International Journal of Coal Science & Technology最新文献

The post-peak characteristics of coal serve as a direct reflection of its failure process and are essential parameters for evaluating brittleness and bursting liability. Understanding the significant factors that influence post-peak characteristics can offer valuable insights for the prevention of coal bursts. In this study, the Synthetic Rock Mass method is employed to establish a numerical model, and the factors affecting coal post-peak characteristics are analyzed from four perspectives: coal matrix mechanical parameters, structural weak surface properties, height-to-width ratio, and loading rate. The research identifies four significant influencing factors: deformation modulus, density of discrete fracture networks, height-to-width ratio, and loading rate. The response and sensitivity of post-peak characteristics to single-factor and multi-factor interactions are assessed. The result suggested that feasible prevention and control measures for coal bursts can be formulated through four approaches: weakening the mechanical properties of coal pillars, increasing the number of structural weak surfaces in coal pillars, reducing the width of coal pillars, and optimizing mining and excavation speed. The efficacy of measures aimed at weakening the mechanical properties of coal is successfully demonstrated through a case study on coal burst prevention using large-diameter borehole drilling.

Abstract

One of the most dangerous safety hazard in underground coal mines is roof falls during retreat mining. Roof falls may cause life-threatening and non-fatal injuries to miners and impede mining and transportation operations. As a result, a reliable roof fall prediction model is essential to tackle such challenges. Different parameters that substantially impact roof falls are ill-defined and intangible, making this an uncertain and challenging research issue. The National Institute for Occupational Safety and Health assembled a national database of roof performance from 37 coal mines to explore the factors contributing to roof falls. Data acquired for 37 mines is limited due to several restrictions, which increased the likelihood of incompleteness. Fuzzy logic is a technique for coping with ambiguity, incompleteness, and uncertainty. Therefore, In this paper, the fuzzy inference method is presented, which employs a genetic algorithm to create fuzzy rules based on 109 records of roof fall data and pattern search to refine the membership functions of parameters. The performance of the deployed model is evaluated using statistical measures such as the Root-Mean-Square Error , Mean-Absolute-Error, and coefficient of determination ( (R_2) ). Based on these criteria, the suggested model outperforms the existing models to precisely predict roof fall rates using fewer fuzzy rules.

In China, coal miners are the primary workforce in coal mining, and among all patients with occupational diseases, 90% suffer from pneumoconiosis. Therefore, the psychological problems resulting from the dual pressures of occupational stress and the high risk of occupational diseases among coal miners are significant factors that affect the development of physical and mental health and even production safety. The Crown–Crisp Experience Index (CCEI) is a multidimensional questionnaire that assesses the psychological state of patients. This study aims to test reliability and validity of Chinese version of the CCEI questionnaire using factor analysis, and apply it to coal miners. We recruited a total of 900 participants from different occupational stages in coal mining, including active miners, Coal Workers’ Pneumoconiosis (CWP) patients, and retired miners, to evaluate the reliability and validity of the Chinese version of the CCEI questionnaire. A questionnaire survey was conducted on three groups of 1000 individuals each, including active coal miners, retired coal miners, and pneumoconiosis patients, to determine the detection rate of psychological problems in each group. An analysis was performed for each group to explore the primary factors influencing anxiety. The exploratory factor analysis yielded six principal components that accounted for a total of 79.389% of variances. The confirmatory factor analysis showed that the Chi-square freedom ratio (χ²/df) was 1.843, the root mean square error approximation was less than 0.044, and the comparative fit index was 0.938 and Tucker–Lewis index (TLI) was 0.934. The Cronbach's alpha coefficient was 0.948, and the scale-level content validity index (S-CVI) was 0.88. Effective questionnaires were obtained from 98.5%, 96.9%, to 91.0% of pneumoconiosis patients, active miners, and retired miners, respectively, with the incidence rates of psychological problems being 21%, 35.8%, and 13.6%, respectively. Compared with retired miners, active miners showed higher levels of psychological problems in the dimensions of depressive symptoms, free-floating anxiety and somatic symptoms, whereas pneumoconiosis patients had higher levels of psychological problems in the dimensions of phobic anxiety and somatic symptoms. This study demonstrates that the Chinese version of the CCEI is highly reliable and valid and can be used as a screening tool to measure patients' anxiety and fear levels in coal minders. Miners face distinct psychological challenges at different stages and require targeted screening and interventions.

Nano-to-micron-sized coal dust can cause coal workers’ pneumoconiosis (CWP), and cutting and drilling are the main coal dust-generating processes. Based on a self-developed simulated coal cutting and drilling dust generation system, the effects of cutting parameters (tooth tip cone angle, impact angle, roller rotary speed, cutting speed) and drilling parameters (drill bit diameter, drilling speed) on the mass concentration distribution, number concentration distribution and fractal dimension of 10 nm – 10 μm coal dust were investigated. Results show that the mass concentration of 10 nm – 10 μm coal dust generated by cutting/drilling peak at 5.7 – 7.2 μm, while the number concentrations during cutting and drilling respectively peak at 60 – 90 nm and 20 – 30 nm. During both cutting and drilling processes, the generated coal dust particles in 10 – 300 nm account for > 90% of the total 10 nm – 10 μm coal particles, while PM2.5 in PM10 is generally below 18%. It is also found that smaller tooth tip cone angle, larger impact angle, lower roller rotary speed, smaller drill bit diameter, or lower drilling speed can reduce the generation of 10 nm – 10 μm coal dust with a fractal dimension of 0.94 – 1.92. This study reveals the distribution characteristics of nano- to micron-sized coal dust particles under different cutting and drilling parameters, and the research results can serve as reference for adjusting cutting and drilling parameters to lower down the 10 nm – 10 μm coal dust generation and thus prevent the CWP.

The microstructure and adhesion force between dust particles determine the dust starting and migration to a certain extent. By use of scanning electron microscopy, the BET method, and the abruption technique, the microstructure and adhesion force of dust on the soil pavement of an open-pit mine were examined. The results indicate that the dust shape of soil pavement is mainly irregular quadrilateral, pentagonal and circular. The adhesion of dust particles in soil pavement reduces as particle size and temperature increase. When the particle size grows from 22 to 30 μm and the ambient temperature rises from 25 to 30 ℃, the adhesion force of dust particles in soil pavement drops dramatically. The adhesion force of dust particles in the soil pavement of open-pit mine increases as environmental humidity and pressure rise. When the environmental humidity exceeds 70% and pressure exceeds 24.79 kPa, the adhesion of dust particles increases dramatically. On the basis of the multiple regression method, a prediction model for the dust adhesion force of open-pit mines’ soil pavement has been developed. However, its accuracy needs to be further enhanced.

To rationalize the setting of joint parameters, model size, and initial value of vertical stress in simulation of mining of steeply inclined coal seams, a fault tree analysis method of discrete element numerical simulation was used and a mathematical model was proposed. A method of eliminating the influences of size-effect errors on the parameters of coal and rock samples was obtained based on previous work. Furthermore, the constitutive equation and eigenvalue determination formula of a joint discontinuity surface were established, and a method of determination of the joint parameters was proposed, forming the complete “coupling chain” between parameters for numerical simulation. In addition, a formula for the initial value of vertical stress was constructed by way of the compression and shear model of the element body. Also, the minimum dimension was determined by means of strength factor analysis of fracture mechanics. Taking the research literature as an example, the model size and initial value of vertical stress were calculated. On this basis, the physical parameters of coal samples, the physical parameters of coal rocks considering the influence of the size effect and the calculated coal rock joint parameters considering the influence of size effect were directly used to comparatively analyze the displacement and stress fields, thus verifying the reasonability and correctness of the mathematical model.

Coal gangue is one of China’s main industrial solid wastes, which contains various harmful heavy metal elements, such as lead (Pb). The long-term accumulation of coal gangue causes Pb to migrate to the surrounding environment due to weathering and rain erosion, eventually endangering human life and health with its continuous accumulation in the food chain. This review discusses the migration and transformation process of Pb in coal gangue under different conditions and summarizes the available forms and mechanisms of Pb in coal gangue. The current prevention and control and comprehensive utilization methods of Pb in coal gangue are comprehensively reviewed, and the characteristics of each method are discussed. In order to realize the economical, efficient, and high resource utilization of coal gangue, this paper provides favorable suggestions and support for subsequent in-depth research and the implementation of heavy metal prevention and control measures.

Coal mining under the geological conditions of a loose layer will lead to the intensification of surface movement and deformation, and mining under the geological conditions of a fault will lead to the living slip of a fault. Mining under both conditions will have a great impact on the safety of coal production. To reveal the evolution law of the coupling mechanism of loose layer and fault on the multi-physical fields of overburden, the numerical simulation method is used to simulate the coupling of loose layer and fault with different thicknesses, analyze the changes of vertical stress on the key strata, the changes of surface subsidence, the evolution of elastic energy on the fault zone and the changes of activated slip area of the fault zone. The simulation analysis shows that the vertical stress change trend of the key strata gradually changes from the "V" shape to the "W" shape at the beginning of mining, and the vertical stress concentration will occur at the fault. The loose layer will promote surface subsidence, and the fault will hinder the surface subsidence to a certain extent. The loose layer and the fault alternately affect the surface subsidence. The elastic energy accumulation on the key strata is mainly concentrated on both sides of the goaf. The elastic energy in the center of the goaf is dissipated. The elastic energy accumulation in the fault zone starts from the shallowly buried fault and gradually develops to the deeply buried fault. The instability of fault activation has gone through the initial stage of activation—the intensification stage of activation—the stable stage of activation. Under the working conditions of no loose layer, thin loose layer, and thick loose layer, the fault zone is the first to undergo living slip, and under the action of an extra-thick loose layer, there is a certain lag in the activation slip of the fault zone.

A comprehensive evaluation method is proposed to analyze dust pollution generated in the production process of mines. The method employs an optimized image-processing and deep learning framework to characterize the gray and fractal features in dust images. The research reveals both linear and logarithmic correlations between the gray features, fractal dimension, and dust mass, while employing Chauvenel criteria and arithmetic averaging to minimize data discreteness. An integrated hazardous index is developed, including a logarithmic correlation between the index and dust mass, and a four-category dataset is subsequently prepared for the deep learning framework. Based on the range of the hazardous index, the dust images are divided into four categories. Subsequently, a dust risk classification system is established using the deep learning model, which exhibits a high degree of performance after the training process. Notably, the model achieves a testing accuracy of 95.3%, indicating its effectiveness in classifying different levels of dust pollution, and the precision, recall, and F1-score of the system confirm its reliability in analyzing dust pollution. Overall, the proposed method provides a reliable and efficient way to monitor and analyze dust pollution in mines.

Among all methods for investigating the complex phenomenon of the coal and gas outburst, numerical modelling is the most comprehensive one that can consider all involved parameters and simulate the complex multi-physical phenomenon. The main aim of this paper is to review recent numerical modelling studies concerning this disastrous phenomenon observed in coal mining. The paper aims to analyse these studies comprehensively and identify any existing research gaps that could be addressed in future research endeavours. To this end, the concepts and equations that have been used in previous studies to simulate the solid and fluid behaviour during outburst initiation and how these equations are coupled to consider multiphysical interactions were reviewed. Both strengths and deficiencies in past outburst modelling work were highlighted. Finally, potential research topics for future studies were discussed in three categories; looking into the outburst phenomenon in the scale of the particles which is mostly focused on the discrete element method, conservation of the energy as a method to quantitively assess outburst initiation, and the application of statistics in both applying the heterogeneity in the models and assessing the possibility of the outburst occurrence.