Fire, Volume 8, Issue 9 (September 2025) – 4 articles

To investigate the distribution law of gas migration in the gob area of a fully mechanized mining face, the similarity principle was employed, combined with Darcy’s law for porous media seepage, to derive the similarity criteria for simulating gas migration in the gob. An experimental platform for a similar model of the gob area in a fully mechanized mining face was designed and constructed, enabling the regulation of ventilation modes, working face airflow velocity, and gas release in the gob. By adjusting the layout of the tailgate, airflow velocity of the working face, and gas release rate, experimental studies were conducted on the gas flow, gas migration, and variation of gas concentration at the upper corner under different airflow velocities in “U ,” “U + I,” and “U + I” type ventilation modes. The results indicate that the ventilation mode determines the spatial variation law of airflow and gas migration in the gob; the airflow velocity of the working face governs the fluctuation degree and influence range of airflow and gas migration in the gob; and both the ventilation mode and airflow velocity affect gas accumulation at the upper corner. The “U + I” type ventilation mode is most effective in reducing gas concentration at the upper corner. Airflow velocities that are too low or too high are not conducive to gas emission at the upper corner, with the optimal control of gas concentration being achieved when the airflow velocity ranges from 1.5 to 2.5 m/s. The experimental results validate the distribution law of airflow and gas migration in the gob of a fully mechanized mining face, providing a basis for selecting ventilation process parameters for such mining operations. Full article

Fire is a disaster that seriously threatens people’s lives. Because fires occur suddenly and spread quickly, especially in densely populated places or areas where it is difficult to evacuate quickly, it often causes major property damage and seriously endangers personal safety. Therefore, it is necessary to detect the occurrence of fires accurately and promptly and issue early warnings. This study introduces YOLOv11-CHBG, a novel detection model designed to identify flames and smoke. On the basis of YOLOv11, the C3K2-HFERB module is used in the backbone part, the BiAdaGLSA module is proposed in the neck, the SEAM attention mechanism is added to the model detection head, and the proposed model is more lightweight, offering potential support for fire rescue efforts. The model developed in this study is shown by the experimental results to achieve an average precision (mAP@0.5) of 78.4% on the Dfire datasets, with a 30.8% reduction in parameters compared to YOLOv11. The model achieves a lightweight design, enhancing its significance for real-time fire and smoke detection, and it provides a research basis for detecting fires earlier, preventing the spread of fires and reducing the harm caused by fires. Full article

Burned area (BA) mapping and fire severity assessment are essential for understanding fire occurrence patterns, formulating post-fire restoration strategies and evaluating vegetation recovery processes. However, existing BA datasets are primarily derived from coarse-resolution satellite imagery and often lack sufficient consideration of fire severity. To address these limitations, this study utilized dense time-series Landsat imagery available on the Google Earth Engine, applying the qualityMosaic method to generate annual composites of minimum normalized burn ratio values. These composites imagery enabled the rapid identification of fire sample points, which were subsequently used to train a random forest classifier for estimating per-pixel burn probability. Pixels with a burned probability greater than 0.9 were selected as the core of the BA, and used as candidate seeds for region growing to further expand the core and extract complete BA. This two-stage extraction method effectively balances omission and commission errors. To avoid the repeated detection of unrecovered BA, this study developed distinct correction rules based on the differing post-fire recovery characteristics of forests and grasslands. The extracted BA were further categorized into four fire severity levels using the delta normalized burn ratio. In addition, we conducted a quantitative validation of the BA mapping accuracy based on Sentinel-2 data between 2015 and 2023. The results indicated that the BA mapping achieved an overall accuracy of 93.90%, with a Dice coefficient of 82.04%, and omission and commission error rates of 26.32% and 5.25%, respectively. The BA dataset generated in this study exhibited good spatiotemporal consistency with existing products, including MCD64A1, FireCCI51, and GABAM. The BA fluctuated significantly between 1985 and 2010, with the highest value recorded in 1987 (13,315 km²). The overall trend of BA showed a decline, with annual burned areas remaining below 2000 km² after 2010 and reaching a minimum of 92.8 km² in 2020. There was no significant temporal variation across different fire severity levels. The area of high-severity burns showed a positive correlation with the annual total BA. High-severity fire-prone zones were primarily concentrated in the northeastern, southeastern, and western parts of the study area, predominantly within grasslands and forest–grassland ecotone regions. Full article

Dust explosion prevention and mitigation of the consequences thereof require measurement of dust explosion parameters. Testing methods are defined by European and American standards, producing results in explosion chambers of a 1 m³ standard volume and, alternatively, 20 L. However, the results are influenced by some processes that are neglected by the standards, perhaps because it is believed that their effect is small in a 1 m³ chamber. But their effect becomes significant in a smaller 20 L chamber. Preconditioning of the system caused by dust dispersion itself, as well as the ignitor flame, is one such problem. The aim of this work is to further investigate the physical and chemical processes caused by dust preheating after an ignitor’s action. Analytical methods, such as STA, GC/MS and FTIR, were used to analyse the composition of the atmosphere after exposure of lycopodium dust, a natural material, to certain temperatures up to 550 °C in air and nitrogen. In the second step, gas samples were taken from the 20 L chamber after dispersion of lycopodium and ignition by two 5 kJ pyrotechnical ignitors. Depending on the temperature and atmosphere, various concentrations of CO, CO₂, H₂O, NO_x and organic compounds were measured. It was observed that the dispersed dust decomposed into mostly CO and CO₂ in the area near the ignitors, even in an atmosphere in which the oxygen concentration was lower than 2% by volume. The concentrations of other organic compounds were very low and included mostly methane, ethylene and acetaldehyde. However, when incorporating CO, the overall concentration of flammables was high enough to generate a hybrid mixture. Full article