Strength criterion effect of the translator and destabilization model of gas-bearing coal seam

Coal seam destabilization inflicts damage to equipment, causes property loss and personnel casualties,and severely threatens mining safety and efficient production. To further understand this destabilization based on the basic theory of Lippmann seam destabilization, a mathematical model was introduced for gas pressure distribution by considering intermediate principal stress and support resistance.Subsequently, we established a translation model suitable for the entire roadway coal seam with rocky roof and floor by applying the unified form of yield criterion in the state of plane strain. We also obtained the analytic expressions of coal seam stress distribution on both sides of the roadway and the widths of plastic and disturbance zones. Afterward, we analyzed several typical cases with different material yield criteria, obtained the plastic zone widths of the coal seam under different gas pressures, and assessed the effects of support resistance, roadway size, and coal strength on coal seam destabilization. Results showed that: the results obtained on the basis of Wilson and Mohr–Coulomb criteria are considerably conservative, and the use of Druker–Prager criteria to evaluate the rockburst-induced coal seam destabilization is safer than the use of the two other criteria; coal seam stability is correlated with gas pressure;and high-pressure gas accelerates the coal seam destabilization.

Heat-fluid-solid coupling model for gas-bearing coal seam and numerical modeling on gas drainage promotion by heat injection

Improving the absorbed gas to active desorption and seepage and delaying gas drainage attenuation are considered as key methods for increasing drainage efficiency and gas output.According to the solid mechanics theory,the nonlinear Darcy seepage theory and thermodynamics,the heat-fluid-solid coupling model for gassy coal has been improved.The numerical model was founded from the improved multi-field coupling model by COMSOL Multiphysics and gas drainage by borehole down the coal seam enhanced by heat injection was modelled.The results show that the heatfluid-solid model with adsorption effects for gassy coal was well simulated by the improved multi-field model.The mechanism of coal seam gas desorption seepage under the combined action of temperature,stress and adsorption can be well described.Gas desorption and seepage can be enhanced by heat injection into coal seams.The gas drainage rate was directly proportional to the temperature of injected heat in the scope of 30-150 ℃ and increasing in the whole modelleddrainage process (0-1000 d).The increased level was maximum in the initial drainage time and decreasing gradually along with drainage time.The increasing ratio of drainage rate was maximum when the temperature raised from 30 to 60 ℃.Although the drainage rate would increase along with increasing temperature,when exceeding 60 ℃,the increasing ratio of drainage rate with rising temperature would decrease.Gas drainage promotion was more effective in coal seams with lower permeability than with higher permeability.The coal seam temperature in a 5 m distance surrounding the heat injection borehole would rise to around 60 ℃ in 3 months.That was much less than the time of gas drainage in the coal mines in sites with low permeability coal seams.Therefore,it is valuable and feasible to inject heat into coal seams to promote gas drainage,and this has strong feasibility for coal seams with low permeability which are widespread in China.

Experimental study on the infrared precursor characteristics of gas-bearing coal failure under loading

The stress and gas pressure in deep coal seams are very high,and instability and failure rapidly and intensely occur.It is important to study the infrared precursor characteristics of gas-bearing coal instability and failure.In this paper,a self-developed stress-gas coupling failure infrared experimental system was used to analyse the infrared radiation temperature(IRT)and infrared thermal image precursor characteristics of gas-free coal and gas-bearing coal.The changes in the areas of the infrared temperature anomalous precursor regions and the effect of the gas on the infrared precursors were examined.The results show that high-temperature anomalous precursors arise mainly when the gas-free coal fails under loading,whereas the gas-bearing coal has high-temperature and low-temperature anomalous precursors.The area of the high-temperature anomalous precursor is approximately 30%–40%under gasbearing coal unstable failure,which is lower than the 60%–70%of the gas-free coal.The area of the low-temperature abnormal precursor is approximately 3%–6%,which is higher than the 1%–2%of the gas-free coal.With increasing gas pressure,the area of the high-temperature anomalous precursor gradually decreases,and the area of the low-temperature anomalous precursor gradually increases.The highand low-temperature anomalous precursors of gas-bearing coal are mainly caused by gas desorption,volume expansion,and thermal friction.The presence of gas inhibits the increase in IRT on the coal surface and increases the difficulty of infrared radiation(IR)monitoring and early warning for gas-bearing coal.

Deep learning CNN-APSO-LSSVM hybrid fusion model for feature optimization and gas-bearing prediction

Conventional machine learning(CML)methods have been successfully applied for gas reservoir prediction.Their prediction accuracy largely depends on the quality of the sample data;therefore,feature optimization of the input samples is particularly important.Commonly used feature optimization methods increase the interpretability of gas reservoirs;however,their steps are cumbersome,and the selected features cannot sufficiently guide CML models to mine the intrinsic features of sample data efficiently.In contrast to CML methods,deep learning(DL)methods can directly extract the important features of targets from raw data.Therefore,this study proposes a feature optimization and gas-bearing prediction method based on a hybrid fusion model that combines a convolutional neural network(CNN)and an adaptive particle swarm optimization-least squares support vector machine(APSO-LSSVM).This model adopts an end-to-end algorithm structure to directly extract features from sensitive multicomponent seismic attributes,considerably simplifying the feature optimization.A CNN was used for feature optimization to highlight sensitive gas reservoir information.APSO-LSSVM was used to fully learn the relationship between the features extracted by the CNN to obtain the prediction results.The constructed hybrid fusion model improves gas-bearing prediction accuracy through two processes of feature optimization and intelligent prediction,giving full play to the advantages of DL and CML methods.The prediction results obtained are better than those of a single CNN model or APSO-LSSVM model.In the feature optimization process of multicomponent seismic attribute data,CNN has demonstrated better gas reservoir feature extraction capabilities than commonly used attribute optimization methods.In the prediction process,the APSO-LSSVM model can learn the gas reservoir characteristics better than the LSSVM model and has a higher prediction accuracy.The constructed CNN-APSO-LSSVM model had lower errors and a better fit on the test dataset than the other individual models.This method proves the effectiveness of DL technology for the feature extraction of gas reservoirs and provides a feasible way to combine DL and CML technologies to predict gas reservoirs.

Pore Connectivity of Deep Lacustrine Shale and its Effect on Gas-bearing Characteristics in the Songliao Basin:Implications from Continental Scientific Drilling

The lacustrine shale of deep Shahezi Formation in the Songliao basin has great gas potential,but its pore evolution,heterogeneity,and connectivity characteristics remain unclear.In this work,total organic carbon analysis,rock pyrolysis,X-ray diffraction field emission scanning electron microscopy,the particle and crack analysis system software,low-temperature nitrogen adsorption experiment,fractal theory,high-pressure mercury injection experiment and nuclear magnetic resonance experiment were used to study the Shahezi shale from Well SK-2.The result indicated that the organic pores in Shahezi shale are not developed,and the intergranular and intragranular pores are mainly formed by illitedominated clay.As the burial depth increases,the pore size and slit-shaped pores formed by clay decrease,and dissolved pores in the feldspar and carbonate minerals and dissolved fractures in the quartz increase.The pore evolution is affected by clay,compaction,and high-temperature corrosion.Based on the pore structure characteristics reflected by the pore size distribution and pore structure parameters obtained by multiple experimental methods,the pore development and evolution are divided into three stages.During stageⅠandⅡ,the pore heterogeneity of the shale reservoirs increases with the depth,the physical properties and pore connectivity deteriorate,but the gas-bearing property is good.In stageⅢ,the pore heterogeneity is the highest,its gas generation and storage capacity are low,but the increase of micro-fractures makes pore connectivity and gas-bearing better.

Numerical analysis on the factors affecting post-peak characteristics of coal under uniaxial compression

The post-peak characteristics of coal serve as a direct reflection of its failure process and are essential parameters for evaluating brittleness and bursting liability.Understanding the significant factors that influence post-peak characteristics can offer valuable insights for the prevention of coal bursts.In this study,the Synthetic Rock Mass method is employed to establish a numerical model,and the factors affecting coal post-peak characteristics are analyzed from four perspectives:coal matrix mechanical parameters,structural weak surface properties,height-to-width ratio,and loading rate.The research identifies four significant influencing factors:deformation modulus,density of discrete fracture networks,height-to-width ratio,and loading rate.The response and sensitivity of post-peak characteristics to single-factor and multi-factor interactions are assessed.The result suggested that feasible prevention and control measures for coal bursts can be formulated through four approaches:weakening the mechanical properties of coal pillars,increasing the number of structural weak surfaces in coal pillars,reducing the width of coal pillars,and optimizing mining and excavation speed.The efficacy of measures aimed at weakening the mechanical properties of coal is successfully demonstrated through a case study on coal burst prevention using large-diameter borehole drilling.

Geological characteristics and exploration breakthroughs of coal rock gas in Carboniferous Benxi Formation,Ordos Basin,NW China

To explore the geological characteristics and exploration potential of the Carboniferous Benxi Formation coal rock gas in the Ordos Basin,this paper presents a systematic research on the coal rock distribution,coal rock reservoirs,coal rock quality,and coal rock gas features,resources and enrichment.Coal rock gas is a high-quality resource distinct from coalbed methane,and it has unique features in terms of burial depth,gas source,reservoir,gas content,and carbon isotopic composition.The Benxi Formation coal rocks cover an area of 16×104km^(2),with thicknesses ranging from 2 m to 25 m,primarily consisting of bright and semi-bright coals with primitive structures and low volatile and ash contents,indicating a good coal quality.The medium-to-high rank coal rocks have the total organic carbon(TOC)content ranging from 33.49%to 86.11%,averaging75.16%.They have a high degree of thermal evolution(Roof 1.2%-2.8%),and a high gas-generating capacity.They also have high stable carbon isotopic values(δ13C1of-37.6‰to-16‰;δ13C2of-21.7‰to-14.3‰).Deep coal rocks develop matrix pores such as gas bubble pores,organic pores,and inorganic mineral pores,which,together with cleats and fractures,form good reservoir spaces.The coal rock reservoirs exhibit the porosity of 0.54%-10.67%(averaging 5.42%)and the permeability of(0.001-14.600)×10^(-3)μm^(2)(averaging 2.32×10^(-3)μm^(2)).Vertically,there are five types of coal rock gas accumulation and dissipation combinations,among which the coal rock-mudstone gas accumulation combination and the coal rock-limestone gas accumulation combination are the most important,with good sealing conditions and high peak values of total hydrocarbon in gas logging.A model of coal rock gas accumulation has been constructed,which includes widespread distribution of medium-to-high rank coal rocks continually generating gas,matrix pores and cleats/fractures in coal rocks acting as large-scale reservoir spaces,tight cap rocks providing sealing,source-reservoir integration,and five types of efficient enrichment patterns(lateral pinchout complex,lenses,low-amplitude structures,nose-like structures,and lithologically self-sealing).According to the geological characteristics of coal rock gas,the Benxi Formation is divided into 8 plays,and the estimated coal rock gas resources with a buried depth of more than 2000 m are more than 12.33×10^(12)m^(3).The above understandings guide the deployment of risk exploration.Two wells drilled accordingly obtained an industrial gas flow,driving the further deployment of exploratory and appraisal wells.Substantial breakthroughs have been achieved,with the possible reserves over a trillion cubic meters and the proved reserves over a hundred billion cubic meters,which is of great significance for the reserves increase and efficient development of natural gas in China.

Stability analysis of longwall top-coal caving face in extra-thick coal seams based on an innovative numerical hydraulic support model

The relationship between support and surrounding rock is of great significance to the control of surrounding rock in mining process.In view of the fact that most of the existing numerical simulation methods construct virtual elements and stress servo control to approximately replace the hydraulic support problem,this paper establishes a new numerical model of hydraulic support with the same working characteristics as the actual hydraulic support by integrating numerical simulation software Rhino,Griddle and FLAC3D,which can realize the simulation of different working conditions.Based on this model,the influence mechanism of the supporting strength of hydraulic support on surrounding rock stress regulation and coal stability in front of the top coal caving face in extra thick coal seam were researched.Firstly,under different support intensity,the abutment pressure of the bearing coal and the coal in front of it presents the “three-stage”evolution characteristics.The influence range of support intensity is 15%–30%.Secondly,1.5 MPa is the upper limit of impact that the support strength can have on the front coal failure area.Thirdly,within a displacement range of 2.76 m from the coal wall,a support strength of1.5 MPa provides optimal control of the horizontal displacement of the coal.

Structural properties of residual carbon in coal gasification fine slag and their influence on flotation separation and resource utilization:A review

Coal gasification fine slag(FS)is a typical solid waste generated in coal gasification.Its current disposal methods of stockpil-ing and landfilling have caused serious soil and ecological hazards.Separation recovery and the high-value utilization of residual carbon(RC)in FS are the keys to realizing the win-win situation of the coal chemical industry in terms of economic and environmental benefits.The structural properties,such as pore,surface functional group,and microcrystalline structures,of RC in FS(FS-RC)not only affect the flotation recovery efficiency of FS-RC but also form the basis for the high-value utilization of FS-RC.In this paper,the characteristics of FS-RC in terms of pore structure,surface functional groups,and microcrystalline structure are sorted out in accordance with gasification type and FS particle size.The reasons for the formation of the special structural properties of FS-RC are analyzed,and their influence on the flotation separation and high-value utilization of FS-RC is summarized.Separation methods based on the pore structural characterist-ics of FS-RC,such as ultrasonic pretreatment-pore-blocking flotation and pore breaking-flocculation flotation,are proposed to be the key development technologies for improving FS-RC recovery in the future.The design of low-cost,low-dose collectors containing polar bonds based on the surface and microcrystalline structures of FS-RC is proposed to be an important breakthrough point for strengthening the flotation efficiency of FS-RC in the future.The high-value utilization of FS should be based on the physicochemical structural proper-ties of FS-RC and should focus on the environmental impact of hazardous elements and the recyclability of chemical waste liquid to es-tablish an environmentally friendly utilization method.This review is of great theoretical importance for the comprehensive understand-ing of the unique structural properties of FS-RC,the breakthrough of the technological bottleneck in the efficient flotation separation of FS,and the expansion of the field of the high value-added utilization of FS-RC.

Theoretical analysis of hydrogen solubility in direct coal liquefaction solvents

The cyclic hydrogenation technology in a direct coal liquefaction process relies on the dissolved hydrogen of the solvent or oil participating in the hydrogenation reaction.Thus,a theoretical basis for process optimization and reactor design can be established by analyzing the solubility of hydrogen in liquefaction solvents.Experimental studies of hydrogen solubility in liquefaction solvents are challenging due to harsh reaction conditions and complex solvent compositions.In this study,the composition and content of liquefied solvents were analyzed.As model compounds,hexadecane,toluene,naphthalene,tetrahydronaphthalene,and phenanthrene were chosen to represent the liquefied solvents in chain alkanes and monocyclic,bicyclic,and tricyclic aromatic hydrocarbons.The solubility of hydrogen X(mol/mol)in pure solvent components and mixed solvents(alkanes and aromatics mixed in proportion to the chain alkanes+bicyclic aromatic hydrocarbons,bicyclic saturated aromatic hydrocarbons+bicyclic aromatic hydrocarbons,and bicyclic aromatic hydrocarbons+compounds containing het-eroatoms composed of mixed components)are determined using Aspen simulation at temperature and pressure conditions of 373–523 K and 2–10 MPa.The results demonstrated that at high temperatures and pressures,the solubility of hydrogen in the solvent increases with the increase in temperature and pressure,with the pressure having a greater impact.Further-more,the results revealed that hydrogen is more soluble in straight-chain alkanes than in other solvents,and the solubility of eicosanoids reaches a maximum of 0.296.The hydrogen solubility in aromatic ring compounds decreased gradually with an increase in the aromatic ring number.The influence of chain alkanes on the solubility of hydrogen predominates in a mixture of solvents with different mixing ratios of chain alkanes and aromatic hydrocarbons.The solubility of hydrogen in mixed aromatic solvents is less than that in the corresponding single solvents.Hydrogen is less soluble in solvent compounds containing heteroatoms than in compounds without heteroatoms.

多功能CoAl-LDH/CdS光催化剂的制备及其性能研究

在能源危机和环境污染的双重挑战下,开发集能量转化和环境治理于一体的多功能光催化剂是促进太阳能-化学能转化的有效策略。采用正六边形的CoAl-LDH纳米薄片为载体,通过原位生长CdS纳米颗粒的方法,构建了CoAl-LDH/CdS的Ⅱ型异质结。利用CoAl-LDH纳米薄片在可见光区域的宽普吸收性和良好载体的特性,结合CdS的高光量子产率,再通过异质结构的构建,获得了多功能CoAl-LDH/CdS光催化材料。并通过优化CdS的负载量,获得的CoAl-LDH/CdS-2光催剂降解罗丹明B的降解率最大(在光催化降解时间t=60 min时内,降解率=88.48%),分别是CdS和CoAl-LDH单体的1.18倍和8.62倍。其中CoAl-LDH/CdS-1的CO产量最高为39.02 mol/g,分别是纯CoAl-LDH和纯CdS的4.2倍和2.5倍,这主要归功于复合材料中CoAl-LDH纳米片和CdS纳米颗粒间紧密异质结构的构建,丰富的耦合界面大大降低了光生载流子的复合率,这为多功能光催化剂的开发提供了理论基础。

Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.

Depositional Environment and Origin of Inertinite-rich Coal in the Ordos Basin

Inertinite-rich coal is widely distributed in the Ordos Basin,represented by the No.2 coal seam of the Middle Jurassic Yan'an Formation.This paper combined coal petrology and geochemistry to analyze the origin of inertinite,changes in the coal-forming environment and control characteristics of wildfire.Research has shown that there are two forms of inertinite sources in the study area.Alongside typical fusinization,wildfire events also play a substantial role in inertinite formation.There are significant fluctuations in the coal-forming environment of samples at different depths.Coal samples were formed in dry forest swamp with low water levels and strong oxidation,which have a high inertinite content,and the samples formed in wet forest swamp and limnic showed low inertinite content.Conversely,the inertinite content of different origins does not fully correspond to the depositional environment characterized by dryness and oxidation.Nonpyrogenic inertinites were significantly influenced by climatic conditions,while pyrofusinite was not entirely controlled by climatic conditions but rather directly impacted by wildfire events.The high oxygen level was the main factor causing widespread wildfire events.Overall,the combination of wildfire activity and oxidation generates a high content of inertinite in the Middle Jurassic coal of the Ordos Basin.

Geochemical and petrological studies of high sulfur coal and overburden from Makum coalfield (Northeast India) towards understanding and mitigation of acid mine drainage

Opencast coal mining produces trash of soil and rock containing various minerals,that are usually dumped nearby the abandoned sites which causes severe environmental concern including the production of acid mine drainage(AMD)through oxidation pyrite minerals.The current study entailed assessing the potential production of AMD from an opencast coal mining region in Northeast part of India.In order to have a comprehensive overview of the AMD problem in Makum coalfield,the physico-chemical,geochemical,and petrological characteristics of the coal and overburden(OB)samples collected from the Makum coalfield(Northeast India)were thoroughly investigated.The maceral compositions reveal that coal features all three groups of macerals(liptinite,vitrinite,and inertinite),with a high concentration of liptinite indicating the coal of perhydrous,thereby rendering it more reactive.Pyrite(FeS_(2))oxidation kinetics were studied by conducting the aqueous leaching experiments of coal and(OB)samples to interpret the chemical weathering under controlled laboratory conditions of various temperature and time periods,and to replicate the actual mine site leaching.Inductively coupled plasma-optical emission spectroscopy(ICP-OES)was operated to detect the disposal of some precarious elements from coal and OB samples to the leachates during our controlled leaching experiment.The Rare earth element(REE)enrichment in the samples shows the anthropogenic incorporation of the REE in the coal and OB.These experiments reveal the change in conductivity,acid producing tendency,total dissolved solid(TDS),total Iron(Fe)and dissolved Sulfate(SO_(4)^(2−))ions on progress of the leaching experiments.Moreover,the discharge of FeS_(2) via atmospheric oxidation in laboratory condition undergoes a significant growth with the rise of temperature of the reaction systems in the environment and follows pseudo first order kinetics.A bio-remediative strategies is also reported in this paper to mitigate AMD water by employing size-segregated powdered limestone and water hyacinth plant in an indigenously developed site-specific prototype station.Apart from neutralisation of AMD water,this eco-friendly AMD remediation strategy demonstrates a reduction in PHEs concentrations in the treated AMD water.

Coal/Gangue Volume Estimation with Convolutional Neural Network and Separation Based on Predicted Volume and Weight

In the coal mining industry,the gangue separation phase imposes a key challenge due to the high visual similaritybetween coal and gangue.Recently,separation methods have become more intelligent and efficient,using newtechnologies and applying different features for recognition.One such method exploits the difference in substancedensity,leading to excellent coal/gangue recognition.Therefore,this study uses density differences to distinguishcoal from gangue by performing volume prediction on the samples.Our training samples maintain a record of3-side images as input,volume,and weight as the ground truth for the classification.The prediction process relieson a Convolutional neural network(CGVP-CNN)model that receives an input of a 3-side image and then extractsthe needed features to estimate an approximation for the volume.The classification was comparatively performedvia ten different classifiers,namely,K-Nearest Neighbors(KNN),Linear Support Vector Machines(Linear SVM),Radial Basis Function(RBF)SVM,Gaussian Process,Decision Tree,Random Forest,Multi-Layer Perceptron(MLP),Adaptive Boosting(AdaBosst),Naive Bayes,and Quadratic Discriminant Analysis(QDA).After severalexperiments on testing and training data,results yield a classification accuracy of 100%,92%,95%,96%,100%,100%,100%,96%,81%,and 92%,respectively.The test reveals the best timing with KNN,which maintained anaccuracy level of 100%.Assessing themodel generalization capability to newdata is essential to ensure the efficiencyof the model,so by applying a cross-validation experiment,the model generalization was measured.The useddataset was isolated based on the volume values to ensure the model generalization not only on new images of thesame volume but with a volume outside the trained range.Then,the predicted volume values were passed to theclassifiers group,where classification reported accuracy was found to be(100%,100%,100%,98%,88%,87%,100%,87%,97%,100%),respectively.Although obtaining a classification with high accuracy is the main motive,this workhas a remarkable reduction in the data preprocessing time compared to related works.The CGVP-CNN modelmanaged to reduce the data preprocessing time of previous works to 0.017 s while maintaining high classificationaccuracy using the estimated volume value.

Agglomeration of coal and polyethylene mixtures during fixed‑bed co‑gasification

The article presents the results of experimental studies on the gasification of mixtures of brown coal and polyethylene(up to 20 wt%fraction)in a laboratory reactor.The work aims to study the agglomeration process during the heating and oxidation of the mixtures.The measurement results(gas composition,pressure drop)provide indirect information on the dynamics of thermal decomposition and structural changes in the fuel bed.We have shown that the interaction between polyethylene and a coal surface leads to the formation of dense agglomerates,in which the molten polymer acts as a binder.Clinkers form as a result of interfacial interactions between components and filtration flow rearranging.The hydrogen/carbon ratio in the solid residue of coal-polyethylene co-gasification increases from 0.07–0.2 to 1.11,indicating the formation of stable hydrocarbon compounds on the carbon surface.The conducted research makes it possible to identify possible interactions between chemical reactions and transfer processes that lead to agglomeration in mixtures of coal with polyethylene.

Thermogravimetric characteristics of corn straw and bituminous coal copyrolysis based the ilmenite oxygen carriers

Herein,the co-pyrolysis reaction characteristics of corn straw(CS)and bituminous coal in the presence of ilmenite oxygen carriers(OCs)are investigated via thermogravimetry coupled with mass spectrometry.The results reveal that the participation of OCs weakens the devolatilization intensity of co-pyrolysis.When the CS blending ratio is<50%,the mixed fuel exhibits positive synergistic effects.The fitting results according to the Coats-Redfern integral method show that the solid-solid interaction between OCs and coke changes the reaction kinetics,enhancing the co-pyrolysis reactivity at the high-temperature zone(750-950C).The synergistic effect is most prominent at a 30%CS blending ratio,with copyrolysis activation energy in the range of 26.35-40.57 kJ·mol^(-1).

Theoretical analysis and engineering application of controllable shock wave technology for enhancing coalbed methane in soft and low‑permeability coal seams

Coalbed methane(CBM)is a significant factor in triggering coal and gas outburst disaster,while also serving as a clean fuel.With the increasing depth of mining operations,coal seams that exhibit high levels of gas content and low permeability have become increasingly prevalent.While controllable shockwave(CSW)technology has proven effective in enhancing CBM in laboratory settings,there is a lack of reports on its field applications in soft and low-permeability coal seams.This study establishes the governing equations for stress waves induced by CSW.Laplace numerical inversion was employed to analyse the dynamic response of the coal seam during CSW antireflection.Additionally,quantitative calculations were performed for the crushed zone,fracture zone,and effective CSW influence range,which guided the selection of field test parameters.The results of the field test unveiled a substantial improvement in the gas permeability coefficient,the average rate of pure methane flowrate,and the mean gas flowrate within a 10 m radius of the antireflection borehole.These enhancements were notable,showing increases of 3 times,13.72 times,and 11.48 times,respectively.Furthermore,the field test performed on the CSW antireflection gas extraction hole cluster demonstrated a noticeable improvement in CBM extraction.After antireflection,the maximum peak gas concentration and maximum peak pure methane flow reached 71.2%and 2.59 m^(3)/min,respectively.These findings will offer valuable guidance for the application of CSW antireflection technology in soft and low-permeability coal seams.

Effect and Mechanism of Rare Earth Hydrotalcite Inhibiting Coal Spontaneous Combustion

A hydrotalcite(layered double hydroxide, LDH) inhibitor which is suitable for the whole process of coal spontaneous combustion and a LDH inhibitor containing rare earth lanthanum elements were prepared. The inhibition effect and mechanism were analyzed by scanning electron microscopy(SEM),X-ray diffraction(XRD), thermal performance analysis, in-situ diffuse reflectance infrared spectroscopy and temperature-programmed experiment. The results have shown that the inhibitor containing lanthanum can play a good inhibitory role in every stage of coal oxidation. During the slow oxidation of coal samples, the inhibitor containing lanthanum ions can slow down the oxidation process of coal and increase the initial temperature of coal spontaneous combustion. At the same time, because the hydroxyl groups in LDHs are connected with-COO-groups on the coal surface through hydrogen bonds, the stability of coal is improved. With the increase of temperature, LDHs can remove interlayer water molecules and reduce the surface temperature of coal. CO release rate of coal samples decreases significantly after adding inhibitor containing lanthanum element, and the maximum inhibition rate of the inhibitor is 58.1%.

Influence mechanism of government subsidy on the green transformation of coal company in China

The optimization of government subsidies to enhance the efficiency of coal companies’green transformation constitutes a critical component in the pursuit of global sustainability.We investigate the influence mechanism of government subsidies on the green transformation using data from the listed coal companies in China from 2007 to 2022.According to our findings and hypothesis testing,previous government subsidies did not have a significant direct impact on coal companies’green transformation.Nevertheless,government subsidies can help coal companies transition to greener practices by promoting innovative green initiatives.Furthermore,we confirmed an indirect route:that government subsidies enable the adoption of low-carbon initiatives,which in turn could facilitate the transition of coal companies towards green practices.In addition,we discovered that the coal company’s digitization will improve this indirect route.Thus,we propose increasing the effectiveness of government subsidies in facilitating coal companies’transition to green practices by focusing on technological advancements and enhancing company digitalization.