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Among all methods for investigating the complex phenomenon of the coal and gas outburst, numerical modelling is the most comprehensive one that can consider all involved parameters and simulate the complex multi-physical phenomenon. The main aim of this paper is to review recent numerical modelling studies concerning this disastrous phenomenon observed in coal mining. The paper aims to analyse these studies comprehensively and identify any existing research gaps that could be addressed in future research endeavours. To this end, the concepts and equations that have been used in previous studies to simulate the solid and fluid behaviour during outburst initiation and how these equations are coupled to consider multiphysical interactions were reviewed. Both strengths and deficiencies in past outburst modelling work were highlighted. Finally, potential research topics for future studies were discussed in three categories; looking into the outburst phenomenon in the scale of the particles which is mostly focused on the discrete element method, conservation of the energy as a method to quantitively assess outburst initiation, and the application of statistics in both applying the heterogeneity in the models and assessing the possibility of the outburst occurrence. [ABSTRACT FROM AUTHOR]

As mining operations delve deeper and mechanization and intelligence levels improve, coal mine disasters are becoming increasingly severe. Consequently, developing effective technology and equipment is crucial to ensure the safety of mining enterprises. This perspective summarizes the technical methods for preventing coal and rock dynamic disasters and controlling dust in coal mines. Furthermore, it provides insights into the future directions of mining disaster prevention techniques and equipment in this field. The aim of this paper is to offer effective disaster prevention strategies, enhance the efficiency and effectiveness of disaster control, and further safeguard the health and safety of miners. [ABSTRACT FROM AUTHOR]

To study the effects of gas hydrates on the prevention and control of coal and gas protrusions, this paper reports the results of acoustic emission experiments on coal bodies containing gas hydrates with different saturation levels. The results showed that few acoustic emission events were generated in the elasticity stages of coal bodies containing gas hydrates, and the first sudden increase in the number of ringing counts generally occurred before and after the yielding point. Additionally, the acoustic emission events in the yielding stage were more active, and the cumulative number of ringing counts increased faster. The peak ringing counts appeared around the damage point, and a small number of acoustic emission events were still generated after destruction of the coal samples. The cumulative ringing counts decreased linearly with increasing saturation. The effect of saturation on the cumulative ringing counts in the elasticity stage of the gas hydrate-containing coal samples was small, but the difference between the cumulative ringing counts in the yielding stage and those in the destruction stage was larger. The total cumulative ringing counts and the cumulative ringing counts during each stage for the gas hydrate-containing coal samples decreased with increasing enclosure pressure. The energy and amplitude of the loading process were consistent with the trend for the ringing counts. The acoustic emission ringing counts of gas-containing coals were greater than those of gas hydrate-containing coals in the yielding and destructing stages. [ABSTRACT FROM AUTHOR]

Coal and gas outburst is one of the main dynamic disasters in coal mine production. In order to deeply understand the overall research progress in the field of coal and gas outburst, the Web of Science (WOS) database is used as the sample source, and the bibliometric analysis of the literature in the field of coal and gas outburst from 2000 to 2021 is carried out by CiteSpace software. The knowledge maps of the publication quantity, country, institution, and keyword cluster are drawn. The results show that the time distribution has gone through three stages of germination period, development period, and growth period. In terms of the cooperation network, China, Australia, and the USA are the main core research countries, while China University of Mining and Technology, Chongqing University, and Henan Polytechnic University are the main core research institutions, and the main core journals are IGCG, IGRMM, and Fuel. By drawing the knowledge map of keywords timeline, the evolution law of keywords in the field of coal and gas outburst with time is obtained. Taking keywords as the object, cluster labels with gas outburst, gas extraction, gas control, and pore structure as the core are presented. On this basis, from a new perspective, this paper outlines the "scientific research landscape map" in the field of coal and gas outburst, in order to provide a scientific reference for coal and gas outburst research. [ABSTRACT FROM AUTHOR]

The shock wave of a coal and gas outburst is a high-pressure and high-speed impact airflow formed rapidly after the outburst. The propagation destroys the ventilation facilities and causes the destruction of the ventilation system. The theoretical research on the outburst shock wave is of great significance. In order to deeply understand the formation mechanism of the outburst shock wave, this paper draws on the shock wave theory to theoretically analyze the microscopic formation process of the outburst shock wave. The main difference between the formation process of a coal and gas outburst shock wave and the formation process of a general shock wave is that the outburst shock wave has a solid–gas flow zone in the high-pressure zone. The calculation formulas of pressure, density, temperature and other parameters before and after the outburst shock wave are derived. After the outburst shock wave passes through, the pressure, temperature and density of the roadway air will change suddenly. The relationship expression between outburst gas pressure and outburst shock wave intensity is derived, which can reflect the role of pulverized coal in the formation process of a shock wave. In order to facilitate the understanding and calculation, the concept of equivalent sound velocity of coal-gas flow is proposed, and the direct calculation of the impact strength of a coal and gas outburst is attempted. This paper is helpful to improve the understanding of the essence of a coal and gas outburst shock wave. It is also of great significance to outburst disaster relief. [ABSTRACT FROM AUTHOR]

With the continuous increase of mining depth, coal and gas outburst poses a significant threat to mining safety. Conducting research on the mechanisms of coal and gas outbursts contributes to understanding the evolutionary process of such incidents, thus enabling accurate prediction and prevention of coal and gas outbursts during mining operations. This paper has developed a comprehensive visual experimental system that is specifically tailored to simulate diverse coal body conditions, ground stress and gas pressures. By monitoring and analyzing the real-time progression of coal fissures during the outburst process, we can obtain valuable insights into the evolution and mechanisms of coal and gas outbursts. Additionally, this study introduces a method to determine the critical threshold for predicting coal and gas outbursts, and the critical gas pressure threshold for Jiulishan Coal Mine (Jiaozuo City, Henan Province, China) is established at 0.6 MPa. [ABSTRACT FROM AUTHOR]

Accurate and rapid prediction of the coal and gas outburst is very significant for preventing accident and protecting environment, the paper presents a novel feature selection and outburst classifier framework which can identify effective candidate features and improve the classification accuracy. First, Apriori is applied for preliminarily extracting the association rules from sample data and attribute features in coal and outburst, and it can present the effective sample data and features for outburst prediction. Second, in order to reduce the redundancy of the strong association rules obtained from Apriori, Boruta is applied for selecting all highly relevant optimal features based on the obtained strong association rules. Third, Random Forest(RF) is used to assign different weights to different features in optimal candidate features considering the importance of different features to outburst, based on the above obtained high-quality sample data and optimal features, the parameters of KNN model optimized by Bayesian Optimization(BO) is used to predict the coal and gas outburst. The experimental results show that the proposed feature selection model Apriori-Boruta can obtain significant sample data, and the proposed RF-KNN optimized classifier model can achieve higher performance in terms of the number of optimal features and prediction accuracy compared with traditional prediction models. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

China's current energy consumption is primarily fueled by coal, increasing coal mining with growing energy demand. Coal and gas outburst accidents are common problems in coal mining, and prediction methods are fundamental for preventing such accidents. The gas emission characteristics of boreholes are a combination of comprehensive coal properties and coal seam gas occurrence status; thus, the accurate prediction of gas emissions from boreholes is crucial for preventing such hazards. This paper presents a method for measuring the gas flow rate in continuous boreholes, which is used to predict outburst danger in front of the working face. The model was compared with field measurement data and found suitable for research. The effects of different initial gas pressures, different borehole radius, and different burial depths on gas emissions from boreholes were studied. The results showed that (1) initial gas pressure is the main influencing factor of gas gushing. The amount of gas emission during drilling and the attenuation of gas pressure are more sensitive to pressure. An increase in gas pressure considerably increases the amount of gas gushing out of drilling holes. (2) The increase in the drilling radius increases the generation of coal cuttings, the area of the drilling hole wall, and the degree of damage to the drilling hole wall. Consequently, the amount of gas gushing out of the drilling hole increases. (3) In situ stress occurs mainly because of the increase in gas pressure with an increase in burial depth and the increase in gas desorption caused by the increase in damage to the borehole wall. This study provides a new outburst prediction method, which involves identifying outburst hazards through the gas gushing out of the borehole. The results are expected to aid the control of underground coal and gas outbursts and ensure the safe production of coal mines. [ABSTRACT FROM AUTHOR]

Studying the evolution of characteristics associated with the energy of gas-bearing coal is essential for exploring the mechanism of coal and gas outbursts and disaster prevention. In this paper, uniaxial compression and acoustic emission (AE) localization experiments were conducted using coal under different gas pressures. The mechanical characteristics, AE parameters and energy evolution of coal were analyzed and compared. The mechanism of the influence of gas on the mechanical characteristics of coal was studied. The connection between the destruction and the energy evolution of coal was revealed. The research showed that gas pressure can induce considerable initial damage inside coal. The compressive strength of coal decreased by 65.82% as the gas pressure increased from 0 to 4 MPa. The energy evolution and the failure characteristics of coal were closely related to the gas pressure. At low pressure, coal underwent elastic deformation before failure, elastic strain energy dominated during the loading process, and slight damage was observed after failure. Based on these observations, the ratio of dissipated energy to elastic energy ( U d / U e ) was used to characterize the severity of the damage. The ratio increased from 0.161 to 2.189 as the gas pressure increased from 0 to 4 MPa. Mild, weak and strong failure occurred when U d / U e < 0.5 , 0.5 ≤ U d / U e < 1 , and U d / U e ≥ 1 , respectively. The results of this study will contribute to future studies of the mechanism of coal and gas outbursts and will provide guidance for the prediction and prevention of outbursts. [ABSTRACT FROM AUTHOR]

The coal mine in deep mining can easily form a compound dynamic disaster with the characteristics of rock burst and gas outburst. In this paper, the analytic hierarchy process (AHP) and the entropy weight method (EWM) are combined, and the fuzzy comprehensive evaluation (FCE) secondary evaluation model of compound dynamic disaster is proposed to evaluate the risk of compound dynamic disaster, which avoids the problems of the imperfect evaluation index system and strong subjectivity of index weight. Based on the statistical analysis of typical compound dynamic disaster cases in China, three first-level indicators were established, and sixteen second-level indicators were developed. The verification results show that the accuracy and weight are better than the traditional evaluation methods. Combined with geological and mining data, the compound dynamic disaster risk assessment was carried out on the second mining area of mine B, in the Pingdingshan mining area, and the result was grade II (weak risk). Corresponding prevention measures and parameters were implemented, and no compound dynamic disaster occurred during the working face excavation. [ABSTRACT FROM AUTHOR]

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Coal and gas outburst is an urgent and constantly perplexing problem with coal resource extraction, threatening coal mine safe and sustainable production severely. Its mechanism and the participation of gas in coal breaking are still unclear. To explore this problem, in this paper, gas desorption-diffusion regularity of bituminous coal with different particle sizes and its influence on outburst-coal breaking were investigated through mercury intrusion porosimetry (MIP) tests, isothermal adsorption tests, and desorption-diffusion tests for coal particles with different sizes. The results indicated that the cumulative diffusion amount ( Q t ) and rate ( Q t / Q ∞ ), the effective diffusion coefficient ( D ′ ), and the kinetic diffusion parameter (υ) decreased as particle size increased. That meant gas was easier to desorb and diffuse from the smaller coal blocks, consequently making coal break into more tiny particles and accelerating gas desorption. As a result, a positive feedback effect that coal breaks continuously and gas releases rapidly and abundantly was formed in a short time when outbursts started, which caused gas release in quantities and promoted the occurrence of outbursts. The findings of this study enhance our understanding of the mechanism of gas participating in coal fragmentation during outbursts, which are significantly conducive to the prevention and control of coal mine disasters and sustainable production of coal resources. [ABSTRACT FROM AUTHOR]

Rock bursts and coal and gas outbursts are geodynamic disasters in underground coal mines. Laboratory testing of raw coal samples is the dominant research method for disaster prediction. However, the reliability of the experimental data is low due to the inconsistency of the mechanical properties of raw coal materials. The utilization of structural coal resources and the development of new coal-like materials are of significance for geodynamic disaster prediction and prevention. This paper studies the failure characteristics and dynamic disaster propensities of coal-like burst-prone briquettes under different gas pressures. A self-made multi-function rock–gas coupling experimental device was developed and burst-prone briquettes were synthesized, which greatly improved the efficiency and precision of the experimental data. The results showed that the burst proneness of the briquette was thoroughly reduced at a critical gas pressure of 0.4 MPa. When the gas pressure was close to 0.8 MPa, both the bearing capacity and the stored burst energy reduced significantly and the dynamic failure duration extended considerably, indicating the typical plastic-flow failure characteristics of coal and gas outbursts. The acoustic emission monitoring results showed that with the increase in gas pressure, the post-peak ringing and the AE energy ratio of coal samples increased, suggesting that the macroscopic damage pattern changed from bursting-ejecting of large pieces to stripping–shedding of small fragments adhered to mylonitic coal. In addition, the transformation and coexistence of coal failure modes were discussed from the perspectives of coal geology and gas migration. This study provides a new method for the scientific research of compound dynamic disaster prevention in burst coal mines with high gas contents. [ABSTRACT FROM AUTHOR]

Coal and gas outbursts represent a major risk in deep gassy coal mines, and de-stress blasting is a commonly applied technology to prevent coal face outbursts. This paper systematically studies the effects of different parameters on de-stress blasting performance. The ultimate goal is to identify optimal parameters (blasting coupling medium, detonation position, and blast hole spacing) to enlarge the stress relief zone and reduce the risk of outburst. Initially, comparative 3D numerical models were developed using ANSYS LS-DYNA to study parametric sensitivities based on the conditions at the #8 coal mine in the Pingdingshan coalfield. We found the blasting power is greatly improved when the blast hole is filled with water, and the blast wave transmission towards the hole packer is greatly reduced. Forward blasting can promote transmission of the blasting wave deeper in the coal seam, which can increase the length of the stress relief zone in front of the coal face. The theoretically calculated cracking radii of water-coupled and air-coupled blasting were consistent with the simulation results. Additionally, an experimental system built for this study was used to verify that water-coupled blasting is preferable to air-coupled blasting, as predicted by the simulations. Ultimately, the optimized approach of water-coupled forward blasting with 6 m hole spacing was applied in an active coal mine, and the risk of outbursts was observed to reduce. [ABSTRACT FROM AUTHOR]

The safety in the coal-producing mines in China is continuously improving, but coal and gas outburst accidents still occur. The prediction of coal and gas outbursts allows the scientific application of outburst prevention measures, which can ensure the safe coal mining to a certain extent. Machine learning is an interdisciplinary field involving probability theory, statistics, and computer science, which can explore the nonlinear relationship between outburst accidents and its associated indicators. The application of machine learning in coal and gas outburst prediction has received relatively widespread attention, and with the rapid progress of artificial intelligence and computer technology, it will play a greater role in the field of outburst prediction. Therefore, this paper provides a comprehensive review of the research on machine learning in coal and gas outburst prediction, analyzes the difficulties in outburst prediction and prospects its development direction. Firstly, the paper provides a brief overview of the research status on the hypothesis, occurrence mechanism, and prediction index selection of coal and gas outbursts. Then, it summarizes the research progress in the field of outburst prediction, including the application of support vector machines, neural networks, extreme learning machines, and ensemble learning algorithms. In addition, it also points out the existing problems in the current research, such as imbalanced samples, missing data indicators, and small sample sizes. Finally, the paper gives an outlook on the developments of coal and gas outburst prediction based on machine learning, including improving algorithm performance, optimizing feature engineering, and increasing sample size. With the continuous improvement of computer performance, more powerful models may be proposed, which can further improve the prediction accuracy of outburst accidents.

Outburst of coal and gas is a major hazard in underground coal mining where coal seam gas content/pressure is high. A cone‐shaped cavity is often observed in the coal seam after bursting, implying the likely mechanical structure being formed during outburst propagation. Although the mechanism for outburst initiation and propagation is very complex, mining‐induced fracturing and damage of the coal material is an essential component. This paper investigates the mechanical conditions that are essential to initiate fractures around a spherical cavity, a simplified form of the cone‐shaped outburst cavity. The cavity is assumed to be situated in an infinite isotropic homogeneous elastic body under internal gas pressure and far‐field hydrostatic compressive stresses as a further simplification for analytical investigation. The analytical conditions under which circumferential and radial fractures can initiate around the cavity are formulated, based on extensional strain criterion for fracture initiation. Low internal pressure on the cavity surface and high far‐field compression lead to circumferential fractures. In contrast, high internal pressure and low far‐field compression lead to radial fractures. Subsequent numerical simulations with FRACOD3D and FRACOD, the 3D and 2D in‐house fracture simulation codes, were carried out to investigate fracture patterns around a cavity and inclusion. The simulation results confirmed the analytical results, including fracture shapes and the size of fractured zone. These results provide a new angle to understand the complex mechanism of outbursts. [ABSTRACT FROM AUTHOR]

The hazard of coal and gas outburst underground is extremely high, with complex influencing factors and uncertain risk categorization. In this case, the traditional regional outburst prediction methods fail to fulfill the demands of spatial risk quantitative distribution, complicating the implementation of targeted regional outburst prevention measures. By combining the matter–element cloud model (MECM) with improved Dempester–Shafer evidence theory, this work proposes a novel regional outburst prediction approach based on the spatial distribution of risk index. First, a 14-indicator risk system (denoted as GCCG in this paper) is constructed using the 50 percent coverage cross-unit division approach from four categories, including gas occurrence, characteristics of coal body, coal seam occurrence structure, and ground stress and concentration, and each indicator, as an independent evidence source, generates basic probability assignments by MECM, which takes into account the contribution of the internal attribute of evidence sources to fusion results through subjective and objective weights. Then, high conflict evidence is filtered using the coefficient K. The Jousselme distance and Euclidean distance (ED) were employed to increase the reliability of evidence sources, thus obtaining comprehensive risk fusion results. The improved Centre of Distribution criterion, which is more suitable for outburst prediction, is developed based on the Centre of Distribution criterion to achieve scientific quantification of outburst risk distribution. Finally, the validity and feasibility of such a prediction method are confirmed by collecting parameters of 294 units divided by field examples, concluding that the improved evidence source of the ED method better satisfies the demand for outburst prediction. [ABSTRACT FROM AUTHOR]

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

Abstract Among all methods for investigating the complex phenomenon of the coal and gas outburst, numerical modelling is the most comprehensive one that can consider all involved parameters and simulate the complex multi-physical phenomenon. The main aim of this paper is to review recent numerical modelling studies concerning this disastrous phenomenon observed in coal mining. The paper aims to analyse these studies comprehensively and identify any existing research gaps that could be addressed in future research endeavours. To this end, the concepts and equations that have been used in previous studies to simulate the solid and fluid behaviour during outburst initiation and how these equations are coupled to consider multiphysical interactions were reviewed. Both strengths and deficiencies in past outburst modelling work were highlighted. Finally, potential research topics for future studies were discussed in three categories; looking into the outburst phenomenon in the scale of the particles which is mostly focused on the discrete element method, conservation of the energy as a method to quantitively assess outburst initiation, and the application of statistics in both applying the heterogeneity in the models and assessing the possibility of the outburst occurrence.

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The primary purpose of this paper is to research the law of gas seepage considering gas desorption in heterogeneous coal theoretically. A mechanical model on gas seepage considering gas desorption in heterogeneous coal is established, and the governing equation of gas seepage is discretized by the finite volume method with a new meshing strategy. Moreover, the gas state distribution and change in coal with different heterogeneity are calculated. The numerical results show that the effects of coal heterogeneity on gas seepage and desorption are significant. The coal with high heterogeneity is not accessible for gas to seep in it, resulting in a great gas pressure gradient, which is necessary for an outburst initiation. Additionally, the gas pressure gradient in the coal with high heterogeneity decreases more slowly than that with low heterogeneity. Hence, the possibility of outburst initiation is greater, and the outburst duration may be longer if the coal has high heterogeneity. Due to the strong randomness of the distribution and change of gas velocity in heterogeneous coal, the coal and gas outbursts in the field may be far more complex than that induced in the laboratory by using briquette, which is close to a homogeneous porous medium. [ABSTRACT FROM AUTHOR]

The objective of this paper is to identify the outburst danger of coal from the perspective of adsorption capacity, nitrogen adsorption experiments had been performed on six different coal samples. With cubic spline interpolation method, the amount of nitrogen adsorbed in the coal at p/p0 = 0.001, 0.01, 0.50, and 0.99 were obtained. The results show that the outburst coal has more micropores than that of non-outburst coal. When the relative pressure p/p0 is 0.001 and 0.50, six coal samples have significant differences in adsorption capacity. Using the adsorption amount of these two points as the quantitative indexes, six coal samples were classified into two types by iterative self-organizing analysis technique (ISODATA). Compared with the results of traditional classification, the results obtained by the new classification method in this paper are consistent with that. The iterative self-organizing analysis technique can be as a method to identify the risk of coal and gas outburst. The cluster center in the classification process can be dynamically optimized. The data obtained in the experiment are limited, and some experiments were needed to continuously optimize the cluster center to make it keep within a little range. This method has a deep understanding of the structure and the quantity of coal pores. It not only has an important significance for studying the mechanism of coal and gas outburst, but also makes the identification of coal and gas outburst easier. [ABSTRACT FROM AUTHOR]

In order to better solve the problem of gas outburst prediction, based on the in-depth study of ant colony algorithm, the ant colony clustering algorithm is improved, and the population classification and ant sensory perception characteristics are applied to make the ant colony the most likely to find. The optimal solution effectively avoids the possibility of local optimization, improves the global optimization performance and convergence speed of the algorithm, and reduces the influence of human subjective factors. Based on the prominent basic speech and actual working conditions, the paper selects five indexes of gas velocity, initial gas velocity, gas content, gas pressure and coal firmness coefficient as clustering attributes, and uses ant colony clustering algorithm to judge outstanding the state of occurrence. The paper uses MATLAB programming language to write a coal and gas outburst prediction program based on improved ant colony clustering algorithm, and predicts a coal mine. The final result is the same as the actual observation. [ABSTRACT FROM AUTHOR]

This paper investigated the effects of gas pressure, in-situ stress, and coal strength on coal and gas outbursts (CGO) based on the laboratory CGO experimental data. Based on the hypothesis of the comprehensive of CGO, the single-factor control variable method was used to analyze and evaluate the relative outburst intensity, the characteristics of outburst holes, the distribution of pulverized coal, the drops of outburst gas pressure, and the pulverized coal density under different outbursts experimental condition. The improved CGO energy equation and instability criterion are proposed as a direction to study the occurrence of CGO as an energy evolution direction. Furthermore, the results shows that the initial outburst gas pressure was 0.45 MPa during the experimental conditions of in-situ stress was 5 MPa, and the coal strength was 0.24 MPa. The gas pressure is directly proportional to the relative outburst intensity, while the in-situ stress and coal strength are inversely proportional to the relative outburst intensity. After the CGO occurred, the outburst coal always show spallation and pulverization characteristics. The results highlight that the gas pressure plays a key role in pulverizing and throwing out the pulverized coal, and the in-situ stress mainly plays a role in destroying the coal, and the coal strength plays a resistance role during the CGO occurs. It is also found that pulverized coal particles size less than 0.28 mm can be used to represent the distribution pattern of the total weight of outburst pulverized coal particles in the different outburst interval. These results clearly illustrate that using effective methods to control gas pressure, in-situ stress, and coal strength has an important role in preventing and controlling CGO on coal mining sites. [ABSTRACT FROM AUTHOR]

Coal and gas outburst (CGO) is a devastating disaster in the coal mining industry at the cost of human life. Considerable efforts have been done to eliminate this hazard, but CGO still occurs frequently. The geological structure is a critical factor influencing CGO, and it has recently been found that sudden change in coal property plays an important role in CGO. In this paper, the stress transmission, coal deformation, energy accumulation, and plastic damage when the roadway is excavated to the geological structure with the sudden change in coal property are analyzed by numerical method, based on Shoushan No.1 coal mine. It is found that the geological interface between soft coal and hard coal transfers the stress from soft coal to hard coal within a certain range, causing the occurrence of tectonic stress. The tectonic stress increases gradually with roadway excavation and finally superimposes with the peak stress. The coal deformation and elastic energy increase, leading to a high probability of CGO. When the heading face is closed to the geological structure, the coal damaged area is obviously increased no matter the roadway is excavated from hard coal to soft coal or from the opposite direction. Engineering trial shows that controlling the tunneling speed and pre-grouting to reinforce the geological anomaly area are effective methods to improve the safety of roadway excavation. [ABSTRACT FROM AUTHOR]

Taking coal mine dynamic disaster as research background in this paper, five samples of coal–rock composite bodies (CRCBs) with different coal thicknesses were designed, and the uniaxial loading tests were carried out on them by using the MTS uniaxial loading instrument and the DS5 acoustic emission instrument, and the damage process of the samples were analyzed from the perspective of energy conversion. The results were as follows. With increase in coal thickness of CRCBs, the uniaxial compressive strength and elastic modulus of CRCBs decreased while the peak strain increased, and the overall bearing capacity of the samples decreased, resulting in a decreasing trend of AE peak ringing count and peak energy. According to the theory of conservation of energy, it was found that the dissipated energy of the samples in the compaction stage accounted for a large proportion, and the elastic stage was dominated by the accumulation of elastic energy. After the plastic stage, the energy conversion rate in the samples accelerated, and the dissipated energy increased rapidly, leading to the gradual failure of the samples. The energy storage limit of samples decreased logarithmically together with increase in coal thickness. Finally, it was found that coal was the main energy storage structure of the whole coal and rock composite system by analyzing the energy accumulation mechanism of coal and rock composite structure in practical engineering. Therefore, to prevent and control underground dynamic disaster in practical engineering, the internal energy storage of a coal seam should be released and the clamping effect of roof and floor on coal body should be weakened. The achievements of this study will be a theoretical guidance for preventing and controlling dynamics. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The section of appropriate prediction index is of great importance for coal and gas outburst prediction. The quantity of gas emission is a key factor directly relating to the outburst risk of tunneling working face in the coal roadways. Therefore, accurately predicting the quantity of gas emission is necessary and critical to prevent and control outbursts. In this paper, using the sphere diffusion equation of coal particle gas and radial unsteady flow equations of coal seam gas to analysis gas flow of fallen coal and coal wall, and a dynamic prediction model of gas emission is established including key factors, research shows that: (1) in tunneling working face, the change rule of gas emission of the new model, in which mechanical state, physical properties of coal seam, roadway tunneling parameters, and gas adsorption parameters are considered, is the same as that of the conventional index, which indicates the feasibility of the new model; (2) The new model shows that the gas emission is positively correlated with the gas pressure, driving speed and permeability coefficient of coal seam, and negatively correlated with the uniaxial compressive strength of coal mass; (3) By comparing the old prediction model of gas emission, the predicted value of the new model is closer to the measured value, fluctuating within a smaller range, and has a higher accuracy after taking the gas emission of coal particle into account. In addition, the multiple characteristics of the coal body in front of the working face are comprehensively considered. The research results offer practical significance for improving gas prevention and control of tunneling working face. [ABSTRACT FROM AUTHOR]

Coal and gas outburst is one of the main disasters that seriously threaten workers' safety during coal production. Timely identification and evaluation of the potential outburst before tunneling helps to implement the targeted control measures. Nevertheless, the influencing factors of outburst are so complex that there is no suitable index system and evaluation method available yet. In this paper, a more reasonable and complete index system (three categories of factors and 16 indicators) for outburst risk is established, in which, the risk level is divided into three levels. Then, the triangular fuzzy numbers are adopted to quantify the indicators and the logarithmic fuzzy preference programming method to calculate the weight. The cloud distribution under finite interval processing is generated based on cloud numerical characters of each indicator. In addition, the risk level is determined according to the calculation results of multi-index comprehensive membership degree. Finally, the entire evaluation system is applied to two excavated coal roadways for experiments, which show that the finite interval cloud model delivers a more objective and reasonable risk assessment. Five potential outburst threat areas of 58 excavation cycles evaluated show different degrees of outburst dynamic appearance, indicating a good relationship between the evaluation results and the actual risk. This method effectively considers the fuzziness and randomness between indexes, and it is able to classify outburst risk effectively, providing insights for the scientific and accurate assessment of such risks in front of the driving face. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Coal and gas outbursts are one of the most serious disasters in coal mining, and disaster prediction and prevention alarms are key technologies to prevent coal and gas outbursts. This paper summarizes the progress of research on outburst prevention alarm indicators and prevention alarm technology for mines; the mechanism of coal and gas outbursts; the relationship between the coal seam geological environment and outbursts; and the relationship between coal seam gas drainage, roadway excavation and mine working face (DEM) operations and outbursts. Prevention alarm indicators are key to effective prevention alarms. The analysis proposes that from the perspective of understanding the relevant theoretical research and the effectiveness, timeliness and comprehensiveness of the prevention alarms, there are still some deficiencies, and establishing preventive alarm indicators and preventive alarm models is difficult. Assuming the reasonable management of coal seam DEM, the coal seam geological environment is established as a secondary indicator. Production, gas drainage, ventilation, monitoring and control, auxiliary production and other systems are the third-level indicators. Catastrophic parameters such as safety distance, pre-extraction time, mining procedures and DEM replacement are used as fourth-level indicators for the outburst disaster risk assessment index system, which provides a basis for understanding mine risk decision-making and disaster prevention and alarms. [ABSTRACT FROM AUTHOR]

The sudden outburst of coal and gas is a complex and dynamic incident in the underground coal mines, resulting in the release of thousands of tons of coal and large amounts of gas into the working face within a short time. Due to a rise in the number of exploitations and the depth of extractions, the intensity, and frequency of explosions have increased in recent years. Consequently, these explosions have endangered miners' health and safety, brought about equipment loss and seriously affected coal production. To overcome these obstacles, the first step is to predict the occurrence of such incidents in the coal mines. There are a lot of factors playing a part in the sudden outburst of coal and gas, which can be categorized into natural and operational parameters, each of which has a different role. In this paper, a novel method is proposed to predict the possibility of gas outburst in coal seams. For this purpose, ten parameters are considered as the main variables influencing the outburst of coal and gas. To study the interrelation between these determining parameters as well as the uncertainty of the effect of one parameter on another, a fuzzy interaction matrix based on Fuzzy Rock Engineering System (FRES) has been employed. To evaluate the capability and efficiency of the proposed classification system, the C1 coal seam of Tabas coal mine is selected, and the proposed index is used to investigate the potential risk of the outburst in this mine. Index as mentioned earlier could be utilized as a basis through which one can decide on the possibility of the outburst of coal and gas in coal mines to reduce the risks of this incident. [ABSTRACT FROM AUTHOR]

Coal and gas outburst seriously threatens the safety of underground coal mining. After the outburst, it will not only cause harm in the near-field outburst roadway but may also have a strong impact on the far-field ventilation network connected to the outburst roadway, expanding the impact of the disaster. In order to define the propagation law of shock wave and airflow induced by the outburst and its influence on the far-field ventilation network, the coal and gas outburst experimental system was used to carry out an experimental study under different air current and local resistance conditions in this paper. The results show that, under different air current states, the first overpressure peak increases with an increase of outburst pressure and decreases with an increase of propagation distance. Compared with the propagation characteristics in a windless roadway, the first overpressure peak and attenuation coefficient of shock wave propagating downwind are smaller, whereas opposite in upwind state. The local resistance enhances the impact and disturbance ahead of it and weakens that after it. When shock airflow propagates downwind, the increase of shock airflow velocity is approximately equal to the original airflow velocity in the roadway, whereas the airflow direction may reverse when the shock airflow propagates upwind. This paper provides some references to prevent the impact expansion of coal and gas outburst, which are of great significance for the optimization of ventilation network and emergency management. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Engineering Geology / Gongcheng Dizhi Xuebao is the property of Journal of Engineering Geology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper analyzes the image characteristics of the thrown coal and rock when rock burst and coal and gas outburst occur. ① The coal and rock thrown out during rock burst and coal and gas outburst are mainly black, but the underground equipment of the coal mine is generally not black. Therefore, nonblack mining equipment can be used as the background and color cameras can be used to identify coal and rock. ② The normal coal falling speed, the moving speed of shearer, roadheader, and the moving speed of underground personnel and vehicles are far less than the speed of coal and rock thrown out in the event of rock burst and coal and gas outburst. Therefore, according to the speed characteristics, the interference from normal coal falling, movement of equipment such as shearer and roadheader, and movement of underground personnel and vehicles can be eliminated. ③ The explosion of gas and coal dust will also cause the objects in the roadway to have a high speed in a short time, accompanied by high brightness. But the rock burst and coal and gas outburst will not produce high brightness. Therefore, according to the average image brightness, the interference of gas and coal dust explosion can be eliminated. The paper proposes a color camera set method. The camera of the heading face should be set at the roof of the heading roadway or near the roof on both sides of the heading roadway. The camera of the working face should be set on the top of the hydraulic support. The paper puts forward a coal mine rock burst and coal and gas outburst perception alarm method based on color image. ① The color camera with fill light shall be set at the roof of the heading roadway or near the roof on both sides of the heading roadway, and at the top of the hydraulic support of the working face. The nonblack mining equipment is used as the background. ② The method monitors and identifies whether the color of the color image has changed greatly. ③ If the image color changes significantly, the average brightness of the image is identified, otherwise the monitoring of the identified image color change continues. ④ If the average brightness of the image is less than the set brightness threshold, the movement speed of the object causing a large change in the image color is identified, otherwise the monitoring of the identified image color change continues. ⑤ If the movement speed of the object is greater than the set speed threshold value, the methane concentration in the monitoring area is identified, otherwise the monitoring of the identified image color change continues. ⑥ If the methane concentration rises rapidly or reaches the alarm value, the coal and gas outburst alarm will be given. Otherwise, the rock burst alarm will be given. The method has the advantages of non-contact, wide monitoring range, low cost, convenient use and maintenance.

The formation and development of faults are a manifestation of stress concentrations and energy release in crustal rocks, and faults have a great influence on the occurrence of dynamic mine disasters. This study proposed mapping technology as a fault identification method. The mapping procedure included four steps: (1) Drawing points on topographic maps. The information of topographic maps, such as elevation, rivers, and lakes was copied onto sulfuric acid paper. (2) Classifying the landform. Based on the highest and lowest points in the studied area, the minimum elevation difference was calculated and the elevation points were graded according to the minimum elevation difference. (3) Determining the block boundaries. The elevation points in the same grade were categorized into the same blocks. (4) Mapping the fault distribution. The boundaries between different blocks were considered as faults. In this regard, numbers were assigned to the faults, and a graphic scale, coordinate grid, and legends were added to the map. Fault identification for classes I–V was conducted at different scales. Fault identification for the next class always retained the previous results. Using this method, the faults in the Pingdingshan coal mining zone were divided into classes I–V. By comparing the classes with historical coal and gas outbursts, it was indicated that more than 90% of the coal and gas outbursts occurred in the vicinity of faults, especially at the intersections of multiple faults and in areas with concentrated faults. This study provided a scientific basis for predicting coal and gas outbursts. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Mine Automation is the property of Industry & Mine Automation Editorial Department and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of China Sciencepaper is the property of China Sciencepaper and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• A two-phase gas-solid flow model for outburst shock waves is established. • Three parameters of the release of gas pressure potential energy are defined according to the energy transformation during gas expansion process. • The gas dynamic characteristics of two-phase flow in the initiation stage are quantitatively studied under the four factors: initial gas pressure, particle volume fraction, particle size and outburst hole size, which is verified by experiments. The dynamic effect of coal and gas outburst seriously threatens the safety of underground equipment and workers in mines. In this paper, the models for outbursts are established, and according to the energy transformation during gas expansion process, three parameters of the release of gas pressure potential energy are defined and the gas dynamic characteristics of two-phase flow in the initiation stage are quantitatively studied under the four factors: initial gas pressure, particle volume fraction, particle size and outburst hole size. The gas dynamic characteristics in numerical simulations are verified by experiments. The results show that for the influence of the factors on the gas dynamic characteristics of two-phase flow, initial gas pressure >outburst hole size >particle volume fraction ≈particle size. The solid particles block the pressure potential energy release from chamber, so does the caliber. However, the maximum of pressure drop occurs when the caliber is 80% of the chamber, which explains the outbursts in mines are so violent due to the caliber smaller than the internal space. This paper provides a novel quantitative research method of gas dynamic characteristics of coal and gas outburst, which is of guiding significance to the design of outburst prevention facilities and emergency rescue measure. [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]

Coal is an important energy resource internationally. However, accidents have severely restricted the clean and safe production of coal resources. Among such accidents, coal and gas outburst accidents are a kind of coalmine disaster with high destructive power. Previous research on coal and gas outburst accidents mainly focused on gas factors but ignored the role of human factors. This paper analyses the coal and gas outburst accidents in China from 2008 to 2018 and studies its macroscopic laws. To better understand the causes of coal and gas outbursts, this paper uses the 24modelel to analyse coal and gas accidents and suggest measures for accident prevention from the two aspects 'gas' (risk control) and 'humans' (behavioural safety). Macroscopic law research found the following: (1) March, May, July, and August are the predominant months for accidents. (2) The second to fourth hours of the working hours and the first hour before the end of work are the peak periods for accidents. (3) Guizhou, Hunan, Henan, Sichuan, Yunnan, and Chongqing are the provinces with the most coal and gas outburst accidents. (4) An overall 75.82 % of accidents occurred in the driving face, and 81.08 % of accidents occurred in coal and gas outburst mines. (5) Blasting, drilling, driving, and coal falling are the main inducing factors. Case analysis of accidents found the following: (1) Human error is the leading cause of accidents. Among the errors, the lack of strict enforcement of outburst prevention measures, illegal command, and the illegal operation of miners are the main unsafe acts. (2) Safety knowledge and awareness of miners is not generally high, and serious habitual violations and unsafe psychologies exist. (3) The gas comprehensive prevention system and supervision system in the coal mine safety management system (SMS) can be easily operated improperly, and the safety training system and emergency management system can be absent. (4) Coalmine enterprises seriously lack safety culture. [ABSTRACT FROM AUTHOR]

Coal and gas outbursts have occurred in the Zhaozhuang coal mine (a high gas coal mine) since its construction, and these outbursts pose a great threat to lives and property. Therefore, the combination of methane desorption experiments and molecular simulations was adopted to investigate the effects of moisture on the methane desorption characteristics of the Zhaozhuang coal, and the microscopic mechanism was analyzed in this paper. The aim of this work is to provide a method for predicting the effect of moisture on coal seam methane desorption, and quantitatively evaluating the control effect of hydraulic measures on coal and gas outbursts from a molecular perspective. The experimental data (methane desorption amount) were measured under various adsorption equilibrium pressures (0.3 MPa, 0.4 MPa, and 0.5 MPa) and moisture contents (0%, 5%, and 9.8%). Based on the Zhaozhuang coal molecular model, the molecular simulation process was conducted using Materials studio software, which can better match the experimental conditions by setting various pressure parameters (0.3 MPa, 0.4 MPa, and 0.5 MPa) and calculating various numbers of H2O molecules (0, 8, and 16) on the coal molecule. The results show that methane desorption decreases with the increasing moisture content in the experiment. The number of CH4 molecules adsorbed on the coal molecule decreases with the increasing number of H2O molecules in the simulation. This phenomenon can be explained by the competitive adsorption between CH4 and H2O molecule: the interaction between coal molecule and H2O molecules is stronger. The affinity between CH4 molecules and the coal molecule is reduced, and CH4 molecules are less aggregated around the coal molecule because of the presence of H2O molecules. [ABSTRACT FROM AUTHOR]

Coal mine accidents have seriously constrained the development of energy economy, in which coal and gas outburst accidents pose the greatest impact, accounting for more than 70% of the accident rate. At present, the mine usually uses the parameters to evaluate the risk of outburst, such as gas desorption index and drilling yield index. However, the traditional index method has the shortcomings of time lag, complicated operation, and difficult real-time monitoring. In this paper, the advanced detection method of multi-component seismic wave is used to obtain the seismic attributes in real time and fast way, and three-component reception and artificial hammer excitation are arranged in the roadway. The field tests were carried out on nine roadways of No. 3 anthracite in Yangquan Mining Area, China. The correlation between the absolute gas emission quantity and attributes of the seismic wave was studied. The results show that under the same coal seam, the correlation between the absolute gas emission quantity and the seismic wave velocity parameters is weak. The absolute gas emission quantity has a good exponential correlation with the quality factor Q, the attenuation coefficient α, and the dominant frequency value fm. The absolute gas emission quantity is negatively correlated with the quality factor Q, and the regression equation is Qg = 3.5644e−0.33Q with correlation coefficient R2 = 0.9126. With the increase of absolute gas emission quantity, the attenuation coefficient of gas-bearing anthracite rises, but the dominant frequency decreases. On account of the high correlation between the absolute gas emission quantity and the quality factor, real-time monitoring of the quality factor of seismic wave have theoretical significance for predicting coal and gas outburst, and it is expected to provide a new way of the prediction of the outburst risk. [ABSTRACT FROM AUTHOR]

In order to solve the problem of gas overlimit in corner corners of coal and gas prominent mines, through the combination of air leakage mechanism in the goaf, near-field fissure expansion and rich area division, blocking material development and optimization, performance measurement of blocking materials and on-site test, we started to study the causes of gas concentration in corner corners, analysis of roof collapse and transparency in corners and performance test of blocking materials, and optimized the blocking materials by combining laboratory test and engineering test. Considering the thickness of the sealing film, the attenuation ratio of the sealing film thickness, the gelation time, and the gelation viscosity under different ratios, we designed a multi factor orthogonal experiment to optimize the optimal ratio suitable for the engineering site. Factors affecting blocking effectiveness, such as gel water retention and gel flame resistance, were also tested. The sealing scheme was implemented in the 2109 working face of a coal and gas outburst mine in Gansu, China. Through on-site monitoring of the changes in temperature, gas concentration, and air leakage at each monitoring point before and after the use of sealing materials, the analysis of the detection results shows that the temperature changes at each monitoring point after the use of sealing materials do not exceed 0.2°C; The change in oxygen concentration is less than 0.27 %; The gas concentration has decreased by more than 60 %, with a decrease of 71.32 % in the gas concentration in the upper corner. The air leakage has decreased by more than 53 %, and the proportion of decrease in air leakage at the upper corner is as high as 56.83 %. This air leakage control technology has remarkable blocking effect, meets the requirements of corner near-field fissure blocking material, and is easy to prepare, inexpensive, non-toxic, tasteless and green, providing a successful experience for the treatment of similar coal and gas outburst mines that can be referenced. [ABSTRACT FROM AUTHOR]

The paper puts forward a perception and alarm method of rock burst and coal and gas outburst based on temperature. The infrared thermal imager is used to monitor the temperature of objects, and the methane sensor is used to monitor the concentration of ambient methane. When the temperature of the objects is higher than the ambient temperature of the coal mine and the temperature of the exposed coal rock, and the number, volume and area of objects that are higher than the ambient temperature and the temperature of the exposed coal rock are large, it is determined that rock burst, coal and gas outburst, mine fire or gas and coal dust explosion accidents have occurred. The temperature of the high temperature object is further determine. If it is greater than the set threshold, it is determined that a mine fire or a gas and coal dust explosion accident has occurred. Otherwise, it is determined that a rock burst or a coal and gas outburst accident has occurred. The change of methane concentration is further analyzed. If the methane concentration rises rapidly, it is determined that a coal and gas outburst accident has occurred. Otherwise, it is determined that a rock burst accident has occurred. The paper puts forward a perception and alarm method of rock burst and coal and gas outburst based on velocity. The lidar, millimeter-wave radar, ultrasonic radar, binocular vision camera are used to monitor the moving speed of objects. The methane sensors are applied to monitor the concentration of ambient methane. When the moving speed of the object is not less than the set threshold, it is determined that rock burst, coal and gas outburst or gas and coal dust explosion accident have occurred. The number, volume and area of objects with abnormal velocity is further determined. If the number of objects with abnormal velocity is small, the volume and area are small, it is determined that a gas and coal dust explosion accident has occurred. If the number of objects with abnormal velocity is large, the volume and area are large, it is determined that a rock burst or a coal and gas outburst accident has occurred. The changes of methane concentration are further analyzed. If the methane concentration increases rapidly, it is determined that a coal and gas outburst accident has occurred. Otherwise, it is determined that a rock burst accident has occurred. A multi-information fusion method for perception, alarming and judging disaster source of rock burst and coal and gas outburst is proposed. The method monitors and integrates various information such as temperature, speed, acceleration, burial depth, sound, air pressure, wind speed, wind direction, dust, methane concentration, equipment status, micro-seismic, geosound, stress, infrared radiation, electromagnetic radiation and images so as to monitor the pressure and coal and gas outbursts. The source of the disaster is determined through the magnitude of parameter changes at different locations, the sequence relationship and sensor damage.

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)