Coal Particle Size Distribution Research Articles

Study on coal pulverization characteristics and gas desorption mechanism based on impact crushing experiment

The coal's particle size distribution properties after pulverization and the gas desorption behavior driven by pulverization are of profound meaning to the study of coal and gas outburst mechanism. In this paper, based on the impact crushing experiment, the tectonic coal and primary coal are crushed under different impact energy conditions. After screening the broken coal, the particle size distribution law is analyzed, and the characterization function suitable for the particle size distribution of coal particles after crushing is determined. The relationship between crushing work and new surface area and fractal dimension of coal body is discussed. The consequences indicated that the mass proportion of tectonic coal below 0.074 mm particle size is much huger than that of raw coal. G-S, R–R, and fractal distribution model describe the best particle size distribution of the two coals in the scope of 0.074∼4 mm. The new surface area added increases with the crushing work, and the tectonic coal is 1.34–1.96 times that of the raw coal. The fractal dimension diminishes first and then increases with the crushing work ratio. In addition, the gas desorption amount of coal particles with different particle sizes after coal pulverization was measured, and a dynamic model suitable for coal pulverization-driven gas desorption was established, and the experimental results were verified. The research results of this paper can provide experimental and theoretical basis for the analysis of energy dissipation in coal and gas outburst.

Fragmentation energy calculation model of coal crushed by impact load

ABSTRACT Rock fragmentation is a common physical and mechanical phenomenon that exists in a variety of ranges from the mining and processing. Communication is an important operation in coal processing whereby the coal block coming from coalmines is crushed into fragmentations with reduced size, which accounts for 80% of the electricity consumption of mineral processing circuits. Fragmentation energy, which is related to the coal particle size distribution, is an essential parameter for improving the efficiency of shearer, road-header, and crusher. Coal particles are generally simplified into fine or near spherical shapes for analytical and numerical simulation purposes. This research aims to establish the fragmentation energy calculation model for coal fragmentations with coarse and wide size distribution based on the analysis of size distribution and energy-size relationships of coal particles. It has been demonstrated by the results that the fragmentation energy of impact load crushed coal can be determined based on Rittinger’s theory with fractal or RR model particle size distribution.

Research on coal crushing behavior under supercritical CO2 transient high-pressure fracturing

CO2 fracturing enhances gas permeability by creating a complex network of fractures in coal seams. Crushing serves as the foundation of fracture development, and studying the coal crushing behavior under supercritical CO2 transient high-pressure fracturing is of great significance to understand fracture evolution and guide precise fracturing. This study utilized a self-built experimental platform for supercritical CO2 transient high-pressure fracturing to obtain fractured coals at different energy levels. Based on multifractal theory, the relationship between fracturing energy and crushing behavior was studied by laser particle analysis and scanning electron microscopy. The results showed that the volume average particle size (D4,3), and the particle sizes at which the cumulative particle size distribution reached 50% (D50), and 90% (D90) decreased significantly with the increase of fracturing energy. The converted diameter and the crushing work ratio exhibited an exponential relationship with the fracturing energy. The larger the fracturing energy, the smaller the values of the multifractal generalized dimension spectrum parameters (D0, D1, and ΔD(q)), the larger the values of the multifractal singular spectrum width (Δα (q)), and the denser and more even the particle size distribution of fractured coal. The multifractal parameters and shape coefficients exhibited phased change during the fracturing process. The coal particles progressed from an initial stage with numerous microcracks and fissures to a honeycomb structures with small pores. After the disintegration of the honeycomb structures, agglomerated ultrafine particles were formed. The findings provide a theoretical reference for optimizing the selection of fracturing parameters.

Optimization of briquetting conditions and influencing factors of high-strength sludge briquette

With the increase of sewage sludge production in China, there is an urgent need for a clean and efficient sludge treatment, and the coupling utilization of sludge and coal to produce briquette is a potential sludge treatment method. In this work, sludge (with blending ratio higher than 40 wt%, dry basis) and one Chinese low-rank pulverized coal were used as raw materials to prepare sludge briquette by cold pressing method without binder. The effect of sludge moisture content (SMC), briquetting load (BL), blending ratio (BR), and particle size distribution of coal (PSD) on the compressive strength of the briquette were explored. Through FTIR, contact angle, Zeta potential, and SEM analysis, the briquetting mechanism of sludge briquette was clarified. The response surface method (RSM) was used to optimize the briquetting process conditions. The results showed that the order of influence of various factors on the compressive strength of the briquette is as follows: BL > PSD > SMC > BR. The results also showed that the interaction among SMC, BL, and PSD is the main factor affecting the compressive strength of sludge briquette. According to regression analysis, the optimum briquetting conditions are SMC of 14.11%, BL of 46.54 MPa, the weight proportion of sludge of 60%, and the weight proportion of R1 in coal of 52.68%. The quadratic regression model was established by RSM, and the predicted value is close to the experimental value.

Energy consumption model of coal grinding based on energy dissipation fractal dimension

Based on particle size distribution characteristics, this paper explored the energy dissipation law in the coal ultrafine grinding process. By studying the fractal dimension of coal particle size distribution under the multi-domain fractal rule, the truncated particle size was introduced to characterize the energy consumption changes of coarse, intermediate, and fine particles. Combined with macro-energy consumption laws and three-piecewise fractal dimensions, a micro-energy consumption theory considering lattice fracture and agglomeration of ultrafine particles was proposed. On this basis, the energy consumption fractal dimension DE was proposed, and its theoretical calculation value was 2.021. The energy consumption formula of coal ultrafine grinding was established, in which energy consumption was characterized by the DE th power of the added surface area of coal particles. The DE obtained by the specific surface area and the adsorption equilibrium constant of pores were 2.285 and 2.564, respectively, which confirmed the reliability of the above theoretical analysis.

Initial exploration on potential fire hazards detection from coal spontaneous combustion applied by acoustic wave

Coal spontaneous combustion often wastes resources and causes environmental pollution. Rapid and accurate identification of high temperature areas in coal is essential to reducing such combustion and environmental pollution. The acoustic thermometry method has the benefits of large temperature measurement space, non-contact, and high interference resistance. Determining the attenuation characteristics of acoustic waves in loose coal is the basis and premise for realizing acoustic temperature measurement. Four types of bituminous coal were scanned by computer tomography equipment. A self-designed acoustic attenuation test device was used to test coal samples under different temperatures and particle sizes. The study result demonstrates that the distribution characteristics of loose coal voids are mainly related to the particle size. The smaller the particle size range, the more uniform the void distribution. As the size of the coal particles increases, the voids become larger. The acoustic attenuation coefficients of four coal samples showed an increasing trend as frequency increased. The influence of coal particle size distribution on the acoustic attenuation coefficient was greater than that of temperature and metamorphic degree. The peak values of coal sound attenuation for different particle sizes were around 400, 700, 1100, and 1600 Hz. This indicated that the distribution of voids was the main factor affecting the propagation of acoustic waves. By analysing the attenuation mechanism of the acoustic wave in loose coal, the attenuation of acoustic temperature measurement signal was caused by the combined effect of loose coal on acoustic wave absorption and scattering. The study results provide theoretical support for the realization of acoustic wave detection of high temperature point in loose coal spontaneous combustion.

Numerical study on the particle distribution of coal for recovery of critical metals

ABSTRACT Coal is considered to be a significant resource of critical metals and minerals. Recovery of these critical metals is considered to be highly important in terms of advancement and technology. This paper presents a numerical study of the particle size distribution of coal and its impact on the recovery of critical metals. This study uses the computational fluid dynamics (CFD) model to simulate the transport and deposition of coal particles inside a helical domain, which can be used as a device for separating particles. The numerical study , based on the particle tracing model for fluid flow and particle tracing, is used to simulate the behavior of coal particles in a slurry under different flow conditions. The transient study for a six-turn helical coil domain is analyzed for different flow velocities ranging from . The simulation results show that the particle size distribution of coal plays a crucial role in the recovery of critical metals. Additionally, the distribution of critical metals inside the domain varies with the size and density of the particles. It is observed that increasing the fluid velocity can significantly increase the recovery of critical metals. Finally, the transmission probability of particles remaining trapped inside the domain is also calculated, which could help in optimizing the helical geometry so that all the particles could come out of the flowing conduit. The number of particles coming out of the helical domain increases with the increase in flow rate. The results of the study show that the particle size distribution of coal plays a significant role in the recovery of critical metals. The findings can help guide the development of more efficient and cost-effective methods for extracting critical metals from coal.

Importance of the average radius of coal particles on determining the methane diffusion coefficient.

The average radius of coal particles is an estimate of the diffusion path in the particle method for determining the diffusion coefficient. It is currently calculated using the arithmetic mean of coal particle sieved intervals. This calculation, however, ignores the coal particle size distribution, resulting in significant deviations when calculating the gas diffusion coefficient. An appropriate average radius calculation method should consider the particle size distribution and the physical essence of diffusion. To accomplish this, a series of methods for calculating the mean particle diameters and their physical significance were reviewed. Next, coal samples were sieved into three intervals, and gas diffusion tests and laser particle size distribution were conducted. Results show that coal particles are within the sieving interval, ranging from 42.01 to 76.18%. By solving the diffusion coefficients using four mean particle diameters based on particle size distribution and diffusive mass transfer, the difference between the arithmetic mean value and these diameters is up to 89.06%. [Formula: see text] and [Formula: see text] are preferred for the calculation of the average radius since they are compatible with coal particle shape and the physical meaning of diffusive mass transfer.

Correcting Coal Miner Respirator Total Inward Leakage Values for Respiratory Tract Deposition.

The great majority of workplace respirator efficacy studies have measured total inward leakage (TIL) for particulate contaminants. One of the first such studies, designated the Harris study, was conducted in the early 1970s in US underground coal mines. As in other particle-based studies, inside-the-facepiece dust sampling was continuously conducted across the inhalation and exhalation phases of the breathing cycle, although unlike in other studies, respirable dust cyclones were used in air sampling. Because exhaled air was partially depleted of dust particles due to deposition in the respiratory tract, the measured time-averaged dust concentration inside the facepiece underestimated the time-averaged dust concentration inspired into the facepiece. In turn, the reported TIL values underestimated the true TIL values experienced, which is to say, overestimated respirator efficacy. This paper describes a method to correct the Harris study's reported TIL values for respiratory tract deposition while accounting for particle size-selective sampling by the cyclone devices. Given the estimated coal mine particle size distribution outside the respirator, it is shown that the reported TIL values should be increased by the multiplicative factor 1.69. This paper also discusses the assigned protection factor (APF) of five for the quartermask respirator class and shows that 4/5 quartermasks in the Harris study did not meet the criterion for complying with this APF value when using the corrected TIL values.

Research on Particle Size and Energy Consumption Law of Hard Coal Crushing under Impact Load Based on SHPB Test

To study the particle size distribution and energy variation law of hard coal under a load, an impact compression test of hard coal specimens under different impact loading conditions was carried out using a Φ50 mm diameter Separate Hopkinson Press Bar (SHPB) test system. We implemented the theory of dynamic impact energy of rock to establish the calculation expression of hard coal impact crushing energy dissipation, and we established the Weibull distribution model of a crushing body to analyze the impact velocity in relation to the particle size distribution of hard coal crushing and crushing energy consumption. The results demonstrate that due to the different original states of the specimens, the damage to the specimens under static action is in the mode of conjugate plane shear damage, single bevel shear damage, and tensile damage. The damage process of the specimen under impact load loading is divided into three stages: elastic deformation, elastic–plastic deformation, and plastic softening, while the increase in the strain rate caused the peak stress of the specimen to increase. The Weibull distribution can characterize the impact crushing size distribution of hard coal specimens very well. The parameter of coal rock crushing degree is a power function that is influenced by the impact velocity; the greater the impact velocity, the higher the coal rock crushing degree, but the characteristic index of coal rock crushing fluctuates with the increase in impact velocity. As the impact velocity increases, the incident energy and reflected energy increase linearly, while the transmitted energy increases first and then decreases. The dissipation energy of coal rock crushing also increases linearly with the impact velocity. There is no obvious regular change between the energy dissipation rate of coal rock and impact velocity during impact damage, and the dissipated energy of macroscopic crushing only accounts for 10~20% of the incident energy; most of the energy is used for damping loss and damage loss.

Implementation of a Model for Predicting the Size Distribution of Coal Particles in a Horizontal Fluid Pipeline

Implementation of a Model for Predicting the Size Distribution of Coal Particles in a Horizontal Fluid Pipeline

Prediction of Gas Emissions in the Working Face Based on the Desorption Effects of Granular Coal: A Case Study

The aim of the study in this paper is to establish a prediction model of gas emission in the working face. The gas desorption variation characteristics of coal with different particle sizes were assessed using physical tests and based on the coal body of No. 2 coal seam in Wangjialing Coal Mine, Shanxi, China, to reveal the influence law of coal particle size on coal gas desorption. The gas desorption characteristics in the working face, the law of gas emission of coal cutting, coal caving, coal wall, and remnant coal in the goaf of the production process were then analyzed after establishing a gas emission prediction model based on the particle size of the coal. The accuracy of the gas emission prediction model was finally validated through actual measurement of the coal particle size distribution and gas emission in the test working face. The results of the current study show that the coal particle size is negatively correlated with the gas desorption capacity within a certain range. The initial desorption intensity of the coal gas decreased with an increase in the coal particle size. However, the initial gas desorption intensity and attenuation coefficient of gas emission were constant after a certain level of increase in the coal particle size. It was found that the average error between the gas emission prediction model and the actual gas emission data in the mining process was 5.29% based on the desorption characteristics of granular coal. Therefore, the established gas emission prediction model can characterize the law of gas emission in the actual production process more effectively. Furthermore, it provides reliable support for the prediction and control of gas emissions from the goaf under the condition of fully mechanized mining with top coal caving.

Study on micro-energy consumption model of ultrafine grinding coal particles

Based on the particle size distribution and surface physicochemical characteristics of coal particles, a micro-energy consumption model of coal particles in the ultrafine grinding process was proposed. This model explained the microscopic mechanical behavior of the ultrafine grinding process by defining factors such as agglomeration between particles and the change in particle surface properties as the microscopic constraint energy of particles. Under the multi-domain fractal law of particle size distribution, the truncated particle size was introduced to eliminate the mutual interference between size grades, and the expression of the micro-energy consumption law in the ultrafine grinding process of coal particles was derived by combining with the surface area theory of macroscopic crushing. Through scanning electron microscopy and infrared spectroscopy analysis, it was confirmed that the evolutionary process of coal particle surface morphology and the fracture law of chemical bonds were in line with the viewpoint of the micro-energy consumption model.

Experimental study on the influence of wetting agent addition on the water adsorption and impact crushing dust generation of coal

AbstractThis study is aimed at investigating the influence of wetting agent addition on the water adsorption capacity, dust generation capacity and dust particle size distribution of coal. To achieve this aim, nonylphenol ethoxylate 10 wetting agent was used as an additive to prepare a 0.1% concentration solution, and a comparative test was conducted on different coal types from three coal mines in different provinces. The test results suggest that the natural saturated water adsorption time of coal was shortened by 33%–67% through wetting agent addition. Therefore, wetting agents are effective for enhancing water injection operations that require a limited construction period. The influence of wetting agent addition on the saturated water adsorption amount differed significantly for different coal types, and the wetting agent did not generally improve the saturated water adsorption rate. However, wetting agent addition alone did not lower the dust generation rate from coal. For a given moisture content, the wetting agent influenced the particle size distribution of dust generated during impact crushing differently between types of coal. For the three coal types investigated, wetting agent addition reduced the concentration of airborne by up to 8%.

Understanding the Role of Polyvinylpyrrolidone on Ultrafine Low-Rank Coal Flotation.

Effective regulation reagents are essential in low-rank coal flotation for improving the floatability of ultrafine particles. Polymer regulators have great potential in the surface modification of ultrafine coal particles. A novel nonionic polymer, polyvinylpyrrolidone (PVP), is evaluated in this study to determine its effectiveness as a regulator in floating ultrafine low-rank coal. Laser particle size analysis is used to discern both the size distribution of coal particles and the change in size distribution. Contact angle tests are carried out to evaluate the wettability of low-rank coal. Surface functional groups of low-rank coal are analyzed by Fourier transform infrared spectroscopy, and the surface interaction energy is tested by X-ray photoelectron spectroscopy. The results show effective adsorption of PVP and demonstrate the effects of PVP at the coal surface. The adsorption of PVP changes the proportion of exposed carbon and oxygen-containing functional groups on the surface of low-rank coal, regulating the size distribution of low-rank coal particles in suspension. The success of polyvinylpyrrolidone as a regulator in low-rank coal flotation is demonstrated, and the mechanisms by which PVP can affect ultrafine low-rank coal flotation are elucidated.

Quantitative evaluation of the influence of coal particle size distribution on gas diffusion coefficient by image processing method

Coal particles have been widely used to measure the gas diffusion coefficient which is a key parameter to characterize the gas diffusion behavior, and the average particle size is a necessary parameter for calculating the diffusion coefficient. At present, people often use the arithmetic mean of upper and lower sieve surface specifications to characterize the average diameter of coal particles, which has large errors. It is necessary to obtain the particle size distribution in advance to determine the average diameter scientifically and accurately. A laser particle analyzer is usually used to measure particle size distribution, but due to the limitation of its measurement principle, it has poor measurement accuracy for irregular and large particles. In this article, we offer an integrated approach for quantitative evaluation of the influence of coal particle size distribution on gas diffusion coefficient. Laser particle analyzer and image analysis were used to measure the particle size distribution of 6 coal samples with the size range of 1 ∼ 2 mm. Based on obtaining the size distribution, the average diameter was calculated. Then the diffusion coefficient was calculated by using the average diameter obtained by different methods. The results show that the particle size distribution measured by the laser method has a large deviation and poor repeatability, and the volume mean diameter calculated by it is far less than the arithmetic mean value of 1.5 mm. The imaging method can extract the morphological data of each particle, and so the obtained particle size distribution is more accurate and reliable. The equivalent area mean diameter calculated by the image method is close to 1.5 mm. The average diameter obtained by considering the particle size distribution can more truly reflect the particle size characteristics of coal samples, while the conventional method of using the arithmetic mean to calculate the diffusion coefficient will produce a non-negligible deviation. This also reveals the importance of obtaining particle size distribution when using the particle method to solve the diffusion coefficient.

Development of method for coal dust particle size distribution characterization by laser diffraction

Development of method for coal dust particle size distribution characterization by laser diffraction

Prediction of medium-to-coal ratio effect in a dense medium cyclone by using both traditional and coarse-grained CFD-DEM models

Dense medium cyclone (DMC) is the working horse in coal industry. In practice, it is usually operated under constant pressure and the operational conditions (mainly medium-to-coal (M:C) ratio and operational pressure) need to be adjusted according to coal washability data (mainly coal particle size and density distributions). Nonetheless, until now it is still not well understood how the M:C ratio would affect the performance of DMCs especially under the practical conditions. In this work, the effect of M:C ratio is for the first time numerically studied under conditions similar to plant operation by using both traditional and coarse-grained (CG) combined approach of computational fluid dynamics (CFD) and discrete element method (DEM), called as traditional CFD-DEM and CG CFD-DEM, in which the flow of coal particles is modelled by DEM or CG DEM which applies Newton’s laws of motion to individual particles and that of medium flow by the conventional CFD which solves the local-averaged Navier-Stokes equations, allowing consideration of particle–fluid mutual interaction and particle–particle collisions. Moreover, impulse and momentum connection law is used to achieve energy conservation between traditional CFD-DEM and CG CFD-DEM. It is found that under constant pressure, the M:C ratio affects DMC performance significantly. The specific effect depends on coal washability or coal type. Under extremely low M:C ratio, the phenomenon that high-quality coal product is misplaced to reject is successfully reproduced, which has been observed in plants in Australian coal industry and called as “low-density tail”. Moreover, strategies are proposed to mitigate the “low-density tail” phenomenon based on the model.

Dynamic Prediction Model of Multisource Gas Emissions in a Fully Mechanized Top Coal Caving Based on the Coal Particle Size Distribution

Coal particle size is an important factor affecting the gas emission law. Taking Wangjialing coal mine as the research object, the particle size distribution of coal mining and caving is analyzed via field tests in order to develop the gas emission theoretical model from granular coal. We also perform the numerical simulation of the coal body and longwall face gas emission characteristics under different particles. Finally, the gas emission rules of coal cutting, caving, longwall face, and goaf in Wangjialing coal mine are analyzed, and the dynamic prediction model, which accounts for the time influence of the coal cutting and coal caving speed based on the particle size distribution characteristics, is derived. Results demonstrate the wide distribution of the coal particle size at Wangjialing coal mine, with a higher proportion of small- and large-sized particles. The smaller the coal particle size, the faster the gas emission and the smaller the desorption ratio of coal at ≥ 20 mm within 30 min. The comprehensive emission intensity of coal mining and caving can be described by an exponential function. The initial emission intensity of coal mining is observed to exceed that of coal caving, while the attenuation laws of the two are essentially equal, and the majority of the gas emission is completed within 5 min. The error between the results of the multisource dynamic prediction model and the field measurement is small, which is of practical application significance.

Comparison of outburst hazard of coal with different failure types: a case study

ABSTRACT Coal and gas outburst, usually takes place in tectonic soft coal areas. It is generally difficult to obtain soft coal samples, which influences the accuracy of outburst hazard determination of coal seams and thus poses a severe threat to the safety production of coal mines. Taking the outburst accident of Chensilou Coal Mine which was previously identified as no outburst risk as an example, comparison and analyses were made on outburst parameters, size distribution characteristics and microscopic pore structure of these coal samples with various failure types. Results suggest that coal samples with different destruction degrees exhibit consistent microstructure and macroscopic behaviors. The critical gas pressures corresponding to primary hard coal, tectonic coal and post-outburst coal are 1.25 MPa, 0.64 MPa and 0.52 MPa, respectively. Based on the particle size distribution of tectonic coal, the primary hard coal was adopted to simulate the tectonic soft coal. The critical gas pressure of the simulated coal sample is 0.66 MPa which approaches the condition of actual tectonic coal, which can improve the prediction accuracy. Hence, this method can make up the loss brought by unreasonable sampling and enhance the accuracy of outburst hazard determination of coal seams.