Fire

The widespread use of mezzanine racks in modern logistics warehouses has significantly increased fire hazards owing to the dense storage of combustibles. However, systematic full-scale studies examining the influence of shelf spacing on radiative ignition between adjacent racks are lacking. In this study, we investigate the effect of shelf spacing on radiative flame spread using full-scale fire tests and cone calorimeter experiments. The decrease in radiative heat flux with an increase in the distance was consistent with the inverse square law. Adjacent shelf ignition was prevented when the spacing was at least 5 m. Cone calorimeter tests identified a critical radiant heat flux of approximately 8 kW/m², and the ignition time decreased nonlinearly from 207.8 to 69.6 s as the radiant flux increased from 10 to 16 kW/m². These findings were cross-validated with the full-scale results, which indicated that a minimum spacing of 5 m serves as a radiative flame-spread barrier under similar storage and ventilation conditions. This study provides practical guidance for the fire-safety design of mezzanine rack warehouses. The effects of storage geometry, surface reflectivity, ventilation, active protection systems, and varying storage densities may be considered in future work to ensure broader applicability. Full article

Pressed-in ventilation provides the possibility of implementing fire smoke control in tunnels during construction. In this study, the impact of the velocity at the air duct outlet, the heat release rate (HRR), and the tunnel geometry on the longitudinal temperature decay of the ceiling (ΔT) and smoke’s back-layering length (SBL) is investigated, using a reduced-scale experiment and the Fire Dynamics Simulator (FDS, version 6.7.6). The results indicate that an increase in the velocity at the air duct outlet and a decrease in the HRR lead to a reduction in the value of both ΔT and SBL in the main tunnel. Predictive models for the dimensionless longitudinal temperature decay of the ceiling and the dimensionless SBL are proposed. Near the fire source, the predicted SBL is relatively high due to thermal radiation. The research results provide valuable references for preventing tunnel fires during construction. Full article

This study investigates the impact of aging on the thermal runaway behavior of lithium-ion batteries. By combining external heating tests, cone calorimetry experiments, and numerical simulations, the thermal runaway characteristics of LFP and NMC batteries at different SOH levels (100%, 90%, 80%) were systematically evaluated. Experimental results show a non-monotonic effect of aging on thermal runaway: mildly aged batteries (90% SOH) exhibited the earliest TR trigger and highest risk due to unstable SEI film growth, while new batteries (100% SOH) released the most energy. Significant differences were observed between battery chemistries: LFP batteries displayed fluctuating temperature curves indicating a staged buffering mechanism, whereas NMC batteries had smooth heating but abrupt energy release. Cone calorimeter tests revealed that aged LFP batteries had multi-stage HRR curves, while NMC batteries showed consistent HRR profiles; mass loss data confirmed reduced active material consumption with aging. Numerical simulations integrating SEI decomposition and other reactions validated the impact of aging on internal processes. The study recommends prioritizing monitoring of moderately aged batteries, optimizing early-warning systems for NMC batteries, and preventing secondary explosions, providing support for safety assessments of aged batteries. Full article

The wildland fire management system is increasingly complex and uncertain, which challenges suppression actions and increases stress on an already strained system. Researchers and managers have called for the use of strategic, risk-informed decision making and decision support tools (DSTs) in wildfire management to manage complexity and mitigate uncertainty. This paper evaluated the use of an emerging wildfire DST, the Risk Management Assistance (RMA) dashboard, during the 2021 and 2022 wildfire seasons. We used a mixed-method approach, consisting of an online survey and in-depth interviews with fire managers. Our objectives were the following: (1) to determine what factors at multiple scales facilitated and frustrated the adoption of RMA; and (2) to identify actionable recommendations to facilitate uptake of RMA. We situate our findings within the diffusion of innovations literature and use-inspired research. Most respondents indicated RMA tools were easy to use, accurate, and relevant to decision-making processes. We found evidence that the tools were used throughout the fire management cycle. Previous experience with RMA and training in risk management, trust in models, leadership support, and perceptions of current and future fire risk affected RMA adoption. Recommendations to improve RMA included articulating how the tools integrate with existing wildland fire DSTs, new tools that consider dynamic forecasting of risk, and both formal and informal learning opportunities in the pre-season, during incidents, and in post-fire reviews. We conclude with research and management considerations to increase the use of RMA and other DSTs in support of safe, effective, and informed wildfire decision making. Full article

Against the backdrop of intensifying global climate change and human activities, the increasing frequency and evolution of major wildfire events pose severe challenges to global disaster prevention and mitigation systems. Systematically understanding their disaster characteristics, spatiotemporal patterns, and societal response efficacy is an urgent scientific requirement for formulating effective coping strategies. This study constructed a comprehensive database covering 137 major global wildfire events from 2018 to 2024, with data sourced from GFED, EM-DAT, and official national reports. Utilizing a synthesis of methods including descriptive statistics, spatiotemporal clustering analysis, K-means pattern recognition, and non-parametric tests, a multi-dimensional quantitative analysis was conducted on disaster characteristics, evolutionary trends, casualty patterns, and policy effectiveness. Despite potential reporting biases and heterogeneous data standards across countries, the analysis reveals the following: (1) All key wildfire metrics (e.g., burned area, casualties, evacuation scale) exhibited extreme right-skewed distributions, indicating that a minority of catastrophic events dominate the overall risk profile; (2) Global wildfire hotspots demonstrated dynamic expansion, spreading from traditional regions in North America and Australia to emerging areas such as Mediterranean Europe, Chile, and the Russian Far East, forming three significant spatiotemporal clusters; (3) Four distinct casualty patterns were identified: “High-Lethality”, “Large-Scale Evacuation”, “Routine-Control”, and “Ecological-Destruction”, revealing the differentiated formation mechanisms under various disaster scenarios; (4) A substantial gap of nearly 65 times in emergency evacuation efficiency—defined as the ratio of evacuated individuals to total casualties—was observed between developed and developing countries, highlighting a significant “development gap” in emergency management capabilities. This study finds evidence of increasing extremization, expansion, and polarization in global wildfire risk within the 2018–2024 event sample. The conclusions emphasize that future risk management must shift from addressing “normal” events to prioritizing preparedness for “catastrophic” scenarios and adopt refined strategies based on casualty patterns. Simultaneously, the international community needs to focus on bridging the emergency response capability gap between nations to collectively build a more resilient global wildfire governance system. Full article

This study investigates the effect of the flame tube convergent segment wall configuration on the performance of a High-Temperature-Rise (HTR) triple-swirler main combustor. Three configurations were evaluated: the Vitosinski principle (Scheme A), the equal velocity gradient criterion (Scheme B), and a novel convex-arc flow-facing method (Scheme C). Three-dimensional numerical simulations were conducted using validated RANS equations with the Realizable k-ε turbulence model and a non-premixed PDF combustion model. The results demonstrate that the proposed Scheme C, characterized by an inflection-free convex contour, successfully avoids the localized high-velocity region and achieves a more uniform flow field. A systematic comparison reveals that Scheme C achieves the highest outlet temperature distribution quality (lowest OTDF and RTDF), the highest combustion efficiency, and the lowest total pressure loss (TPL) in the convergent segment among the three designs. In conclusion, the comprehensive analysis confirms that the convex-arc design (Scheme C), by eliminating the geometric discontinuity of an inflection point, provides the best overall performance for the HTR combustor under takeoff conditions. Full article

Wildfires are a recurring dry-season hazard in northern Thailand, contributing to severe air pollution and trans-boundary haze. However, the region lacks the ground-based measurements necessary for monitoring Live Fuel Moisture Content (LFMC), a key variable influencing vegetation flammability. This study presents a preliminary framework for near-real-time (NRT) LFMC estimation using Sentinel-2 multispectral imagery. The system integrates normalized vegetation and moisture-related indices, including the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Infrared Index (NDII), and the Moisture Stress Index (MSI) with an NDVI-derived evapotranspiration fraction (ETf) within a heuristic modeling approach. The workflow includes cloud and shadow masking, weekly to biweekly compositing, and pixel-wise normalization to address the persistent cloud cover and heterogeneous land surfaces. Although currently unvalidated, the LFMC estimates capture the relative spatial and temporal variations in vegetation moisture across northern Thailand during the 2024 dry season (January–April). Evergreen forests maintained higher moisture levels, whereas deciduous forests and agricultural landscapes exhibited pronounced drying from January to March. Short-lag responses to rainfall suggest modest moisture recovery following precipitation, although the relationship is influenced by additional climatic and ecological factors not represented in the heuristic model. LFMC-derived moisture classes reflect broad seasonal dryness patterns but should not be interpreted as direct fire danger indicators. This study demonstrates the feasibility of generating regional LFMC indicators in a data-scarce tropical environment and outlines a clear pathway for future calibration and validation, including field sampling, statistical optimization, and benchmarking against global LFMC products. Until validated, the proposed NRT LFMC estimation product should be used to assess relative vegetation dryness and to support the refinement and development of future operational fire management tools, including early warnings, burn-permit regulation, and resource allocation. Full article

Lightning-ignited wildfires represent a dominant natural disturbance agent in the Greater Khingan Mountains of northeastern China; however, the relationship between their occurrence and lightning characteristics remains insufficiently quantified. This study analyzed cloud-to-ground (CG) lightning data (2019–2024) and 417 lightning-ignited wildfires (2019–2024) using a full-waveform lightning detection network and spatial matching based on the Minimum Distance Method. Lightning activity shows pronounced spatiotemporal clustering, with more than 93% of flashes occurring in summer and a diurnal peak at 15:00. About 74.6% of wildfires ignited within 1 km of a lightning strike, and the holdover time exhibited clear seasonality, peaking in August (≈317 h). Negative CG (−CG) flashes dominated ignition events (56.5% multiple-stroke, average multiplicity = 2.60), and igniting flashes were concentrated within the −10 to −30 kA peak-current range, suggesting a key threshold for ignition. Vegetation type strongly influenced ignition efficiency: cold temperate and temperate coniferous forests recorded the highest lightning and fire counts, while alpine grasslands and sedge meadows showed the highest lightning ignition efficiency (LIE). These findings clarify how lightning electrical properties and vegetation conditions jointly determine ignition probability and provide a scientific basis for improving lightning-ignited wildfire risk monitoring and early-warning systems in boreal forest regions. Full article

Fire incidents pose a significant threat to urban communities. However, the inherent vulnerability of old communities to fire incidents is often overlooked, resulting in a lack of targeted evaluation methods for old community fire resilience (OCFR). Therefore, this study aims to propose a comprehensive evaluation model to systematically measure the level of OCFR. Initially, an evaluation indicator system for the OCFR was developed based on the pressure–state–response (PSR) model and 4M (man, machine, media, management) theory. Subsequently, an integrated evaluation model combining the coefficient of variation (COV) and the fuzzy comprehensive evaluation (FCE) approach was established to ensure objective weighting and reliable assessment. Finally, the Community W in Xuzhou City of China was selected as a typical case, and data from 210 valid resident questionnaires were utilized to evaluate its OCFR and propose targeted improvement strategies. The key findings indicate that the ‘state’ dimension holds the largest weight, with the top-weighted indicators being OCFR210 (firefighting investment development), OCFR211 (disaster prevention education and publicity), and OCFR214 (emergency rescue organization and management). The OCFR score for Community W was 70.256, placing it in the ‘good’ level. Furthermore, sensitivity analysis revealed the robustness of the evaluation model for OCFR. This research not only introduces a novel evaluation model that expands the body of knowledge on fire resilience but also provides practical strategies to mitigate fire risks and enhance fire management in old communities, with the ultimate goal of reducing community fire incidents. Full article

To investigate the fire suppression effectiveness of perfluorohexanone in low-pressure environments, a self-built fire suppression experimental platform was utilized to analyze the influence of ambient pressure and heat release rate on its performance. The results demonstrate that under normal-pressure conditions, the extinguishing time increases with the heat release rate of the fire source, whereas under low-pressure conditions, the extinguishing time decreases as the heat release rate increases. Specifically, under normal pressure, the extinguishing times for Fire Pan A (10 cm × 10 cm × 10 cm), Fire Pan B (15 cm × 15 cm × 10 cm), and Fire Pan C (20 cm × 20 cm × 10 cm) were 5.03 s, 8.15 s, and 9.63 s, respectively. In contrast, under low pressure, the extinguishing times were significantly shorter, with reductions of 2.8 s, 6.59 s, and 8.45 s, respectively. In terms of temperature reduction, the flame temperature decreased by approximately 300 °C under normal pressure, while under low pressure, it decreased by only about 100 °C. The concentration of hydrogen fluoride (HF) produced after extinguishment was relatively low, indicating limited toxicity. The HF concentration under normal pressure was, on average, approximately 59.2% higher than that under low-pressure conditions. Based on parameters such as the mass of the extinguishing agent, temperature changes, and hydrogen fluoride content, a fire suppression effectiveness model was established. The results show that the weight coefficient for chemical inhibition intensity is as high as 38.81, significantly exceeding other factors, demonstrating that perfluorohexanone primarily relies on chemical inhibition to interrupt the combustion chain reaction. This conclusion provides an important theoretical basis for the design and optimization of fire suppression systems in low-pressure environments such as aviation and high-altitude areas. Full article

Wildfires are a major source of greenhouse gases (GHGs), particulate matter (PM), and atmospheric pollutants, exerting widespread impacts on air quality, human health, and global climate. To address knowledge gaps, this study conducts a literature review of GHG emissions from wildfires across diverse ecosystems and fire regimes. The analysis quantifies emission magnitudes and compositions, evaluates their influence on regional and global climate processes, and synthesizes trends and methodological advances. Results show that the burned area is the main determinant of total emissions, with CO₂ as a robust predictor for estimated CO and CH₄, reflecting coupled emission behavior under varying combustion conditions. The Modified Combustion Efficiency (MCE) demonstrates a stronger predictive capacity for the CO/CO₂ ratio than for CH₄/CO₂, suggesting that CO/CO₂ can be predicted from MCE. Complete combustion dominates most fire events, while incomplete combustion increases the release of CO, CH₄, N₂O, and PM, contributing to tropospheric ozone formation and enhanced radiative forcing. Exposure to PM_2.5 and ozone remains a major health concern in fire-affected regions. This review provides a quantitative synthesis linking combustion efficiency and GHG co-variability, offering insights to refine emission modeling and guide climate mitigation strategies. Full article

Car parks are a vital component of infrastructure in modern cities. However, fire in car park buildings may lead to significant structural damage and casualties, highlighting the urgent need for fast forecasting methods. Traditional simulation methods are computationally prohibitive for immediate decision-making during a fire incident. This study develops a unified deep learning architecture for a real-time prediction of both the temperature distribution and structural response in car park fires. A numerical database was established using FDS and Abaqus, considering key variables including fire size, fire location and load level. A deep learning model based on the convolutional neural network and long short-term memory networks was proposed. The model takes a 10 s history of gas temperatures from ceiling sensors and the applied load level as input to give predictions on the spatial temperature distribution at a 2 m height 3 min into the future and the vertical deflection of the slab edge for up to 5 h after fire ignition. The model achieved high accuracy, with R² values of 92% for temperature prediction and 95% for deflection prediction. This study provides a new approach for real-time fire and structural safety early warning. Full article

Prescribed fire is a critical land management practice in the Great Plains of North America, helping to maintain native rangelands and reduce wildfire risk. Barriers to prescribed fire practice remain due to concerns on potential fire escape and fire danger. A localized fire danger index can help address these concerns by providing clear, science-based guidance, encouraging safer and confident use of prescribed fire. Our goal is to support the development of a localized Grassland Fire Danger Index (GFDI) for prescribed fire management in the Great Plains. The specific objective of this study is to develop user-friendly sub-models for dead fuel moisture content (DFMC) and grass curing, which serve as components of the proposed GFDI. DFMC reflects short-term fuel moisture that affects ignition and fire spread, while grass curing represents seasonal drying that controls fuel availability. Both are critical for fire prediction and safe burns. Lower DFMC and higher grass curing levels are strongly associated with wildfire risks. Using Oklahoma Mesonet weather data, the DFMC sub-model improves the accuracy and sensitivity of existing models. The grass curing sub-model shows that 50% curing usually occurs around April 15–16, which matches the time for the most intensive prescribed fire activities in the region, indicating it as a safe and effective window for prescribed fire recognized by landowners. Our sub-models lay the foundation for development of GFDI in the region. Full article

This research employs an integrated experimental and numerical simulation approach to investigate how varying angles of continuous elbows in a “Z”-shaped pipeline affect the deflagration behavior of hydrogen-propane-air mixtures. Findings indicate that centrifugal forces acting on the flame front as it traverses an elbow cause a distinctive “tongue-shaped” propagation along the inner wall. A cavity that generates unburned gas near the outer wall. The volume of this cavity increases significantly with the Angle of the elbow. The flame propagation is regulated by it and presents three distinct stages: the initial development section within the straight pipe section, the disturbance section when entering the first elbow, and the subsequent suppression section under the action of the cavity. The more intense turbulent combustion occurs at the 90° bend, with the highest peak flame velocity. On the contrary, the 120° and 150° elbows suppress the spread of flames. In addition, the angle of the elbow has a significant effect on the second overpressure peak, which exhibits strong non-linear growth. The value at 150° is 2.7 times greater than that at 30°. This is mainly caused by the energy focusing effect of the reflected pressure wave in the cavity magnified by the large-angle elbow. These findings provide mechanism-level understanding for the safe design of complex hydrogen pipeline systems. Full article

Fire is a key driver of ecosystem dynamics under global change, and understanding its complex relationship with the climate system is crucial for regional wildfire risk management and the development of ecological adaptation strategies. The western United States is a critical region for studying fire–climate interactions due to its pronounced environmental gradients, diverse fire regimes, and high vulnerability to climate change, which together provide a robust natural laboratory for examining spatial variability in fire responses. Based on tree-ring fire-scar records systematically collected from five major ecoregions in the western United States via the International Tree-Ring Data Bank (ITRDB), this study reconstructed fire history sequences spanning 430–454 years. By integrating methods such as correlation analysis, random forest regression, superposed epoch analysis, and effect size assessment, we systematically revealed the spatial differentiation patterns of fire frequency and fire spatial extent across different ecoregions, quantified the relative contributions of key climatic drivers, and identified climatic anomaly characteristics during extreme fire years. The results indicate that: (1) there are significant differences in fire frequency between different ecological areas; (2) summer drought conditions (PDSI) are the most consistent and strongest driver of fire across all ecoregions, and ENSO (NINO3) also shows a widespread negative correlation; (3) random forest models indicate that the Sierra Nevada and Madrean Archipelago ecoregions are the most sensitive to multiple climatic factors, while fire in regions such as the Northern Rockies may be more regulated by non-climatic processes; (4) extreme fire years across all ecoregions are associated with significant negative PDSI anomalies with prominent effect sizes, confirming that severe drought is the dominant cross-regional precondition for extreme fire events. This study emphasizes the region-specific nature of fire–climate relationships and provides a scientific basis for developing differentiated, ecoregion-specific fire prediction models and prevention strategies. The methodological framework and findings offer valuable insights for fire regime studies in other global forest ecosystems facing similar climate challenges. Full article

Forest fires continue to pose a significant threat to public and personal safety. Detecting smoke in its early stages or when it is distant from the camera is challenging because it appears in only a small region of the captured images. This paper proposes a small-scale smoke detection algorithm called TCSN-YOLO to address these challenges. First, it introduces a novel feature fusion module called trident fusion (TF), which is innovatively designed and incorporated into the neck of the model. TF significantly enhances small target smoke recognition. Additionally, to obtain global contextual information with high computational efficiency, we propose a Cross Attention Mechanism (CAM). CAM captures diverse smoke features by assigning attention weights in both horizontal and vertical directions. Furthermore, we suggest using SoftPool to preserve more detailed information in the feature map. Normalized Wasserstein Distance (NWD) metric be embedded into the loss function of our detector to distinguish positive and negative samples under the same threshold. Finally, we evaluate the proposed model using AI For Humankind dataset and FlgLib dataset. The experimental results demonstrate that our method achieves 37.1% APs, 90.3% AP50, 40.4% AP50:95, 45.34 M Params and 170.5 G FLOPs. Full article

Type IV composite overwrapped pressure vessels—characterized by a polymer liner fully wrapped in fiber-reinforced polymer—are emerging as lightweight, corrosion-proof alternatives to traditional metal cylinders in fire safety applications. This paper presents a comprehensive review of Type IV high-pressure vessels used in portable fire extinguishers and self-contained breathing apparatus (SCBA) systems. We outline recent material innovations for both the non-metallic liners and composite shells, including multilayer liner designs (e.g., high-barrier polymers and nanocomposites) and advanced fiber/resin systems. Key manufacturing developments such as automated filament winding, resin infusion, and in-line non-destructive testing are discussed. Technical performance in fire applications is critically examined: current standards and certification requirements (EU and international), typical design pressures (e.g., 300 bar in SCBA) and safety factors, common failure modes (liner collapse, fiber rupture, etc.), inspection protocols, and a comparison with Type IV hydrogen storage cylinders. Market trends are also reviewed, highlighting the major manufacturers and the growing adoption of composite extinguishers (e.g., 20-year service-life composite units) versus conventional steel. The review draws on 7–10 peer-reviewed studies to analyze the state of the art, finding that Type IV vessels offer significant weight reduction (>30%) and corrosion resistance at the cost of more complex design and certification. In firefighting use, these cylinders demonstrably improve firefighter mobility and reduce maintenance, while meeting rigorous safety standards. Remaining challenges include further improving liner permeability barriers to prevent gas leakage or collapse, understanding long-term composite aging under cyclic loads, and optimizing fire resistance. Overall, Type IV composite pressure vessels represent a major innovation in fire suppression technology, enabling safer and more efficient extinguishing equipment. Future research and standardization efforts are recommended to fully realize their benefits in fire protection. Full article

The safe operation of hydrogen transmission pipeline stations is paramount for the widespread adoption of hydrogen energy. This study addresses the significant hazard of hydrogen leakage in high-pressure pipeline stations by employing numerical simulations to investigate the dispersion behavior under various conditions. It specifically focuses on the complex interplay between meteorological factors, operational parameters, and station layout. A key finding is that the structural configuration of obstacles—namely their height and distance from the leakage source—serves as the dominant mechanism controlling the evolution of the hazard radius, overshadowing the influence of traditional parameters like wind speed and leak diameter in obstructed environments. Based on this insight, a novel and robust predictive model for the dynamic hazard radius was developed using multiple regression analysis. The model accurately quantifies the impact of leakage duration, obstacle spacing, and obstacle height, achieving an excellent fit (R² = 0.9848) with a prediction error of less than 5% compared to simulation data. This study provides valuable insights for defining risk zones and supports the development of effective safety measures and emergency response strategies for hydrogen infrastructure, thereby contributing to the secure and sustainable deployment of hydrogen energy. Full article

Addressing the environmental challenges posed by traditional foam extinguishing agents containing persistent pollutants, the development of eco-friendly alternatives has become imperative. This study investigates the effect of xanthan gum (XG) on the fire extinguishing performance of PFH-BZ foam formulated with short-chain fluorocarbon surfactant. By analyzing foam formation, drainage characteristics, and suppression process, the underlying mechanism by which XG influences foam extinguishing performance was elucidated. The results indicate that XG exerts dual effects on foam properties. While its viscosity-increasing effect improves foam stability, excessive XG addition impairs foaming and spreading capabilities, reducing fuel surface coverage and smothering efficiency. Moreover, a high concentration of XG hinders drainage behavior, which in turn inhibits the formation of spreadable aqueous films, thereby reducing cooling and extinguishing efficiency. The PFH-BZ foam with 0.02 wt.% XG exhibits excellent foaming and spreading capabilities, enabling rapid coverage of fuel surfaces. Additionally, its moderate drainage characteristics facilitate spreadable aqueous film formation, achieving efficient cooling and smothering effects. The optimized PFH-BZ foam exhibits the shortest extinction time of 35.4 s, the lowest transient temperature rise of 60.8 °C, and the highest cooling rate of 16.8 °C/s. Environmental assessments reveal that the optimized PFH-BZ foam exhibits higher biodegradability than conventional foam. Full article