Coal Production Research Articles

Study on particle size and density segregation law in the separating process of poor quality coal with high gangue content under the action of composite force field

ABSTRACT Thin-seam mining frequently captures a significant proportion of gangue and interbedded coal in surface coal mines. Consequently, raw coal has a broad range of particle size distributions and a high percentage of components with intermediate densities, which are complex and challenging to separate. This study aims to determine the method of product division and the segregation law of particle size and density of raw coal during the separation process using a vibration and airflow composite force field. A difference in the particle size segregation of the coal particles was evident. Particle-size segregation primarily occurs in the separation area. Large-particle-size coal has a wide distribution range, spreading over the entire bed and fully utilizing the bed to achieve separation. The material becomes increasingly displaced into the separation area as its particle size decreases, thereby weakening the separation effect. Large coal particles can undergo density segregation in the vertical direction, with low-density material placed in the upper layer. This ensures that low-density material is incorporated into the refined coal product. Regardless of density, the coal tended to tilt more toward the bottom layer as the particle size decreased. This results in a poor density stratification effect with refined coal products mixed with gangue and an increase in the mismatch content. The extent of fine coal discharge was determined to be two-fifths of the entire length of the discharge side. This ensures that the majority of refined coal is recovered and that there is no excessive gangue mixing with the refined coal output. Achieving a 55.54% yield, refined coal lowers its ash content by 16%, increases its calorific value by 1400 kcal/kg, and effectively separates coal with a high gangue concentration.

Low-carbon development path based on carbon emission accounting and carbon emission performance evaluation: a case study of Chinese coal production enterprises.

Carbon emission accounting is the basic premise of effective carbon emission reduction and management. This study aimed to establish the carbon emission model and performance evaluation framework of coal mine production enterprises and clarify the low-carbon development path of enterprises. In this study, we took a typical coal production enterprise (K enterprise) in the Shanxi province of China as the research object. We also estimated the carbon emissions of the enterprise mainly according to the Chinese Carbon Emission Accounting Standard (GB/T 32151.11-2018). The triangular model was used to construct the carbon performance evaluation framework. On this basis, we suggested the enterprise's low-carbon development path. The results showed that (1) the carbon emission of K enterprise in 2021 was 36,875.38 tCO2eq; the carbon emission intensity of each ton of coal produced was 0.089 tCO2eq. The critical carbon emissions were electricity consumption and methane fugitive emissions during production. (2) The evaluation indicators for carbon emission performance revealed an imbalance in K enterprise's economic, energy, and environmental development in 2021. The work on energy saving and consumption reduction was relatively weak. (3) Countermeasures for low-carbon development, including a carbon emission ledger, were proposed based on carbon emission accounting and performance evaluation results. This study can help typical underground coal production enterprises in Shanxi province obtain more accurate carbon emission data, providing practical guidance and reference for the same underground coal production enterprises to improve the carbon emission control effect.

Experimental study on the mechanical characteristics of weakly cemented mudstone under different loading rates

With the gradual shift of coal mining to the western coal mining region of China, floor heave in weakly cemented mudstone roadways has become an issue affecting the safety and efficiency of coal mine production. Additionally, different mining rates can lead to fluctuating support stresses on the roof and floor of weakly cemented mudstone roadways. Therefore, obtaining a comprehensive understanding of the mechanical properties of weakly cemented mudstone at different loading rates is conducive to improving the issue of floor heave in such roadways and provides a theoretical basis for further study. In this context, a series of uniaxial mechanical tests with concurrent acoustic emission monitoring were conducted on specimens of weakly cemented mudstone under various loading rates (0.005, 0.01, 0.05, and 0.1 mm/s). The stress‒strain and acoustic emission response curves were obtained to effectively characterize the strength, deformation, damage, macroscale instability, and crack propagation characteristics of the mudstone under the influence of loading rate effects. The research results support the following findings: (1) With increasing loading rate, the peak strength and elastic modulus of weakly cemented mudstone significantly increase, while the peak axial strain and peak radial deformation significantly decrease. (2) With increasing loading rate, the stress required to trigger the expansion of weakly cemented mudstone gradually increases, and a significant power-law relationship arises between the strain of the mudstone at the start of expansion and the loading rate. (3) With increasing loading rate, the acoustic emission ringing count of weakly cemented mudstone increases: The failure of weakly cemented mudstone changes from small-range progressive failure to sudden failure, and the failure mode transitions from shear failure to tensile‒shear composite failure. (4) The studied mudstone damage variables increase with increasing loading rate, following an approximate exponential function. The conclusions obtained in this work can provide a theoretical basis for the evolution mechanism and control of floor heave in deep roadway mining.

Analysis of Indonesian coal export policy

Indonesia's coal exports play an important role in driving the country's economy and are one of its main export commodities. As one of the world's largest coal producers, Indonesia consistently contributes significantly to the global market. This research aims to provide an in-depth analysis of the export policy of coal commodities in Indonesia. The research method is qualitative, using a descriptive analysis approach. The study examines policies related to coal exports, including government regulations, trade rules, environmental regulations, and other policies that influence the Indonesian coal export process or policy changes that affect Indonesian coal exports. At the same time, it analyses the effects and implications of these policies on the export of coal commodities in Indonesia. The research uses the theory of trade liberalism as a framework to address the research objectives. The findings indicate that Indonesia's coal export policy significantly impacts the coal industry, the national economy and international market dynamics. Although mercantilism may persist for a certain period, the dominance of liberalism, which adheres to the principles of market mechanism, has successfully surpassed the influence of mercantilism. Thus, this research contributes to a better understanding of the role of coal in Indonesia's export context and provides a basis for future policy improvements.

Carbon emission and environmental cost from coal production in Indonesia

Indonesia primarily exports coal, with an average annual quantity of over 421 million tonnes in the past decades (2011-2020), reaching its peak at 616 million tonnes in 2019. Despite its economic benefits, coal production carries hidden costs. This research delves into using life cycle assessment (LCA) to gauge the environmental impact of coal production and estimate external cost (EC) related to Greenhouse gases (GHG) and air pollutants (AP). The study applied the benefit transfer method to make these estimations, focusing on coal mining and international transport processes. The findings revealed that over the past decades, per tonne coal mining contributed an estimated EC of $12.54-15.26 for GHG and $3,439-5,250 for AP, while transport abroad per-tonne-km coal incurred an EC of $19.98-23.94 for GHG and $19.58-23.30 for AP. Moreover, coal mining contributes to water pollution and substantial water depletion. Despite the coal production in Indonesia generating around $40 billion in revenue in 2020, the study shows that the total EC from GHG and AP is up to $2,131 billion, which is 53 times the revenue, posing serious health and ecological risks to Indonesians and exacerbating global climate change. Notably, these estimates exclude EC from water pollution (WP) and water depletion. With the global push towards ‘net zero emissions’, the coal industry as a whole faces an urgent need to curb its GHG and AP emissions from its.

Coal and Lignite Production

Current data on coal and lignite production, as well as a breakdown of production by country. Updated on a monthly basis.

TRAFFIC CAPACITY ANALYSIS OF EXISTING CONDITIONS WITH THE EFFECT OF ADDITIONAL COAL TRANSPORTATION TARGETS ON THE TANJUNG ENIM - TARAHAN RAILWAY LINE

The production volume target from 24.8 million tons in 2020 to 29.5 million tons in 2021 underlies the optimization of transportation availability in distributing coal mining products carried out by PT Bukit Asam Persero in achieving the growing target until 2023. In 2021, the Company will increase investment in developing business diversification, downstream coal. The railway network in Sumatra has a strategic role in serving the distribution of coal transportation. The railway line, which is directly connected to the location of the mining plant to port access and the availability of locomotive facilities and wagons that are very adequate, is an attractive option for mining companies and freight forwarders to establish coal transportation cooperation by rail. To meet the Babaranjang train tonnage target of 52 tons / year in accordance with the target of PT Bukit Asam (Persero), the Loop rail line design at TLS T4 PT Bukit Asam Muara Enim used the most effective classification. From the calculation results, 55 train trips are required per day to transport the production target of 57 tons / year in 2023. It is necessary to pay attention to the adequacy of the rail track from the TLS loop to Tanjung Enim Baru here it is necessary to conduct a study regarding the traffic from TLS to Tanjung Enim Baru because the number of trains set per day is 55 sets.

Experimental study on classification and identification method for fault signals of mining steel wire ropes

Abstract In the coal mining production process, wire ropes play a crucial role as the main tool for transporting personnel and materials in the entire coal mine hoisting system, and their fault identification is particularly critical. To address the problem of fault identification of mining wire ropes, a recognition model design combining K Singular Value Decomposition (SVD) with Genetic Algorithm (GA) optimized Support Vector Machine (SVM) is proposed. Firstly, K Singular Value Decomposition is used to denoise the collected wire rope damage signals. Feature vectors are extracted from the denoised and reconstructed signals to form the feature set of wire rope damage. Genetic Algorithm is utilized to select the optimal parameters of the Support Vector Machine and train it to obtain the optimal identification model for wire rope damage. Simulation and experimental results show that compared with wavelet thresholding and Empirical Mode Decomposition (EMD) denoising algorithms, the method using K Singular Value Decomposition for denoising achieves a signal-to-noise ratio of 25.166dB and a root mean square error of 0.805. Compared with Particle Swarm Optimization (PSO) optimized Support Vector Machine identification model, the identification rate of the Support Vector Machine identification model optimized by Genetic Algorithm is higher, reaching 96.67%. This method realizes accurate identification of different damage signals of wire ropes, which is conducive to ensuring the safe and efficient production of coal mines.

Extension Mechanism of Water-Conducting Cracks in the Thick and Hard Overlying Strata of Coal Mining Face

It is of great significance for coal safety production and water resource protection in the Yuheng mining area to master the evolution law of water-conducting fractures under the condition of thick and hard overburden. This research focuses on the 2102 fully mechanized mining face in the Balasu Coal Mine as the research background. The fracture evolution and strata movement characteristics in thick and hard overlying strata are simulated and analyzed by combining numerical simulation with physical simulation, and the formation mechanism of a water-conducting fracture in the overlying strata is revealed and verified by field measurements of the development height of “two zones”. The results show that the anisotropy of fracture propagation in low-position overlying strata is high, and the fracture propagation in high-position overlying strata is mainly vertical, which indicates characteristics of leapfrog development. The number and development height of fractures undergo the change–growth process of “slow–rapid–uniform”. Multiple rock strata together form a complex force chain network with multiple strong chain arches. The local stress concentration leads to the initiation of micro-cracks in contact fractures, and the cracks gradually penetrate from bottom to top and then the strong chain arches are broken. The water-conducting cracks in overlying strata show a dynamic expansion process of “local micro-cracks–jumping cracks–through cracks–water-conducting cracks”. The fracture between the caving zone and fracture zone presents obvious layered characteristics, the overall shape of the water-conducting fracture zone is “saddle-shaped”, and the maximum development height lags behind the coal mining face by about 180 m. Through the observation of water injection leakage and borehole TV observation of three boreholes under underground construction, combined with the results of water pressure tests, it is comprehensively determined that the height of the water-conducting fracture zone is 103.68~107.58, and the fracture–production ratio is 31.42~32.60, which is basically consistent with the results of numerical simulation and physical simulation. This research provides theoretical guidance and a scientific basis for coal mine water disaster prevention under similar geological conditions.

Оценка хозяйственных рисков при реализации технологий угледобычи в современных условиях недропользования

Introduction. This paper presents research in the field of methodology of assessment and monitoring of associated under ground coalmining risks in order to level their impact on the resulting technical and economic indicators of production and economic activities in modern conditions of subsoiluse. The functioning of technological systems of coal mining enterprises at the present stage of subsurface use occurs in a highly dynamic and highly variable functional environment with a fair degree of uncertainty, which is generated by a significant variety of parameters and characteristics of the initial mining, geological and mining engineering environment, which, in turn, generates the emergence of various groups and risk factors for subsurface use. The established procedures and methods of risk forecasting currently do not give satisfactory results due to the globalization of world markets and high volatility of prices for coal products. Leveling the negative degree of influence of the risk component on the resulting indicators – indicators of technical and economic activity can be achieved through the introduction of an operational system for assessing and monitoring various groups of risk factors. Materials and methods. For the purpose of evaluation, it is proposed to use the methodological and methodological foundations of the method called “vector norms”, which involves the use of Affine space, the constituent areas of compromises and the introduction of utility estimates. A complete model representation of the assessment and monitoring of the impact of various risk factors of subsurface use, taking into account their clustering and ranking, is presented. The algorithmic support of this method is reduced to the following components-iterations: 1. Formation of criteria-based assessment matrices of various factors of subsurface use risk groups. 2. Assignment of optima to evaluation criteria. 3. In order to ensure the legality of the use and implementation of mathematical procedures and operations, the reduction of multi-dimensional evaluation criteria to a relative form, taking into account the assigned optima. 4. Formation of the objective function of the “norm of the vector” (integral indicator) and the development of a procedure for selecting the optimal option. Since the use of the methodological and methodological foundations of the method called “vector norms” allows us to form quantitative estimates of the presented factors-types of risk of subsurface use, this makes it possible to implement the clustering procedure or ranking of a selected set of coal mining enterprises in conjunction with existing risk areas. Results. Quite high values of correlation coefficients were obtained with a significant closeness of the relationship of inversely proportional dependencies of generalizing integral indicators of the degree of risk and the level of achievement of planned indicators and development of production capacity with the level of operational profitability from the conduct of production and economic activities of coal mining enterprises with a directly proportional dependence on the operating costs of mining 1t of coal. Discussion. Сomplete model representation of the assessment and monitoring of the impact of various risk factors of subsurface use, taking into account their clustering and ranking, is presented. As a practical component of the research, variable series of areas of integral degree of risk in the functional environment of Kuzbass coal mines are presented. The use of software modules for correlation and regression analysis, taking into account three-year retrospective dynamics, made it possible to establish the legality and objectivity of the proposed methodological apparatus for integrated risk assessment of the implementation of coal mining technologies in modern conditions of subsurface use. Conclusion. The results of the implementation of the theoretical components of the methodology and model representations of the developed conceptual foundations for the integrated risk assessment of the implementation of coal mining technologies in modern conditions of subsurface use, taking into account five-year retrospective dynamics, showed that in the Kuznetsk basin there was a steady tendency to reduce the cluster of coal mines, which is characterized by high risks of carrying out production and economic activities in the presence of a disproportion of resource potential (the emergent part). The accompanying processes of formation of this trend are manifested in a quantitative increase in the functional units of the rating cluster of group 2B with an average resource potential and inherent moderate risk. It is within this cluster that strategies for prioritizing investments for the development and renewal of technological systems and structures of coal mining are being formed, since only they are able to provide the fastest possible return on invested funds. Resume. The article presents the results of research in the field of methodology for assessing and monitoring the risks associated with underground coal mining in order to level out their impact on the resulting technical and economic indicators of production and economic activity in modern conditions of subsoil use. The research results can be useful in the implementation of coal mining technology in modern conditions of subsoil use.

Recognition and Prediction of Precursory Feature Signals of Coal Mine Rock Burst Based on Random Forest and MK Trend Test

This paper aims to identify and predict the precursory characteristic signals of coal mine rock burst by employing the Random Forest and MK (Mann-Kendall) trend test methods. Initially, the study conducts data preprocessing and analysis on indicators such as electromagnetic radiation intensity, acoustic wave intensity, and type. It uses clustering methods to distinguish various data types and analyzes the data after visual representation. The visualization of data illustrates the distribution and trends, which aids in understanding the characteristics of the data, such as the upward trend observed in precursory feature data. During the data preprocessing phase, diagrams of various classes of data for Acoustic Emission (AE) and Electromagnetic Radiation (EMR) intensity are presented, providing an intuitive reference for subsequent analysis. The research utilizes the Random Forest algorithm and MK trend test to recognize precursor signals and predict their occurrence intervals. The Random Forest model is chosen for its efficiency and accuracy in handling classification and regression issues, while the MK trend test provides a statistical basis for identifying precursory signals by analyzing monotonic trends within the dataset. This study not only enhances the accuracy of precursory signal identification for coal mine rock bursts but also offers scientific early warning and control measures for coal mine safety production, which is of significant practical value.

The Influence of Reference Coal Prices, Earnings per Share, and Dividend per Share on Stock Prices in Coal Industry Companies in 2017-2022

This study aimed to analyze the effect of Reference Coal Price (HBA), earnings per share, and dividends per share on stock prices in coal industry companies in 2017-2022. The study used energy sector companies in the coal production industry sub-sector listed on the IDX for the 2017-2022 period as the object of research, using a sample of 13 coal industry companies that met the predetermined sample criteria and an observation period of 6 years so that the observation data amounted to 50 data. The data collection method uses secondary data taken from the company's financial statements from the Indonesia Stock Exchange (IDX) and the official website of each company sampled. The analysis methods used in this research are descriptive statistical analysis, normality test, multiple linear regression analysis, and hypothesis testing. Based on the results of data analysis and hypothesis testing, it shows that the HBA variable has a negative effect on stock prices, while the EPS and DPS variables have a significant positive effect on stock prices.

·OH Scavenger Optimized Grounding Electrode Atomization Corona Discharge Technology for Treatment of Coal Mine Acidic Wastewater

Coal mine acid drainage is a type of industrial wastewater generated in the process of coal production and utilization that has a low pH and contains a small amount of organic matter and SO42−, which is harmful to the environment. The ·OH scavenger was used to optimize the grounded electrode atomized corona discharge (GEACD) technology for the treatment of coal mine acidic wastewater. The effects of various factors on the discharge effect were investigated, and the optimal operating scheme for the subsequent test was determined as 35 mm distance between barrel electrodes, 0.6 mm diameter of wire electrodes, and a flow rate of 45 mL/min. The effects of discharge voltage, discharge time, and ·OH scavenger on COD removal rate and pH in coal mine acid drainage were also investigated. The results showed that at the optimum discharge voltage of 12 kV, discharge time of 66 min, and SO42− to ethanol concentration ratio of 1, the COD value decreased from 152.84 mg/L to 43.27 mg/L, and the pH value increased from 5.6 to 6.1.

Research on the Synergy between Economic Returns and Safety Investments in Enterprises

Coal, as a key input factor to ensure China's economic growth, plays an important role in the orderly development of its industry. The safety guarantee of production link is the only way to ensure the stable development of the industry, so it is in urgent need of the investment of safety funds and effective implementation to protect it. As a high-risk industry, the coal industry has a poor working environment, difficult working conditions, backward safety technology, and endless hidden dangers. In the process of development, the coal industry blindly pursues benefits while ignoring safety investment, which is exactly a common problem in China's coal enterprises and also the deep cause of coal mine safety accidents. This paper uses relevant theories to analyze the effect of coal enterprises' safety investment on economic benefit and determine its equilibrium point of safety and economic benefit. From micro level of building model, neural network model for coal enterprise economic benefit is explained variable, safety input as explanatory variables, core number of coal production, labor, labor productivity, and fixed assets and intangible assets investment as a intervening variable, such as inspection cause nonlinear relationship between safety investment and economic benefit are intermediary variables, measure the influence of different variables on economic benefit enterprise security mechanism, which integrated the result of theoretical analysis and empirical research, puts forward coal enterprises safety investment economic efficiency maximization of promotion strategy.

Coal in the 21st century: Industry transformation and transition justice in the phaseout of coal-as-fuel and the phase-in of coal as multi-asset resource platforms

The coal industry is enjoying long-term investments in new coal-fired power generation even as coal mining and production have been declining. Recent conflict in Europe has disrupted energy supplies and reinvigorated coal use. The duration of the retrenchment to coal may be short lived, but the end point of “short lived” remains uncertain. The present state of the coal industry and the investment community that underpins its growth obviates any meaningful acceleration in coal's phaseout as a core fuel resource. However, coal can be recast as a catalyst for achieving clean energy and economy futures. This can be done by seeing coal hydrocarbon deposits and byproducts of coal processing as long-term multi-asset resource platforms (MARPS), which integrate multiple new revenue streams on coal lands other than just mining coal as a fuel. New value comes from repurposing and leveraging mining lands, harvesting minor and trace elements from coal, and creating new revenue from harvesting hydrogen and carbon materials from coal bed methane, raw coal, coal tailings, and fly ash residues. We make the case that Coal Mining Enterprise (CME) value can be enhanced by ending the use of coal-as-fuel and creating new value streams serving existing and emerging markets by fully assessing, evaluating, and utilizing the portfolio of natural resources that are collocated within a typical coalfield. Coal sector investors tend not to see undervaluation in coal assets because CMEs focus predominantly on mining, processing, and shipping coal-as-fuel for electricity production and industrial processes. Formulating and asking the correct questions about how much value is being left on the table may bring innovation into a new frontier of coal as multi-asset resource platforms. Co-benefits of the approach include job creation across many viable emerging markets where “refining” coal is a competitive source of factor inputs. Moreover, it aids governments in aggressive support of coal industry transformations, through which lasting coal transition justice can be achieved. Ironically, despite all the technological and market uncertainties, coal in the 21st century can be, and should be, a critical success factor in achieving clean energy and economy futures.

The Decline of Paget’s Disease of Bone and Domestic Coal Use—A Hypothesis

The cause of Paget’s disease of bone (PDB) is unknown. It emerged as a distinct entity in Britain in the late nineteenth century when it was prevalent, and florid presentation not uncommon. Epidemiological surveys in the 1970s showed that Britain had a substantially higher prevalence of PDB than any other country. Studies in the late twentieth and early twenty-first centuries have documented an unexplained change in presentation, with a greatly reduced prevalence and less severe disease than formerly. The emergence of PDB in Britain coincided with rapid industrialization which, in turn, was driven by the use of coal for energy. In the home, bituminous coal was customarily burnt on an open hearth for heating. Using data on coal production, population size, and estimates of domestic use, the estimated exposure to domestic coal burning rose threefold in Britain during the nineteenth century and began to fall after 1900. This pattern fits well with the decline in PDB documented from death certification and prevalence surveys. Colonists moving from Britain to North America, Australia and New Zealand established coal mines and also used coal for domestic heating. PDB was found in these settler populations, but was largely absent from people indigenous to these lands. In all parts of the world PDB prevalence has fallen as the burning of coal in open hearths for domestic heating has reduced. The nature of the putative factor in coal that could initiate PDB is unknown, but possible candidates include both organic and inorganic constituents of bituminous coal.

Simultaneous removal of Ni2+ and Congo red from wastewater by crystalline nanocellulose - Modified coal bionanocomposites: Continuous adsorption study with mathematical modeling

Due to ultra-fast technological improvement and rapid urbanization nowadays, industries have generated a huge amount of wastewater that is discharged directly into the environment. Resulting in harsh damage to ecology and public safety/security by contaminating the ground/surface water sources. Therefore, it is very crucial to purify this wastewater before discharging/reusing. This study will be devoted to the latest enhancements along with the new route of production of the multifunctional Crystalline Nanocellulose-Modified Bituminous Coal (CNC-MC) bionanocomposites. Besides these, the significant implementation of the fabricated CNC-MC bionanosorbents for the simultaneous removal of Ni2+ and Congo red (CR) from bulk-scale industrial wastewater has been stated. Conversely, influential parameters like inlet concentration (25–45 ppm), flow rate (3–5 mL/min), and adsorbent bed height (0.2–0.8 cm) were explored. The bionanosorbents were characterized by using some state-of-the-art equipment such as FTIR-ATR, XRD, BET, FESEM, and TGA analysis, while the water samples were analyzed by AAS and UV-NIR techniques. Results suggested that the fabricated CNC-MC bionanocomposites possessed a considerable amount of active binding sites/functional groups, showed high thermal stability up to 700°C, and had a high crystallinity index (around 92.41 ± 0.009%). They revealed a noteworthy honeycomb-like mesoporous microstructure with a significant specific surface area. Due to these outstanding features, this multifunctional bionanosorbents has exhibited sensational adsorption performance. Meanwhile, the maximum removal efficiency and percentage were observed at approximately 328.7 and 478.3 mg/g, as well as around 67.95 and 76.65% for Ni2+ and CR. The experimental data was evaluated by three well-known column models, namely the Thomas, Adam-Bohart, and Yoon-Nelson models, and respectable agreement was found. That is similarly appropriate for the justification of the experimental breakthrough curve by supporting the Langmuir isotherm and 2nd-order reversible reaction kinetics. Hence, this novel CNC-MC bionanosorbent could be beneficially used to purify industrial wastewater in an economical and eco-friendly way for sustainable environmental safety.

Simulations on coal water slurry gasification by molecular dynamics method with ReaxFF.

Coal water slurry (CWS) is a new type of liquid coal product with low pollution, which is mainly used in the chemical industry to produce syngas (CO + H2). It is of great significance to study the microscopic mechanism of CWS gasification reaction for improving the efficiency of coal gasification. In this paper, the method of molecular dynamics based on reaction force fields (ReaxFF-MD) is used to study the gasification process of CWS/O2 system at different temperatures. The results show that, in the range of 1600-2400 K, the macromolecular network structure of lignite is decomposed into a large number of small molecular structures and a small number of light tar free radical fragments, and the types and quantities of reaction products increased rapidly. At 2400-4000 K, the free radical fragments of light tar are further decomposed and reacted with gasification agents, but the types and quantities of reaction products have little change. At 3600 K, a full gasification reaction occurred in the system, and the content of syngas is the highest. The model was established and optimized by Materials Studio (MS) software. Based on ReaxFF-MD method, Lammps software was used to simulate the gasification process of CWS/O2 system, and the reaction force field files containing C, H, O, N, and S element were used. By calculating the activation energy of gasification reaction, the rationality of the model and calculation method was illustrated. The post-processing of the results was implemented using OVITO, ChemDraw software, and self-programmed Python scripts.

Full-scale study on the coupling settling behavior of droplets and PM10 particles based on the CLSVOF method and wetting experiments

Coal mines produce large quantities of dust during production and transportation of coal, especially respirable particulate matter of diameter < 10 µm (PM10). This not only jeopardizes the health of workers but also pollutes the environment. Currently, spraying is the most commonly used dust reduction technology. Traditional spraying techniques use pure water; however, the wetting and condensing of dust by pure water droplets is poor, resulting in low dust reduction efficiency. To address this issue, we used orthogonal tests to determine the optimal ratio of composite dust-reducing agents. Using the coupled level set and volume of fluid (CLSVOF) method, we investigated the dynamic wetting process of PM10 when using solutions of dust-reducing agents. We found that a particle size ratio of ≥ 2 and an initial velocity of droplets of 20–40 m/s resulted in optimal wetting and encapsulation of dust particles by droplets. We then conducted macroscopic experiments and found that the settling efficiency of PM10 reached 88.98 % when using a 1.5-mm caliber fine atomizing nozzle and a spray pressure of 6 MPa. Our findings reveal the dynamic wetting law of droplets and dust during the process of spray dust reduction, which could lead to improved efficiency of dust-reducing agents and better management of respirable dust. These findings will help to improve clean production in coal mines and the occupational health of coal miners.

InSAR-CTPIM-Based 3D Deformation Prediction in Coal Mining Areas of the Baisha Reservoir, China

Time series dynamic prediction of surface deformation in mining areas can provide reference data for coal mine safety and production, which has important impacts. The combination of interferometric synthetic aperture radar (InSAR) technology and the probability integral method (PIM) is commonly used for predicting deformation. However, most surface subsidence prediction in mining areas is based on the static PIM parameters, failing to achieve the three-dimensional (3D) dynamic deformation prediction. This paper proposed a 3D deformation dynamic prediction model (InSAR-3D-CTPIM) between InSAR deformation observations and dynamic coordinate-time PIM (CTPIM) parameters, which can realize the prediction of east–west, north–south, and vertical series deformation caused by mining. The method has been validated by simulation experiments and real experiments in the mining area of Jiansheng Coal Mine in Baisha Reservoir, Henan Province, China. The results showed that the modeling accuracy was improved by 34.3% compared to the traditional multi-rate model, and the accuracy was improved by 28.5% compared to the vertical deformation obtained by the traditional static PIM method. The InSAR-3D-CTPIM model can be used to predict the evolutionary history of basin-wide surface deformation dynamics in coal mining areas, and provide a reference for the early warning and prediction of geological hazards in coal mining areas.