Coal Extraction Research Articles

Analisis Pengendalian Persedian Bahan Pupuk Pada Kebun Kelapa Sawit Di PT Austindo Nusantara Jaya Agri Binanga

This research aims to investigate two aspects: (1) the methodology used to record the coal extraction process at PT Austindo Nusantara Jaya Agri Binanga, and (2) the effectiveness and efficiency of the current coal extraction system at PT Austindo Nusantara Jaya Agri Binanga. The research methodology used in this study falls into the domain of cross-sectional and qualitative investigations. The data collection process includes surveys and observations as the main methodology. After starting the verification process, the data entered undergoes analysis through techniques such as data cleaning, data processing, and interpretation of results.The research results show that the application of the Docflow method and fish bone diagrams in fish feeding at PT. Austindo Nusantara Jaya Agri Binanga, along with the use of feeding control procedures such as min-mix (s,S), System (s,Q), System (R,s,S), and System(R,S), is very effective and useful in feeding fish. During the land development phase, per meter counts are carried out to ensure that stocks are monitored and maintained in abundant quantities.

Effects of coal mining and climate-environment factors on the evolution of a typical Eurasian grassland

Coal mining can significantly impact vegetation evolution, yet the limited information on its patterns and driving factors hampers efforts to mitigate these effects and reclaim abandoned mines. This study aimed to 1) examine vegetation evolution in a semiarid steppe watershed in northeast China; and 2) characterize the driving factors behind this evolution. We analyzed the impact of twelve selected driving factors on fractional vegetation coverage (FVC) from 2000 to 2021 using a dimidiate pixel model, Sen's slope analysis, Mann-Kendall trend test, coefficient of variation analysis, and Geodetector model. At a significance level of α = 0.05, our findings revealed a south-to-north decline pattern in FVC, a significant decrease trend in proximity to coal mines, and a notable increase trend adjacent to river channels. Approximately 37% of the watershed exhibited low FVC, while the overall temporal trend across the watershed was deemed insignificant. Areas surrounding the mines experienced a substantial reduction in FVC due to coal mining activities, while FVC variations across the watershed were linked to precipitation, temperature, and soil type. FVC predictions improved notably when interactions between multiple two-way factors were considered. Each driving factors displayed an optimal range (e.g., precipitation = 63–71 mm) for maximizing FVC. Given the study watershed's status as a national energy base, understanding vegetation responses to coal mining and climate-environment changes is crucial for sustaining fragile terrestrial ecosystems and socioeconomic development. Achieving a long-time balance between coal extraction and ecological protection is essential. The study outcomes hold significant promise for advancing ecological conservation, vegetation restoration, and mitigation of environmental degradation in semiarid regions affected by extensive coal mining and climate fluctuations. These findings contribute to the strategic management of such areas, promoting sustainable practices amidst evolving environmental challenges.

Study on Aeolian Sand-Box Backfill Geomechanical Characteristics and Overlying Strata Control Effects

The aeolian sand-box backfilling method proves effective for environmentally friendly coal extraction in northwestern regions, including Xinjiang. This study investigated the geomechanical characteristics of aeolian sand-box backfill material and its control effects on overlying strata through indoor experiments, mechanical analysis, and numerical simulations. Uniaxial compression tests on models with varying mesh sizes, wire diameters, and dimensions revealed that larger mesh sizes and wire diameters increased the bearing capacity of the aeolian sand-box backfill material, while increasing dimensions had the opposite effect. A mechanical analysis of the metal mesh box deformation produced equations describing its restraining force. Subsequent experiments and simulations on models of different dimensions consistently demonstrated the material’s mechanical properties, with stress-displacement curves closely aligned. 3DEC5.2 software simulations highlighted the effectiveness of aeolian sand-box backfill material in controlling displacement and stress variations in goaf areas. Notably, smaller-sized backfill material exhibited a more pronounced impact on controlling overlying strata displacement and stress development.

Stress distribution and roof subsidence of surrounding strata considering in situ coal conversion and CO2 mineralization backfilling: Photoelastic experiments using 3D-printed models of mining faces and goafs

Coal, a reliable and economical fuel, is expected to remain the primary energy source for power generation for the foreseeable future. However, conventional mining and utilization of coal has caused environmental degradation and infrastructure damage. An in situ coal conversion method has been proposed to mitigate environmental problems and reduce CO2 emissions resulting from coal extraction and utilization. This method involves the in situ conversion and utilization of coal, backfilling of waste rock, and CO2 mineralization to backfill the goaf. In this study, the impact of mining and conversion activities on the surrounding strata was evaluated to ascertain the effectiveness and advantages of the in situ coal conversion method. Transparent stope models were created using three-dimensional printing technology. The stress distribution and deformation characteristics of the surrounding strata were examined using photoelasticity and digital image correlation methods. The results were compared with those obtained using the traditional backfill mining method. The comparison revealed that the disturbance to the surrounding strata was 14.4 times less in the in situ conversion method than in the traditional backfill mining method. Additionally, the disturbance height at the roof and the disturbance depth at the floor were 4.2 and 2.1 times lower, respectively. The roof subsidence in the in situ conversion method was 1.97 times less than that in the traditional backfill mining method. These results confirm the advantages of minimizing the disturbance to surrounding rocks and controlling the subsidence of roof strata.

Active–Passive Remote Sensing Evaluation of Ecological Environment Quality in Juye Mining Area, China

The coal industry is a crucial component of China’s energy sector. However, the persistent exploitation of coal resources has gravely impacted the ecological environment. While the Remote Sensing Ecology Index (RSEI) is predominantly used for assessing ecological quality, its primary focus has been urban or aquatic environments. There is limited research focused on the evaluation of the ecological environment quality in mining areas. Moreover, the information regarding surface deformation caused by coal mining extraction is an essential factor in the ecological monitoring of mining areas. Therefore, this study proposed the Modified Remote Sensing Ecology Index (MRSEI). This enhanced model merges active and passive remote sensing techniques and incorporates a deformation factor (Surface Deformation Index, SDI) to provide a holistic evaluation of mining area ecologies. Furthermore, for comparative verification, we developed the Eco-environmental Quality Index (EQI) model by selecting 12 ecological parameters and employing a hierarchical analysis. The Juye mining area in Shandong Province was selected as the region of study. MRSEI results from 2015 to 2021 indicate a decline in the ecological quality of the Juye mining area, with MRSEI values registering at 0.691, 0.644, and 0.617. The EQI model mirrors this decreasing trend over the same period. Despite MRSEI using fewer indicators, its assessments align closely with the multi-indicator EQI method. This validates the accuracy of the MRSEI method, providing reliable technical support for the monitoring and evaluation of ecological environment quality in mining areas.

Coal and Gangue Classification Based on Laser-Induced Breakdown Spectroscopy and Deep Learning.

During the extraction and processing of coal, a large amount of solid waste, collectively known as gangue, is produced. This gangue has a low carbon content but a high ash content, accounting for approximately 15 to 20% of the total coal yield. Before coal is used, coal and gangue must be effectively separated to reduce the gangue content in the raw coal and improve the efficiency of coal utilization. This study introduces a classification method for coal and gangue based on a combination of laser-induced breakdown spectroscopy (LIBS) and deep learning. The method employs Gramian angular summation fields (GASF) to convert 1D spectral data into 2D time-series data, visualizing them as 2D images, before employing a novel deep learning model-GASF-CNN-for coal and gangue classification. GASF-CNN enhances model focus on critical features by introducing the SimAM attention mechanism, and additionally, the fusion of various levels of spectral features is achieved through the introduction of residual connectivity. GASF-CNN was trained and tested using a spectral data set containing coal and gangue. Comparative experimental results demonstrate that GASF-CNN outperforms other machine learning and deep learning models across four evaluation metrics. Specifically, it achieves 98.33, 97.06, 100, and 98.51% in the accuracy, recall, precision, and F1 score metrics, respectively, thereby achieving an accurate classification of coal and gangue.

Distribution, occurrence and identification of dibenzofuran, benzo[b]naphthofurans and their alkyl derivatives in Gippsland Basin source rocks

Dibenzofuran, benzo[b]naphthofurans and a series of their alkylated isomers were identified in coal, coaly shale, and shale extracts from the Gippsland Basin (Victoria, Australia). The dibenzofuran series include C0-C4 dibenzofurans, and the benzo[b]naphthofuran series are composed of benzo[b]naphthofuran, methylbenzo[b]naphthofurans, and possible dimethylbenzo[b]naphthofurans. Seventeen C2 dibenzofurans isomers (including six new isomers) were tentatively identified in rock extracts from the Gippsland Basin. The distribution and contents of C0-C4 dibenzofurans are different for Eocene and Paleocene rocks, providing a source rock age diagnostic correlation tool. Biological origin is the main factor that controls the abundance and distribution of dibenzofuran, benzo[b]naphthofuran and their alkylated isomers, based on investigation of source-, environment- and maturity-derived parameters. Variations in the C1 dibenzofurans/dibenzofuran ratio and the benzo[b]naphtho[2,1-d]furan/benzo[b]naphtho[1,2-d]furan ratio may reflect local paleoclimate changes in the Gippsland Basin.

A novel process of gradient oxidation roasting-acid leaching for vanadium extraction from stone coal

Efficient green vanadium extraction is a research direction of stone coal. This study focuses on efficient green vanadium extraction of stone coal. A gradient oxidation roasting-acid leaching (GORA) process was proposed, which is additive-free and effectively improves the leaching efficiency with preliminary oxidation and further high-temperature reoxidation. The results of this study showed that 95.59 % of −0.074 mm particles were the most appropriate. The suitable roasting temperature and time for preliminary oxidation roasting were 650 °C and 0.5 h, respectively. A porous structure was formed with a specific surface of 2.61 m2/g, and a total pore volume of 0.0164 cm3/g. Further, the optimal conditions of high-temperature reoxidation roasting were 850 °C, 3 h, 35 % O2, and 600 ml/min. The best V2O5 leaching rate of the GORA was 68.89 %, which was 36.23 % higher than that of the raw ore. It was discovered that stone coal could withstand high temperatures without sintering after preliminary roasting. High-temperature reoxidation is a prerequisite for destroying the lattice of vanadium-bearing minerals and promoting vanadium release. Meanwhile, the loose and porous honeycomb particle products promoted subsequent gas–solid and liquid–solid reactions. Therefore, this study provides a novel and effective method for extracting vanadium from stone coal.

Assessing environmental health impacts of coal mining exploitation in Iran: A Rapid Impact Assessment Matrix (RIAM) approach for environmental protection

Environmental Impact Assessment is the process of evaluating the effects caused by a project on the environment. The outcomes generated by this assessment can lead to a reduction of the negative effects and an increase in the positive effects caused by mine projects. The present study was conducted to evaluate the environmental impact assessment of the Goliran Coal Mine in northern Iran. In the descriptive-analytical study, to achieve the objectives, observatory surveys were conducted around the coal mine using a checklist, which was about the positive and negative effects of a coal mine. Then the data were entered into the RIAM and the positive and negative effects were ranked and the most important effects were determined. In RIAM, one point is assigned to each component. 17 important activities for environmental impacts were identified using a checklist. Among the activities carried out at the coal mine site, the major ones included tunnel excavation, construction of the rail line collection and disposal of coal mine effluent, coal transportation, collection and disposal of mine tailings, and technical defects and leakage. The scores of each environmental factor were based on the four environmental components: physical/chemical, biological/ecological, social/cultural, and economic/operational. The results of the present study showed that the most negatively affected environmental components are the physical/chemical components derived from three activities; the construction of the underground tunnel; the construction of a coal transport rail line; and the actual transportation of coal extracts. The scores of each environmental factor based on the four components at the Goliran coal mine in northern Iran indicate that the highest negative score was -64, corresponding to the physical/chemical component, and was assigned to air pollution. On the other hand, the highest positive score corresponds to the economic/operational component with +54, assigned to the income that employees earn from the mine. Overall results showed that the coal mine in northern Iran had negative effects on the environment but the effects were not severe. It is suggested that for future research, corrective measures should be taken in the form of an environmental management plan to reduce the negative effects caused by coal mining, and then prospective research should be done to check the extent of reducing the negative effects.

UTILIZATION OF 100% WASTE OIL IN DELTA E EMULSION EXPLOSIVE MIXTURE FOR COAL OPEN MINE

The limitation of coal reserves poses a challenge for the mining industry to optimize coal extraction. Innovations are constantly being sought to enhance efficient productivity while considering environmental sustainability. The innovation of utilizing waste oil up to 100% as a substitute for fuel in the emulsion production process is expected to improve environmental quality without compromising blasting quality. The results showed that the fragment size (P80) in the 85% waste oil trial was 227.8 mm, while in the 100% waste oil trial, it was 325.1 mm. The recovery rate in the 85% waste oil trial location was 95.7%, whereas in the 100% waste oil trial location, it was 95.9%. The measured VoD in the 85% waste oil trial was 4636 m/s, while in the 100% waste oil trial, it was 4632 m/s. VOD numbers show that explosives performed well with no decrease in quality. No fumes appearance shows proper chemical reaction within explosives detonation. 100% waste oil usage is proven to deliver optimum blast results, hence providing efficiency on fuel saving and delivering additional value on recycled hazardous waste produced from mining activity.

Degradative solvent extraction of low rank coal: Structural evolution of extraction products

The degradative solvent extraction method was proposed to convert low rank coals into carbon-enriched products under mild condition. However, limitations in the understanding of the structure evolution of products and reaction mechanism of the extraction process hinder the targeted regulation of the products. Therefore, in this work the structural evolution of products during the extraction for different types of coals and by different types of solvents were investigated. Synthesized molecular structural models of the products were constructed and the reaction mechanism was then discussed. Results show that the industrial compounding solvent (ICS) is capable of extracting more single-ring aromatic organics from coals and increasing the yields of the main products by approximately 10% compared to 1-methylnaphthalene. During the extraction process, the main reaction of the sub-bituminous coal is the breakage of unstable chemical bonds and functional groups, while the reaction of lignite is the thermal decomposition and deoxygenation of massive small molecules in the coal. Moreover, the ICS promotes aromatization reactions during the extraction, which indicates that the ICS is the appropriate industrial solvent for the degradative solvent extraction. This research proved a theoretical guidance for the industrialization of DSE technology and the targeted regulation of the products.

Research on Prediction of Surface Deformation in Mining Areas Based on TPE-Optimized Integrated Models and Multi-Temporal InSAR

The prevailing research on forecasting surface deformations within mining territories predominantly hinges on parameter-centric numerical models, which manifest constraints concerning applicability and parameter reliability. Although Multi-Temporal InSAR (MT-InSAR) technology furnishes an abundance of data, the underlying information within these data has yet to be fully unearthed. Consequently, this paper advocates a novel methodology for prognosticating mining area surface deformation by integrating ensemble learning with MT-InSAR technology. Initially predicated upon the MT-InSAR monitoring outcomes, the target variables for the ensemble learning dataset were procured by melding distance-based features with spatial autocorrelation theory. In the ensuing phase, spatial stratified sampling alongside mutual information methodologies were deployed to select the features of the dataset. Utilizing the MT-InSAR monitoring data from the Zixing coal mine in Hunan, China, the relationship between fault slippage and coal extraction in the study area was rigorously analyzed using Granger causality tests and Johansen cointegration assays, thereby acquiring the dataset requisite for training the Bagging model. Subsequently, leveraging the Bagging technique, ensemble models were constructed employing Decision Trees, Support Vector Regression, and Multi-layer Perceptron as foundational estimators. Furthermore, the Tree-structured Parzen Estimator (TPE) optimization algorithm was applied to the Bagging model, resulting in an optimal model for predicting fault slip in mining areas. In comparison with the baseline model, the performance increased by 25.88%, confirming the effectiveness of the data preprocessing method outlined in this study. This result also demonstrates the innovation and feasibility of combining ensemble learning with MT-InSAR technology for predicting mining area surface deformation. This investigation is the first to integrate TPE-optimized ensemble models with MT-InSAR technology, offering a new perspective for predicting surface deformation in mining territories and providing valuable insights for further uncovering the hidden information in MT-InSAR monitoring data.

ПЕРСПЕКТИВНЫЕ НАУЧНО- ОБРАЗОВАТЕЛЬНЫЕ НАПРАВЛЕНИЯ ТЕХНОЛОГИЧЕСКОГО РАЗВИТИЯ УГОЛЬНОЙ ОТРАСЛИ

An outstanding input of Yury Malyshev in the reformation of coal mining has conditioned a technological development of the industry. Our reality dictates a further development of the new technologies, including the ones for underground coal extraction.

Разработка мощного пологого пласта с выпуском угля подкровельной толщи роботизированным комплексом

Introduction. When developing coal deposits using underground method, the greatest success was achieved for the seams with the thickness of up to 7 m by means of complex mechanization in one layer. The productivity of a cleared face reaches 6–8 thousand tons per day. A method of coal extraction from the top coal layer is used to mine seams of greater thickness. The limiting factor is the inability to control of the extraction process and, as a result, significant operational losses. Objective. The research aims to develop promising technologies for efficient and safe mining of thick flat coal seams using a robotic complex with controlled extraction from the top coal layer. Methods. The research is based on the analogy method. Results. By closing the gates installed on the extended sides of the line conveyor sections during the operation of the coal cutterloader and opening them during the release of coal, penetration of the loosened coal into the “pockets” of the support sections is eliminated. This reduces the operational loss of coal, the likelihood of “floating” sections of the support, as well as risks of emergencies. Due to the presence of an additional bunker on the side of the mined-out space, the coal from the top layer is collected, temporarily withheld, and then gravity fed into the outlet opening. Elimination of the advance preparation of the top coal layer in the area above the planned break-down chamber prevents man-induced discontinuities inside the rock mass above the breakdown chamber, which increases its stability. Construction of the break-down chamber with an inclination against the working face provides a sequential introduction of the support sections into the break-down chamber, one at a time, which allows timely preparation and release of coal.

Использование метода дискретных элементов для имитационного моделирования выемки угля очистным комбайном

Timulation modeling as a method of studying complex technological processes is successfully used in mining. Due to the creation of digital models, it is possible to estimate and improve the efficiency of technical and organizational solutions used in difficult mining and geological conditions. The article describes the development of a simulation model of coal extraction by a shearer and its transportation to an armored conveyer. Fragmentation of a high coal seam was simulated under the action of the cutting planes of the shearer. The created model in the Rocky DEM simulation environment takes into account the physical and mechanical properties of materials and 3D structures of mining equipment. The method of discrete elements was used as a mathematical tool for computing fragmentation of the coalbed, which helped to perform the computing without loss of the initial mass and volume of the materials. During the validation of the simulation model, a series of tests were carried out to determine the angle of natural slope of non-spherical coal particles close in granulometric composition to the mass formed during the fragmentation of the coalbed. Based on the test results, an array of values of coal particle adhesion parameters was obtained, which allows conducting simulation studies in conditions of existing and projected coal mines.

A Landscape-Scale Comparison of Wetlands Associated with Surface Coal Extraction and Naturally-Occurring Wetlands in the Central Appalachian Mountains, USA

A Landscape-Scale Comparison of Wetlands Associated with Surface Coal Extraction and Naturally-Occurring Wetlands in the Central Appalachian Mountains, USA

Energy prices volatility, natural resource policy-making and green economic recovery in post COVID-19 era: Evidence from BRICS countries

The connectedness of natural resource volatility and economic growth has been an area of central attention for academicians and researchers before and even after the COVID-19 pandemic. The global as well as the Asian financial crises have negatively impacted the natural resources and economic growth of countries. Literature lacks the impact of crises on natural resources especially in BRICS economies. Hence, the current study examines the agriculture, livestock, crude oil, metal, and, coal-based natural resource commodities in determining the sustainable economic growth of BRICS countries. To achieve the objectives, data from the GSC index (Goldman Sachs Commodity Index) and different World Bank indicators is collected over a period from 2002 to 2022 which also includes the era of Post COVID-19 pandemic. Augmented dicky fuller test is used to explore the stationarity of constructs while ECM (error correction model) and Granger causality test are used to capture the connectedness between the explanatory and dependent variables. The empirical results infer that prices of commodities based on agriculture, livestock, oil, coal, and valuable metals are positively linked with sustainable economic performance in BRICS Countries. The results may be supportive of accelerating economic growth by improving the extraction and consumption of natural resources, livestock, agriculture, precious metals, oil, and coal.

Fostering the National Interest: Utilizing Hungarian State Property in the Jiu Valley to Build a Modern Coal Industry

Abstract After the 1867 Ausgleich, the Kingdom of Hungary sought to foster coal extraction to fuel the growing needs of transport and industrialization. In developing the rich deposits of the Jiu Valley in Transylvania, the state did not wait for private, profit-driven development. Instead, the ministries in Budapest both developed state-operated mines in the region and supported private companies’ efforts, shifting the relative importance of each over the following four decades as the situation required. The ministries worked with private corporations to design model “company towns” and provided consistent support for their upkeep—demonstrating the extensive nature of state influence at the local level. The Jiu coal mines as a case study reflect that the Hungarian state saw property not simply in economic terms but as part of a wider framework of the modernization of the country, including its society. Royal Hungary’s property regime was one that provided legal recognition of the right to private property, but at the same time one in which the state frequently intervened to ensure economic development that served its perceived interests.

Thermal stability prediction of frozen rocks under fluctuant airflow temperature in a vertical shaft based on finite difference and finite element methods

There are abundant coal resources in the permafrost regions of the Qinghai-Tibet Plateau. Open-pit mining is the primary method for coal extraction due to its simple technology and cost-effectiveness. However, the mining process can lead to degradation in permafrost regions. Underground coal mining has been adopted as an option to minimize the impact on the permafrost environment. However, underground coal mining in permafrost regions, along with ventilation, can disrupt the thermal equilibrium of frozen rocks around the shaft, leading to changes in the permafrost table and the seasonal thawed layer around the shaft. Therefore, it is necessary to predict the temperature field of frozen rocks under mine ventilation. Some researchers focus on the temperature of frozen rocks in respect to constant airflow temperature. In fact, the airflow temperature in the shaft varies related to shaft depth, ground temperature, ventilation amount, and ventilation time. In this study, we utilize field data to construct two numerical models for predicting the temperature regime of frozen rocks. The first model, using the finite difference method, describes airflow temperature in the shaft within permafrost regions, accounting for variations in shaft depth, ground temperature, initial rock temperature, ventilation time, and ventilation amount. A fitting equation is then determined as a third boundary condition. The second model employs the finite element method to solve the heat transfer equation with phase change. The results indicate that the maximum thaw depth of frozen rocks around the shaft of Jiangcang coal mine ranged from 3.25 to 5.3 m at various shaft depths. This maximum thaw depth occurs on September 15th and is correlated with ventilation time, stabilizing after three years. Natural ventilation offers protection to frozen rocks around the shaft, and these results can serve as references for designing support systems in underground mining within permafrost regions.

Optimization and Application of Water Injection Process in Gas-Bearing Coal Seam

Coal seam pre-drainage technology is widely used to prevent and control gas in China’s high-gas coal seams, and upward drilling is a safe and reliable technology. Using the Luling Coal Mine as the study location, according to the actual situation of the site, a layer-through drilling process was proposed. Relying on a cross-layer extraction borehole, coal seam water injection efficiency extraction and high-efficiency water injection dust prevention can be performed in the later stage of borehole extraction, enabling one-hole multi-purpose and “gas-powder” integrated prevention and control. In order to study the “stress-seepage” coupling characteristics of the coal around the borehole, a numerical simulation of the coal seam water injection process was conducted. Based on the simulation results, a field test of water injection in coal seam upward drilling was performed. The field monitoring data show that the water injection and water content of the coal seam were increased by about 3.07 m3 and 0.69%, respectively, compared with the traditional water injection process. The water injection effect is remarkable, which is of great significance to ensure the safe and efficient production of the mine.