Coal Excavation Research Articles

Implications of Coalfield Dynamics on Associated Ecosystems: A Tangential Review

Traditionally, the coal has stood as a resourceful entity for the energy demands of the society. The coalmines are the driving forces in the sufficing the energy and economy of the nation. Certainly, the existence of coal and its excavation is a much aspired endeavours for the development of any society. There are numerous prospective, functional and abandoned coalmines all over the world. Along with the intrinsic worth of the coal excavations, many studies have decisively elucidated the associated environmental complications. The ecological devastation is one of them. The ecological sphere whether it be macro or micro, is a fragile entity and must be taken care of accordingly. The process of coal excavations involves large scale landscape alteration where the entire native vegetation is removed. The ecological domain developed through an extensive period over the landscape vanishes in no time. The hydrological fluctuation also in terms of water chemistry destroys the aquatic habitat prominently known as hydroecology. The microclimatic shift is also a factor affecting drastically on the associated ecologies. The present review article strives to understand the various influencers in the coalfields dominating over the accompanying ecologies through selective endeavours executed all over the world. It also deliberates the probable measures to be taken to shield the associated ecologies in and around coalfields including the sensitization drives for protecting ecologies.

Semi-continuous cultivation of microalgae to treat coal mine effluent in pilot scale: Nutrient removal, biodesalination and fatty acid composition analysis

Coal excavation is associated with discharge of an enormous amount of mine water rich in salt and trace metal ions, which require efficient treatment before use. Considering the potentiality of microalgae for high salt tolerance, salt removal and metallic pollutant removal from aqueous system, present study focuses semi-continuous cultivation of candidate microalgae Chlorella pyrenoidosa (NCIM 2738) in bubble column reactor (BCR) and open raceway pond (ORP) for nutrient supplemented coal mine effluent (NSCME) treatment. In between different hydraulic retention times (HRTs), HRT 6 d provide maximum average biomass productivity of 950 mg L−1 d−1 in BCR and 728.4 mg L−1 d−1 in ORP. HRT 9 d facilitates a maximum lipid content of 1.8 g L ̶ 1 in BCR and 1.4 g L ̶ 1 in ORP. Further, HRT 9 d had the maximum COD removal efficiency (96.5 % in BCR and 94.2 % in ORP) and maximum salinity removal efficiency (93 % in BCR and 92 % in ORP). Fatty acid methyl esters (FAME) characterization highlighted potential biodiesel applicability with cetane number (CN) of 53.94. Energy dispersive X-ray spectroscopy (EDS) revealed an excess amount of salt and metal ions deposition on the surface of harvested microalgae samples. Outdoor large-scale C. pyrenoidosa cultivation can be integrated with coal mine closure plans to meet sustainable development goals (SDGs) 6, 7 and 13.

Taxonomic and functional diversity along successional stages on post-coalmine spoil heaps

Coal is the most abundant fossil fuel in Europe, but the excavation of hard coal has covered large areas with disposed rock waste, and turned the natural habitats into disturbed novel ecosystems with harsh conditions differ in time and space. To examine the spontaneous complex successional gradient, we studied a large number of post coalmine heaps in Upper Silesia, which differ in vegetation type and age. Cluster analysis based on plant community composition (367 species in total) separated all surveyed plots on coal mining spoil heaps with herbaceous vegetation from Late Stage (LS) forests aged 14–56 years. Furthermore, the herbaceous vegetation was sub-grouped to three stages: Initial Stage (IS) aged 2–5 years, Early Stage (ES) aged 3–8 years and Mid-Stage (MS) aged 5–12 years. MS vegetation was characterised by the highest species richness and diversity (47 and 2.79) compared to ES (30 and 2.18) and IS (9 and 1.6), but higher species number and a similar diversity index occurred in LS (37 and 2.81). Functional diversity (FD) and community weighted mean (CWM) of nine functional traits showed higher (23.1) functional richness, higher (0.72) functional divergence, higher (4.5) functional dispersion, and higher value (24.4) of Rao’s quadratic entropy in LS compared to those calculated from the first three stages. Species at the initial successional stage (IS) were characterised by lower canopy height, seed mass, higher lateral spread, and specific leaf area (SLA). Additionally, the lowest (0.22 mg CO2 per hour per square metre) soil respiration (Sr) rate was recorded from IS compared to (0.53, 0.82 and 1.00) from ES, LS and MS, respectively. The soil water content (SWC) was the most important factor affecting the soil respiration, while the soil temperature (St) did not follow the well-studied relationship between soil respiration and soil temperature. Our spatial and temporal analyses illustrated changes in plant community assembly processes in the course of spontaneous vegetation succession on post coalmine spoil heaps. The importance of trait mediated abiotic filtration in community assembly in initial-, early-, and mid-stages of succession with an increase in competitive exclusion at the late successional stage was emphasized.

Process Mining of Mining Processes: Analyzing Longwall Coal Excavation Using Event Data

Process Mining of Mining Processes: Analyzing Longwall Coal Excavation Using Event Data

RANCANGAN TEKNIS DAERAH TANGKAPAN HUJAN UNTUK MENGURANGI PENGIKISAN BIDANG LERENG DAN MENCEGAH AIR LIMPASAN DENGAN METODE CROSS FALL PADA TEMPAT PENYIMPANAN TANAH PUCUK

Mining activities often cause environmental damage, such as landslides, floods and ecosystem changes. These activities include land clearing, top soil stripping, overburden stripping, coal excavation, coal transport and processing. It is necessary to have an activity as an effort to rehabilitate so that there is no sustainable environmental damage. Therefore topsoil storage must be carried out in order to return the post-mining area to green again. The consideration of replanting ex-mining areas uses a comprehensive environmental management strategy, especially in terms of handling nutrient-rich topsoil. Topsoil is peeled to a thickness of 0.5 – 1 meter using an excavator. Then it is stacked and stockpiled in a place that is safe from mining activities so that later it can be reused in reclamation activities. The purpose of this research is to obtain a technical design on the corner of the storage area to reduce the eroding impact of rain runoff or other mining activities. Where the method used is to calculate the erosion that occurs on each slope where the test is carried out with 4 different slope angles such as 20⁰, 25⁰, 30⁰ and 35⁰. After obtaining the erosion data, the researchers created an ideal design to reduce the impact by considering the balance aspects of the slope and the material itself. Where the recommended angle data obtained to reduce the eroding impact is 25⁰.

Particle swarm optimization support vector machine-based coal and rock cutting tool load spectrum identification method

The goal of this research is to achieve safe and efficient excavation of coal and rock tunnels with complex geological structures, and to enhance the self-sensing ability of coal and rock cutting equipment and tools. Particle swarm optimization support vector machine is used to identify the cutting state of disc cutting tools. EDEM finite element analysis software is used to analyze cutting process characteristics of the disc cutting tool when used to cut through coal and rock with different compressive strengths. Empirical mode decomposition is used to decompose the load spectrum characteristics; for this purpose, the first-order and seventh-order intrinsic mode functions containing all the feature information of the original signal of the load spectrum are selected. The sample entropy is calculated as the feature input vector. The extracted feature vector is input into the trained support vector machine model and the particle swarm optimization support vector machine model. By extracting the sample entropy of the load spectrum of the disc cutter as the feature vector, the particle swarm optimization support vector model is used to identify the cutting state of the coal and rock. The recognition accuracy of the support vector machine model before and after the improvement is compared and analyzed. The results show that compared to the unoptimized support vector machine, the support vector machine optimized by particle swarm optimization can identify the load spectrum of the coal more quickly and accurately. The recognition accuracy is 96,82%, which verifies the effectiveness of the particle swarm optimization support vector machine model in identifying the load spectrum of the coal and rock disc cutter.

Determination of the Caving Zone and Fracture Zone Heights by Using the LK-Means Algorithm

The caving zone and fracture zone frequently appear after coal excavation. However, the caving zone and fracture zone can hardly be obtained with an empirical equation. Therefore, identifying a proper method to determine the caving zone and fracture zone is critically important to engineering practice. In this paper, Universal Distinct Element Code numerical simulations were conducted. Furthermore, the LK-means algorithm was used to determine the caving zone and fracture zone heights. To verify the validity of the proposed method, two engineering case studies were used. It could be found that the height calculated by the proposed method agrees well with that determined in engineering tests. Hence, the proposed method can be used in engineering practice.

Feasibility study of concentration of chemical and physical parameters in excavated water coal mining as a cage fishing destination

A research was carried out on the feasibility of chemical and physical concentrations in coal mine excavation water for use in cage fisheries. This research aims to analyze the concentration conditions of chemical parameters (NH3, pH, Cu and Fe) and physical parameters (DO, temperature and turbidity) in water originating from coal excavations which are already in the form of lakes. Samples were prepared before analysis by adding concentrated nitric acid. Analysis of Cu and Fe concentrations was carried out using an Atomic Absorption Spectrophotometer (AAS), ammonia using a UV-Vis Spectrophotometer, DO concentrations were analyzed using the titration method, turbidity analysis using a nephelometer, temperature using a thermometer and pH using a pH meter. From the research results, it was found that the physical parameters of lake water from former coal mine excavations were pH, temperature, DO, NH3 and turbidity is suitable because it has not yet passed the quality standards for designation as a cage for cultivating freshwater fish. The concentration of the heavy metal Cu in coal excavation water has exceeded the quality standards set for cultivating freshwater fish and the metal concentration Fe has not exceeded the quality standards set. Research analysis of the average concentrations of heavy metals in water samples from former coal mining pools, namely Cu (0.166; 0.278; 0.284 mg/L), and Fe (0.020; 0.029; 0.023 mg/kg).

A Data-Driven Approach Using Enhanced Bayesian-LSTM Deep Neural Networks for Picks Wear State Recognition

Picks are key components for the mechanized excavation of coal by mining machinery, with their wear state directly influencing the efficiency of the mining equipment. In response to the difficulty of determining the overall wear state of picks during coal-mining production, a data-driven wear state identification model for picks has been constructed through the enhanced optimization of Long Short-Term Memory (LSTM) networks via Bayesian algorithms. Initially, a mechanical model of pick and coal-rock interaction is established through theoretical analysis, where the stress characteristic of the pick is analyzed, and the wear mechanism of the pick is preliminarily revealed. A method is proposed that categorizes the overall wear state of picks into three types based on the statistical relation of the actual wear amount and the limited wear amount. Subsequently, the vibration signals of the cutting drum from a bolter miner that contain the wear information of picks are decomposed and denoised using wavelet packet decomposition, with the standard deviation of wavelet packet coefficients from decomposed signal nodes selected as the feature signals. These feature signals are normalized and then used to construct a feature matrix representing the vibration signals. Finally, this constructed feature matrix and classification labels are fed into the Bayesian-LSTM network for training, thus resulting in the picks wear state identification model. To validate the effectiveness of the Bayesian-LSTM deep learning algorithm in identifying the overall picks wear state of mining machinery, vibration signals from the X, Y, and Z axes of the cutting drum from a bolter miner at the C coal mine in Shaanxi, China, are collected, effectively processed, and then input into deep LSTM and Back-Propagation (BP) neural networks respectively for comparison. The results showed that the Bayesian-LSTM network achieved a recognition accuracy of 98.33% for picks wear state, showing a clear advantage over LSTM, BP network models, thus providing important references for the identification of picks wear state based on deep learning algorithms. This method only requires the processing and analysis of the equipment parameters automatically collected from bolter miners or other mining equipment, offering the advantages of simplicity, low cost, and high accuracy, and providing a basis for a proper picks replacement strategy.

The Importance of the WF Coefficient in Forecasting Climatic Conditions in Coal Excavations

The Importance of the WF Coefficient in Forecasting Climatic Conditions in Coal Excavations

Health Risks of Exposure to Cadmium in Tila Fish in The Community of Kerta Buana Village, Kutai Kartanegara District

The presence of heavy metal cadmium in ex-mining ponds results from coal excavation and refining activities. Ex-mining ponds are used by the community for fishing and fish farming, the community uses ex-mining ponds. Communities often consume fish without fully understanding its quality and the potential health risks it poses. As a result, it is necessary to conduct community research on environmental health risk analysis (EHRA) as a first step to estimating or predicting health risks. The research was conducted for one month, from June to July 2022. Data collection was carried out using questionnaires, food models, and anthropometric measurements. Fish samples were collected from five different locations in ex-mining ponds, while human samples were taken from 20 respondents. The analysis of cadmium concentration in fish was done using the Atomic Absorption Spectrophotometry (AAS) method. The study's results showed that the highest number of samples was about 0.0006 mg/kg of cadmium, while all of the respondents had a risk level value (RQ) of less than 1. This indicates that none of the respondents faced any health risks. It is recommended that people know and pay more attention to the types and sources of fish produced.

Quantitative assessment of energy changes in underground coal excavations using numerical approach

Quantitative assessment of energy changes in underground coal excavations using numerical approach

Fabrication and application of porous materials made from coal gangue: A review

AbstractCoal gangue (CG), which is mainly generated during coal excavation, mining, and coal washing, is an industrial solid waste that is recognized as an environmental pollutant. The ever‐increasing amount of CG produced is a serious threat to the ecological environment and property safety, especially in China, which is the largest coal producer and consumer in the world. Considerable studies have investigated means for utilizing CG worldwide. This review summarizes and discusses various porous inorganic materials made from CG, including cement‐based porous materials, porous bricks, porous ceramics (cordierite and mullite) and glasses, porous geopolymers, zeolites, aerogels, and porous carbon materials. Different preparation processes and performances of each type of porous inorganic materials were reviewed. Porous CG‐based materials can be used as promising adsorbents for the removal of various pollutants and have good potential for use in construction industry as well as catalyst material applications. Besides, porous materials obtained from CG have also been tested as slow‐release fertilizers after the absorption of phosphate, as electrode materials, and as oil‐in‐water separation agents. The systematic summary of porous materials based on CG aims at promoting high‐value‐added applications for this waste. Future research directions for the use of CG as a raw material are also presented.

Experimental Study on the Dynamic Tensile Characteristics of Coal Samples.

As coal mines continue deep mining, the frequency of coal and rock dynamic disasters has also gradually increased. In this paper, dynamic tensile strength deformation, energy evolution, and crack development under an impact test were studied on Brazilian coal samples, using a split Hopkinson pressure bar (SHPB) test device. A high-speed camera was adopted to capture the failure process of the coal specimens. The research results demonstrate that when the impact velocity is greater than 4.75 m/s, the dynamic tensile strength of the vertical bedding direction is higher than that of the parallel bedding direction of the coal samples. With the increase in the impact velocity, the dynamic strain and ultimate strain rate of two types of coal samples are increased, and the average value of the first and second dynamic deformation moduli of coal samples shows decreasing characteristics. As the incident energy increases, the sum of reflected and transmitted energy increases, and the absorbed energy also increases in the two types of coal samples. The two types of Brazilian disc coal samples mainly showed tensile and shear failure characteristics. The dynamic tensile deformation characteristics of the two types of coal specimens are less affected by the impact angles. However, the crack propagation of coal samples was mainly influenced by the impact angles. The test results can be used for the prediction of coal and rock outburst in deep underground coal excavation.

In-situ experimental study on hydro-borehole technology application to improve the hard coal excavating techniques in coal mine

The hydro-mining technology is considered as a promising method of bituminous coal excavation. The paper presents the results of the in-situ experimental campaign and modelling of hydro-cutting technology application. The proposed innovative technology was tested in terms of the effects of the distance between the outlet of water from the nozzle and a sidewall, pressure of the water jet, as well as the type of a nozzle on hydro-mining effectiveness. The hydro-cutting tests of coal seam performed in the Experimental Mine “Barbara” in Poland proved that the increase in water pressure in the range 20–40 MPa only slightly affects the coal face structure, while high pressure, of 80–100 MPa, has a significant impact on a coal face structure. The experimental results also showed the major effects of operating time as well as the distance of the water jet on the effectiveness of coal face mining.

Movement Law of Overlying Strata and Abutment Pressure Redistribution Characteristic Based on Rigid Block

Abstract Roof movement induced by coal excavation is the immediate cause of rock pressure redistribution and strata behavior. The rigid block in PFC3D was used to generate a multijointed rock mass, and the PFC3D–FLAC3D coupling model was used to study the movement law of the highly developed structural plane of the overlying strata. Strata movement and abutment pressure redistribution characteristics were obtained. The numerical simulation results showed that the multijointed rock mass model reproduced a rock mass with highly developed structural planes. After coal seam mining, the immediate roof caved and filled the goaf, forming an irregular and regular caved zone. The immediate roof shear slipped along the coal wall. The fracture of the basic roof formed a fractured zone, and the maximum height of the fractured zone first increased and then decreased, exhibiting continuous slow subsidence. The fluctuation of the front abutment pressure was reduced, and the abutment pressure in the goaf jumps was discontinuous. The abutment pressure in the goaf was high in the middle and low on both sides. After the initial fracture of the basic roof, the stress concentration of some rock blocks in the goaf exceeded the in-situ stress, and the average abutment pressure increased with the working face advancing length. With the coal wall of the working face gradually moving away from the goaf, the abutment pressure of the goaf first increased and then remained unchanged; the porosity first decreased sharply and then declined slowly; the coordination number of particles rose sharply and then increased slowly, indicating that the goaf gradually stabilized. Similar simulation results indicated that the variation law of abutment pressure, caving characteristics of the immediate roof, and continuous slow subsidence of the basic roof were the same as those of the numerical simulation.

GPR is Used to Detect and Apply the Fault of the No. 2 Coal Seam of Yuwang Coal Mine

In order to accurately analyze the geological anomalies encountered in the tunnel of coal mine excavation, this paper uses ground penetrating radar to follow up and detect faults in front of coal excavation. Ground penetrating radar is a wide range of survey methods that can quickly cover large areas and locate gaps, while using other invasive methods to locate gaps is difficult and expensive. And the ground penetrating radar can infer details of the location of the fault and the length of the fault. Therefore, the manageability and non-invasive nature of ground penetrating radar makes it particularly suitable for advanced detection in coal mines.

Ground Stress Analysis and Automation of Workface in Continuous Mining Continuous Backfill Operation

The cost, complexity, lack of filling space and time create challenges in the longwall backfill operation, resulting in poor subsidence control and reduced productivity. This paper proposes an automated continuous mining and continuous backfill (CMCB) method by examining its key requirements and investigates the optimum sequence of coal panel (such as drifts) excavation to ensure ground strata control at relatively high productivity. The automated CMCB adopts the highwall mining technique underground, which enables easier automation at the workface. A numerical simulation of the Changxing coal mine in China was undertaken, and five different sequences of coal excavation were investigated, using the automated CMCB excavation parameters (assuming a 4 m width cut, 5 m mining height for a 200 m long coal slice) to determine the optimum sequence of resource excavation. The plastic zones and vertical displacement across the five models were analyzed. Simulation results of the 5 m high coal seam excavation show that the odd-even slice (OES) mining sequence, which has a vertical ground displacement of 74 mm, is the most efficient excavation method, due to its effective stress redistribution and lower induced ground displacement.

Corporate Responsibility For Environmental Protection And Management In Ex-Mining Land

Exploiting natural resources must be based on an environmental approach. This is reasonable because environmental problems are closely related to the process of population growth, which is the high demand for natural resources. One of the most widely used natural resources by humans for various purposes is coal. The negative impact of coal mining is that it triggers deforestation (deforestation) and exacerbates climate change. Therefore, in the exploration and exploitation management process, every mining material, especially coal, requires various AMDAL mechanisms as part of environmentally sound development management. Provisions regarding mineral and coal mining activities oblige mining companies to carry out reclamation and post-mining activities over the mining areas they manage. The scope of the implementation of reclamation activities starts from exploration, land clearing, excavation of topsoil and over burden, coal excavation, land management, revegetation including preparation of nurseries, and maintenance and evaluation of activity results. The implementation of reclamation is carried out no later than one month after there are no more mining business activities on disturbed land. Reclamation and post-mining activities are one of the obligations of mining business activities that should be taken into account.

Mining Hazards to the Safety of Segment Lining for Tunnel Boring Machine Inclined Tunnels

The segment lining is a new type of support structure for mining tunnels. The disturbance of coal excavation leads to the deformation of segment lining and has great hazards to the safety of the tunnels. Based on the tunnel boring machine (TBM) inclined tunnels in Xinjie mine, the ultimate span L0 of the rock beam on the top slab of the coal seam was calculated according to the bending (tension) damage theory. A numerical model was built to simulate the bottom area of the inclined tunnels. During the coal mining, the additional displacements and additional stresses of the segment lining were analyzed, and then the safety factors of the support structure were calculated. Finally, the width of the coal pillar to protect the inclined tunnels was determined. The results showed that the ultimate span of the rock beam on the top of the coal seam is 31.7 m, the deformation of the inclined tunnel has a fish-belly shape, and the deformation leads to the increase of maximum axial force and bending moment. For the inclined tunnels in Xinjie coalmine, a total width of 91.3 m of coal pillar must be reserved to keep the safety factor of the structure higher than 2.0 and prevent the inclined tunnels from the mining hazards.