Fire, Volume 8, Issue 2 (February 2025) – 50 articles

This study investigates the latency of lightning-caused fires in the boreal coniferous forests of the Greater Khingan Mountains, employing advanced machine learning techniques to analyze the relationship between meteorological factors, lightning characteristics, and fire ignition and smoldering processes. Using the Random Forest Model (RFM) combined with Recursive Feature Elimination with Cross-Validation (RFECV) and SHapley Additive exPlanations (SHAP), the study identifies key factors influencing fire latency. Two methods, Min distance and Min latency, were used to determine ignition lightning, with the Min distance method proving more reliable. The results show that lightning-caused fires cluster spatially and peak temporally between May and July, aligning with lightning activity. The Fine Fuel Moisture Code (FFMC) and precipitation were identified as the most influential factors. This study underscores the importance of fuel moisture and weather conditions in determining latency of lightning-caused fire, offering valuable insights for enhancing early warning systems. Despite limitations in data resolution and the exclusion of topographic factors, this study advances our understanding of lightning-fire latency mechanisms and provides a foundation for more effective wildfire management strategies under climate change. Full article

The demand for renewable and environmentally friendly fuels has prompted the exploration of alternative energy sources to replace conventional fossil fuels. This work investigates the optimization of a ternary blend comprising cottonseed oil (CSO), neem oil (NO), and orange peel Oil (OPO) for improved combustion characteristics, enhanced performance, and reduced exhaust emissions. Biodiesels like Cotton Seed Oil Methyl Ester (CSOME), Neem Oil Methyl Ester (NOME), and Orange Peel Oil Methyl Ester (OPOME) were made from CSO, NO, and OPO, respectively. The experimental results show major improvements in thermal efficiency and reductions in key pollutants, including NOx, CO, HC, and smoke. The best blending ratios are determined through a methodical process that employs optimization tools such as Grey Relation Analysis (GRA) with the Taguchi Method and ANOVA for validation. Then, various proportions of these biodiesels were tested in a CRDI engine to optimize the ternary blend proportions. The addition of 10% CSO and 10% OPO to NO reduces NOx emissions by 10% at CR17 as compared to diesel. Brake thermal efficiency improved by 9.08%. HC emission decreased by 10%. Average smoke opacity decreased by 27.65%. Cylinder pressure remains unchanged, but the Net Heat Release rate increased by 2%. Optimum parameters obtained are G2B10 Blend, Load 100%, CR17 and 10% EGR. The findings underscore the potential of this ternary blend as a viable alternative to conventional diesel fuel, with GRA using Taguchi proving to be an effective optimization tool for Multi-Criteria Decision Making (MCDM). Full article

Brominated flame retardants (BFRs), including tetrabromobisphenol A (TBBPA) and dibromoneopentyl glycol (DBNPG), are present in both saturated and unsaturated polyester resins (UPRs). Given their toxicity, it is imperative to assess the content of this group of chemicals to ensure product safety and environmental sustainability, considering the paucity in the literature of analytical methods to evaluate them, particularly in solid matrices as UPRs. This study aimed to develop a fully automated gas chromatographic analysis of these BFRs, utilizing a flame ionization detector (FID), with prior derivatization of TBBPA and DBNPG with acetic anhydride. A chemometric evaluation was conducted for the derivatization step to enhance the yield of the procedure. The optimized method met the desired requirements for specificity, accuracy, and sensitivity, showing limits of detection (LOD) and quantitation (LOQ), respectively, of 1.1 µg/mL and 3.3 µg/mL for DBNPG and 3.6 µg/mL and 10.8 µg/mL for TBBPA. Other conventional detectors, i.e., an Electron Capture Detector (ECD) and a Mass Spectrometer (MS), were tested. The ECD showed a higher sensitivity than the FID and MS; however, its linearity proved to be more limited, making it unsuitable for higher concentration scenarios. The MS detector yielded results comparable with those of the FID, yet the latter is a cheaper and more sensitive alternative. Full article

A demand to replace an easily combustible wood with wood–plastic–rubber composite with better thermal performance than wood is at its peak globally. Wood-based composite materials in the form of wood–polymer composite (WPC) have emerged as new materials that can replace wood to produce wood products for various use. The use of recycled polymers as biodegradable polymer blended with fiber particles, waste tire powder, and other substances to manufacture new products known as wood–rubber–plastics composite (WRPC) for building construction and other different applications, has piqued the interest of numerous researchers. High flammability and weak combustibility parameters are a setback for many wood-based composites because of the flammability of these composites. Fabricated WRPC based on non-toxic fire retardants and other additives used to modify the flame-resistant quality of these composites, the fabrication techniques, and mechanical characteristics are herein reviewed. It is hoped that better composite in the form of WRPC can be used as building materials for informal and formal dwellings. Full article

This study systematically reviews the application of virtual reality (VR) in building evacuation scenarios in disaster contexts, highlighting its transformative potential to enhance preparedness, evacuation strategies, and safety training. Disasters such as fires, earthquakes, and multi-hazard emergencies pose significant challenges in densely populated urban environments, requiring innovative solutions beyond traditional methods. Analyzing 48 peer-reviewed studies (2014–2024) following PRISMA guidelines, this review focuses on VR applications in public buildings, transportation hubs, and high-risk workplaces, with VR simulations emerging as the predominant methodology. Key findings demonstrate VR’s ability to simulate realistic scenarios, improve spatial navigation, and optimize crowd dynamics and mobility accessibility. VR enhances evacuation efficiency and safety compliance by enabling adaptive training for diverse populations, including students, professionals, and vulnerable groups. In public and high-risk environments, VR addresses challenges such as visibility limitations, structural complexity, and the need for customized evacuation protocols. However, gaps remain in exploring multi-hazard environments and mixed-use spaces and ensuring scalability. Future research should integrate VR with artificial intelligence and machine learning for predictive and adaptive evacuation models. Expanding VR applications to underrepresented groups, including individuals with disabilities and the elderly, and collaborating with policymakers and urban planners are vital for translating research into practice. Overall, VR provides a scalable, adaptable, and inclusive solution for building evacuation preparedness, offering actionable insights to enhance resilience and safety in diverse architectural and disaster contexts. Its ability to transform evacuation strategies positions VR as a pivotal tool in advancing disaster management. Full article

Electric power transmission lines both cause and are impacted by wildfires and fuel breaks are crucial to mitigate wildfire hazard along and in conjunction with these infrastructures. Information about fuel dynamics is crucial for planning and maintaining fuel treatments, namely, to define their frequency. We sampled mechanically treated power line corridors representative of wide variation in climate, soil, and plant communities in Portugal and at different times since treatment. Non-destructive methods were used to assess ground cover and height per fuel stratum and the corresponding phytovolumes and fine fuel loads were calculated. Variability in fuel metrics was described by fitting logistic generalized linear models or linearized power functions based on time since disturbance and categorical variables for the effect of regeneration strategy, soil-richness structure, and climate. Time since treatment dominated fuel abundance and recovery was faster in communities of obligate resprouters in comparison with obligate or facultative seeders and in light- versus heavy-textured soils. No apparent effect of local climate was found given the short-lived impact of fuel treatments under the productive regional Mediterranean climate. The results provide a decision-making basis to refine the current treatment periodicity. Mechanical-treatment intervals of 3–5 years or 6–10 years are advised, respectively, for wildfire control and to minimize infrastructure damage. Full article

In crude oil storage tank fires, large amounts of firefighting water are used, which may trigger boilover. Variations in oil level affect ullage height, while firefighting water injection alters the water layer thickness, with both processes influencing boilover behavior. This study conducts boilover experiments with 3 types of crude oil to investigate the effects of ullage height and water layer thickness. The results show that the water-cooling effect delays boilover onset time, suppresses intensity, and reduces the mass burning rate, with Jidong crude showing the highest reduction (19.2%). However, the water-cooling effect has a limit, and its influence weakens when the water layer thickness exceeds 6 cm. Ullage height affects flame behavior. A moderate increase enhances combustion and shortens boilover onset time, while further increases cause self-extinction. The oil–water interface temperature varies nonlinearly between approximately 100 and 120 °C with changing ullage height. The variation trends of hot wave propagation rate with water layer thickness and ullage height are consistent with those of the burning rate, and correlation equations between them are established. Additionally, the study shows that light crude oil exhibits a later boilover onset with a longer duration and experiences 2~3 distinct boilover events, whereas high-viscosity Jidong crude oil undergoes a single short and intense boilover. Full article

This study analyzes the implementation of firefighting procedures and evacuation methods in a hospital environment, with a focus on ensuring rapid rescue operations and evacuation methods in a real fire in 2024. This research emphasizes the integration of firefighting technologies, including fire detection systems, real-time communication networks, and specialized evacuation strategies for immobile patients. This work further examines the optimization of the emergency response through the coordinated efforts of an integrated rescue system, emphasizing tactical decision making and resource allocation. The findings demonstrate the effectiveness of evacuation methods in the event of needing to evacuate a larger number of people, as well as meeting the need to ensure that active fire protection systems are in an operational state. This research provides key recommendations for improving fire protection measures in healthcare facilities, ensuring faster response times and increased patient protection. Subsequently, after evaluating and reviewing all the options, conclusions were drawn from the on-site results, and recommendations were defined for future fires in similar facilities. Full article

The microwave chemical looping synergistic gasification characteristics of municipal solid waste polypropylene plastic and the organic solid waste water hyacinth are experimentally investigated in this study. In addition, the characterizations of oxygen carriers before and after the reaction are combined to analyze the evolution of the microscopic morphology of oxygen carriers and the changes in the relative contents of each valence state of Fe and O elements. The results show that an increase in the water hyacinth mixing ratio presents positive effects on tar cracking and a slight negative effect on syngas yield. At the water hyacinth mixing ratio of 75%, the cold gas efficiency and carbon conversion can reach maximum values of 77.64% and 69.9%, respectively. The H₂ yield and H₂/CO ratio in syngas can be also improved to 0.34 Nm³/kg and 1.62, respectively. In addition, a minimum tar yield of 0.133 g/g (fuel) can be obtained at this mixing ratio. Moreover, the addition of water hyacinth has a continuous increase effect on monocyclic aromatic hydrocarbon (MAH) products of tar, and a continuous decrease effect on naphthalene and bicyclic aromatic hydrocarbons (NAH) products. This work explores the synergistic properties of organic waste plastics and agroforestry wastes during microwave chemical looping gasification, which is a useful exploration for solving the environmental problems caused by waste materials and agroforestry wastes as well as realizing the resourceful utilization of solid wastes. Full article

This study presents an experimental investigation into the effects of fire size on burning characteristics within well-confined military vehicle engine compartments. The research evaluates burning duration, self-extinguishing phenomena, heat release rates, pressure dynamics, and flame morphology using heptane pool fires of varying pan diameters (8 cm, 16 cm, and 24 cm). Key findings include the proportional relationship between fire size and heat release rate, with larger pans causing higher oxygen consumption, elevated pressure differences, and increased total heat flux. Self-extinguishment was observed for larger pans due to oxygen depletion, with extinction time linked to the ratio of compartment volume to heat release rate. Temperature measurements revealed significantly higher ceiling temperatures and heat flux levels for larger fires, emphasizing the structural and thermal risks. These results contribute to understanding fire behavior in confined spaces, offering practical implications for designing fire protection systems tailored to military vehicles. Full article

The ability of computer simulations to model airflows in a tunnel can significantly contribute to the effectiveness of fire safety precautions. This study examines two ways of modelling the Polana tunnel (Slovakia) and its influence on the airflow created via longitudinal ventilation using a fire dynamics simulator. The first class of studied models is based on the assumption that the airflow in the tunnel is influenced to a large extent by the supporting structures and other installations under the tunnel ceiling. Due to the resolution of the computational grid, the constructions are modelled using a system of cuboids distributed along the tunnel at regular distances. The second class of models combines this approach with the previous one, in which tunnel drag is modelled by increased roughness of the tunnel walls. Unlike the previous model, the roughness values are not constant but reflect the curvature of the tunnel walls. The simulations results are compared against on-site measurements during a full-scale ventilation test conducted in 2017 by a grid of five anemometers, as well as with the results of the previous model. The results agree well with the experimental data with relative errors below 2% for bulk velocities and with mean absolute percentage deviations of 3, 6, and 10% for velocities measured using individual grid anemometers for three ventilation modes. The new models achieve several improvements in accuracy compared to the previous one. Full article

Thermoplastic resins are indispensable materials in various applications, including automotive, electronics, packaging, and construction, owing to their superior mechanical strength, ease of processing, and versatility. However, their inherent flammability poses a significant challenge to fire safety, limiting their broader use in environments demanding stringent flame-retardant performance. MXenes, a newly emerging class of two-dimensional (2D) nanomaterials, have recently attracted significant attention for their application in flame-retardant polymer composites because of their multilayered structure and exceptional versatility. This review comprehensively explores the state-of-the-art advancements in flame-retardant thermoplastic resins, focusing on the use of MXenes and MXene-based materials to meet high-performance requirements, including mechanical strength, thermal stability, flame retardancy, electromagnetic interference (EMI) properties, and multifunctionality. Furthermore, the modification approaches of MXene-based flame retardants, the preparation of MXene-based thermoplastic resin composites, and the mechanisms of action for different matrices are also discussed in this review. Finally, this review discusses the challenges and potential developments for MXene-based thermoplastic composites, offering insights into the practical applications and growing demands for flame-retardant materials. Full article

This study examined atmospheric mechanisms affecting the East Bay Hills Fire (1991) in Oakland, California, using the Advanced Weather Research and Forecasting (WRF) model and North American Regional Reanalysis (NARR) dataset. High-resolution WRF simulations, initially at 16 km, were downscaled to 4 km and 1 km for analyzing primary and secondary circulations at synoptic and meso-α/meso-β scales, respectively, before the fire. Additionally, the interaction between the synoptic-scale and mesoscale environments was examined using backward trajectories derived from NARR data. The findings reveal that a strong pressure gradient created by a ridge over the Great Basin and a trough off the Pacific coast generated favorable meso-α conditions for the hot, dry northeasterly winds, known as “Diablo winds”, which initiated the wildfire in northern California. Mountain waves, enhanced by jet stream dynamics, contributed to sinking air on the Sierra Nevada’s western slopes. The main conclusion is that jet circulation did not directly transport warm, dry air to the fire but established a vertical atmospheric structure conducive to wave amplification and breaking and downward dry air fluxes leading to the necessary warm and dry low-level air for the fire. The hot–dry–windy (HDW) fire weather index further confirmed the highly favorable fire weather conditions. Full article

Wildfire is a key factor in regulating ecological processes in grassland ecosystems; however, changes in land use/cover have modified the intensity and frequency of fires as they occurred naturally. Different factors have caused a rise in woody vegetation in these ecosystems, leading to changes in species composition, diversity, and biogeochemical cycles. Prescribed burns are a tool for controlling and eradicating shrubs; however, their effectiveness depends on vegetation composition, biomass availability, and the objectives of restoration. We evaluated the effectiveness of fire as a shrub controller in a semi-arid grassland ecosystem. We measured several shrub dasometric parameters and the percentage of damage in ten 2000 m² plots three months after a prescribed burning was performed. Both crown height and width and total height were the main variables that explained the percentage of shrub damage by fire. Individuals with a height greater than 1.6 m and wide crowns did not suffer damage. Moreover, even though 97% of the total shrubs presented some fire damage, 86% recovered after the rain period. Our results show that fire could be an effective strategy to control early-growing shrubs, but on overgrazed arid lands it would be difficult to have enough biomass to implement burning programs. Full article

Seasonally dry mature and old-growth (MOG) forests in the western USA face increasing threats from catastrophic wildfire and drought due to historical fire exclusion and climate change. The Emerald Point forest at Lake Tahoe in the Sierra Nevada of California, one of the last remaining old-growth stands at lake level, is at high risk due to elevated fuels and tree densities. The stand supports huge trees and the highest tree diversity in the Lake Tahoe Basin and protects important raptor habitat. In this study, we simulate forest response to vegetation management and wildfire to assess the impacts of four fuel-reduction scenarios on fire behavior and stand resilience at Emerald Point. Results: Our results demonstrate that restorative forest management can greatly improve an MOG forest’s resistance to catastrophic fire. Thinning to the natural range of variation for density, basal area, and fuel loads, followed by a prescribed burn, was most effective at reducing large-tree mortality, maintaining basal area, and retaining live tree carbon post-wildfire, while reducing secondary impacts. Conclusions: Our findings highlight the value of proactive management in protecting old-growth forests in seasonally dry regions from severe fire events, while also enhancing their ecological integrity and biodiversity. Full article

Extinguishing methanol fires poses significant challenges due to methanol’s high toxicity, polarity, and fluidity. While conventional fire suppressants, such as alcohol-resistant firefighting foam, water mist and dry powders, can extinguish methanol fires, they fail to prevent the spread of liquid methanol, creating a risk of environmental contamination as the mixture of suppressants and methanol flows into surrounding soil and water resources. To address this issue, a novel kind of composite dry powder has been developed to effectively combat methanol pool fires. The powder can not only rapidly extinguish flames but also transform liquid methanol into gel-like substances, significantly reducing the hazards caused by the flow of harmful liquids. Laboratory experiments identify an optimal mass ratio of 0.16 between the composite powder and methanol to achieve complete flame extinction and liquid solidification. The superior performance of as-prepared composite powder could be mainly ascribed to the cooperation of metallic salts, polymers, and silica additives. Additionally, the powder is effective for extinguishing ethanol fires, making it a valuable tool for the emergency management of alcohol fires in leakage incidents. Full article

This study addresses the task of ecologically assessing the consequences of natural fires. Statistical data are presented on the carbon dioxide emissions in millions of tons and analytical data on the locations of peat fires, as well as modern methods of detection and control of peat and forest fires, divided into groups. An analysis of the works of leading Russian and international scientists and research organizations engaged in the search for methods of peat fire forecasting is also presented. Our aim was to develop a more effective method of preventing peat soil ignition by changing its physical and moisture characteristics. To that end, peat samples were selected in the Tver region. The laboratory equipment and the methodology of our experimental studies are described in detail, in which we simulated the natural climatic conditions in the center of the Russian Federation. This study provides a mathematical description of the process of spontaneous ignition, which occurs according to the following steps: a heat flow heats the surface to the ignition temperature, creating a self-heating zone; eventually, a wave of ignition (smoldering) capable of self-propagation is formed. We experimentally determined the spontaneous thermal ignition conditions in our experimental studies of the fire hazards of selected peat samples, where the test material was loaded in a cylindrical container made of brass net with a 0.8 mm mesh, of the dimensions 30 × 30 mm. Thermocouple elements were placed inside the container, fixing the temperature of the surface and the center of the sample, where the smoldering or ignition zone of the test material formed. We analyzed the results of our experimental studies on peat samples’ self-heating chemical reaction, leading us to draw conclusions about the possibility of fires on peat soil depending on its physical and chemical characteristics. We also offer recommendations that will improve peat soils’ fire safety, permitting agricultural crop production without a peat fire risk. Full article

An aircraft hangar is a special large-space environment containing a lot of combustible materials and high-value equipment. It is essential to quickly and accurately detect early-stage fires when they occur. In this study, experiments were conducted in a real aircraft hangar to simulate the occurrence of early-stage fires, and the collected images were classified, labeled, and organized to form the dataset used in this paper. The fire data in the dataset were categorized into two target classes: fire and smoke. This study proposes an aircraft hangar fire detection method that integrates an attention mechanism, which was based on the You Only Look Once Version 8 Nano (YOLOv8n) framework and further improved. Technically, the optimization of YOLOv8n was mainly carried out in two stages: Firstly, at the network structure level, the neck network of YOLOv8n was reconstructed using a large separable kernel attention (LSKA) module; secondly, in terms of loss function design, the original CIoU loss function was replaced with a dynamic focus-based Wise-IoU to enhance the detection performance of the model. This new algorithm is named LSKA-YOLOv8n+WIoU. Experimental results show that the LSKA-YOLOv8n+WIoU algorithm has superior fire detection performance compared to related state-of-the-art algorithms. Compared to the YOLOv8n model, the precision increased by 10% to 86.7%, the recall increased by 8.8% to 67.2%, and the mean average precision (mAP) increased by 5.9% to 69.5%. The parameter size was reduced by 0.5MB to 5.7MB. Through these improvements, the accuracy of flame and smoke detection was enhanced while reducing computational complexity, increasing computational efficiency, and effectively mitigating the phenomena of missed and false detections. This study contributes to enhancing the accuracy and speed of fire detection systems used in aircraft hangar environments, providing reliable support for early-stage aircraft hangar fire alarm work. Full article

The rapid expansion of the electric vehicle (EV) market has raised significant safety concerns, particularly regarding fires caused by the thermal runaway of lithium-ion batteries. To address this issue, this study investigates the real-time fire detection performance of segmentation-based object detection models for EVs. The evaluated models include YOLOv5-Seg, YOLOv8-Seg, YOLOv11-Seg, Mask R-CNN, and Cascade Mask R-CNN. Performance is analyzed using metrics such as precision, recall, F1-score, mAP50, and FPS. The experimental results reveal that the YOLO-based models outperform Mask R-CNN and Cascade Mask R-CNN across all evaluation metrics. In particular, YOLOv11-Seg demonstrates superior accuracy in delineating fire and smoke boundaries, achieving minimal false positives and high reliability under diverse fire scenarios. Additionally, its real-time processing speed of 136.99 FPS validates its capability for rapid detection and response, even in complex fire environments. Conversely, Mask R-CNN and Cascade Mask R-CNN exhibit suboptimal performance in terms of precision, recall, and FPS, limiting their applicability to real-time fire detection systems. This study establishes YOLO-based segmentation models, particularly the advanced YOLOv11-Seg, as highly effective EV fire detection and response systems. Full article

In cold regions, fire pipes are highly susceptible to freezing, which can obstruct water flow and lead to pipe ruptures. Accurately predicting the freeze thickness is crucial to maintaining the functionality of fire protection systems. Traditional methods for predicting fire pipe freezing often rely on simplified models or time-consuming simulations, which limits their accuracy in complex environments. A model for predicting the freeze thickness of fire pipes under low-temperature conditions was developed by integrating Computational Fluid Dynamics with an Artificial Neural Network (ANN). The CFD model was validated to generate data for training and optimizing an ANN based on collected experimental data. The CFD results demonstrate a nonlinear relationship between the freeze thickness of the fire pipe, ambient temperature, and time. Afterwards, the optimal ANN topology, determined through hyperparameter tuning, was found to consist of 12 neurons, the trainlm training function, and tansig–purelin activation functions. Eventually, the ANN model achieved high prediction accuracy with a mean squared error (MSE) of 6.62 × 10⁻⁴ on the test set and a regression coefficient R greater than 0.98 across all datasets. Furthermore, the ANN model agrees closely with the simulated data, not only for trained temperature conditions (−5 °C to −50 °C) but also for unseen temperature conditions (−55 °C and −60 °C), indicating excellent generalization performance. Full article

As the demand for high-performance polymers broadens, polyurethane (PU) polymers with various chemical modifications have attracted attention. This review explores the chemical structure and functional variations of PUs. PUs are used in a variety of fields, ranging from aerospace engineering to daily necessities, and show remarkable safety adaptability through designable synthesis processes. This study is divided into four main parts: (1) synthesis and structure, covering the synthesis of PU base and modification of additive compounds; (2) performance, studying physical properties and thermal degradation processes; (3) application, evaluating the commercial potential of PU polymers; and (4) flame retardancy, analyzing five established flame-retardant mechanisms. The last part discusses how PUs can meet sustainable development goals by replacing petroleum-based materials with green materials. By emphasizing non-petroleum resources and novel, sustainable modification strategies, this review conducts guidance for the safe and environmentally friendly application of PUs in the future. Full article

The paper presents a numerical analysis of the possibilities of replacing the aluminum serpentines in the current construction of battery thermal management systems (BTMS) with cooling serpentines made of fireproof composite materials with high heat transfer parameters (fireproof epoxy resin + nano boron nitride). This approach was given by the need to replace aluminum (which, in case of fire, maintains and accelerates the combustion process) with fireproof materials that reduce/eliminate the fire risk due to improper battery operation. Numerical analysis methods were used through simulation to identify the most efficient design among the single-channel, multichannel, multiflow and multiple coolant inlet–outlet solutions for cooling serpentine. In addition to these geometric constructive parameters, the variation of the coolant flow rate (9, 12, 15 and 18 L/min) and coolant inlet temperature (17, 20 and 25 °C) was also considered. The obtained results showed that the single-inlet nanocomposite resin cooling serpentine four-channel configuration presents the highest cooling efficiency of the cells that form the battery module while ensuring very good thermal uniformity as well. These findings are supported by the lowest average heat absorption by the batteries, of 34.44 kJ, as well as the lowest average internal resistance difference (caused by thermal gradients), of 5.23%. Future research is needed to identify the degree of structural resistance of serpentines made of fireproof composite material to external stresses (vibrations characteristic of the operation of electric vehicles). Full article

Fire detection presents considerable challenges due to the destructive and unpredictable characteristics of fires. These difficulties are amplified by the small size and low-resolution nature of fire and smoke targets in images captured from a distance, making it hard for models to extract relevant features. To address this, we introduce a novel method for small-target fire and smoke detection named YOLOv7scb. This approach incorporates two key improvements to the YOLOv7 framework: the use of space-to-depth convolution (SPD-Conv) and C3 modules, enhancing the model’s ability to extract features from small targets effectively. Additionally, a weighted bidirectional feature pyramid network (BiFPN) is integrated into the feature-extraction network to merge features across scales efficiently without increasing the model’s complexity. We also replace the conventional complete intersection over union (CIoU) loss function with Focal-CIoU, which reduces the degrees of freedom in the loss function and improves the model’s robustness. Given the limited size of the initial fire and smoke dataset, a transfer-learning strategy is applied during training. Experimental results demonstrate that our proposed model surpasses others in metrics such as precision and recall. Notably, it achieves a precision of 98.8% for small-target flame detection and 90.6% for small-target smoke detection. These findings underscore the model’s effectiveness and its broad potential for fire detection and mitigation applications. Full article

The frequent occurrence of forest fires in mountainous regions has posed severe threats to both the ecological environment and human activities. This study proposed a multi-target firefighting task planning method of forest fires by multiple UAVs (Unmanned Aerial Vehicles) integrating task allocation and path planning. The forest fire environment factors such high temperatures, dense smoke, and signal shielding zones were considered as the threats. The multi-UAVs task allocation and path planning model was established with the minimum of flight time, flight angle, altitude variance, and environmental threats. In this process, the study considers only the use of fire-extinguishing balls as the fire suppressant for the UAVs. The improved multi-population grey wolf optimization (MP–GWO) algorithm and non-Dominated sorting genetic algorithm II (NSGA-II) were designed to solve the path planning and task allocation models, respectively. Both algorithms were validated compared with traditional algorithms through simulation experiments, and the sensitivity analysis of different scenarios were conducted. Results from benchmark tests and case studies indicate that the improved MP–GWO algorithm outperforms the grey wolf optimizer (GWO), pelican optimizer (POA), Harris hawks optimizer (HHO), coyote optimizer (CPO), and particle swarm optimizer (PSO) in solving more complex optimization problems, providing better average results, greater stability, and effectively reducing flight time and path cost. At the same scenario and benchmark tests, the improved NSGA-II demonstrates advantages in both solution quality and coverage compared to the original algorithm. Sensitivity analysis revealed that with the increase in UAV speed, the flight time in the completion of firefighting mission decreases, but the average number of remaining fire-extinguishing balls per UAV initially decreases and then rises with a minimum of 1.9 at 35 km/h. The increase in UAV load capacity results in a higher average of remaining fire-extinguishing balls per UAV. For example, a 20% increase in UAV load capacity can reduce the number of UAVs from 11 to 9 to complete firefighting tasks. Additionally, as the number of fire points increases, both the required number of UAVs and the total remaining fire-extinguishing balls increase. Therefore, the results in the current study can offer an effective solution for multiple UAVs firefighting task planning in forest fire scenarios. Full article

By developing a conceptual framework that integrates the use of fire in agricultural activities, the occurrence of wildfires, and the perception of wildfire risk, this article examines the interplay among these three elements within both wet and dry Puna grasslands. The analysis focuses on two peasant and agropastoral communities, Vilcabamba and Apachaco, both located in the Cusco region—an area with the highest incidence of wildfires in Peru. This study highlights the sociocultural significance and persistence of agricultural burnings within Puna agropastoral communities and the necessity of considering changes in agricultural activity, mutual aid systems, and communal institutions—particularly regarding land ownership—to understand the factors contributing to wildfire occurrence. Furthermore, it reveals the widespread recognition of wildfire risk among community members, who are acutely aware of both the likelihood and potential severity of wildfire events, while governmental policies aimed at addressing this hazard predominantly focus on raising awareness and enforcing bans on agricultural burning, with limited consideration of these complex sociocultural dynamics. Full article

Forest fires pose a severe threat to ecological environments and the safety of human lives and property, making real-time forest fire monitoring crucial. This study addresses challenges in forest fire image object detection, including small fire targets, sparse smoke, and difficulties in feature extraction, by proposing TFNet, a Transformer-based multi-scale feature fusion detection network. TFNet integrates several components: SRModule, CG-MSFF Encoder, Decoder and Head, and WIOU Loss. The SRModule employs a multi-branch structure to learn diverse feature representations of forest fire images, utilizing 1 × 1 convolutions to generate redundant feature maps and enhance feature diversity. The CG-MSFF Encoder introduces a context-guided attention mechanism combined with adaptive feature fusion (AFF), enabling effective multi-scale feature fusion by reweighting features across layers and extracting both local and global representations. The Decoder and Head refine the output by iteratively optimizing target queries using self- and cross-attention, improving detection accuracy. Additionally, the WIOU Loss assigns varying weights to the IoU metric for predicted versus ground truth boxes, thereby balancing positive and negative samples and improving localization accuracy. Experimental results on two publicly available datasets, D-Fire and M4SFWD, demonstrate that TFNet outperforms comparative models in terms of precision, recall, F1-Score, mAP50, and mAP50–95. Specifically, on the D-Fire dataset, TFNet achieved metrics of 81.6% precision, 74.8% recall, an F1-Score of 78.1%, mAP50 of 81.2%, and mAP50–95 of 46.8%. On the M4SFWD dataset, these metrics improved to 86.6% precision, 83.3% recall, an F1-Score of 84.9%, mAP50 of 89.2%, and mAP50–95 of 52.2%. The proposed TFNet offers technical support for developing efficient and practical forest fire monitoring systems. Full article

This paper provides information about (a) 15 wildfire-related accidents that took place during 12 wildfires due to eruptive fire behavior in the 1982–2016 period and (b) six additional cases of “chimney effect” and “flame attachment” occurrence that caused no deaths or injuries, in the 2007–2019 period, in Greece. The work is based on (i) detailed documentation and reconstruction of wildfire behavior and spread, (ii) coupling of wildfire behavior with geospatial data and analysis, (iii) location information and field evidence for firefighter and citizen fatalities, and (iv) events surrounding those fatal accidents. These are matched with corresponding weather and fuel information, creating a rather complete picture of the conditions that entail a great risk to firefighters and citizens. The objectives of our effort are (a) to identify the common elements present in these cases and extract conclusions about the common denominators that may lead to fatal or near-fatal firefighter accidents, (b) to discuss how the findings compare with similar accidents in other countries, and (c) to develop clear messages for firefighters and citizens to help improve their safety. Full article

Solid recovered fuel (SRF) is highly suited for thermal treatment, but its low bulk density and other physical properties limit the number of compatible energy systems that can effectively process it. This study presents the findings on SRF energy utilisation, focusing on mechanical treatment and a novel approach to its small-scale co-combustion with certified softwood (SW) pellets and catalytic flue gas control. In this study, the processes of certified SRF feedstock characterisation and mechanical treatment were thoroughly examined. Unique SRF pellets of proper mechanical properties were experimentally prepared for real-scale experiments. Mechanical and chemical properties, such as mechanical resilience, toughness, moisture and heating value, were examined and compared with standard SW A1 class pellets. The prepared SRF pellets possessed an energy density of 30.5 MJ∙kg⁻¹, meeting the strict requirements from multiple perspectives. The influence of pelletisation temperature on pellet quality was investigated. It was found that increased resilience and a water content of 1.59% were achieved at a process temperature equal to 75 °C. Moreover, the moisture resilience was found to be significantly better (0.5 vs. 14.23%) compared with commercial SW pellets, while the hardness and durability values were reasonably similar: 40.7 vs. 45.2 kg and 98.74 vs. 98.99%, respectively. This study demonstrates that SRF pellets, with their improved mechanical and energy properties, are a viable alternative fuel, from a technical standpoint, which can be fully utilised in existing combustion units. Full article

A subway transfer station hall is crowded and complex in structure, which makes evacuation more difficult in case of a fire, but also provides more strategic options for smoke extraction. Full-scale experiments and numerical simulations are conducted to investigate the feasibility and performance of coordinated ventilation in a T-shaped transfer station hall, accounting for different fire source locations, ventilation modes, and fire shutter operations. It is found that the optimal ventilation strategy varies based on the fire location within the T-shaped configuration. For fires on the ‘T’s horizontal side, lateral airflow from longitudinal fans can effectively disrupt smoke spreading, with coordinated extraction strategies outperforming the traditional methods. However, for fires on the ‘T’s longitudinal side, horizontal fans are ineffective in controlling smoke flow, making the traditional fire shutter closure optimal. The idea of dispersing hot smoke to a reasonable degree can create better evacuation conditions for people near a fire, while creating almost no new danger zones. Full article

This paper presents investigations concerning the thermal firebrand reaction due to its accumulation in the top of ceramic roof tiles, commonly applied to the exterior of dwellings in southern Europe. A large-scale fire experiment is conducted, wherein firebrands are placed above the tiles and temperature readings are taken from multiple layers of the building components. The selection of materials for the roof layer assembly was based on recommendations for either fire resistance or high temperature behaviour. The test follows the fire setup recommended in the California Building Code for firebrand deposition. This investigation will allow for a more accurate verification of the firebrand reaction in the roof, including the type of ignition, the creation of smoke and droplets, and even their mechanical ability to withstand elevated temperatures. Full article