Coal-fired Research Articles

Study on thermal damage characteristics and micromechanical behavior of structures induced by spontaneous combustion of low-rank coal

Thermal damage induced by coal spontaneous combustion (CSC) has a significant impact on its development. In this study, low-rank coals were heat-treated (25–500 °C). Experiments such as nuclear magnetic resonance, scanning electron microscopy, and uniaxial compression were used to visualize and quantify the evolution of pore structure and structural strength during CSC. A multi-component discrete-element model of coal thermal fracture was developed and a sensitivity analysis of the micromechanical behavior of CSC was carried out. The results showed that during CSC, the micropores in coal gradually evolved into mesopores or macropores, and the pore diameter, porosity and permeability can be increased to 5.51 μ m, 21.05 % and 1.51 mD respectively with the temperature. Significant thermal damage occurred in low-rank coal at 100 °C, leading to a sharp decrease in its load-bearing capacity, which made it easier to reach the damage condition and produce more cracks. And then the thermal damage was fluctuating with the increase of temperature. From 100 °C to 500 °C, the micromechanical behavior of low-rank coal is similar, and the variation of the critical value with temperature is small. The study results can serve as a reference for controlling coal fires.

Synthesis and Characteristics of Thermosensitive Hydrogel for Extinguishing Coal Mines Fire

ABSTRACT Thermosensitive hydrogel shows good application prospect in the prevention of coal spontaneous combustion. In this study, a kind of thermosensitive hydrogel was synthesized by adding sodium polyacrylate (PAAS) and magnesium chloride (MgCl2) into methylcellulose (MC). Single-factor experiments and central composition design（CCD method）were carried out to optimize the gel ratio, the inhibitory effect of the gel on three kinds of bituminous coal was analyzed, a test platform was set up (coal capacity of 200 kg) to test the gel’s fire-fighting performance. Results showed that the optimal preparation ratio of gel was MC: PAAS: MgCl2 = 1.3:2.11:16, resulting in the three response parameters of Y1[gelation time, 50 s], Y2[gel strength, 53 KPa], and Y3[viscosity, 11.6 Pa·s]. Temperature programmed experiment indicated that the gel can reduce the release of CO and C2H4 emission and oxygen consumption rate, thus it raising CPT of long flame coal by 5°C and inhibition rate by 63.71%. After injecting the gel in the burning coal, the thermosensitive hydrogel took phase change and absorbed the high temperature as well as thermal energy, reducing the composite speed of the coal and oxygen, causing the coal fire to go out. Research can provide new ideas for the research and application of gel fire extinguishing agents.

Advanced machine learning schemes for prediction CO2 flux based experimental approach in underground coal fire areas

IntroductionUnderground coal fires pose significant environmental and health risks due to releasing CO2 emissions. Predicting surface CO2 flux accurately in underground coal fire areas is crucial for understanding the distribution of spontaneous combustion zones and developing effective mitigation strategies. In recent years, advanced machine learning techniques have shown promise in various carbon-related studies. This research uses an experimental approach to explore the power of advanced machine learning schemes for predicting CO2 flux in underground coal fire areas. ObjectivesBy leveraging the power of advanced machine learning schemes and experimental approaches, this research aims to provide valuable insights into CO2 flux prediction in coal fire areas and inform environmental monitoring and management strategies. MethodsThe study involves the collection of an experimental dataset specific to underground coal fire areas, encompassing various parameters related to CO2 flux and underground coal fire characteristics. Innovative feature engineering techniques are applied to capture the unique characteristics of underground coal fire areas and their impact on CO2 flux. Different machine learning algorithms, including Natural gradient boosting regression (NGRB), Extreme gradient boosting (XGboost), Light gradient boosting (LGRB), and random forest (RF), are evaluated and compared for their predictive capabilities. The models are trained, optimized, and assessed using appropriate performance metrics. ResultsThe NGRB model yields the best predictive performances with R2 of 0.967 and MAE of 0.234. The novel contributions of this study include the development of accurate prediction models tailored to underground coal fire areas, shedding light on the underlying factors driving CO2 flux. The findings have practical implications for delineating the spontaneous combustion zone and mitigating CO2 emissions from underground coal fires, contributing to global efforts in combating climate change.

An experimental study on monitoring and early warning of spontaneous coal combustion fires using CPM

At present, the conventional indicator gas has a blank temperature interval in the monitoring of coal spontaneous combustion fire area, and the monitoring accuracy is easy to be interfered by wind flow, which leads to the inaccurate grasp of the situation of the fire area. To solve this problem, the characteristics of condensable particulate matter (CPM) released into the air during spontaneous combustion and heating are analyzed in this paper through a particle collection system. The results showed that the CPM captured by the system gradually increased when the coal temperature rose above 250℃, and the diameter was above 1um. After 300℃, the release of CPM increased significantly, which was more than 10 times that below 300℃. Test analysis showed that these CPMs were mainly phenols and polycyclic aromatic hydrocarbons, which accounted for 22 % and 37 % respectively after 300℃. CPM mainly comes from the pyrolysis stage and the early stage of combustion of coal. Aliphatic macromolecules and polycyclic aromatic compounds generated by pyrolysis are the precursors of CPM. Due to the limitation of oxygen diffusion, these compounds are released into the air due to insufficient oxidation and eventually form CPM. It is worth noting that the release amount and composition of CPM have a good correspondence with coal temperature. The research results can fill the temperature gap of monitoring fire situation by conventional gas, and help to improve the accuracy of monitoring, which is of great significance for the protection of coal resources and safe production.

Machine learning approach for detection of land subsidence induced by underground coal fire using multi-sensor satellite data

ABSTRACT High-rank coal reserves in Jharia Coalfield (JCF, India), are invariably associated with underground coal fires and land subsidence. This study explores multi-sensor time series satellite data (Landsat 8 OLI and Sentinel-1) through machine learning (ML) to determine the regional ground deformation accompanying coal fires and their contextual relationship. The results show that the highest degree of subsidence is closely associated with the active mine benches with overburden dumps. The relationship between the coal fire and land subsidence parameters is considered as a binary classification problem, explored by calculating the probability of subsidence with a desirable categorical outcome through different ML models. The accuracy of the models is validated using performance metrics that shows that the Random Forest (RF) metrics predict the probability of deformation locations in response to the volume reduction of the burning coal fire and vertical compression due to Overburden Dump (OBD) near active mine benches. The estimated displacement trends have been used to forecast the Autoregressive Integrated Moving Average (ARIMA) method, estimated using Line-of-Sight (LOS) displacement values vary around the best fit within the 95% confidence limits. The trend shows ∼15–25% increase in subsidence compared to the cumulative subsidence.

Temporal and Spatial Dynamics of Subsidence in Eastern Jharia, India

Abstract. Jharia, one of the oldest and most significant mining areas, is facing the issue of subsidence for different reasons, such as coal fires, underground mining, and soil sensitivity towards seasonal change. This paper concentrates on the subsidence analysis of the Eastern region of the Jharia Coalfield from January 2018 to January 2021. Sentinal-1 SLC SAR imagery is used for multi-image sparse point processing and generating time series. Data processing is done using SARPROZ software. Further, the PS points inside the study area are filtered, and a classification map is drawn using ArcGIS software. The yearly percentage change of different classified zones is examined. The percentage change is significant for subsiding and uplifting zones but minimal for stable zones. Different critically and highly subsiding areas are identified by overlaying the classification zones on the topographic map. The seasonal variation of cumulative displacement is also examined, and patterns are analyzed. Different regions have different sensitivity towards seasonal variation. Overall, this paper provides insightful deformation results over Eastern Jharia for 2018–2021.

Study on Multi-Parameter Variation of Smoke Flow in Inclined Roadway Fire

ABSTRACT Based on the fluid similarity theory, a “Mine inclined roadway fire simulation experimental system” with similarity ratio of 1:20 is established. The temperature, velocity, density and dynamic pressure of fire smoke under different inlet wind speed (0.5 m/s, 1.0 m/s, 1.5 m/s) were tested and analyzed, and the distribution of temperature, velocity, density and dynamic pressure of inclined roadway during fire was simulated and analyzed by Ansys numerical simulation software. The research shows that: The higher the inlet wind speed, the faster the heat diffusion and the temperature field tends to be flat and long, the wind speed changes in advance and the change is drastic, the gas density decreases, the dynamic pressure first decreases and then increases and then tends to stabilize, but the change trend of temperature, wind speed, gas density and pressure in the overall combustion process remains unchanged. The numerical analysis results are in good agreement with the experimental results. By studying the change law of smoke temperature, velocity, density and dynamic pressure of coal mine inclined roadway fire, the theory of coal mine roadway fire is further perfected, and the level of coal mine fire prevention and rescue is improved.

Synergistic inhibition kinetics and mechanisms of polyethylene glycol – citric acid on non-caking coal oxidation at low temperature

ABSTRACT Focused on the insufficient efficacy of conventional flame retardants in mitigating coal spontaneous combustion (CSC), a novel composite flame retardant synthesized from polyethylene glycol (PEG) 2000 and citric acid (CA) is proposed. Through Differential Scanning Calorimetry (DSC) and Fourier Transform Infrared Spectroscopy (FTIR) experiments, the inhibitory kinetics and mechanisms were conducted. By enhancing heat absorption rate and enthalpy, with a significant increase by 90 kJ·mol−1 of activation energy, CSC resistance is improved. CA-metal ion interaction raises activation energy to inhibit methyl/methylene oxidation, while PEG disrupts aromatic oxidation by generating H ions upon hydration. This composite retardant offers a promising avenue for CSC mitigation in coal, enhancing coal fire safety.

Study on multi-field coupling characteristics of underground coal combustion and nitrogen injection parameter optimization

Underground coal fires, which are widely distributed and cause serious resource waste and environmental hazards, have become a common concern of the international community. This paper aims to reveal the mechanism of coal spontaneous combustion and the expansion law of underground coal fires. A void rate model from the goaf to the ground surface and a multi-field coupling model for underground coal fires were established. Based on which, the combustion process from the beginning of oxidation to the formation of large-scale fire of the remaining coal in goaf was analyzed. Furthermore, the evolution law of underground coal fire after nitrogen injection and the influence of different nitrogen injection parameters were analyzed. The results show that the coal spontaneous combustion can be divided into three stages: slow reaction stage (stage Ⅰ), violent combustion stage (stage Ⅱ), and stable combustion stage (stage Ⅲ), and the transformation of different stages is mainly controlled by the oxidation reaction rate of coal. To obtain the optimal parameters for nitrogen injection for fire suppression, the fire extinguishing efficiency concerning nitrogen injection time, nitrogen injection amount and nitrogen injection position, as well as the distribution law of nitrogen in rock strata were analyzed. Through range analysis, it is determined that the most effective fire extinguishing occurs with the injection rate of 0.15 m3/s in stage I, and the injection position has little influence on the fire extinguishing effect. This understanding contributes to a deeper understanding of the multi-field coupling mechanism of underground coal fires and provides a guidance for extinguishing and preventing underground coal fires.

Calculating the Spontaneous Combustion Temperature of Coal Based on Measured Gas concentration: A Case Study in the Huangshan Mine, China

ABSTRACT The actual coal temperature of “spontaneous combustion zone” is not convenient to obtain, which causes a lot of inconvenience to the prevention and control of coal spontaneous combustion fire. The traditional temperature measurement method does not consider the influence of gas flow in the goaf, so the measured coal temperature cannot directly reflect the actual state of coal spontaneous combustion. This paper presents a method to predict the coal temperature in the “spontaneous combustion zone” based on the theoretical data obtained in the laboratory, combined with the actual coal temperature in the “dissipation zone,” and applies it to the B4 layer coal mine in Huangshan, Jiangxi Province. The results show that the method is objective and effective, and can be used for the prediction of CSC (coal spontaneous combustion) in the goaf of coal mines.

Cancer incidence after an open cut coal mine fire

Using population-level cancer diagnosis data, we compared cancer incidence in locations affected by smoke from a six week-long open cut coal mine fire in regional Victoria, Australia, up to seven years following the event. There was no detectable effect on cancer incidence overall. While several subgroups exhibited changes, these were more likely due to statistical chance rather than real effects. These findings may be limited by low statistical power and short duration of follow up. To confirm the influence of open cut coal mine fires on cancer incidence, further research and an extended follow-up duration are necessary.

Dynamic correlation between surface carbon response and underlying emissions from spontaneous combustion goaf: field study of an abandoned coal mine

Abandoned coal mine goaf is affected by air leakages and prone to spontaneous combustion, resulting in environmental pollution and geological disasters. Haizhou Open-pit Mine adopts both underground and open-pit mining methods. During the long-term mining process, the original stable stratum structure is constantly destroyed, and the slope slides, increasing cracks and severe air leakage around the goaf and roadway. The spontaneous combustion of coal is particularly prominent after the mine shut down. At present, there is no suitable indirect monitoring method to effectively explore the spontaneous combustion area in goaf. The study developed an all-weather monitoring plan and conducted multi-point continuous long-term measurements of the spontaneous combustion state in one abandoned coal mine goaf located in the eastern part of the Haizhou Open-pit Mine. We evaluated the dynamic correlation between surface CO2 flux (SCF) and changes in the underground fire areas, determined the scope and evolution trend of the fire areas, and identified the distribution and change laws of SCF. The results show a significant positive correlation between SCF and soil temperature; moreover, the SCF value was found to reflect the CO2 emission intensity of the goaf. The high SCF in the test area showed month-wise expansion and increase, while the CO2 emission gradually increased monthly, and the calculated annual total emission was approximately 7017 t. Hence, the study can further provide guidance for the monitoring of spontaneous combustion in shallow coal seams, goaf and the assessment of CO2 emissions from underground coal fires through the on-site monitoring and analysis results.

Investigating how oxygen levels and particle size impact the thermodynamics of low temperature coal oxidation: A case study using weakly caking coal

Oxygen concentration and particle size play critical roles in the combustion of coal. Notably, the low temperature oxidation stage is considered pivotal for coal spontaneous combustion (CSC). In this study, we examined the exothermic oxidation of low-temperature weakly caking coal. We used a C80 microcalorimeter to assess the impact of different oxygen concentrations and particle sizes. For weakly caking coal during low-temperature oxidation, the heat flow (HF) curve decreases as oxygen concentration drops. The characteristic temperature increases, and the HF curve shows a noticeable lag. Under identical external conditions, decreasing the particle size of coal results in a reduced minimum floating coal thickness, lowers the oxygen concentration needed for CSC, increases the upper-limit of air leakage intensity, and makes the coal more susceptible to CSC. Reducing the particle size significantly increases the exothermic heat release during low-temperature oxidation, leading to a higher risk of CSC. These research results not only deepen the understanding of the law of coal spontaneous combustion, but also provide a scientific basis for improving the technical level of coal spontaneous combustion fire prevention and control.

Assessing the Influence of Safety Culture to Employee Safety Performance Mediated by Safety Communication in Coal-Fired Power Plant

This study analyzes the effect of safety culture on employee safety performance at a Coal Fired Power Plant (CFPP) in Java, as well as the mediating role of safety communication and moderating role of service years. This study aims to investigate the direct and indirect effects between the variables of safety culture, safety communication and employee safety performance. In addition, the study also explored the moderating role of service year in the relationship between safety culture and employee safety performance. Data was obtained from distributing questionnaires to CFPP employees using a stratified sampling method. SmartPLS SEM. The findings reveal that safety culture does not have a significant direct effect on employee safety performance. However, safety communication significantly mediates the relations between safety culture and employee safety performance. The service year does not moderate the relationship between safety culture and employee safety performance This indicates that other factors such as continuous training, reward system, and work environment may be more influential in this context.

Experimental investigation on the impact of water immersion time and particle size on the ignition characteristics of coal dust

After drying, water-immersed coal is more prone to spontaneous combustion than raw coal. However, the influence mechanisms of particle size and water immersion duration on the physicochemical properties of coal dust, as well as the explosion and fire hazards of water-immersed coal dust, have not been sufficiently investigated. In this study, two particle sizes of coal dust were selected, and experiments were conducted using the Godbert-Greenwald furnace, Hartmann tube, Muffle furnace, and Fourier Transform Infrared Spectrometer. The study investigated the impact of different water immersion times, dust particle sizes, and dust concentrations on the sensitivity of coal dust fires and explosions, analyzed the process of functional group changes in coal dust particles in water and other mechanisms of transformation. The results indicated that the water immersion process increased the number of active functional groups on the surface of coal dust, significantly reducing the Minimum Ignition Temperature (MIT) and Minimum Ignition Energy (MIE) values for different samples, and also enhancing the ignition sensitivity and peak temperature of coal dust layer fires. This study contributes to a deeper understanding of the characteristics of coal dust and is of great significance for improving the prevention and control of coal dust fires and explosions.

High fat diet-induced obesity and gestational DMBA exposure alter folliculogenesis and the proteome of the maternal ovary†.

Obesity and ovotoxicant exposures impair female reproductive health with greater ovotoxicity reported in obese relative to lean females. The mother and developing fetus are vulnerable to both during gestation. 7,12-dimethylbenz[a]anthracene (DMBA) is released during carbon combustion including from cigarettes, coal, fossil fuels, and forest fires. This study investigated the hypothesis that diet-induced obesity would increase sensitivity of the ovaries to DMBA-induced ovotoxicity and determined impacts of both obesity and DMBA exposure during gestation on the maternal ovary. Female C57BL/6J mice were fed a control or a High Sugar High Fat (45% kcal from fat; 20% kcal from sucrose) diet until ~30% weight gain was attained before mating with unexposed males. From gestation Day 7, mice were exposed intraperitoneally to either vehicle control (corn oil) or DMBA (1mg/kg diluted in corn oil) for 7 d. Thus, there were four groups: lean control (LC); lean DMBA exposed; obese control; obese DMBA exposed. Gestational obesity and DMBA exposure decreased (P < 0.05) ovarian and increased liver weights relative to LC dams, but there was no treatment impact (P > 0.05) on spleen weight or progesterone. Also, obesity exacerbated the DMBA reduction (P < 0.05) in the number of primordial, secondary follicles, and corpora lutea. In lean mice, DMBA exposure altered abundance of 21 proteins; in obese dams, DMBA exposure affected 134 proteins while obesity alone altered 81 proteins in the maternal ovary. Thus, the maternal ovary is impacted by DMBA exposure and metabolic status influences the outcome.

Pore Morphology and Oxidation Behaviour of Deep-Loaded Granular Coal at High Initial Temperatures

ABSTRACT As coal mining proceeds deeper, fragmented coal is subjected to high geostress and elevated thermal environments, causing changes in its micro-physical properties and spontaneous combustion (SC) risks. Deep mining operations entail significant risks of coal fires. In order to investigate the effects of high stress and high thermal environments on the microstructural and physicochemical damage of fragmented coal, and to elucidate the mechanisms influencing oxidation behavior, we conducted experiments including low-temperature nitrogen adsorption, synchronous thermal analysis, and in-situ diffuse reflectance spectroscopy. These experiments aimed to explore the pore morphology and oxidation characteristics of high initial temperature unloading granular coal (HITU-GC) unloading conditions. The results indicate that with increasing initial temperature, characteristic point temperatures initially rise and then decrease, while both the mass loss and heat release during the low-temperature oxidation stage decrease. After pressure-unloading composite treatment, the oxidation process accelerates with more intense reactions, resulting in an overall increase in heat release. The pore shapes of HITU-GC show no significant difference compared to the original coal, mainly comprising non-rigid aggregates of micropores, platy or layered matrix particles, including numerous slit-shaped pores. The coal surface also exhibits ink bottle-shaped pores and cone-shaped pores. Higher pre-oxidation temperatures correlate with higher specific surface areas. Higher stress levels from pressurized unloading correlate with lower specific surface areas. The specific surface area of sample O60-P16 is reduced by 0.879 m2/g compared to sample O60-P0. Pressurized unloading treatment disrupts mesoporous pores. Following thermal environment and pressure-unloading, the coal’s aromatic hydrocarbon content decreases, while the contents of hydroxyl, aliphatic hydrocarbons, and oxygen-containing functional groups (FG) all increase. Sample O60-P4 shows the highest content of active FG. While thermal environments enhance coal oxidation activity, pressure-unloading treatment increases the extent of coal surface fragmentation. The synergistic effect of both significantly increases the SC risk of coal. This study provides a theoretical basis for controlling thermal hazards associated with high-initial-temperature unloading fragmented coal in deep goaf areas.

ANN-weighted Distance Grey Wolf Optimizer for NOx Emission Optimization in Coal Fired Boilers of a Thermal Power Plant

ANN-weighted Distance Grey Wolf Optimizer for NOx Emission Optimization in Coal Fired Boilers of a Thermal Power Plant

Comprehensive review of unmanned aerial vehicle application to safety mining management

The increasing interest of users in unmanned aerial vehicle (UAV) technology has developed new fields of application for it. Presently, UAVs are working in so many areas and the mining industry has shown grown interest in the use of UAVs for routine operations in surface, underground mines, and mine waste dumps. In this paper, a thorough review has been performed on the application of UAVs in mine safety management. Systematic reviews were conducted to summarize the results of over 60 papers published during the 2010-2021 period. The study offers a review of the most common applications involving mine safety, the styles of flying control, and the UAV types exploited. The paper also contributes to the identification of prevalent data acquired by sensors and points out the most popular processing techniques of aerial imagery. The obtained results revealed that UAVs are used at mining sites for safety purposes including mine surface displacements, stability monitoring, working environment, coal fire identification, drill and blast, and mine waste dump operations. This research hopes to provide a technical reference, expanding the knowledge and recognition of UAV monitoring to manage mine safety, as well as an assessment of applications in mining activities.

A Lab-Scale Experiment on the Spontaneous Combustion Behavior of Chronic Naturally–Oxidized Coal in Re-Mining Coal Mine

ABSTRACT Spontaneous combustion of coal in re-mining coal mine is a serious threat to the safety recovery of coal resources. In this paper, six coal samples, including two raw bituminous coal samples from the new mining working face and four oxidized bituminous coal samples from the re-mining working face, are selected. The pore structures, thermogravimetric properties, and spontaneous combustion characteristics of raw coal and oxidized coal are studied. The pore structures show that the surface of oxidized coals has more cracks and higher macropore volume and porosity as compared with raw coal. The thermogravimetric experiments demonstrate that the oxidized coal has a higher combustion rate and turns to the combustion reaction zone in advance. Moreover, the oxidized coals perform a better combustion property by showing a comprehensive combustion index of 6.7 × 10−9 min−2·°C−3 and 8.9 × 10−9 min−2·°C−3, higher than the raw coal of 4.0 × 10−9 min−2·°C−3. The spontaneous combustion characteristics show that the oxidized coal performs a greater rate of oxygen consumption and more oxidation products released than raw coal. The CPT of raw coal is higher than 157°C, while the CPT of oxidized coal is between 132°C and 140°C. The research results can provide a risk assessment method for coal spontaneous combustion in the re-mining coal mine, and provide guidance for avoiding the occurrence of coal fires.