Coal Quantity Research Articles

Unveiling the heterogeneity of environmental impacts of China's coal washing plants by a configuration-specific life cycle assessment

Coal washing is considered a promising method of mitigating coal-induced air pollution in China because of the limited end-of-pipe treatment potential for coal pollution. However, the estimated benefits of coal washing have been overly optimistic due to the lack of comprehensive research on the environmental burden of coal washing and its related indirect impacts. Moreover, the specific coal quantity and quality requirements for various downstream sectors cannot be effectively addressed because the environmental effects of the differentiated scales and technologies used in coal washing plants have not been determined. The objective of this study is to quantify both the direct and indirect environmental impacts of Chinese coal washing plants and innovatively reveal the internal disparities and their formation mechanisms. A total of 2367 coal washing plants were investigated, and 20 configurations that combined both the washing scale and technology were categorized. Plant-level input and output data were modeled by the ReCiPe 2016 methodology to perform a configuration-specific life cycle assessment. The results showed that enlarging the plant scale increased the environmental benefits by 11.0–38.4 % in most cases. Washing coal via flotation and heavy medium methods generally resulted in higher environmental impacts of 2.0–16.0 % and 0.6–7.3 % compared to that of jigging due to the use of chemical reagents and medium powders, respectively. Different configuration structures across provinces induced spatially heterogeneous environmental impacts, which were high in southern and eastern China and low in northern and western China. The results highlighted the considerable environmental impacts of coal washing hidden in the coal production and consumption chain. Moreover, the findings reveal a spatially explicit configuration strategy for downstream-specific demands and show that enhancing solid waste utilization can reduce toxic environmental impacts.

Study on the evolution characteristics of molecular surface active sites of low-rank coal in low-temperature oxidation stage

Compared with other coal types of coal, low - metamorphic coal contains numerous active sites, making it susceptible to spontaneous combustion and posing significant risks during production, transportation, and storage. To further reveal the evolution characteristics and laws of low-rank coal's active sites during the process of low-temperature oxidation of coal (LTOC), X-ray photoelectron spectroscopy (XPS), 13C nuclear magnetic resonance (13C NMR), and Fourier transform infrared (FTIR) experiments were used to determine the basic structural parameters such as the valence state of non-carbon features, types of carbon elements in coal macromolecules, and structure and quantity of functional groups. Combined with molecular modelling software (GaussView 6.0) and macromolecular calculation software (Grimme-XTB), macromolecular models of coal at different temperature points were constructed, and the surface energy field distribution was calculated. The number and energy change information of chemical and physical adsorption sites of low-rank coal during heating were obtained. The results show that during the LTOC, the chemical adsorption sites such as aliphatic hydrocarbons (-CH3/-CH2) have higher reactivity and can be converted into oxygen-containing functional groups (-CHO, –OH, –COOH); the number of physical adsorption sites increased first and then decreased, and reached the maximum at 50 °C. Coal exhibited a higher affinity for O2 at this temperature. The peroxide (-C-O-O-H) undergoes thermal decomposition, leading to H2O and weight loss of coal. The –CO and –COO structures undergo decarboxylation to generate CO, CO2, and other gases. This study comprehensively revealed the evolution of active sites through two key coal oxygen processes, physical and chemical adsorption, based on the gradual temperature elevation of low-rank coal. This holds immense significance for improving and enriching the understanding of the mechanism of coal spontaneous combustion(CSC), preparing more targeted CSC inhibition, and formulating efficient fire prevention and extinguishing measures.

Research on the decision-making method of coal order price and coal purchase quantity based on prediction

The imbalance of coal supply and uncertainty of demand changes have brought great challenges to the stable supply of coal. In the actual trading process, there are problems such as variable demand and incomplete information on both, and the trading process lacks scientific and effective guidance. Therefore, game theory is introduced into the coal trading process, and a decision-making method based on predicted coal supply and demand order price and coal purchase quantity is proposed. Firstly, the prediction method is introduced, and the Long Short Term Memory (LSTM) and Autoregressive Integrated Moving Average Model (ARIMA) model are used to predict the coal purchase quantity and coal price of the supply and demand, which provides a basis for the formulation of the initial scheme of the bilateral game between supply and demand. Secondly, a bilateral game model of coal supply and demand based on prediction is established, and a bilateral order game-solving strategy of coal supply and demand based on a genetic algorithm is proposed. Finally, the proposed method was verified by setting up three different example scenarios for thermal coal trading, and the optimal coal price and coal purchase quantity under equilibrium are solved, and the results showed that the profit of supply and demand is increased by 4.65% and 2.97%, respectively, and the calculation time is reduced by 21.12%, which improves the speed of solving the game model, maximizes the benefits of both the coal supply and demand sides and provides a theoretical basis for the scientific and efficient order formation of coal mining enterprises.

Dynamic performance analysis and control strategy optimization for supercritical coal-fired boiler: A dynamic simulation

The flexibility of the coal-fired boiler depends on the control system, which is designed according to its dynamic characteristics. In this paper, a detailed dynamic model of a supercritical coal-fired boiler is developed in Dymola, and the necessary control models are built. The model is validated against the design values under various conditions with a maximum error of 2.19%. The model is further validated by comparing dynamic simulation results with operating data. Then, the dynamic behavior of the boiler is analyzed under the single- and two-parameter disturbances. When the feedwater temperature, feedwater flow, and coal quantity are all disturbed by −5%, the maximum deviations of the live steam temperature are −21 °C, +32 °C, and −34 °C, respectively. Compared to the simultaneous change of feedwater and fuel, the maximum value of the live steam temperature is reduced by 21.56 °C when the coal quantity is changed 100 s before the feedwater flow. Besides, a first-order inertia compensation element is developed ahead of the feedwater flow command, which effectively improves the performance of the water-fuel ratio control. As the load-variation rate increases, the deviation in the transient process of the thermodynamic parameters increases, and the time required for stabilization lengthens.

Variation of coal quantity accumulated in the Mississippian to Pennsylvanian coal seams (Upper Silesia and Lublin Coal basins, Poland): a reflection of changes in climate and CO2 availability

Many coal seams of varied thickness and aerial extent occur in the Upper Silesia and Lublin basins within Mississippian and Pennsylvanian coal-bearing deposits. Well-documented data on coal quantity in the seams identified allows visualization of their variation within the stratigraphic succession and analysis of the time-dependent coal accumulation process. Some characteristic features of this variation were observed. Coal seams of the Mississippian age (Serpukhovian, Paralic Series), formed within a near-shore environment, most often constitute small resources. There were only two intervals of increased coal accumulation in seams of >100 million tons, in the lower and uppermost parts of the Paralic Series. Within the Pennsylvanian coal-bearing succession of terrestrial fluvio-lacustrine origin, a specific, wave-like pattern of seam resource variations and four intervals of increased coal accumulation are observed. In the Lublin Coal Basin, the Lublin Beds only, deposited during the Late Bashkirian, are coal-bearing, in which a bell-shaped pattern of seam resource variation in the stratigraphic succession is observed. The location of enhanced coal accumulation events in the stratigraphic succession suggests their repetition at ~1–4 My intervals. The characteristic features of the quantitative variation in these coal seams may be correlated with glacial-interglacial and climate humidity changes, and interpreted as a response to variable volcanogenic CO2 supply.

Life cycle assessment of fly ash bottom ash in coal power plants: A review

Fly ash (FA) and bottom ash (BA) from coal combustion give environmental impacts and health problems. As the demand for coal increases, FABA quantity and environmental impacts will also increase. Thus, to reduce the environmental impact, the utilisation of FABA is key. To properly utilise FABA as a sustainable material, FABA’s life cycle in Indonesian power plants needs to be studied. For initial work and comparison, this study conducted a literature review related to Life Cycle Assessment (LCA) of FABA from coal-fired power plants. The literature review used descriptive method, with the criteria for the main articles’ selection are published papers within the last ten years. This paper discusses system boundary, inventory, environmental impact, improvement efforts, and challenges. The main beneficiaries of FABA are construction and geotechnical industries, other studies have also shown a wider range of uses in various fields. The wide utilisation of FABA faces challenges from the intrinsic character variation, non-technical issues, standards, and knowledge for proper utilisation in composite materials.

Numerical Simulation of the Temperature Distribution and Evolution Law of Underground Lignite Gasification.

To study the temperature distribution characteristics and evolution law of underground lignite gasifiers, a three-dimensional heat conduction model of underground lignite gasification was constructed. Moreover, the effects of different coal thicknesses, advance speeds of the flame working face, and surrounding rock types on the gasifier were analyzed. The results show that with the increase in the coal thickness, the transfer range and distance of temperature in the roof, floor, and coal seam gradually increase, as does the coal quantity in the three zones. The heat loss rate of the gasifier decreased gradually with the coal seam thickness. When the advance speed of the flame working face is 0.5 m/d, the ideal gasification coal thickness range of lignite is 2.5–17.5 m. With the increase in the gasification rate, the maximum transfer distance of temperature to the roof and floor, the average temperature of the gasifier, and the coal quantity of the three zones gradually increase. Conversely, the coal thickness corresponding to the intersection of the coal quantity of the oxidation and reduction zones and the heat loss rate of the gasifier gradually decrease. When the coal seam below 2.5 m is gasified, the gasification rate can be increased appropriately. When the coal seam is above 13 m, increasing the gasification rate will make the coal quantity in the oxidation zone close to or even higher than that in the reduction zone. Regarding the surrounding rock types comprising a combination of siltstone, mudstone, sandy mudstone, and fine sandstone, the most favorable roof and floor type for underground coal gasification is the combination of fine sandstone and sandy mudstone (without considering the sealing and mechanical properties). These results provide important theoretical support for the industrialization of underground coal gasification.

Experimental study on combustion optimization of four-corner tangential boiler for alleviating high temperature corrosion

In order to reduce the volume fraction of H2S in the water wall area of the four-corner tangential boiler and achieve the purpose of alleviating the high temperature corrosion of the water wall, a thorough test was carried out on the 600MW boiler. The results show that the high temperature corrosion of the water wall under high load is obviously more serious than that under low load, the high temperature corrosion of the water wall of the front wall is more serious than that of the other walls, and the high temperature corrosion of the furnace wall area downstream of the burner is generally higher than that of the other walls. Other areas. The reason for this phenomenon is that the uniformity of the pulverized coal quantity in each pulverized tube is large, the air distribution is unreasonable, the primary and secondary air are separated, and the secondary air cannot completely cover the primary air; The uniformity of pulverized coal distribution, the proper increase of the total air volume, and the proper increase of the perimeter air volume can significantly reduce the volume fraction of H2S in the water wall area and alleviate high temperature corrosion.

Power Consumption Model of Permanent-Magnet Direct-Drive Belt Conveyor System Based on GACO–BP

Permanent-magnet direct-drive belt conveyors (PMDDBCs) rotate at high speed most of the time, resulting in a large number of invalid energy consumption. To realize the speed regulation of PMDDBC, it is necessary to clarify the relationship between the belt speed, coal quantity of the conveyor and total power of the system. Based on the BP neural network, this paper establishes the power consumption model of PMDDBC, which is related to coal quantity, belt speed and total power. Furthermore, an improved hybrid algorithm (GACO) that combines the advantages of genetic algorithm (GA) and ant colony optimization (ACO) is proposed to optimize the BP power consumption model. The GACO–BP power consumption model is obtained. The original power consumption model is compared with the GACO–BP power consumption model through experiments. Results demonstrate that the GACO–BP power consumption model reduces various prediction errors, while the optimization ability, prediction accuracy and convergence speed are significantly enhanced. It provides a reliable speed regulation basis for the permanent-magnet direct-drive belt conveyor system and also provides a theoretical reference for energy savings and consumption reduction in the coal industry.

Analysis of Energy Consumption of the Lyophilizer System Using Solar Absorption Refrigeration

To design a lyophilizer plant in Guangzhou, the author of this paper used a solar energy absorption refrigeration system and a waste heat of solar absorption refrigeration system. Using Trnsys software, the simulation results show that the solar assurance rate of 74.96% on July 28th can save coal quantity of about 236.8 kg, a solar assurance rate of 53.48% in July can save coal quantity of about 4790.9 kg, and an annual solar assurance rate of 39.06% can save about 40657.1 kg, and each have good environmental benefits.

Study of Ash and Total Moisture Effects on Calorific Value in Coal Seam at West Banko Field, PT. Bukit Asam, Tbk., Tanjung Enim, South Sumatra

In the coal mining industry, the coal quality is as crucial as the coal quantity because it can impact the coal usefulness. The quality of coal itself can be influenced by several factors, such as moisture content, ash, sulfur, and volatile matter. This study tries to understand the coal quality and its variation in the Muara Enim Formation of South Sumatra Basin. The research was conducted in the West Banko field, PT. Bukit Asam, Tbk., Tanjung Enim, South Sumatra. By using linear regression, this study found that increasing ash and total moisture content will lead to a decreasing amount of the calorific value. Additionally, the value of coal quality content such as ash and total moisture can be affected by the depositional environment, sedimentation rate, and coal characteristics in the study area thus affecting the calorific value. Transitional lower delta plain depositional environment with low sedimentation rate and coarsening upward sandstone sequence indicates lower ash and total moisture content in the study area. The highest calorific value found in the study area is in C1 seam, this can be seen from the ash quality and total moisture distribution map which inversely proportional to the calorific value.

Dynamic Coal Quantity Detection and Classification of Permanent Magnet Direct Drive Belt Conveyor Based on Machine Vision and Deep Learning

Real-time and accurate measurement of coal quantity is the key to energy-saving and speed regulation of belt conveyor. The electronic belt scale and the nuclear scale are the commonly used methods for detecting coal quantity. However, the electronic belt scale uses contact measurement with low measurement accuracy and a large error range. Although nuclear detection methods have high accuracy, they have huge potential safety hazards due to radiation. Due to the above reasons, this paper presents a method of coal quantity detection and classification based on machine vision and deep learning. This method uses an industrial camera to collect the dynamic coal quantity images of the conveyor belt irradiated by the laser transmitter. After preprocessing, skeleton extraction, laser line thinning, disconnection connection, image fusion, and filling, the collected images are processed to obtain coal flow cross-sectional images. According to the cross-sectional area and the belt speed of the belt conveyor, the coal volume per unit time is obtained, and the dynamic coal quantity detection is realized. On this basis, in order to realize the dynamic classification of coal quantity, the coal flow cross-section images corresponding to different coal quantities are divided into coal type images to establish the coal quantity data set. Then, a Dense-VGG network for dynamic coal classification is established by the VGG16 network. After the network training is completed, the dynamic classification performance of the method is verified through the experimental platform. The experimental results show that the classification accuracy reaches 94.34%, and the processing time of a single frame image is 0.270[Formula: see text]s.

Research on Power Consumption Model of Permanent Magnet Direct Drive Belt Conveyor System Based on Fruit Fly Optimization Algorithm-Generalized Regression Neural Network-Particle Swarm Optimization

The permanent magnet direct drive electric drum is used to replace the driving device of the traditional belt conveyor, which simplifies the structure. However, the permanent magnet direct drive electric drum still operates in a high speed and stable state after starting, and cannot transport materials reasonably, belt speed cannot match the coal quantity reasonably; the problem of energy waste is still severe. Thus, based on fruit fly optimization algorithm-generalized regression neural network-particle swarm optimization algorithm, the power consumption network model of the permanent magnet direct drive belt conveyor system is established. The relationship among belt velocity, coal transport quantity and power is obtained, and the optimal belt velocity is found with the power consumption network model. Thus, the minimum power is obtained. The algorithm selects the optimal smoothing factor by fruit fly optimization algorithm, inputs the optimal smoothing factor into generalized regression neural network and establishes the optimal power consumption model. Then establishes the matching relationship of coal quantity, optimal power, and optimal belt speed in the power consumption model by the adaptive weight particle swarm optimization. The model is compared with the network model with smoothing factors of 0.7 and 0.4. The comparisons show that the optimized model performs better, which can be better applied to establish the energy consumption model of the system.

Numerical simulation study on gas drainage by interval hydraulic flushing in coal seam working face

In order to solve the problem of difficult gas extraction in coal mine, a method of gas extraction from coal seam by interval hydraulic flushing is put forward. Based on the coal seam gas occurrence conditions of 7609 working face in Wuyang Coal Mine, the numerical simulation research on gas drainage by ordinary drilling and hydraulic flushing drilling was carried out by using COMSOL numerical simulation software. The results show that with the increase of hydraulic flushing coal quantity, the effective gas drainage radius also increases. The effective extraction radius of ordinary drilling is 0.5 m, and the effective extraction radius is 1.0 m, 1.2 m and 1.3 m respectively when the coal flushing quantity is 0.5t/m, 1.0t/m and 1.5t/m. As multiple boreholes are drained at the same time, the boreholes will affect each other, which will reduce the gas pressure and increase the effective drainage radius, the spacing between boreholes can be greater than twice the effective drainage radius of a single borehole when arranging boreholes. And the smaller the flushing interval, the more uniform the gas pressure reduction area. According to the numerical simulation results, the ordinary drilling and 1.0t/m interval hydraulic flushing test were carried out in the field. Through observation and analysis, the gas concentration of the interval hydraulic flushing drilling module was increased by 31.2% and the drainage purity was increased by 5.77 times compared with the ordinary drilling module. It shows that the interval hydraulic flushing drilling can effectively improve the gas drainage effect.

Study on the Parameter Equation of Coal and Gas Outburst Hole

Studying the parameters of a coal and gas hole (CGOH), such as the hole shape, hole size and volume, coal quantity of CGOH, coal throw distance, calculated hole density, and gas pressure, is helpful in revealing the coal and gas outburst mechanism. In this study, we found that there were close mathematical relationships between these parameters. A nonlinear composite function relationship (CGOH parameter equation) was observed between the coal quantity, CGOH volume, and throw distance. The correctness of these relationships was verified using the Origin software. The stagnation point and inflection point of the parameter curve were obtained through the derivation of the parameter equation, and the transformation path from coal and gas outburst to coal and gas extrusion or dumping was clarified. At the same time, the equations of gas pressure, coal quantity, and throw distance are derived.

Application of feedforward predictive control in DC furnace coordination system

In order to solve the control difficulties such as large dynamic delay, serious coupling between machine and furnace and strong nonlinear, the feedforward and feedback predictive control is proposed to control the coordinated system on the basis of multi-model predictive control, and the static feedforward part designs the feed line feedforward of coal quantity against coal quality disturbance on the basis of the accurate balance of energy. Thus, the reference total fuel quantity under the target load instruction is determined, and the dynamic part fully considers the dynamic compensation of the unit energy storage, gives a certain overshoot fuel quantity to the boiler regulation, speeds up its response, and ensures the rapidity of the unit. The real-time simulation results of virtual DPU (Distributed Processing Unit) show that the designed feedforward-feedback predictive control can quickly respond to load change, improve the resistance to fuel disturbance, reduce the fluctuation of main steam pressure, and better ensure the safe, economic and stable operation of the coordination system.

Detection method of coal quantity and deviation of belt conveyor based on image recognitio

Detection method of coal quantity and deviation of belt conveyor based on image recognitio

Factors Influencing on Coal Price and Development of a Pricing Model for Indian Coal

Coal plays a crucial role in India as it fulfills almost 67% of the total commercial energy consumed in Indian industries. Fossil fuels are the major drivers of the country's economy. The coal price is affected by many parameters including its grade, demand at the national level and international coal price. We observed in the year 2017-18, the total production of coal in India was 675 MT but the actual demand for coal in India was 884 Million Tonnes (MT), with the actual supply falling short resulting in a demand deficit. This deficit was offset by import 202 MT of coal. Over 22.8% of coal imports in 2017-18 were sourced from Indonesia followed by import from Australia and South Africa. The study identifies some major factors that may have an influenced on Indian coal price, including coal export, coal import and international coal prices by analysing and processing of Indian coal data which is from 1993to2018 with the help of SPSS software by the regression analysis. The logarithmic coal price is the dependent variable and the hypothesized independent variables are relative value of demand and supply, export, import, stock, international coal price, international oil prices. According to the result, the factors like a relative value of demand and supply, coal production, international oil price are no significant influencing on Indian coal prices and the significant variables are helpful to developing coal pricing mode for Indian coal. The coal pricing model has useful to estimate the future price of Indian coal and also to identify the impact of import coal quantity on Indian coal prices.

Incorporating Silica Sol as a Binder to Improve Long-Term Stability of Blocky Coal

Long-term stability evaluation of grouting materials is critical to the safe operation of geological engineering. Taking blocky No. 8 coalseam of Huaibei coalfield as engineering background, taking coal fragmentation distribution and grouting quantity as the control variables, uniaxial compression tests were conducted every 1 or 2 months to study long-term mechanical behavior of silica sol grout. Results indicated that (a) long-term strength stability of samples could not be achieved in the case that silica sol was mixed into coal samples including big fragments (5–10 mm); (b) in the case that silica sol was mixed into coal sample without big fragments (5–10 mm), 200 days was the least maintenance time that the strength need to turn stable; (c) in the case that silica sol was mixed into the coal samples with small fragments (< 2 mm), long-term stiffness of samples could be achieved. In other words, coal fragmentation had a negative correlation with the long-term consolidated stability of silica sol grouting. Generally, grouting quantity had a linear positive correlation with strength, peak strain, brittleness coefficient, and had an exponential function increasing relation with pre-peak strain energy density. But grouting quantity was of no influence on secant modulus. There existed a lower limit of grouting quantity and long-term stability of silica sol grouting strength couldn’t be achieved when grouting quantity was below the limit. The research results can guide grouting design and long-term stability evaluation of grouting.

Application of Hydraulic Flushing in Coal Seams To Reduce Hazardous Outbursts in the Mengjin Mine, China

Abstract Hydraulic fracturing and waterjet slotting fracturing have been demonstrated to be effective in creating artificial fractures and stimulating gas production in hard coal seams. However, these methods are inefficient for soft-outburst coal seams because these created fractures are short and easy to close. To eliminate the outburst risk of soft coals, a novel enhanced coalbed methane under-panel cross-strata drainage technique via hydraulic flushing was proposed in this work. The hydraulic flushing effects of boreholes of different sizes in the coal seam were also pre-evaluated by a simulation approach. The modeling results indicate that as the radius of the borehole increases, the plastic and stress-decreasing zone expands. A field test was also conducted in the Minjin mine, China, that investigated the gas pressure variation between three monitoring boreholes at different distances from a hydraulic flushing borehole. Test results indicate that the effective influence radius of gas extraction is approximately 5.5 m. Based on the results of the field test and borehole camera observation, the unloaded coal quantity and the average diameter of the boreholes were estimated to be 8.0 t and 942 mm, respectively. The borehole diameter expanded up to 10 times larger than its original size. The average gas extraction concentration and gas flow rate increased by approximately 2 and 3.5 times, respectively, demonstrating the effectiveness of the proposed hydraulic flushing in improving the gas extraction efficiency. The hydraulic flushing technique therefore is proved to be efficient in eliminating the outburst risk of coal and reducing greenhouse gas emissions.