, and 1 using a Φ 50 mm split Hopkinson pressure bar (SHPB) test system. This study researched the stress uniformity and deformation behavior of coal samples with different L / D ratios during dynamic compression, defined the stress equilibrium coefficient ξ , proposed a new method for determining whether a sample meets the stress uniformity hypothesis, and obtained the critical L / D ratio of 0.6 and the optimal L / D ratio of 0.3 or 0.4 for coal samples to obtain the stress equilibrium. The experimental results showed that the dynamic stress-strain curve of coal had an elastic stage, a plastic stage, and a failure stage. As the L / D ratio increased, the proportion of the elastic stage to the prepeak curve of the samples declined progressively; with an increase in the L / D ratio, the peak part of the curve also changed from “sharp” to “stagnated,” while an increase in the plasticity led to strain softening. As the L / D ratio of the samples increased, the average strain rate decreased approximately as a power function, and the decreasing trend was gradually reduced from 296.49 s−1 ( L / D =0.3) to 102.85 s−1 ( L / D =1), with a reduction of approximately 65.31%. With an increase in the L / D ratio, the peak strain gradually decreased exponentially. This study concluded that the SHPB test protocol design is of a certain reference value for low-density, low-strength, heterogeneous brittle materials, such as coal.

The effects on geotechnical properties of rock mass from the constituent particle morphology have been acknowledged since long. Particle morphology is among the most important parameters affecting the mechanical characteristics of rock, such as shear strength, cohesion, friction angle, porosity, groundwater seepage, and angle of repose. This review summarizes the current advancement in numerical simulation-related particle morphology and its impact on the mechanical behavior of rock mass. Several scholars assessed the influence of particle morphology on macroscopic mechanical response using experimental and numerical simulation techniques. The clump particle approach based on discrete elements methods (DEM) reproduces mechanisms between rock particles to illustrate the correlation of mechanical performance and particle morphology. However, this approach presents the statistical limits of particle shape and size distribution of clump particles to rock particles. Particle shape has distinct effect on geotechnical properties of rock; conversely, each descriptor is case sensitive to a specific attribute of shape. The diversity of the outcomes of the conducted study in the geotechnical field revealed an ambiguity associated with the correlation of particle size distribution with the mechanical behavior of rock and granular material. Nevertheless, further research is essential to address some of the issues that have not yet been tackled, few of which are identified throughout this review article.

The geological strength index (GSI) is one of the most exceptional rock mass classification system which is used to evaluate very weak and highly jointed rock mass by different approaches and related to rock mass geomechanical properties including generalized Hoek & Brown constants, deformation modulus, strength properties, and Poisson’s ratio for an appropriate design of tunnels, caverns, and other engineering structures. The distinctiveness of this system over the rock mass rating (RMR), Q-system, and other empirical methods is as follows: it utilized field observations, blockiness of rock mass, and surface joint characteristics during the evaluation process of rock mass and efficiently espoused as an empirical tool for estimation of geomechanical properties of rock mass required for pre-post stability of engineering structures using numerical modeling. This study presents the review of the 19 years of research studies conducted by different researchers about the GSI in a systematic way, i.e., origination, modifications, applications, and limitations. Furthermore, this study will provide a better understanding to field professionals (geologists, mining and civil engineers) about the qualitative and quantitative estimation of the GSI and its application as an empirical estimating tool for an appropriate design of engineering structures in rock mass environments.

The influence of acid solutions was investigated on the mechanical properties of mudstone. Uniaxial compression tests on mudstone samples were conducted to determine the variations of relative mass, porosity, deformation, and strength characteristics of mudstone subjected to acidic solutions with different pH values. The change of pH, relative mass, and porosity of mudstone in the process of acid solution immersion was monitored during soaking. The mechanism of hydrochemical corrosion of mudstone samples was preliminarily discussed. The damage parameter was introduced based on the porosity rate. The results show that with increased solution acidity, the peak stress and elastic modulus decreased to different levels, while the peak strain increases in the rock samples. The increased chemical damage parameters reduce the mechanical parameters and increased the deformation parameters. On the basis of the mechanical test, considering the stress-strain relationship of rock in the compaction stage, a segmented damage constitutive model of rock based on chemical damage parameters is established, and the test results are verified. The results show that the correlation coefficient between the theoretical curve and the experimental data is as high as 0.98, and the model is suitable for the analysis of chemically corroded rock under the uniaxial compression test. The results provide a reference for the analysis and design of coal-bed methane wells where the rocks frequently become acidic during the production of methane.

The risk of a coal burst rises with the excavation depth and other mining-related activities. These devastating coal burst activities are a major concern during deep coal mining. During such activities, the loading rate is a major cause of damage. Different indexes, including the elastic strain modulus index (Wet), bursting energy index (Ke), dynamic failure time index (DT), and compressive strength index (Rc), are used for coal bursting intensity; however, the loading rate and damage factors are not included in these indexes. In this study, a new coal bursting liability index called the elastic modulus damage index (EMDI) was developed using rock damage variables and the elastic strain modulus index, and is based on energy evolution characteristics under different loading rates. The results of this new index were compared with the existing indexes, and their range was proposed to evaluate coal bursting liability. The EDMI shows a positive polynomial second order degree relationship with Wet and Ke, having a determination factor of 0.99, while DT shows a negative polynomial second order degree relationship with a determination factor of 0.94. The EDMI and Rc show a positive power relationship having a determination factor of 0.99. The relationships with other indexes revealed that the EDMI can be effectively used in evaluating the coal bursting liabilities in different stress environments. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. Funding: The authors would like to thank the YUTP under grant numbers 015LC0-150 and 015LC0-326 for providing financial assistance.

During the stress-induced rock failure process, anomalies in the Infrared Radiation (IR) can be observed. To study the response relationships between rock IR temperature and spatial-temporal evolution process of cracks in sandstone, the IR and Acoustic Emission (AE) were both measured during uniaxial compression. The multi-frames accumulation average technology and background thermal noise correction method were used to correct the IR temperature. According to the AE results, the temporal evolution process of cracks was divided into six stages: initial crack closure, linear elastic deformation, micro-crack development, macro-crack initiation, macro-crack propagation, and macro-crack coalescence. It was found that the changing rate of the Average Infrared Radiation Temperature (AIRT) changed with the crack evolution stage changed, which could be regarded as a basis for dividing the evolution stages of rock cracks using IR. The accumulated energy density map of AE events was used to analyze the spatial distribution characteristics of cracks and determine the Low Damage Area (LDA) and High Damage Area (HDA) of the rock samples. It was found that the AIRT variations were consistent between LDA and HDA during the entire loading process. However, since the stage of micro-cracks development, the difference value in AIRT between LDA and HDA gradually increased with time. The research results can provide a reference for the study of the rock crack evolution process with the surface IR information and are helpful to the early warning of rock failure.

The Infrared Radiation (IR) on the surface of a rock being loaded will change significantly during its failure process. To effectively monitor and predict rock failure by the IR method, in this paper, the Infrared Radiation Variation Temperature Field (IRVTF) of rock under uniaxial compression was identified. It was found that some IRVTF thermal images were characterized by obvious temperature rise in the later stage of rock loading. The temperature distribution characteristics of IRVTF were analyzed. It was observed that the temperature of the IRVTF exhibited the logarithmic linear distribution within the selected statistical temperature range, with an average coefficient of correlation greater than 0.96. On this basis, the index of “Infrared Radiation b-value (bIR-value)” of rock under uniaxial compression was defined for the first time, and the threshold for identifying its sudden change was proposed. It was found that the sudden changes of bIR-value could be observed with the generation of large-scale micro-cracks. The average amplitude of the bIR-value at first sudden change for all samples was 16.58 times of the mean amplitude before the sudden change on average, which indicated the significance of the bIR-value sudden change. The first sudden change of the bIR-value was 22.5 s ahead of the peak stress on average, which could be used as a precursor of rock failure and instability. The findings of the research can help with the monitoring and early warning of surrounding rock instability in mines, tunnels, and other geotechnical projects.

The rock failure process is always accompanied by dilatancy. This study investigated the average infrared radiation temperature (AIRT) characteristics in the rock dilatancy process. An Infrared Radiation (IR) dilatancy precursor point was found prior to the failure of the rocks under load. During the uniaxial loading process, the stress levels of upward-AIRT and downward-AIRT rock samples at the initial point of rock dilatancy were 0.74 σmax and 0.80 σmax, respectively. After rock dilatancy, the AIRT change rate of upward-AIRT sample increased by 1.48 × 10−4°C⋅s−1, and AIRT change rate of downward AIRT sample dropped by 1.29 × 10−4°C⋅s−1. From the initial point to the process reached rock failure, the AIRT change was almost linearly correlated with volumetric strain increment. Based on the IR thermogram, the IR hot spot was defined, and a new index—high temperature point scaling factor (HTPSF)—was proposed for qualitative analysis. The calculated HTPSF values of upward-AIRT and downward-AIRT rock samples at the IR dilatancy precursor point were 0.4 and 0.6, respectively. This study provides a new thought to determine the initial point of rock dilatancy.

The problem of water resources damage caused by coal mining has restricted the sustainable development of Yu-Shen mining area. Illustrating the relationship between mining and water resources carrying capacity is of great significance to solve this problem. In this study, the authors proposed an appraisal and prediction model of water resource carrying capacity in the mining area (WRCCMA) based on the analytic hierarchy process (AHP)-fuzzy comprehensive evaluation method. A triple-leveled structure model was developed, and the main influencing factors of the WRCCMA and the membership functions were analyzed. The prediction model was applied to Yubujie colliery to test its validity by investigating the changes of vegetation coverage and the ground deformation of the colliery and its adjacent coal mine before and after mining. Subsequently, we obtained the WRCCMA of the study area and zoning map of different grades of WRCCMA in the mining area by applying this model to the whole Yu-Shen mining area. Furthermore, three countermeasures to maintain the WRCCMA and realize water conservation coal mining (WCCM) were provided to collieries with different WRCCMA grades, including mining methods selection, mine water reutilization, and water-resisting layer reconstruction. Reasonable mining methods and water-resisting layer reconstruction can reduce the development of water conductive fractures and thus prevent groundwater from penetrating into the goaf. Mine water reutilization provides a source of water demand for collieries and families, contributing to the reduction of abstraction of water resources. These three countermeasures can help to maintain the WRCCMA. This paper successfully combines the fuzzy theory with mining engineering and provides theoretical and practical guidance for other mining areas in arid and semi-arid regions of Northwest China.

Water saturated rock strain energy evolution was measured using infrared radiation (IR) under uniaxial load of sandstone samples. The variation in the characteristics of total strain, elastic strain, dissipated strain energies and maximum IR of saturated rock under stress were analyzed. The results reveal the degree of saturation has a significant effect on rock strain energy. The total strain and elastic strain energies correlated linearly negatively, dissipative strain energy were correlated exponentially negatively, and maximum infrared radiation variance (IRV) correlated quadratically at peak stress point with different degree of saturation of rock samples. The relationship between total strain, elastic strain energies, and ΔIRV was a linear function under different saturated conditions. It was found that there was a linear energy transfer and linear energy storage function in the rock. Based on linear energy transfer and storage, two coefficient in the presence of IR were introduced, i.e., the Total Energy Infrared Radiation Coefficient (TEIRC) and Energy Storage Infrared Radiation Coefficient (ESIRC). These can be used with variation in infrared radiation variance (ΔIRV) to determine total strain and elastic strain energies of saturated rock. Furthermore, a quantitative analysis index of energy dissipation infrared radiation ratio (EDIRR), i.e. the ratio of dissipative strain energy to ΔIRV, has been proposed which can be used to predict and identify the failures of saturated rock. The inflection point of rock EDIRR from horizontal to rapid growth can be regarded as the precursor point for rock failure, and the EDIRR mutation after the precursor point can be used as the new criterion to monitor rock failure and instability.

Limestone is the main constituent as raw material used in manufacturing of cement. In this study the limestone deposits of Khyber Karimabad, Passu and Morkhun-Gircha Upper Hunza Valley, Gilgitbaltistan were evaluated for its suitability to be used raw material for cement industry through chemically and mineralogical techniques. The representative limestone's samples from different geological beds of the proposed area were collected. These samples were investigated petrographic study, X-ray diffraction (XRD), Scanning electron microscopy coupled with X-ray diffraction (SEM-EDX), X-ray fluorescence (XRF) and reserve estimation of the proposed deposit was carried out using Geological Information System (GIS). Geological review shows that there is a good potential for industrial-grade limestone, the composition of this limestone can be generally expressed in terms of CaO, MgO, Al2O3, and SiO2, that may be used in place of similar commodities of good quality cement raw materials. After analysis of results, it is concluded that limestone and other raw materials of Khyber Karimabad (KKLS) are is of good quality and can fulfills the international standards of cement and while limestone and other raw materials of Passu and Morkhun-Gircha is not suitable to be used as raw material for cement industry.