Coal Mines In China Research Articles

Game Analysis of the Influence of the Miner under Carbon Emotion on the Intelligent Development Strategies of the SMEE in Coal Mines

The intelligent development of coal mines is a crucial way to achieve the safe, efficient, green, and low-carbon transformation of the coal industry and to reach the “double carbon” target, which is related to the life and health of miners, the stable development of enterprises and the national energy reform. As directly affected subjects, the cooperative attitudes of miners in different emotional states have a significant impact on the smooth implementation of intelligent coal mine renovation projects. Hence, we combined the RDEU theory and game theory, constructed a three-party evolutionary game model of the small and medium-sized energy enterprises (SMEE), the government, and the miner, considered the influence of the strategies made by the miner on the equilibrium strategy choices of other game subjects in the intelligent coal mine construction under the rational and irrational emotional states of the miner, and finally used MATLAB 2021 to simulate and analyze the impact of the evolution of the gaming system from 3 key elements: initial participation rate, construction costs, and government support. The study found the following: (1) The government will insist on actively promoting intelligent coal mine construction regardless of the miner’s emotional state. (2) Both moderate pessimism and optimism will, to a certain extent, give a positive impetus to the development of intelligent coal mine construction. (3) The miner’s emotions have a greater impact on SMEE than on the government’s strategic behavior. (4) Excessive construction costs or low government support will make SMEE may reduce the enthusiasm of SMEE to carry out an intelligent construction of coal mines. Accordingly, corresponding suggestions and countermeasures are put forward, aiming to provide targeted and practical ideas for the efficient construction of intelligent coal mines in China, thereby accelerating the green and low-carbon transformation of energy.

Thermal Environment Control at Deep Intelligent Coal Mines in China Based on Human Factors

Mechanical cooling of the entire mining tunnel, widely used in deep coal mines, has a significant energy-intensive consumption, particularly for intelligent mining tunnels. Therefore, localized cooling would benefit the intelligent mining industry. Current studies on the temperature, relative humidity, and air velocity under localized cooling for working protection are still unclear. A modified predicted heat strain model that is appropriate for warm and humid conditions is presented in this article and calculated using MATLAB. Results reveal that air temperature was the primary factor affecting underground miners’ safety. Increasing air velocity would improve the working environment when the thermal humidity index is lower than 32. Reducing total working time and wet bulb temperature would benefit underground miners’ security. For the cooling of intelligent mining tunnels, the recommended air velocity would be 2 m/s, and the maximum wet bulb temperature would be 28 °C for the 6-h working period and 26 °C for the 8-h working period. Results would be beneficial to the cooling of intelligent mining in China.

Analysis of water inrush at Dongyu coal mine in China from an old water-logged goaf associated with a syncline fractured zone

Analysis of water inrush at Dongyu coal mine in China from an old water-logged goaf associated with a syncline fractured zone

Dynamic optimization of open-pit coal mine production scheduling based on ARIMA and fuzzy structured element

A dynamic optimization method was created to address the production schedule issue in an open-pit coal mine while taking into account the characteristics of the fuzzy structured element. The fuzzy mining capacities of all “geologically optimal push-back bodies” were then examined using the moving cove method. One of the most crucial elements in the process of open-pit coal mine production scheduling optimization is coal pricing. As a result, this work also presents a dynamic optimization technique for production scheduling that incorporates the prediction of economic time series and the generation of dynamic economic indices. An appropriate time series model is created to forecast the future coal price based on previous data on coal prices. The prediction results are used in the calculation of optimal mining body generation to dynamically obtain the optimal production scheduling model. The Baorixile Open-pit Coal Mine in China’s Inner Mongolia Autonomous Region is using this method. The Autoregressive Integrated Moving Average Model ARIMA is constructed to anticipate the coal price in the future 23 years by evaluating and processing the coal price from 2009 to 2022, and the ideal production scheduling scheme of the mine economics is afterwards identified. The ideal fuzzy coal mining volume, the potential production life, and the fuzzy total net present value (NPV) of the annual production scheduling are all provided at the same time. The optimization findings can better give fundamental support for mine design and future production since the fuzzy problem is accurately expressed by correct formulations.

An Improved Machine Learning Approach for Optimizing Dust Concentration Estimation in Open-Pit Mines.

Dust is a severe environmental issue in open-pit mines, and accurate estimation of its concentration allows for viable solutions for its control and management. This research proposes a machine learning-based solution for accurately estimating dust concentrations. The proposed approach, tested using real data from the Haerwusu open-pit coal mine in China, is based upon the integrated random forest-Markov chain (RF-MC) model. The random forest method is used for estimation, while the Markov chain is used for estimation correction. The wind speed, temperature, humidity, and atmospheric pressure are used as inputs, while PM2.5, PM10, and TSP are taken as estimated outputs. A detailed procedure for implementing the RF-MC is presented, and the estimated performance is analyzed. The results show that after correction, the root mean squared error significantly decreased from 7.40 to 2.56 μg/m3 for PM2.5, from 15.73 to 5.28 μg/m3 for PM10, and from 18.99 to 6.27 μg/m3 for TSP, and the Pearson correlation coefficient and the mean absolute error also improved considerably. This work provides an improved machine learning approach for dust concentration estimation in open-pit coal mines, with a greater emphasis on simplicity and rapid model updates, which is more applicable to ensure the prudent use of water resources and overall environmental conservation, both of which are advantageous to green mining.

Research on Efficient Construction Paths for Intelligent Coal Mines in China from the Configuration Perspective

The intelligent transformation of coal mines is an inevitable choice to promote the green transformation of energy and to achieve safety and efficiency in the industry. Exploring the path of its efficient construction is the key to realizing the construction of intelligent coal mines in China. To analyze the configuration paths for the efficient construction of intelligent coal mines, 17 typical coal-producing provinces in China were used as the research object of a fuzzy set qualitative comparative analysis (fsQCA), and five conditional variables, namely research funds, technical talent, government importance degree, national demonstration, and basic resource support, were selected from four levels (technology, organization, environment, and resources) based on relevant national data from 2019–2021, and multiple configurations as well as multiple driving paths for the construction of intelligent coal mines were discussed. We found that there are three configuration paths that will enable the construction of intelligent coal mines: a technology-driven path under the government’s supervision, a path jointly driven by three-prongs, and a policy-driven path under the resource priority. The critical importance of the government is the common factor among the three driving modes. These research results can provide useful construction ideas for the construction of intelligent coal mines in different regions and enable provincial governments to carry out strategic combination actions according to local conditions to contribute to the efficient construction of intelligent coal mines and the green transformation of energy across the country.

Development of Intelligent Technologies and Machinery for Coal Mining in China's Underground Coal Mines

Development of Intelligent Technologies and Machinery for Coal Mining in China's Underground Coal Mines

华北煤矿区PM<sub>2.5</sub>中水溶性离子特征及来源解析

华北煤矿区PM<sub>2.5</sub>中水溶性离子特征及来源解析

Failure Mechanism and Control Technology for Coal Roadway in Water-Rich Area

Accurate analysis of failure mechanisms and scientific support for design of coal roadways in water-rich areas plays an important role in the long-term stability control of roadways. In this study, taking the water-rich 1044 return laneway in the Taoyuan Coal Mine of China as an example, laboratory experiments and field tests were performed to study the potential failure mechanisms of the roadway. It was found that the microcracks inside the coal body increase and strength of the coal decreases with the long-term influence of groundwater. The weak surrounding rock and high vertical in-situ stress were the main internal causes of roadway instabilities. Based on the potential failure mechanisms, a new optimal support design including bolt, cable, metal mesh, shotcrete, and grouting was proposed and detailed support parameters were introduced. A field experiment was performed with the new support, and surface deformations of the experimental roadway were monitored. Results show that the new support can reduce the deformation of the 1044 return laneway by nearly 90% compared with those of the original design. Support technology presented in this contribution provides a significant reference for the control of roadways in water-rich areas.

Research on composite dynamic disaster prevention and control system of mine earthquake and shock in thick and hard rock mines

Abstract With the rapid entry into deep mining of coal mines in China, the impact composite dynamic disaster of thick and hard layer mines and mine earthquakes has increasingly become a major disaster that threatens the safe and efficient mining of deep coal. Studying its occurrence mechanism, disaster prevention and control system has become a new major scientific issue in the field of coal mine safety. This paper proposes a framework for a composite dynamic disaster prevention and control system framework for thick and hard rock mines. First, the gravity forms, extents and deformation characteristics of different rock layers of the structural model are analysed, and the expressions of concentrated force and periodic breaking step distance of rock beams in thick and hard rock layers at the fixed support end are deduced. Then, according to the cause of the shock composite dynamic disaster, finally, the specific testing and calculation methods of mine earthquakes in thick hard rock mines are designed. The regional and local measures to manage compound dynamic disasters are put forward. Experiments show that the system is successfully applied to the mining practice of working face, and the results of water conservancy and stress monitoring support the rationality of the system. And through the implementation of impact prevention and control measures, the safety and disaster prevention and control of the working face was finally realised.

Triaxial mechanical behaviour and energy conversion characteristics of deep coal bodies under confining pressure

To understand more about damage, failure, and transformation of coal, this paper performed triaxial loading tests on coal samples obtained from a deep coal mine in China. Results showed that the brittle failure characteristics of the specimens were obvious under single-axis loading, and that the ductile failure characteristics of the specimens increased as confining pressure increased. The ultimate strength and residual strength of the samples exhibited a sound linear growth relationship with confining pressure. And according to the change trend of damage variable with axial strain, the damage process of coal body is divided into four stages: initial damage stage, stable damage stage, rapid damage stage and damage failure stage. The energy conversion characteristics of the samples were thoroughly analysed and it was found that with the increase of confining pressure, the proportion of elastic energy of coal samples increases, while the proportion of dissipated energy decreases, indicating that confining pressure can inhibit the expansion of fractures and strengthen the energy storage capacity of coal samples. It was also discovered that the greater the confining pressure, the greater the ultimate elastic energy of the samples. This study is of great significance for mastering high energy level disasters in deep mines.

Identifying an over tenfold variation in carbon intensities of coal mines in China by multi-scale multi-benchmark accounting

Complete and accurate accounting of greenhouse gas (GHG) emissions from coal mines in China is a critical basis for identifying mitigation potential and making reduction strategies. Previous studies based on the emission factor method and life cycle assessment are limited in accounting scope completeness, data reliability, or result applicability at multiple scales and benchmarks. The objective of this study was to carry out a multi-scale multi-benchmark GHG accounting of Chinese coal mines to build a shared understanding and facilitate discussion on this topic. We established a complete accounting model to cover upstream indirect, direct, and downstream indirect GHG emissions related to coal mining. A total of 1151 operating coal mines were investigated to model site-level carbon emissions based on mass and energy benchmarks and then aggregated to 99 cities, 19 provinces, and the country for accounting. The results showed an over 14-fold variation in mass-based site-level accounting, with the highest uncertainty of less than 15%. This variability performed almost the same at city-level aggregating, whereas narrowed to over twofold at the provincial level. Energy-based accounting presented an over 17-fold variation at the site-level with a similar uncertainty to mass-based accounting. Such variability was narrowed to over sevenfold and approximately threefold in the city- and province-level aggregations, respectively. The national average mass- and energy-based carbon footprint of coal mining were 0.39 kg CO2-eq/kg and 0.0185 kg CO2-eq/MJ, respectively, in which approximately 36% of the total GHG emissions were omitted if mining methane escape was reported only. These results suggest improving the methane utilization rate and optimizing coal production and consumption patterns, which implicates cleaner production and sustainable development strategies for the coal industry in China. The conclusions are helpful to identify individual carbon emission gaps, clarify regional emission responsibilities, coordinate the national carbon neutrality process, and promote a low-carbon coal supply system.

Numerical simulating of pre-grouting in multi-jointed rock mass in deep coalmine roadway excavated via TBM

Tunnel Boring Machines (TBMs) have been used in many underground coal mines in China in recent years, most of which are open-type. The open-type TBM is unfavorable to advance in complex geological conditions, especially in heavily jointed rock mass. When the TBM advance in multi-jointed soft rock mass, the surrounding rock frequently damages and deforms around the tunneling face uncontrollably, which brings risk for the workers and reduces the advance rate. Pre-grouting the rock mass ahead before excavating is a common measure used to handle the above-mentioned condition. However, it is difficult to evaluate how the slurry diffuses and how it enhances the rock mass. Therefore, it is short of guidance to determine the parameters of the pre-grouting. In the present research, a 3D Ubiquitous-Multiple-Joint (UMJ) model was first proposed to simulate the mechanical behavior of rock mass affected by multiple sets of joints around the excavating face of TBM. Then, a seepage model with an equivalent anisotropic permeability tensor was proposed to simulate the diffusion of slurry in the jointed rock mass for pre-grouting. Following the in-situ action, the numerical model was first excavated using the UMJ model and then grouted according to the equivalent permeability tensor. After that, the grouted rock mass was enhanced by improving the mechanical parameters of joints. The effect of pre-grouting reinforcement could thus be simulated. Using the method, this paper studied the effect of grouting parameters and proposed some suggestions for TBM tunneling in multi-jointed rock mass.

Variance Analysis in China's Coal Mine Accident Studies Based on Data Mining.

The risk of coal mine accidents rises significantly with mining depth, making it urgent for accident prevention to be supported by both scientific analysis and advanced technologies. Hence, a comprehensive grasp of the research progress and differences in hotspots of coal mine accidents in China serves as a guide to find the shortcomings of studies in the field, promote the effectiveness of coal mine disaster management, and enhance the prevention and control ability of coal mine accidents. This paper analyzes Chinese and foreign literature based on data mining algorithms (LSI + Apriori), and the findings indicate that: (1) 99% of the available achievements are published in Chinese or English-language journals, with the research history conforming to the stage of Chinese coal industry development, which is characterized by "statistical description, risk evaluation, mechanism research, and intelligent reasoning". (2) Chinese authors are the primary contributors that lead and contribute to the continued development of coal mine accident research in China globally. Over 81% of the authors and over 60% of the new authors annually are from China. (3) The emphasis of the Chinese and English studies is different. Specifically, the Chinese studies focus on the analysis of accident patterns and causes at the macroscale, while the English studies concentrate on the occupational injuries of miners at the small-scale and the mechanism of typical coal mine disasters (gas and coal spontaneous combustion). (4) The research process in Chinese is generally later than that in English due to the joint influence of the target audience, industrial policy, and scientific research evaluation system. After 2018, the Chinese studies focus significantly on AI technology in deep mining regarding accident rules, regional variation analysis, risk monitoring and early warning, as well as knowledge intelligence services, while the hotspots of English studies remain unchanged. Furthermore, both Chinese and English studies around 2019 focus on "public opinion", with Chinese ones focusing on serving the government to guide the correct direction of public opinion while English studies focus on critical research of news authenticity and China's safety strategy.

Analysis of Mining-Related Injuries in Chinese Coal Mines and Related Risk Factors: A Statistical Research Study Based on a Meta-Analysis.

Coal mine injuries commonly occur, affecting both the safety and health of miners, and the normal operation of the coal mine. Accordingly, this study aimed to explore the regularity of injury and injury-related risk factors in coal mines in China so as to establish a scientific basis for reducing the incidence and promoting the prevention and control of injuries. A meta-analysis of casualty cases and injury-related risk factors from 1956 to 2017 in China was conducted utilizing data from six databases, including CNKI, Web of Science, PubMed, Medline, Embase, and Wanfang data. Summary estimates were obtained using random effects models. There were statistically significant variations in coal mine accident types, types of work, injury sites, age, experience, months, and shifts (p < 0.001). Eight types of accidents were susceptible to the risk of injury, and the greatest risk was presented by roof-related accidents (odds ratio (OR) = 0.46, 95% confidence interval (CI) = 0.32-0.6). Coal miners and drillers were at a greater risk of injury (OR = 0.39, 95% CI = 0.35-0.44; OR = 0.22, 95% CI = 0.17-0.26, respectively). The extremities and the soft tissues of the skin were at the greatest risk of injury (OR = 0.44, 95% CI = 0.3-0.58; OR = 0.23, 95% CI = 0.1-0.48, respectively). Compared with other ages, miners aged 21-30 were at a greater risk of injury (21-30 years, OR = 0.45, 95% CI = 0.42-0.47; 31-40 years, OR = 0.29, 95% CI = 0.25-0.32; <20 years, OR = 0.13, 95% CI = 0.03-0.23; >40 years, OR = 0.17, 95% CI = 0.09-0.25). Compared with other miners, those with 6-10 years of experience were at a greater risk of injury (6-10 years, OR = 0.29, 95% CI = 0.25-0.32; 2-5 years, OR = 0.33, 95% CI = 0.25-0.41; <1 year, OR = 0.22, 95% CI = 0.08-0.33; >11 years, OR = 0.22, 95% CI = 0.17-0.27). During the months of July to September, the risk of injury was elevated (7-9th months, OR = 0.32, 95% CI = 0.25-0.39; 10-12th months, OR = 0.24, 95% CI = 0.16-0.31; 1st-3rd months, OR = 0.22, 95% CI = 0.16-0.28; 4-6th months, OR = 0.21, 95% CI = 0.16-0.27). In the three-shift work system, the risk of injury was higher during night shifts (22:00-06:00, OR = 0.43, 95% CI = 0.3-0.56; 14:00-22:00, OR = 0.3, 95% CI = 0.23-0.27; 06:00-14:00, OR = 0.27, 95% CI = 0.18-0.35). The results of this research study reveal that coal mine injuries are prevalent among coal miners. These injuries are often related to the age, experience, months of work, and the three-shift work system of miners.

Construction and Application of VR-AR Teaching System in Coal-Based Energy Education

Coal-based energy has provided strong support and made outstanding contributions in the process of China’s economic development. Coal mining in China has gradually developed into intelligent, refined and green mining. However, due to the lack of effective science popularization and propaganda in coal mining for a long time, people’s understanding of coal mining often stays in the stereotype of dirty, messy and very dangerous. Based on this fact, this paper firstly discusses the difficulties and pain points of the popularization of science in coal mining based on the questionnaire survey. And then a VR-AR system for intelligent coal mining was developed. Finally, popular science teaching activities based on VR-AR system were carried out during the “Open Day” activity and “Entering Campus” activity. It is found that the long-term negative reports of coal mining and the complexity of coal mining system make the science popularization and propaganda in coal mining less effective. The proportion of primary and secondary school students with bad impression reached 85.0% and 90.3%, respectively, and 63.1% for college students. With our VR-AR system in coal-based energy education, the impression of the coal industry has increased significantly, the proportion of bad impression decreased to 23.4%. This helps to form the nationwide coal mining science popularization and justifies China’s coal mining.

Insights into fundamental problems of rockburst under the modern structure stress field

Rockbursts are some of the most severe dynamic disasters in coal mines. In this paper, the discrimination method of the tectonic stress field is proposed by analyzing the modern stress field in China. The tectonic stress field formed by modern tectonic movement guides in situ stress measurements. According to the stress state classification, most rockbursts in coal mines in China are closely associated with tectonic stress. For tectonic stress-driven rockbursts, modern tectonic movement and modern tectonic stress fields must be considered. The stress change and energy transfer caused by tectonic movement affect the geological structure where coal mines are located. Energy accumulation under rockburst conditions is mainly formed by natural geo-dynamic movement and the mining configuration, and energy accumulation is the basis for rockbursts. The application of the geo-dynamic environmental evaluation method to determine the coalfield geo-dynamic process and the influence of modern tectonic movement is proposed. Accordingly, the classification method of rockbursts in coal mines is established. Based on the distribution characteristics of modern tectonic conditions in China, it is revealed that these dynamic disasters follow a “110” distribution. Finally, a “three condition” criteria of rockbursts is proposed: the geo-dynamic environment is a necessary condition for rockbursts, mining disturbance is a sufficient condition for rockbursts, and risk-releasing measures are a condition controlling rockburst risk mitigation.

Instability Mechanism and Surrounding Rock Control Technology of Roadway Subjected to Mining Dynamic Loading with Short Distance: A Case Study of the Gubei Coal Mine in China

Instability Mechanism and Surrounding Rock Control Technology of Roadway Subjected to Mining Dynamic Loading with Short Distance: A Case Study of the Gubei Coal Mine in China

The strata movement and ground pressure under disturbances from extra thick coal seam mining: a case study of a Coal Mine in China

The strata movement and ground pressure under disturbances from extra thick coal seam mining: a case study of a Coal Mine in China

Precise application of grouting technology in underground coal mining: water inrush risk of floor elimination.

Many coal mines in China suffer from the Ordovician limestone (OL) and Carboniferous limestone (CL) containing water inrush frequently due to the complex geology condition; water inrush has become a serious disaster in coal mining. To prevent water-bursting disaster from the floor of mine and cutting down deaths and economic loss, a grouting method for limestone fracture aquifer has been widely adopted. In this paper, a time-dependent empirical grouting model considering (1) time-dependent behavior of the injected slurry, (2) response of the rock, and (3) interaction between the slurry and rock was proposed to describe the slurry diffusion mechanism in rock fracture. Aiming at the problem of water disaster prevention of a coal seam floor in 16,104 working face of Luxi coal mine, that was, the grouting failed to seal the water flow channel of aquifer, the causes of the failure of grouting for water sealing were analyzed. According to the aquifer parameters and model calculation results, a grouting scheme with a slurry diffusion radius of 20m and grouting pressure of 8MPa was proposed; 2 rounds of grouting were implemented, following the split spacing principle, to ensure that finer fractures can be sufficiently sealed. Finally, with the comparative analysis through the network parallel electrical method (NPEM) and the drilling exploration method for water-rich areas before and after grouting, it was verified that the grouting effect for floor limestone aquifer was good, and the grouting scheme proposed and the grouting pressure designed were reasonable. Results may provide reference to a karst fractured aquifer grouting project, as well as reduced the losing because of blindness and experience.