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Coalbed methane (CBM) content is a crucial parameter for CBM exploitation and disaster prevention, with accurate gas loss calculation being essential for improving measurement precision. To investigate the physical response to gas loss and quantify the impact and interrelation of various factors, this study developed a comprehensive model incorporating the effects of gas diffusion, temperature, and pressure effects on porosity and coal deformation. By utilizing the OpenFOAM platform and C++ for numerical solution development and establishing an experimental system for gas loss measurement, the model's reliability was confirmed. The new model demonstrates an 8.56% average error, representing a significant improvement over traditional methods, with error reductions of 26.59% and 18.31% compared to the square root of time and power function methods, respectively. The hierarchy of gas loss is determined to be gas flow > gas-coal deformation coupling > gas-temperature coupling > gas-coal deformation-temperature coupling. Average diffusion contributions are identified as 41.43% from surface diffusion, 30.71% from Knudsen diffusion, and 27.86% from viscous flow. The factors affecting gas loss, in decreasing order of impact, are adsorption equilibrium pressure, temperature, porosity, moisture, and adsorption constants. These findings provide theoretical support for enhancing gas content measurement accuracy and techniques, significantly benefiting CBM extraction and mine safety. [ABSTRACT FROM AUTHOR]

The characteristics of coal desorption strain play a crucial role in coal permeability, coalbed methane (CBM) recovery, and the prevention of outbursts. This study developed an improved thermomechanical diffusion–seepage (TMDS) coupling model to investigate the strain evolution during the gas desorption process in coal. The model considers the time-varying diffusion coefficient, the Klinkenberg permeability effect, and the impact of moisture on adsorption, amending the traditional coal deformation equation and coal permeability model. Utilizing this model, the study explored the mechanism, contribution, and spatiotemporal evolution of desorption strain, while analyzing quantitatively the effects of gas types and TMDS parameters on the dynamics of desorption strain. The results demonstrate that desorption strain consists of fracture pressure, matrix pressure, desorption action, and temperature effects, with desorption action being the predominant factor. The impact of gas type, especially CO2, on desorption strain is significant, with CO2 enhancing CH4 desorption strain more than N2. Additionally, the study explored the sensitivity of desorption strain to TMDS parameters, revealing that gas pressure, permeability, and Langmuir pressure significantly impact desorption strain. Desorption strain can serve as an indicator for predicting and evaluating the risk of outbursts, and the injection of low-temperature liquid nitrogen could help reduce this risk. This research provides insights for further understanding the desorption mechanism in gas-bearing coal, improving CBM recovery, and preventing disasters. [ABSTRACT FROM AUTHOR]

Coalbed gas pressure and content are fundamental parameters for mine gas recovery and disaster prevention. In response to the lengthy measurement cycles and low accuracy of existing models, this research proposes a new model for determining coalbed gas pressure and content based on image analysis. Utilizing dual-threshold edge detection and dynamic cycle extraction algorithms, a desorption image database was developed, enabling rapid inversion of gas pressure/content through an enhanced image similarity calculation method and cycle comparison algorithm. Field experiments demonstrate the high accuracy of the image analysis model in determining gas pressure/content, controlling the absolute error of gas pressure below 0.08 MPa and maintaining relative errors of 2.27–8.05%; for gas content, the absolute errors range 0.105–0.674 ml/g, with relative errors of 1.32–8.21%. Compared to previous desorption models, the image analysis model improves accuracy by 6.30% and reduces the measurement time to within 1.5 h, thus facilitating rapid and precise determination of coalbed gas pressure/content. Furthermore, by applying image recognition principles, this study delves into the critical points and significant change areas of the desorption rate curve, providing new insights into gas desorption behavior and expanding the application potential of image analysis technology in coalbed methane recovery. [ABSTRACT FROM AUTHOR]

Coalbed methane (CBM) is a clean energy source, but its utilization is inefficient due to the complexity and low accuracy of its emission prediction model. In this research, we constructed a mathematical model of gas emission from the excavation workface, and combined the experimental results to propose a new model for accurate and concise prediction. The new model was validated in the field workface and compared with the traditional prediction model. Moreover, the sensitivity of gas emission parameters and the participation ratio of gas emission sources were analyzed. The study results show that the new model has higher calculation accuracy than the old model prediction, with an average error reduction of 4.693%. In the excavation workface, the coal fall gas emission conforms to the negative power function equation, and the coal wall gas emission conforms to the negative exponential function equation. In the early stage of excavation, the proportion of coal fall gas emission is higher than that of coal wall gas emission, and the peak proportion reaches 58.5%. In the later stage, the proportion of coal fall gas emission gradually decreases to below 30%. The order of the sensitivity of gas emission parameters is coal wall gas initial velocity > coal fall gas decay coefficient > coal fall gas initial velocity > coal wall gas decay coefficient. The new model is successfully applied in engineering, which helps to improve the efficiency of coal mine gas disaster control and utilization. [ABSTRACT FROM AUTHOR]

Glucagon‐like peptide‐1 (GLP‐1) can improve cardiac function and cardiovascular outcomes in diabetic cardiomyopathy; however, the beneficial effect of GLP‐1 on human diabetic cardiomyocytes (DCMs) and its mechanism have not been fully elucidated. Here, the DCMs model by human‐induced pluripotent stem cells‐derived cardiomyocytes is developed. Two subtypes of GLP‐1, GLP‐17–36 and GLP‐19‐36, are evaluated for their efficacy on the DCMs model. Diabetogenic condition is sufficient to induce most characteristics of diabetic cardiomyopathy in vitro, such as cardiac hypertrophy, lipid accumulation, impaired calcium transients, and abnormal electrophysiological properties. GLP‐17−36 and GLP‐19–36 can restore cardiomyocyte hypertrophic phenotype, impaired calcium transient frequency, abnormal action potential amplitude, depolarization, and repolarization velocity. Interestingly, RNA‐seq reveals different pathways altered by GLP‐17–36 and GLP‐19–36, respectively. Differentially expressed gene analysis reveals that possible targets of GLP‐17–36 involve the regulation of mitotic nuclear division and extracellular matrix–receptor interaction, while possible targets of GLP‐19–36 involve kinetochore assembly, and the complement and coagulation cascades. This study demonstrates the therapeutic effects of GLP‐1 on human DCMs and provides a novel platform to unveil the cellular mechanisms of diabetic cardiomyopathy, shedding light on discovering better targets for novel therapeutic interventions. [ABSTRACT FROM AUTHOR]

The content of coalbed methane (CBM) is an important parameter that affects the performance of coal extraction and the safety of coal mines. The importance of this parameter is especially more pronounced when using the direct method to determine CBM content, in which the measuring accuracy of the lost gas affects the results. The loss is affected by the gas pressure and exposure time. In this article, the influence of gas pressure and exposure time on the estimation results and loss rate was investigated. Moreover, the influence of the sampling interval and observation time on the accuracy of the kinetic model in simulating the desorption process was analyzed. The obtained results demonstrated that the lost gas is positively associated with pressure and exposure time, and the lost gas rate is proportional to the exposure time. It was found that although the Barrer method outperforms the power function method, in terms of calculation accuracy, both methods have large errors. In terms of physical sense and model accuracy, the pore diffusion (IDM) model best fits the desorption kinetics of this coal. In the stable desorption stage, the desorption process is more consistent with Henry's law. When the desorption changes violently, the desorption process is more consistent with Fick's diffusion law. In order to ensure the consistency between the model and the experiment (95% confidence interval), the sampling interval of IDM model at 1 MPa should be more than 30 s. [ABSTRACT FROM AUTHOR]

Gas drainage technology is closely related to the flow of methane in coal. Desorption and diffusion of gas in coal is an important basic research area, and particle size is one of the influencing factors. In this study, the desorption and diffusion characteristics of coal samples mixed with different particle sizes over time were measured under constant temperature and pressure. The results show that in the initial stage, the desorption volume and desorption rate of coal samples are relatively large. The improved desorption model can well fit the data and the order of desorption volume is negatively correlated to the mean particle size of coal samples. The single small particle coal sample has the largest desorption volume which reached 3.77ml/g. Both the unipore model and the constructed unsteady dynamic diffusion model can well describe the diffusion of gas in coal, the diffusion coefficient of coal sample decreases with time, and the decay rate decreases gradually with time until it remains unchanged. The calculation results of the two models show that the diffusion coefficient ranges of gas in coal between 10−10m2/s and 10−12m2/s. For single-particle coal samples, the diffusion coefficient is positively correlated with particle size. The diffusion coefficient D is affected by the particle size and the degree of compaction between coal particles. These observations indicate that coal samples with different particle sizes will affect the desorption and diffusion of gas, and it has a positive impact on methane recovery. [ABSTRACT FROM AUTHOR]

Water-based fracturing fluid is a key component in coal bed methane (CBM) extraction, which is a promising way forward for the green extraction of methane. The adsorption by coal is highly affected by tiny particles in the fracturing fluid. Aiming at exploring the effect of mixing non-adsorbent particles into coal on the adsorption, an atmospheric pressure granulated coal adsorption system with a flow meter was designed to perform tests. During the experiments, the effect of coal particle size, coal mass, and addition of tiny granules on adsorption was analyzed. The obtained results show that the addition of iron powder reduces the adsorption capacity and average adsorption rate of granular coal, and makes the adsorption speed peak earlier. It is found that the change in the adsorption amount has a weak positive correlation with the coal particle size, and the change of the average adsorption rate has a weak positive correlation with the size. However, in the absence of iron powder, the average adsorption rate is negatively correlated with the coal size, and the effect of the coal mass on the average adsorption rate and adsorption capacity is very weak. In large granular coal, the adsorption capacity is independent of size. Under the experimental conditions, strong adsorption occurred between 500 and 1750 s, and the adsorption kinetic process showed a slow-fast-slow "S"- curved distribution. [ABSTRACT FROM AUTHOR]

Mining disasters such as coal and gas outbursts and rock bursts seriously threaten safe coal mining. Accordingly, it is important to analyze the dynamic damage characteristics of gas-bearing coal and achieve safe coal mining. In the present study, the criterion of crack arrest for gas-bearing coal was set in accordance with the theory of gas dynamics and fracture mechanics. Then, the impact failure characteristics of gas-bearing coal subjected to an impact load were investigated. In this regard, different parameters, including the impact energy, gas pressure, and gas type, were considered. Moreover, the transient effect of the free gas on the coal destruction was analyzed. The influence of free gas-induced damage on the coal structure was also simulated using ANSYS 17.0 software. The obtained results show that, during the impact crushing of gas-bearing coal, the gas moves in the coal body, which tears the coal body and increases the crushing effect of coal. The crushing effect of gas-bearing coal has a linear correlation with gas pressure, impact energy, and gas adsorption strength. It was concluded that the proposed crack arrest criterion and numerical methods are powerful measures for analyzing the failure characteristics of gas-bearing coal. [ABSTRACT FROM AUTHOR]

The depressurization process usually occurs in a cargo compartment when an aircraft is taking off. The fire detection based on the vision-based flame has unique advantages in the confined and inaccessible environment. In this study, the n-heptane pool fires with a diameter of 30 cm were performed in a pressure cabin under decreasing pressure from 101 to 30 kPa. The vision-based flames were recorded by a high-resolution monitoring camera with a fixed aperture and exposure time. The shape features and texture features including flame area, perimeter, convexity, derived ratio, contrast, and correlation of gray-level co-occurrence matrix (GLCM) were extracted, which form a multidimensional vector. Then, the dimensionality reduction was conducted using principal component analysis (PCA) method, and a principal component was obtained to characterize the flame image, whose value had an excellent linear relationship with the instantaneous decreasing pressure. Further, the relationship was verified by a series of 20-cm-diameter pool fires. The study proves the feasibility of the quantitative fire detection method based on visual flame and provides the theoretical basics in applying to the confined and inaccessible space. [ABSTRACT FROM AUTHOR]

Coal and gas outbursts are complex dynamic phenomena and are highly hazardous. This article established an experimental system to research the damaging effect of gas on particulate coal during coal and gas outbursts, which replicated the outburst scenario by instantaneously releasing different-pressure gas. The results show that the higher the gas pressure is, the larger the new surface area is, and the gas damages the pulverized coal more drastically. The mass ratio of new granular size coal is between 8–27%. The surface area increased significantly (73.0%-245.2%). The mean order of increasing surface area is SC (1.102 m2)> DC (0.9875 m2)> SN (0.8999 m2)> DN (0.8369 m2), which indicates that the extent to which gas destroys particulate coal is inversely proportional to the solidity coefficient and positively proportional to the adsorptivity. The ability of weakly adsorbable gases to break particulate coal is more affected by gas pressure. The degree of breakage of low-firmness coals is more responsive to gas pressure. The percentage of coal mass broken by gas is positively correlated with gas pressure and adsorptivity and negatively correlated with the firmness coefficient. Finally, the quick release of gas occurs in three stages: an acceleration section (0–0.05 s), a high-speed section (0.05–0.15 s), and a deceleration section (after 0.15 s). [ABSTRACT FROM AUTHOR]

Coal is a complex porous medium. When gas exists in the coal body, the fissure structure of coal and the occurrence of gas adsorption make the stress state of gas-bearing coal different from that of ordinary coal. Therefore, the stress state of gas-bearing coal cannot be accurately described by the Terzaghi effective stress, which ignores the effects of crack deformation and methane. To improve the accuracy of gas-bearing coal analysis, this study considered the corrosive effect of free gas and adsorbed gas and the crack closure effect to establish a novel statistical damage constitutive model with consideration to the combined effects of free gas, adsorbed gas, and coal cracking. The established model was used to elucidate the effects of gas-bearing coal on the coal's mechanical deformation and damage characteristics under different stress conditions. The model was validated through full stress–strain experiments on gas-bearing coal under different axial pressure and gas pressure. The results obtained by the proposed statistical damage constitutive model can better describe the stress state of the gas-bearing coal, particularly in the initial stage of void compaction, and are in good agreement with the experimental data. The proposed model provides the theoretical foundation for future studies on the characteristic mechanism of gas-bearing coal. [ABSTRACT FROM AUTHOR]

Fractality is one of the inherent characteristics to present the irregularity and self-similarity of an object. In this study, the fractal theory was applied to the fire scene under decreasing pressure in an aircraft cargo compartment, considering that the compartment is usually inaccessible in flight and flame images are a kind of convenient monitoring information compared to other detection methods. A series of n-heptane pool fires were performed under decreasing pressure with four depressurized rates. The flame image was captured by a video camera with fixed aperture and exposure time. The fractal dimension (FD) of flame images was computed via two approaches, i.e., the box-counting (BC) and differential box-counting (DBC) methods. The results show that n-heptane pool fires have a good fractal property for both binary and grayscale images. The FD via BC method shows little sensitivity with decreasing pressure. However, the FD via DBC method presents a significant linear relationship with a slope of 0.0016 in the range from 2.85 to 2.75 during the depressurization. The quantitative correlation was brought into the classical radiation modeling, and the exponential function between FD and MLR of n-heptane was established. [ABSTRACT FROM AUTHOR]

Summary: As a form of energy dissipation, electromagnetic radiation (EMR) is gradually becoming a mainstream method prediction method for damage monitoring of coal and rock. To better improve the prediction accuracy of EMR, it is crucial to investigate time‐frequency characteristics of EMR and the influence of coal and rock properties on EMR that occurs in the fracture process. In this paper, the deformation and fracture process of raw coal, shaped coal, and cement specimens under compression are observed, and time‐frequency evolution characteristics of EMR below ultralow frequency (ULF) under different loading stages are evaluated. Then, the inherent reasons of time‐frequency evolution of EMR reflecting the damage performance are analyzed. Meanwhile, the effect of loading condition and composition and structure of materials on EMR is discussed. Results show that there is obvious EMR below ULF in the deformation and fracture process of coal and rock materials, and the combined denoising method of ensemble empirical mode decomposition (EEMD) and wavelet is suitable for extraction of EMR. Besides, the amplitude is approximately inversely proportional to frequency of electromagnetic signals, and the relationship between pulse count of EMR and damage is related to the homogeneity of coal and rock materials. Moreover, the time‐frequency characteristic parameter of EMR, such as amplitude, pulse count, and frequency spectrum, can indirectly reflect the damage evolution process of coal and rock. These results can provide a theoretical basis for remote monitoring of coal and rock dynamic disaster using EMR below ULF. [ABSTRACT FROM AUTHOR]

Understanding gas diffusion characteristics of coal particles is a significant theoretical basis for the exploitation of coalbed methane. Generally, diffusion experiments are performed under constant pressure conditions, and scholars seldom discuss gas desorption experiments with constant volume, but the recognition of this characteristic is also equally important. Based on this, the paper conducted coal particles desorption experiments under conditions of constant volume to explore gas diffusion characteristics under different adsorption equilibrium pressures and initial emission environmental pressures. The experimental data showed that the variation law of desorption amount with time under constant volume conditions conformed to the Langmuir-like equation. Meanwhile, the rising of initial emission environmental pressure reinforced the linear relationship between the limitation desorption amount and the adsorption equilibrium pressure. When the initial emission environmental pressure was 0.10 MPa, the correlation coefficient of linear fitting between them was as high as 0.9826. To better describe the diffusion process of this condition, a dynamic diffusion model of coal particles gas diffusion under constant volume conditions was established. The calculated values of this model had a preferable consistency with the experimental data, and the correlation coefficients were all over 0.99, which verified the reliability of the model. This research makes up for the theory of gas diffusion and provides a theoretical basis for coalbed methane extraction. [ABSTRACT FROM AUTHOR]

In the process of intelligent manufacturing, appropriate learning algorithm and intelligent model are necessary. In this work, a novel learning algorithm named random vibration and cross particle swarm optimization algorithm was proposed. The proposed algorithm is used for the prediction and optimization of machining process. Tool wear is an important factor that affects the machined surface quality during machining process, so it is necessary to find qualified tool wear prediction model and obtain the best combination of machining parameters to prolong tool life. In this study, the adaptive network–based fuzzy inference system was established to predict the tool wear width size. The random vibration and cross particle swarm optimization algorithm was tested using benchmark functions, and the results showed that random vibration and cross particle swarm optimization algorithm is able to find global optimum. Compared with the adaptive network–based fuzzy inference system trained by particle swarm optimization algorithm and adaptive network–based fuzzy inference system trained by differential evolution models, the results showed that the adaptive network–based fuzzy inference system trained by random vibration and cross particle swarm optimization algorithm can give a more accurate predicted value for offline prediction of the tool wear width size. In order to obtain the best combinations of cutting parameters under different removal area, the multi-objective optimization based on random vibration and cross particle swarm optimization algorithm was established. The optimized cutting parameters were verified and could be accepted to prolong tool life and improve machining efficiency. [ABSTRACT FROM AUTHOR]

In the machining process, the machining performance which mainly refers to machined surface quality and cutting forces is hard to predict under different tool wear status. In this work, an improved case-based reasoning (ICBR) method is proposed to predict both the cutting force and machined surface roughness. With the emergence of new problem, ICBR method obtains solutions to new problem through case retrieval and reuse. In case retrieval stage, K similar cases to the new problem were retrieved using K nearest neighbor method. By means of the K similar cases, support vector regression machine (SVR) model was established to give the solution of the new problem in case of the reuse stage of ICBR method. Artificial neural network (ANN) was introduced to estimate the influence of machining parameters and tool wear on machining performance. As the ANN and SVR models contain unknown parameters, the novel particle swarm optimization algorithm was proposed to train these models for its capability of fast convergence and global optimum. The proposed ICBR method was used to predict the surface roughness and cutting force. The results showed the proposed ICBR method can give superior prediction accuracy and lower Mean square error than other popular intelligent models. Meantime, the ICBR method possesses good robustness and can be used for the actual machining process. [ABSTRACT FROM AUTHOR]

The lattice Boltzmann method (LBM) and large-eddy simulation (LES) are combined with a scalar subgrid-scale model to simulate the indoor air velocity field and harmful gas dispersion. The LBM-LES model is validated by comparing its results with published experimental and numerical simulation results. Taking a simplified chemical building as the scenario, the relative ventilation efficiency is evaluated based on the maximum harmful gas concentration, and configurations with centralized and distributed harmful gas sources with both mixing ventilation (MV) and displacement ventilation (DV) systems are considered. According to the results, if the density of the harmful gas is less than the air density, the DV system is more efficient than the MV system. The DV system is more stable than the MV system under fluctuating relative ventilation efficiency due to changes in the distance between the ventilation vents and in the distance between the centralized gas sources and the exhaust air vent. [ABSTRACT FROM AUTHOR]

Mine disasters, as associated problems in the development of coal resources, always threaten the life safety of miners and the production safety of enterprises. In coal roadway excavation, the coal in front of the excavation face is in a state of concentrated stress and the deformation is serious. The instability of the coal seam under stress is an important cause of the occurrence of coal and gas outburst. Thus, knowing the mechanical characteristics of surrounding rock in front of the working face is of great significance for deep understanding and effective prevention and control of coal-rock dynamic disasters. By analyzing the characteristics of stress evolution and deformation and failure in front of the heading face, the analytical solution of plastic region distribution in front of the heading face is obtained. According to the established mechanical model, MATLAB numerical calculation software is used to analyze different examples. The influence of different mechanical parameters on the stress state of the working face is studied. The influence parameters of the morphological characteristics of the plastic region are determined, and the change law and characteristics of the plastic region in front of the working face are studied. At the same time, through the characteristics of stress field, the working face dynamic risk assessment of coal and rock dynamic disaster can be realized, which can provide a powerful guarantee for the prevention and control of gas dynamic disasters in deep mine. [ABSTRACT FROM AUTHOR]

The influences of shape characteristics and pressure on n-Heptane ring fire were investigated through two groups of experiments. In group A, the ring fire with varying shape characteristics was conducted. In group B, the ring fire was performed under sub-atmospheric pressures including 45 kPa, 60 kPa, 75 kPa, and 90 kPa. The results show that the mass loss rate is determined by combined results of air entrainment and heat dissipation effect. The flame structure is divided into merged flame and separated flame. The axis temperature has no significant difference in growth stage but presents a corresponding relationship in decrease stage. [ABSTRACT FROM AUTHOR]

In the high speed milling process, the accurate predictions of surface roughness and residual stress can avoid the deterioration of machined surface quality. But it's hard to estimate the surface roughness and residual stress under different tool wear status and cutting parameters. In this work, a novel intelligent reasoning method-improved case based reasoning (ICBR) was proposed to predict the surface roughness and residual stress. The inputs of ICBR are cutting parameters and tool wear status. The corresponding outputs of ICBR are surface roughness and residual stress. In the ICBR, K-nearest neighbor method and artificial neural network (ANN) as case retrieval was introduced to retrieve the K similar cases to the inputs. Through retrieving K similar cases, the Gaussian process regression (GPR) model as case reuse was established to output the surface roughness and residual stress. The vibration particle swarm optimization algorithm is proposed to optimize the ANN and GPR models. The high speed milling experiments of Compacted Graphite Iron was performed to validate the performance of ICBR. The experimental results showed that the cutting speed is the most important factor affecting the surface roughness. The feed rate is the most important factor affecting the residual stress. The ICBR gives the accurate estimation of surface roughness with the Mean Absolute Percentage Error of 11.6%. As for residual stress, the prediction accuracy using ICBR is 87.5%. Compared with Back-Propagation neural network, standard CBR and GPR models, the ICBR has better predictive performance and can be used for estimations of surface roughness and residual stress in the actual machining process. [ABSTRACT FROM AUTHOR]

Compacted graphite iron (CGI) plays an important role in contemporary manufacturing of automobile engine, and coated tool is the best choice for milling of CGI. But studies about the estimation of the wear of coated tool are still rare and incomplete. As tool wear is the main factor that affects the quality of machined surface, in this study, we proposed an intelligent model-adaptive neuro fuzzy inference system (ANFIS) to estimate the tool wear, and ANFIS was learned by the improved particle swarm optimization (PSO) algorithm. As the PSO algorithm is easy to fall into the local minimum, the vibration and communication particle swarm optimization (VCPSO) algorithm was proposed by introducing the self-random vibration and inter-particle communication mechanisms. Besides that, to obtain the optimal combination of milling parameters, the multi-objective optimization based on minimum cutting power, surface roughness and maximum material removal rate (MRR) was studied using VCPSO algorithm. The experimental results showed that the ANFIS learned by VCPSO algorithm (ANFIS-VCPSO) has better performance for the estimation of tool wear compared with other intelligent models. The VCPSO algorithm was tested using Benchmark functions, and the results showed VCPSO algorithm has the global optimization ability. Meantime, the best combinations of milling parameters under different tool wear status were obtained through VCPSO algorithm. The proposed ANFIS-VCPSO model as a new intelligent model can be applied for real-time tool wear monitoring, which can improve the machining efficiency and prolong tool life. In order to meet the requirements of green and intelligent manufacturing, the best combination of milling parameters was also obtained in this work. [ABSTRACT FROM AUTHOR]

Coal and gas outburst is a serious disaster in the mining, and crosscut coal is the most prone to cause the coal and gas outburst. In order to study the mechanism of outburst, this paper studied the stress distribution characteristics in front of the working face in the process of rock roadway driving before implementing crosscut coal firstly. On this basis, the hypothesis of stress distribution on the "strong and soft face" of coal-rock mass was proposed. And by using the hypothesis, the mechanical equation for the parameter changes of the plastic zone in front of the working face in crosscut coal was established, and the width and morphological characteristics of the plastic zone in crosscut coal were analyzed. The results show that during the process, as the working face moves forward, the shape distribution of the plastic zone in front of the working face changes from the "semielliptical" to "semibutterfly," And based on the distribution characteristics of plastic zone in working face in crosscut coal, modification proposals for outburst-prevention measures were proposed and provided technical support for the outburst-prevention measures and key parameters setting to prevent the coal outburst in crosscut coal. [ABSTRACT FROM AUTHOR]

The high‐pressure gas expansion‐induced deformation and dynamic fracture of coal are important parts of coal and gas outburst. To better understand the law of this process, laboratory experiments and numerical simulation are used to study the law of damage. A cavity with different pressures of CH4 or N2 was destroyed by a jack to achieve the rapid expansion of the gas and coal fracture inside. The particle size distribution of the coal particles before and after the experiment was measured, and the breakage ratio and the newly added surface area were calculated. The experimental results indicate that during the gas expansion process, the breakage ratio of coal and the newly added surface area clearly increase with the increase in gas pressure. Finally, a numerical model based on peridynamic theory was developed to simulate crack generation and the propagation of coal induced by the expansion of gases at different pressures. The numerical simulation results show that the higher the initial gas pressure is, the higher the number of failure units. Moreover, only when the gas pressure is large enough will the coal crack in various directions at the same time. [ABSTRACT FROM AUTHOR]

Although there are many types of cutting tool materials, no single cutting tool material meets all the needs of machining applications because of the complex and changeable cutting conditions. It is crucial to study the matching between tool materials and workpiece materials for improving productivity, obtaining good surface quality and reducing machining cost. In this paper, rule-based reasoning (RBR) method and gray complex proportional assessment (COPRAS-G) method are applied to solve the problem of cutting tool material selection. RBR is used for primary selection of tool materials to reduce the number of alternatives and the computational complexity in COPRAS-G method. Ten attributes of tool materials including physical, mechanical, chemical, and cost parameters are selected as criteria in the COPRAS-G method, and entropy method and analytic hierarchy process (AHP) are used to determine the objective weights and subjective weights of attributes, respectively. Finally, the ranking of several alternatives is obtained to select the most suitable cutting tool material. Taking the cutting tool material selection of machining CGI as an example to validate the method proposed in this paper. The research results revealed that the alumina ceramic has the best comprehensive performance, alumina ceramic cutting tools containing carbides to improve the flexural strength and fracture toughness, or cemented carbide cutting tools with alumina coating are preferred for machining CGI. High-speed milling experiments of CGI were carried out, and the results showed that the alumina-coated tungsten carbide tools had longer tool life than the silicon nitride ceramic tools, which confirmed the effectiveness of the proposed cutting tool material selection method. And this method can be extended to other engineering applications in material selection problems. [ABSTRACT FROM AUTHOR]

Summary: The ring fire usually originates from the combustion of the annular‐distributed fuel, and it may occur in the low‐temperature environments such as the Arctic area and plateau area, which is kind of different from the conventional environment. In this paper, the annular pools with various shape characteristics were designed. The outside diameter ranged from 14.9 to 30.0 cm, the inside diameter increased from 0 to 24.5 cm, and the diameter ratio was from 0 to 0.858. A series of n‐heptane ring fire experiments were carried out. The results showed that for the annular pools with the same outside diameter, the mass loss rate (MLR) per unit area presents a piecewise trend with the diameter ratio. When the diameter ratio increases from 0 to 0.7, the MLR per unit area increases linearly because of the domination of air entrainment effect. When the diameter ratio is larger than 0.7, the MLR per unit area is independent of the annular shape due to the strong heat dissipation effect. Finally, a parameter named the outside circumference per unit area is put forward to characterize the annular pool. A corrected pressure modeling is established to normalize the ring fire with various shape characteristics. [ABSTRACT FROM AUTHOR]

Gas distribution ahead of the coal tunnel is the key risk factor controlling coal and gas outburst. Based on an analysis of the influence of the stress state on the porosity of the coal seam, an improved quartet structure generation set (QSGS) random porous media generation tool is used to reconstruct the coal structure. Adopting the reconstructed pore structure of the coal as the boundary of the flow field, the Lattice Boltzmann method (LBM) is used to simulate the gas dynamic distribution law ahead of the coal tunnel. The gas pressure of the coal seam decreases obviously in the fracture zone only, and the change in gas pressure is very small in the stress concentration zone and ahead of the coal seam. This research is of significance for gas drainage and the prevention of coal and gas outburst hazards in the working face during coal tunneling. [ABSTRACT FROM AUTHOR]

This paper establishes a mechanical model of the stress distribution in front of the driving face during coal roadway excavation. Theoretical research shows that the stress state in the plastic zone of the driving face is consistent with the limit equilibrium equation, and the elastic zone is in accordance with the equilibrium equation based on elasticity mechanics. Based on this improved mechanical state solution model, different coal material constitutive hypotheses are used for the analysis. The width of the plastic zone calculated under the brittle-perfectly elastic model can reach 2–5 times the height of the roadway, and the stress concentration coefficient can reach two or more times. 3DEC numerical simulation software was used to simulate the stress distribution of the heading face. The results of the simulation are similar to those of the theoretical analysis. Compared with the elastic-perfectly plastic model, the calculated results of the brittle-perfectly elastic model are more consistent with the numerical simulation results. The heading face coal during roadway excavation shows obvious damage, and the strength characteristics of the coal decrease. [ABSTRACT FROM AUTHOR]

Compacted graphite iron (CGI) has gradually replaced the gray cast iron (GCI) in the automobile engine and becomes the first choice for making the diesel engine cylinder blocks and heads, because of its better mechanical properties than GCI. However, the good mechanical properties of CGI are at the expense of its poor machinability. Therefore, it is necessary to select the proper cutting tool materials and cutting parameters to machine CGI with economy and efficiency to meet the requirements of machining and application. The present study investigates the influence of milling parameters, such as milling speed v, feed per tooth f on the milling force, the tool life and tool wear, and the machined surface integrity during the high-speed finish milling process of CGI by cemented carbide tools and ceramic tools. It was found that the milling force of ceramic tool for milling CGI was greater than that of cemented carbide tool. When the milling speed was increased from 400 to 800 m/min, the life of cemented carbide tool decreased sharply, while the life of ceramic tool decreased slightly, and the cemented carbide tool life can be four times (v = 400 m/min) or two times (v = 800 m/min) longer than that of ceramic tool. The analysis of tool failure mechanism showed that adhesive wear, crack, tipping, and chipping were common wear mechanisms of cemented carbide tools, while the main wear mechanisms of ceramic tools were diffusion and oxidation. Besides, the study on the machined surface morphology, surface roughness, and surface residual stress indicated that the machined surface integrity was greatly influenced by the milling tool materials and milling parameters. The machined surface quality of CGI milled by ceramic tools was better than that milled by cemented carbide tools. It was concluded that, for conditions similar to those used in this work, carbide is better than ceramic in terms of tool life, while ceramic is better than carbide to obtain smaller surface roughness for the high-speed finish milling of CGI. And cemented carbide tools are more suitable for milling CGI at the lower speed (v = 400 m/min), while ceramic tools exhibit better performance at the higher speed (v = 800 m/min). [ABSTRACT FROM AUTHOR]

An experiment designed to simulate coal during excavation was conducted. Microseismic signals of coal under vibration conditions during excavation and subsequent waiting time of the coal roadway at different excavation speeds were collected and analyzed. During the excavation and subsequent waiting time, the stress in coal is redistributed, and the concentrated stress is gradually transferred to the deeper section of the coal seam. The Hilbert–Huang transform (HHT) is used to effectively denoise the collected signals. According to the noise-reduced signal, the amplitude and pulse number of the microseismic signals emitted during the excavation process are much larger than those of the waiting time process. During excavation, the energy and event numbers of microseismic signals increase first and then decrease as the excavation speed increases. The faster the excavation speed, the more the energy, and the higher the event numbers of the microseismic signals released during the subsequent waiting time. When the excavation speed is faster, more elastic potential accumulates in the coal seam and the concentration stress is greater. As the concentrated stress moves forward in time without excavation, more coal seams fail, and more microseismic signals are released. The microseismic signal and the stress evolution law can provide a reasonable explanation for the forward movement of the concentrated stress and coal failure during roadway excavation. [ABSTRACT FROM AUTHOR]

To investigate the fracture characterizations of rocks under high strain rate tensile failure, a series of dynamic Brazilian tests was conducted using Split Hopkinson pressure bar (SHPB), and a high-speed digital camera at a frame rate of 50,000 frames per second (FPS) with a resolution of 272 × 512 pixels was adopted to capture the real-time images and visualize the failure processes. Using the extracted cracks and image processing technique, the relationship between loading condition (impact velocity), crack propagation process (crack velocity, crack fractal characteristic, and crack morphological features), and dynamic mechanical properties (absorbed energy and strain-stress parameters) was explored and analyzed. The experimental results indicate that (1) impact velocity plays a critical role in both crack propagation process and dynamic mechanical properties, (2) the crack fractal dimension is positively correlated with crack propagation velocity and has a linear relationship with the proposed morphological feature of crack, (3) mean strain rate and max strain of rocks under SHPB loading both decrease with the increase of crack propagation velocity, and (4) the energy absorbed by the rocks increases with increasing impact velocity and has a strong negative correlation with a proposed novel crack descriptor. Experimental studies pertaining to the measurement of crack propagation path and velocity, in particular, some crack feature extraction approaches, present a promising way to reveal the fracture process and failure mechanisms of rock-like materials. [ABSTRACT FROM AUTHOR]

Tooth modification is an effective method for reducing the undesirable effects introduced by misalignments, but the magnitude of such modifications with respect to any given misalignments is uncertain and largely based on experience. A mathematical model of a helical gear pair is established to study the coupling effects of tooth modifications and misalignments on the system's multi-contact behavior. Misalignments are defined as the deviations of the ends of axes in gear and pinion mechanisms from their ideal positions, and they affect the contact behavior through transformation matrices. Deformations in the gear and pinion are computed by a finite element method. Misalignments, tooth modifications, and the gear's deformation influence the contact behavior by altering the distances between contact lines at corresponding contact tooth pairs. The actual contact is believed to occur at the contact line section(s) with the smallest distance. Using the proposed model, the influences of misalignments, tooth modifications, and their couplings on the contact load distribution, contact load share ratio, and contact load deviation factor are analyzed. The results show that an optimum tooth modification does exist for helical gear pairs under a given external load and misalignments. [ABSTRACT FROM AUTHOR]

Compacted graphite iron (CGI) possesses good mechanical properties and thermal properties in comparison to gray cast iron (GCI) and spherical graphite spheroidal cast iron (SGI). However, the machinability of CGI is poor, and the cutting tool wear is very fast during the machining of CGI, which can lead to the changes of the cutting force and the machined surface integrity. The present study investigates the influence of workpiece material removal volume (Q) on the cutting tool wear, cutting force, machined surface roughness, and morphology under normal (V = 134 m/min) and high cutting speed process (V = 800 m/min). The result shows that Q had a more obvious effect on the value of cutting forces when the cutting speed was 800/min, while the effect was slight when the cutting speed was 134 m/min. However, the effect of Q on the direction of the resultant cutting force was small, and the direction of the resultant cutting force was more likely to be affected by the increase of cutting speed. The effect of Q on the machined surface roughness Ra and Rz was different between normal and high cutting speed process. Dark and bright areas can be found on the machined surfaces obtained under the normal speed cutting process, and the ratio of dark area to total area P can be used as a parameter to measure the machined surface quality. The flank wear of the cutting tool used for normal speed cutting process can be divided into brighter cemented carbide region and darker coating wear region due to the low wear rate, while only the brighter cemented carbide wear region was found on the tool used for high cutting speed process. Cracks could be found on the cutting tool used for both normal cutting speed process and high cutting speed process. However, the crack propagation appeared faster under high cutting speed process, chipping was formed near the crack. The depth and width of the crater wear under normal cutting speed process were larger than that under high cutting speed process. [ABSTRACT FROM AUTHOR]

The studies of tool life and formation of cutting burrs in roughing machining field are core issues in high speed milling of compacted graphite iron (CGI). Changing any one of the cutting parameters like cutting speed or feed rate can result in varied tool life and different height of the cutting burrs. In this work in order to study the relationship between cutting parameters and tool life and height of the cutting burrs, a new differential evolution algorithm based on adaptive neuro fuzzy inference system (DE-ANFIS) as a multi-input and multi-output (MIMO) prediction model is introduced to estimate the tool life and height of the cutting burrs. In this model, the inputs are cutting speed, feed rate and exit angle, and the outputs are tool life and height of the cutting burrs. There are 12 fuzzy rules in DE-ANFIS architecture. Gaussian membership function is adopted during the training process of the DE-ANFIS. The proposed DE-ANFIS model has been compared with PSO-ANFIS, Artificial Neural Network (ANN) and Support Vector Machines (SVM) models. To construct the predictive models, 25 cutting data were obtained through the experiments. Compared with PSO-ANFIS, ANN and SVM models, the results indicate that DE-ANFIS can provide a better prediction accuracy of tool life and height of the cutting burrs, and achieve the required product and productivity. Finally, the analysis of variance (ANOVA) shows that the cutting speed and feed rate have the most effects on the tool life and height of cutting burrs, respectively. [ABSTRACT FROM AUTHOR]

The good physical and mechanical properties of compacted graphite iron (CGI) make it the ideal material for modern fuel-efficient diesel engine. However, it is difficult to be machined in comparison with gray cast iron (GCI). Serrated chip is a common phenomenon in the milling of CGI, and the formation of the serrated chip can influence the oscillation of the cutting force, fluctuation of the contact length, and roughness of the machined surface. This study investigated the chip formation process and the change of chip morphology in the milling process of CGI (GJV450) with an increase in the cutting speed and feed rate under normal and high cutting speed process. The results showed that the cutting chip changed from serrated-type to needle-type with an increase in the cutting speed. Although the cutting speed is far below the normal cutting speed range, continuous chip cannot be formed. For high cutting speed, increase in feed rate changed the chip type from serrated-type to needle-type. Both the cutting speed and feed rate influenced the serrated morphology sizes. Adiabatic shear zone cannot be found on the serrated chip, and brittle fracture surface was found on the upper side of the serrated chip side surface while the plastic fracture surface was found on the lower side of the side surface. The periodic brittle fracture theory can be used to explain the formation mechanism of the serrated chip during milling of CGI. [ABSTRACT FROM AUTHOR]

Compacted graphite iron (CGI) is considered as the ideal material to make modern fuel-efficient diesel engine. Due to the vermicular or worm-like graphite distributed among the ferrite/pearlite matrix, CGI behaves better physical and mechanical properties in comparison with gray cast iron (GCI) and spherical graphite spheroidal cast iron (SGI). However, these good properties bring about the machining challenges. So it is important to appropriately select cutting parameters to machine this material with economy and efficiency. The present study investigated the influence of cutting parameters, such as cutting speed V, feed rate f, and exit angle Ψ, on workpiece material removal volume Q and cutting burr height on the entrance side H1 and on the exit side H2 during high-speed milling of CGI by the coated carbide tools. On this basis, the relatively optimum high-speed cutting parameters were selected under the research condition. Cutting tool failure mechanism was also investigated with the aid of scanning electronic microscope (SEM) and energy-dispersive system (EDS) (SUPRA55, Germany) analysis. The results showed that Q, H1, H2, and the type of cutting burr on the exit side of the machined surface could be influenced by the cutting parameters. And the relatively optimum cutting parameters are V = 800 m/min, f = 0.25 mm/rev, and Ψ = 60°. Adhesive wear and thermal cracks which were perpendicular to the cutting edge were common wear mechanisms during the cutting process. However, with an increase in feed rate, mechanical cracks which were parallel to the cutting edge could be found on the flank face of the cutting tool. [ABSTRACT FROM AUTHOR]

In the coal mining process, the destabilization of loaded coal mass is a prerequisite for coal and rock dynamic disaster, and surface cracks of the coal and rock mass are important indicators, reflecting the current state of the coal body. The detection of surface cracks in the coal body plays an important role in coal mine safety monitoring. In this paper, a method for detecting the surface cracks of loaded coal by a vibration failure process is proposed based on the characteristics of the surface cracks of coal and support vector machine (SVM). A large number of cracked images are obtained by establishing a vibration-induced failure test system and industrial camera. Histogram equalization and a hysteresis threshold algorithm were used to reduce the noise and emphasize the crack; then, 600 images and regions, including cracks and non-cracks, were manually labelled. In the crack feature extraction stage, eight features of the cracks are extracted to distinguish cracks from other objects. Finally, a crack identification model with an accuracy over 95% was trained by inputting the labelled sample images into the SVM classifier. The experimental results show that the proposed algorithm has a higher accuracy than the conventional algorithm and can effectively identify cracks on the surface of the coal and rock mass automatically. [ABSTRACT FROM AUTHOR]

We have studied the influence of an electrostatic field on the process of methane adsorption on the surface of coal under various conditions. We have determined the values of the Langmuir adsorption constants for the coal samples and have analyzed the adsorption mechanism. We found that gas adsorption is intensified in an electric field. We established that one of the Langmuir constants for tectonically deformed coal is larger than for raw coal, while the other constant, which usually remains unchanged, tends to increase when exposed to the field. We estimated the surface free energy of the system and we established that it increases with an increase in the electric field intensity. According to the thermodynamics of spontaneous processes, usually the Gibbs free energy of a system tends to decrease as a result of intensification of adsorption, and therefore application of an electric field leads to its increase. [ABSTRACT FROM AUTHOR]

With the decline of shallow coal reserves and increase in demand of coal consumption, the hazard of coal and rock dynamic disasters is expanding. In this paper, we conducted some laboratory scale tests on coal, cement, and glass materials to figure out the microseismic (MS) characteristic differences among materials. A new method, denoted as WPT-LMD, is proposed to conduct signal denoising and analysis work. A series of basic analyses regarding MS are conducted, including the relationships between MS characteristics and loading rate, coal powder particle size, loading stage, and MS event statistics. Research results show that the damage of all these three materials is accompanied with MS events, abundant with low frequency component (0–200 Hz). But cement and coal specimens produce with relative wide frequency distribution in sample frequency domain, while glass specimens were found to only produce low frequency event. The powder particle sizes have obvious influence on the strength of coal specimen, but the loading rate seems to have no influence on the MS characteristics. The outcome of the paper will further provide a theoretical basis for understanding the mechanism of MS activities and has great significance to improve the coal mining safety. [ABSTRACT FROM AUTHOR]

An experiment simulating coal seam under forced vibration conditions was conducted. Acceleration response and microseism signal during the experiment were collected and analyzed. It is found that, with an increasing amount of vibration, the natural frequency of the specimen decreases, and this phenomenon reflects fractures appearing in the specimen. Acceleration response signals show that peaks in shock excitation frequency and shock excitation acceleration affect the acceleration response, which reflects damage to the specimen. When shock excitation frequency nears natural frequency, the acceleration response first decreases and then increases. When resonance occurs, it reaches its maximum value. As shock excitation acceleration peaks increase, the acceleration response peak of the specimen also increases. We conclude that destruction is mainly concentrated in the coal seam evidenced by specimen destruction situation. Then shock excitation frequency and shock excitation acceleration influence on microseism signals were analyzed by Hilbert-Huang transform. By receiving these signals and analyzing their characteristics, it is beneficial to develop new methods to predict disasters underground dynamically in the future. [ABSTRACT FROM AUTHOR]

Polypropylene/carbon nanotubes (PP/CNTs) nancomposites were prepared with a single screw extruder by adding maleic anhydride-grafted poplypropylene (PP-g-MAH) as compatibilizer to polypropylene (PP) with different amounts of carbon nanotubes (CNTs) in the range of 0.1-0.7 wt.%. Structure and morphology of the prepared samples were examined by Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), polarizing light microscopy (PLM) and X-ray diffraction (XRD). The results showed that PP spherulites decreased in size when CNTs were introduced into the polymer. Mechanical properties of the samples were also studied. Tensile tests showed that with increasing amount of CNTs the strain at break decreased whereas the Young's modulus was improved of 16.41 % to 36.05 % and tensile strength of 36.67 % to 64.70 % compared to pristine PP. The SEM microphotographs showed that majority of the CNTs were dispersed individually and oriented along the shear flow direction. [ABSTRACT FROM AUTHOR]

The deformation and failure of coal and rock materials is the primary cause of many engineering disasters. How to accurately and effectively monitor and forecast the damage evolution process of coal and rock mass, and form a set of prediction methods and prediction indicators is an urgent engineering problems to be solved in the field of rock mechanics and engineering. As a form of energy dissipation in the deformation process of coal and rock, microseismic (MS) can indirectly reflect the damage of coal and rock. In order to analyze the relationship between the damage degree of coal and rock and time-frequency characteristics of MS, the deformation and fracture process of coal and rock materials under different loading modes was tested. The time-frequency characteristics and generation mechanism of MS were analyzed under different loading stages. Meanwhile, the influences of properties of coal and rock materials on MS signals were studied. Results show that there is an evident mode cutoff point between high-frequency and low-frequency MS signals. The properties of coal and rock, such as the development degree of the original fracture, particle size and dense degree have a decisive influence on the amplitude, frequency, energy and other characteristic parameters of MS signals. The change of MS parameters is closely related to material damage, but has no strong relation with the loading rate. The richness of MS signals before the main fracture depends on the homogeneity of materials. With the increase of damage, the energy release rate increases, which can lead to the widening of MS signals spectrum. The stiffness and natural frequency of specimens decreases correspondingly. Meanwhile, the main reason that the dominant frequency of MS detected by sensors installed on the surface of coal and rock materials is mainly low-frequency is friction loss and the resonance effect. In addition, the spectrum and energy evolution of MS can be used as a characterization method of the damage degree of coal and rock materials. Furthermore, the results can provide important reference for prediction and early warning of some rock engineering disasters. [ABSTRACT FROM AUTHOR]

The diffusion coefficient of gases in coal varies with time. This study aims to develop an unsteady dynamic diffusion (UDD) model based on the decay of diffusion coefficient with time and the change of integral. This study conducted a series of gas desorption and diffusion experiments with three different combinations of particle sizes and gas pressures and compared the diffusion coefficients of the three models. The UDD model exhibited good fitting results, and both the UDD and bidisperse models fitted the experimental data better than the unipore model. In addition, the dynamic diffusion coefficient (DDe) decreased rapidly in the initial stage but gradually decreased to a stable level in the later stage. All the effective diffusion coefficients of the three models negatively correlated with the particle size. In the unipore model, the diffusion coefficient of coal samples with three particle sizes increased with gas pressure. In the bidisperse and UDD models, the diffusion coefficients (Dae, Die, and DDe) of 0.25–0.5 mm and 0.5–1.0 mm coal samples increased with gas pressure. However, DDe and Dae of 1.0–1.25 mm coal samples increased first and then decreased. Furthermore, Die decreased first and then increased, with no sign of significant pressure dependence. Finally, the correlation and significance between the constant and diffusion coefficient in the UDD model was investigated. [ABSTRACT FROM AUTHOR]