Coal Type Research Articles

Experimental Studies on the Crack Initiation and Propagation of Hydraulic Fracturing with Different Coal Structure Combinations.

Coal structure is one of the key geological factors that affects the effect of coal reservoir stimulation. Based on the geological spatial combination characteristics, thickness, and proportion of different coal structures, the coal reservoir is divided into different coal structure combination types. The hydraulic fracturing device is used to carry out indoor fracturing experiments and dissect the crack initiation and expansion characteristics with different coal structure combinations. The results show that the coal structure combination is of the binary type (undeformed coal + granulated coal or cataclastic coal + granulated coal), and the undeformed coal (cataclastic coal) can overcome the tensile strength and minimum principal stress when it is driven by the high-pressure fluid. The undeformed coal (cataclastic coal) ruptures and forms longitudinal cracks. The increasing proportion of granulated coal inhibits crack expansion and promotes the transverse deformation of coal. The interface contact point between the undeformed coal (cataclastic coal) and granulated coal easily fractures along the cross section of the specimen. When the coal structure combination is the triplex type (undeformed coal + granulated coal + cataclastic coal or cataclastic coal + granulated coal + cataclastic coal), the undeformed coal or cataclastic coal is transformed. The forming fractures in the undeformed coal (cataclastic coal) can cut through the soft coal when the thickness of the undeformed coal (cataclastic coal) is large and the thickness of granulated coal is thin. On the contrary, it is not easy to cut through. When the coal structure combination is granulated coal + cataclastic coal + granulated coal, the cataclastic coal fails under shear stress and forms the crack along the cross section of the coal sample. The granulated coal inhibits the crack expansion at both ends. The research results have an important indicative significance for further understanding the fracture initiation and propagation mechanism of hydraulic fracturing with complex coal structures in coal reservoirs.

Effect of coal tar pitch on highly reactive coke properties and microstructure

ABSTRACT Highly reactive and high-strength cokes are important for developing and producing hydrogen-rich blast furnaces. The work aimed to produce cokes with high reactivity and high post-reaction strength. The coal tar pitch (CP) was added to improve the post-reaction strength of cokes on the premise of adding alkali metals or alkaline earth metals to improve the reactivity of cokes. The chemical reactivity index of coke samples generally decreases by about 1%, while the post reaction strength of coke samples shows a significant improvement after the addition of coal tar pitch, with coke rich in CaO increasing by about 6% and coke rich in K2CO3 and Na2CO3 increasing by about 3% after adding the CP. Besides, the structural strength and micro strength of coke samples from the composite CP were improved. The microstructure analysis of the coke samples before and after the composite CP showed that the addition of the CP could weaken the originally developed pore structure of the coke samples and reduce the surface area of the gasification reaction of coke samples. Therefore, the gasification reaction of coke samples was inhibited. Moreover, the CP reduced the damage of alkali or alkaline earth metals to the dense aromatic-ring structure in the carbon matrix during the carbonization process of coking coal. It increased the amount of qualitative carbon in the coke samples and the order of carbon microcrystals. The effect of the CP on coke samples varied due to differences in coking coal and catalyst types.

Influence of the natural content of mineral impurities and moisture on the manifestation of hazardous properties of coal seams

It is not possible to determine the type of coal in terms of reducibility from thermal decomposition without access to air for volatile maters to dry ash-free mass, which provides establishing the ratio between oxygen content and other essential components of organic mass. The hazards of coal mine operations depend to a large extent on the ratio of the main components, both in organic matter and in mineral impurities. Methods for determining the yield of volatile maters make it impossible to assess the effect of the main components of organic matter and mineral impurities on the hazard characteristics of coal seams. The volatile maters index reflects only the sum of the thermal decomposition gases: hydrogen, methane, carbon monoxide and carbon dioxide without considering the ratio between them. The determination of the hazard properties of a seam in relation to metamorphic transformations factor should include a case-by-case examination of the relationship between the major components of fuel both the organic and mineral, including the moisture content, for each coal seams.

The influence of combustion of various types of hard coal on the level of pollutant emission

The influence of combustion of various types of hard coal on the level of pollutant emission

Air distribution and coal blending optimization to reduce slagging on coal-fired boiler water wall based on POD reduced order modeling for CFD

Slagging is a common phenomenon interfering with the safe and efficient operation of coal-fired boilers. Due to the lack of monitoring methods for species and temperature distribution near the water wall, which is critical for slagging formation, it is a tricky problem to detect and reduce the slagging in real time. A method for slagging distribution prediction and anti-slagging optimization of a 330 MW tangentially coal-fired boiler is developed in this paper. Proper orthogonal decomposition (POD) reduced order modeling and support vector machine (SVM) are used to predict the distribution of temperature and O2 near the water wall by taking 15 variables as input parameters (load, coal types, primary air rate, secondary air rate, excess air coefficient, and secondary air velocities). Next, fuzzy comprehensive evaluation (FCE) is employed to quantify the slagging occurrence and distribution on the water wall. Furthermore, the real time slagging prediction is realized with the combination of POD, SVM, and FCE. Finally, the conventional genetic algorithm (CGA) and simulated annealing genetic algorithm (SAGA) are adopted to optimize the air distribution schemes and coal blending schemes to reduce the slagging ratio, and their performances are compared. The results indicate that the predictions of temperature and O2 with POD show a good agreement with CFD simulations. In the optimization process, whether air distribution is optimized alone or both coal blending and air distribution are optimized simultaneously, the performance of SAGA is better than that of CGA. After optimizing the air distribution with SAGA, the slagging ratio of a typical operating condition with a load of 330 MW is reduced from 14.21% to 7.16%. The slagging ratio is further reduced to 5.36% after optimizing air distribution and coal blending schemes simultaneously. The proposed slagging prediction and optimization for anti-slagging opens a new perspective to alleviate slagging of water walls effectively.

Система совместного использования обедненного метана угольных пластов и биогаза для выработки электроэнергии в угольных шахтах

Purpose: Justification and development of new resource-saving technologies aimed at utilization of coal bed methane. The problem of low efficiency of utilization of lean methane-air mixtures is primarily due to the low content of methane itself, which varies significantly depending on the type of coal or concentration. This paper discusses the concept of a co-production system that mixes low-methane methane-air mixtures and biogas to generate power. Methods: Analysis of the possible volumes of utilized methane, biogas requirements and the suitability of the primary feedstock for co-generation of heat and electricity. Selection of appropriate parameters for the processes of utilization of mine methane. Analysis of the merits of the proposed method of utilization of lean coal mine methane. Results: It is recommended that biogas produced by agriculture and forestry in the vicinity of the mines be added to the dry methane stream to obtain the necessary gas concentration for electricity generation. Potential electricity production and greenhouse gas emission reductions have also been evaluated. The result shows that the co-production system can significantly improve the efficiency of poor methane-air mixtures in coal mines. Practical significance: The joint use of lean methane and biogas from straw offers practical advantages both economically, ensuring sufficient energy supply in mines, and as a foundation for broad future prospects. It allows for energy cost reduction and environmental pollution reduction, such as decreasing carbon dioxide emissions.

Evaluation and Optimization of Multi-Parameter Prediction Index for Coal Spontaneous Combustion Combined with Temperature Programmed Experiment

Coal spontaneous combustion (CSC) is a serious threat to the safe mining of coal resources, and the selection of suitable gas indicators to predict the CSC state is crucial for the prevention and control of coal mine fires. In this paper, the temperature-programmed experiment of CSC was first carried out to analyze the gas components and compositions in the oxidative pyrolysis process of three coal samples (lignite, long-flame coal, and lean coal) with different coalification degrees. Subsequently, the spontaneous combustion tendency of these three coal samples was evaluated. Finally, through the variation of gas concentration, gas concentration ratio, and fire coefficient with coal temperature, the indicators suitable for predicting the spontaneous combustion of coal were preferred, and a multi-parameter indicator system was established to make a comprehensive judgment on the spontaneous combustion status of coal. The results show that coal rank is negatively correlated with oxygen consumption rate. The higher the coalification degree of coal, the slower the oxidation reaction and the later the characteristic temperature point appears. The lignite selected in this experiment is a type of coal that is more prone to spontaneous combustion than long-flame coal and poor coal, and the CO concentration, C2H6/CH4, and second fire coefficient R2 can be used as the main indicators for predicting CSC, while the other gases, olefin-alkane ratio and fire coefficient can be used as auxiliary indicators. To some extent, the research content can effectively and accurately determine the stage and degree of coal spontaneous combustion, which has a certain guiding role in predicting CSC.

Geologic and Geochemical Features of the Upper Devonian Coals of the North Timan (the Sula River Coal Field)

Abstract —The composition of the oldest coals of the Timan–northern Urals region has been studied comprehensively, and their hydrocarbon and microcomponent characteristics are given. The relationship between different types of coals and Late Devonian plant communities of the North Timan is revealed. It is also determined that some samples contain microspores, megaspores, and plant remains belonging mainly to the lycopod Helenia. The most probable source of jet coals is identified as the wood of the progymnosperm Callixylon. The values of vitrinite reflectance and Tmax and the data on the distribution of polycyclic biomarkers and methylphenanthrenes indicate the low maturation of the coal organic matter. The coal bitumen investigated here is characterized by the dominance of steranes and diaster-13(17)-enes of compositions C28 and C29. The following diterpanes are identified: beyerane, 16α(H)-kaurane, 16β(H)-kaurane, and 16α(H)-atisane. At the same time, phyllocladane is absent.

Coal Classification Based on Reflection Spectroscopy and the IAT-TELM Algorithm.

As a principal energy globally, coal's quality and variety critically influence the effectiveness of industrial processes. Different coal types cater to specific industrial requirements due to their unique attributes. Traditional methods for coal classification, typically relying on manual examination and chemical assays, lack efficiency and fail to offer consistent accuracy. Addressing these challenges, this work introduces an algorithm based on the reflectance spectrum of coal and machine learning. This method approach facilitates the rapid and accurate classification of coal types through the analysis of coal spectral data. First, the reflection spectra of three types of coal, namely, bituminous coal, anthracite, and lignite, were collected and preprocessed. Second, a model utilizing two hidden layer extreme learning machine (TELM) and affine transformation function is introduced, which is called affine transformation function TELM (AT-TELM). AT-TELM introduces an affine transformation function on the basis of TELM, so that the hidden layer output satisfies the maximum entropy principle and improves the recognition performance of the model. Third, we improve AT-TELM by optimizing the weight matrix and bias of AT-TELM to address the issue of highly skewed distribution caused by randomly assigned weights and biases. The method is named the improved affine transformation function (IAT-TELM). The experimental findings demonstrate that IAT-TELM achieves a remarkable coal classification accuracy of 97.8%, offering a cost-effective, rapid, and precise method for coal classification.

Effect of the Type and Particle Size of Coal on Inhibitory Influence for Coking Coal by Semi-soft Coking Coal

Effect of the Type and Particle Size of Coal on Inhibitory Influence for Coking Coal by Semi-soft Coking Coal

Effects of pressure and heating rate on coal pyrolysis: A study in simulated underground coal gasification

Underground coal gasification (UCG) is a promising technology which in-situ converts coal into fuel gases through controlled chemical reactions. In order to precisely control coal pyrolysis and increase the char yield, it is vital to understand the influences of operating factors such as heating rate and pressure, on coal pyrolysis. In this study, the effects of heating rate and pressure on the char formation of bituminous coal pyrolysis are investigated. The reaction mechanism of coal pyrolysis and the solid-state kinetic model are firstly reviewed. Subsequently, thermal experiments are conducted to study the effects of heating rate and pressure on coal pyrolysis characteristics. Moreover, the connection between the dominant coal pyrolysis reaction type and corresponding solid-state kinetic model is revealed. An empirical model of coal pyrolysis rate, pressure, and heating rate is also developed, which can be used to quantitatively predict pyrolysis rates under varying heating rate and pressure conditions. The results show that the optimal heating rate for char generation is at around 10 °C/min. On the other hand, when the pressure exceeds 2 MPa, it will enhance the char production by obstructing the physical release of volatiles and has insignificant impact on the reaction type. This study contributes to our understanding of the coal pyrolysis mechanism, and the proposed empirical model can provide valuable insights for optimizing operating parameters during UCG process.

Experimental Research on Combustion, Pyrolysis Characteristics, and Kinetics of Three Different Coal Samples in China.

Coal thermal and kinetic parameters are important for the design of combustion reactors and risk assessment. Two methods were employed to investigate such key parameters of lignite, bituminous, and anthracite coal samples from China. With thermogravimetry (TG) and differential scanning calorimetry (DSC) methods, two distinct transitional stages were found in all coal samples combustion, but reaction intervals shifted to higher temperatures from lignite to anthracite and varied between 317 and 665 °C depending on the sample nature. Compared to the other two coal types, the pyrolysis of anthracite was less sensitive to increasing temperature, and its combustion process occurred at a much higher temperature. The results indicated that anthracite is difficult to ignite but has a considerable heat of reaction of 22.6 kJ/kg if ignited, which is close to that of bituminous. The basket heating method was used to obtain the kinetic data. Sample activation energies varied in the ranges of 38-51 kJ/mol from TG analysis and 49-67 kJ/mol from basket heating tests. Both results were comparable and consistent with the reference data. Due to its higher activation energy, anthracite poses a lower risk of thermal runaway than other coal types. This conclusion was validated by performing a minimum ignition temperature determination of a dust layer (MITL). In contrast, lignite and bituminous should be handled with greater safety precautions in coal-related process industries. The data presented will be used for hazard analysis and for designing more efficient combustion reactors in power plants. The data collected led to an extension of the current data for coal dust, as found in the literature.

Ignition characteristics and alkali metal release behaviors of single-particle coal in O2/CO2 or O2/N2 atmospheres using optical diagnostic technology

In this study, the ignition characteristics of and alkali metal release behaviors of single-particle coal were investigated using single-particle coal combustion system coupled with optical diagnostic technology. Furthermore, the effects of coal types (Yangchangwan bituminous coal (YCW), and Naomaohu lignite (NMH)) and oxygen concentration in different atmospheres (i.e., O2/CO2 and O2/N2) were analyzed. The results show that since the specific heat capacity of CO2 is higher than that of N2, the flame temperature in the O2/CO2 atmosphere is lower in the combustion process of coal particles, resulting in a longer ignition delay and combustion time for both coals than in the O2/N2 atmosphere. The maximum flame area of the YCW is twice as long as that of the NMH coal in the different atmospheres. The Na* and K* radiation intensity of coal particles in the O2/N2 atmosphere is stronger than in the O2/CO2 atmosphere, and due to the influence of the volatile matter content of NMH. However, the Na* radiation intensity in the O2/N2 atmosphere is more likely to show a bimodal distribution with increasing oxygen concentration, i.e. the boundary between the volatile reaction phase and the coke combustion phase is clearer.

Relationship between fluorescence characteristics of coal macerals and excitation time

The fluorescence characteristics of coal macerals can be used as one of the indexes to evaluate the properties of coking coal. In this work, a single-wavelength laser with a wavelength of 360 nm was used as the excitation source to excite the surface of particulate block under a polarizing microscope. Effect of excitation time on fluorescence characteristics of the macerals was studied. The relationship between spontaneous fluorescence intensity and the excitation time of each maceral of six kinds of coking coals show that the fluorescence characteristics of coal macerals are related to the type and metamorphism of coal. The excitation time has a certain effect on the fluorescence parameters of the macerals. By comparing the relative fluorescence intensity values under different excitation times, it is found that the mean relative fluorescence intensity within 15 s can be used as an optical parameter to characterize the structure and metamorphic grade of different macerals. The essence of this method is to express movement of electrons in outer layer of nucleus by macroscopic fluorescence spectrum and relative fluorescence intensity of the initial state value and simplify microscopic complexity into macroscopic and numerical form generally accepted.

Online Coal Identification Based on One-Dimensional Convolution and Its Industrial Applications

In order to improve the utilization rate of coal generation and reduce carbon emissions from coal-fired boilers, the operation parameters of power plant boilers should be matched with the actual burning coal. Due to the complex and high-risk blending process of multiple coal types, the actual application of coal types inconsistent with expectations may lead to low combustion efficiency of boilers, cause disturbances to the normal operation of thermal power units, increased energy waste and carbon emissions, and even lead to serious explosion accidents. Therefore, the online identification of coal types for thermal power units is of great significance. To obtain the precise type of coal online, in the present work, a data-driven coal identification method is proposed based on convolutional networks that do not necessitate additional hardware detection equipment and are easy to implement. Experimental results indicate that the proposed method exhibits superior performance in comparison to traditional methods, thus ultimately improving the performance of thermal power plant.

Dual-energy X-ray transmission identification method of multi-thickness coal and gangue based on SVM distance transformation

By weakening the influence of dual-energy X-ray transmission (DE-XRT) thickness on the coal and gangue identification, this study aims to reveal the effect of thickness, density, and coal type on sorting. Considering the imaging law of coal and gangue in R-I two-dimensional extended space, on the basis of particle swarm optimization (PSO) and support vector machine (SVM), a distance transform image processing and identification method is provided in this study. For this method, the distance between the (R, I) coordinates of coal and gangue and the SVM hyperplane is expressed as the relative density, indicating the details of the internal density change of the coal and gangue target. The average value ME of a single target distance d and the proportion RA of positive value of d can be used as sorting parameters to adjust the sorting. Both ME and RA are verified to have high correlation with density. When the gangue density is higher than 1.8 g/cm3, ME and RA are set to 0.05 and 50%, respectively, thereby realizing the gangue pre-discharge of 5 ∼ 150 mm thick raw coal. Raw coal pre-discharge has the identification rate of 100%, and the recognition rate of different densities and coal types mixed is 96.32%. Within the thickness range of 5 ∼ 150 mm, ME and RA still depend on thickness. By adjusting ME and RA, coal with large thickness and low density may be excluded by mistake. Compared with RA, ME exhibits a higher correlation with density and a lower correlation with thickness. Hence, ME can be selected to participate in regulatory sorting, thereby obtaining more accurate results. For parameter selection and regulation of DE-XRT separation of multiple thicknesses, densities, and coal types, this study provides a new method and practical guidance.

Residential combustion of coal: Effect of the fuel and combustion stage on emissions

Worldwide coal is still used for household heating purposes not only because it is available and cheap but also due to behavioural issues. Regional variability in fuels and combustion appliances make accurate emission estimates from this source hard to achieve. In the present study, gaseous (CO, VOCs, SO2 and NOX) and particulate matter (TSP) emission factors (EFs) were determined for Spanish household coal combustion covering three commercial coals and distinct combustion stages and mimicking usage patterns in real households. TSP samples were analysed to determine water-soluble inorganic ions, metal(loid)s, and organic and elemental carbon (OC and EC). Additionally, the morphology of the emitted particles was also characterised.CO (3.43–169 g kg−1), NOX (1.29–6.00 g kg−1) and SO2 (8.96–22.3 g kg−1) EFs showed no trend regarding the combustion stage or coal type tested. On the other hand, VOC, TSP and EC EFs were higher for the ignition/devolatilisation combustion stage, regardless of the fuel tested. TSP EFs (0.085–1.08 g kg−1) increased with increasing coal volatile matter while the opposite trend was recorded for VOC emissions (0.045–3.39 gC kg−1).TSP carbonaceous matter was dominated by EC while OC represented a small fraction of the particulate mass emitted (less than 8 %wt.). Inorganic compounds composed an important fraction of the TSP samples. Sulphate particulate mass fractions (8.66–22.9 %wt.) appeared to increase with coal S-content. Coal combustion released particles with diverse morphologies, including silicate-rich particles, ferro- and glassy-spheres. This study provides novel emission factors to update emission inventories of residential coal combustion. Additionally, detailed chemical profiles were obtained for source apportionment.

Transformation of Zn and Cr during co-combustion of sewage sludge and coals: influence of coal and steam.

Combustion experiments of sewage sludge (SS) blended with low-rank coal were conducted through a drop tube furnace (DTF) to explore the effects of low-rank coal type, blending ratio, and steam on the transformation of Zn and Cr. The results showed that the retention rates of Zn and Cr in ash increased from 24.35% and 71.49% for sludge combustion alone to 53.77% and 117.49%, respectively, for coal blended to SS with a mass ratio of 7:3. The greater the proportion of low-rank coal in the fuel, the greater the residual rate of heavy metals in the ash. Meanwhile, rapid diffusion of vapor occupied adsorption sites on metal mineral surfaces, reducing the retention of Zn and Cr in the co-combustion ash. The leaching toxicity analysis of ash showed that the co-combustion ash of SS with coal was free from leaching toxicity hazards in simulated scenarios. The extraction rate of Zn in co-combustion ash increased from 90.72% with hydrothermal acid leaching to 95.46% with microwave-assisted in 2mol/L H2SO4 extract. The extraction rate of Cr in hydrothermal acid leaching was 62.80%, which was much higher than that in microwave-assisted extraction (31.76%).

Investigation on the mechanism of solvothermal extraction of coals by macromolecular models

In this study, solvothermal extraction of two coals (Fangezhuang fat coal, FGZ; Sima lean coal, SM) were conducted by N-methylpyrrolidone (NMP); the molecular models of corresponding hypercoals (HPC) were firstly constructed besides that of coals to clarify the extractions mechanism, aiming to provide a technically feasible route to investigate the mechanism of other extraction processes. The structural parameters were obtained by means of proximate analysis, ultimate analysis, carbon-13 nuclear magnetic resonance spectroscopy, X-ray photoelectron spectroscopy and Fourier Transform infrared spectroscopy. The results showed that aromatic ring types of both raw coals were mainly naphthalene and anthracene, nitrogen atoms existed in pyrrole and pyridine whilst sulfur atoms in thiophene substantially, aliphatic carbons presented in the form of methyl and methylene groups while oxygen-containing functional groups mainly consisted of phenolic hydroxyl, carbonyl, carboxyl and a few ether bonds. Thus, the macromolecular structure models were constructed, with simulated molecular formulas were C168H136N2O12S, C135H74N2O12S, C166H136N2O6S and C128H82N2O11, respectively. After modifying the macromolecular models by Materials Studio for geometric optimization, annealing dynamics calculation, density simulation and analysis of chemical bonds, these four models reflected the macromolecular structural characteristics precisely. On the other hand, both models of raw coals changed significantly in functional groups, branched chain length and quantity pre and post thermal extraction, indicated that the thermal extraction process was mainly affected by swelling behavior and pyrolysis. This study provided new theoretical support in the development of coal extraction technology and understanding of HPC on the macromolecular level by a model basis.

Changing Law of Permeability of Coal Reservoirs under Variable Pressure Conditions and Its Influence on Extraction Efficiency of Coalbed Methane

Coal permeability data are critical in the prevention and control of coal and gas outbursts in mines and are an important reservoir parameter for the development of coalbed methane. The mechanism by which permeability is affected by gas pressure is complex. We used a self-developed true triaxial seepage experimental device that collects lignite and anthracite coal samples, sets fixed axial pressure and confining pressure, and changes gas pressure by changing the orientation of the coal seam to study the influence of the gas pressure on the permeability of the coal seam under the conditions of different coal types and different bedding orientations. Coal permeability decreased rapidly and then decreased slowly and tended to be stable with the increase in gas pressure. This conformed to the power exponential fitting relationship, and the fitting degree reached more than 99%. The comparison of the two anthracite coal samples showed that the sample’s permeability with a bedding plane vertical to the seepage direction was significantly lower than that of the bedding plane parallel to the seepage direction, indicating that gas seeped more easily along the bedding. The sensitivity coefficient of permeability with the change in gas pressure was calculated. The analysis showed that coal permeability was sensitive to changes in gas pressure during the low-pressure stage. When the gas pressure was greater than 0.8 MPa, the sensitivity coefficient was significantly reduced, which may have been related to the slow increase in the amount of gas absorbed by the coal seam in the high-pressure stage. A theoretical calculation model of coal seam permeability considering adsorption/desorption and seepage effects was proposed and then verified with experimental results showing that the theoretical model better reflected the permeability characteristics of coal and predicted its permeability. Using the finite element simulation software COMSOL, the extraction efficiency of the coal seam gas under different gas pressure conditions was simulated. The results showed that coal permeability and extraction efficiency decreased with an increase in gas pressure. In the low-pressure stage, the reduction in the extraction efficiency was more evident than that in the high-pressure stage.