Authors: Shihai Wang Zhonghui Li Qimiao Xie Zhangyu Chang Zuoqi Xu Jing Zhang
With the rapid growth of global waterborne tourism, the passenger capacity of ships continues to increase, which means passenger evacuation safety is becoming a critical concern. Existing passenger ship evacuation prediction methods mainly rely on computationally intensive evacuation simulations, which suffer from high computational cost. This limitation hinders rapid evacuation assessment and emergency decision-making for large passenger ships. The objective of this study is to develop a rapid and interpretable surrogate prediction model for passenger ship evacuation time. To achieve this objective, Sobol sequence sampling is employed to efficiently construct representative evacuation scenarios, while Bayesian optimization is used to improve the prediction performance of the Random Forest model. The results show that the Sobol sequence sampling method efficiently designs multi-scenario evacuation cases for the passenger ship. The optimized model achieves high prediction accuracy with an R2 of 0.901, effectively capturing the nonlinear relationship between evacuation factors and total evacuation time. Feature importance analysis demonstrates that stairways near the embarkation stations and passengers positioned farther away from them significantly affect total evacuation time, highlighting the spatial disparity in evacuation efficiency. This study provides a reliable data-driven approach and technical support for emergency decision-making and safety management in passenger ships.
]]>Authors: Charlotte Wierling Susanne Lott Alexander D. Gelner Simone Krüger Tim Rappsilber Tina Raspe Hans-Georg Schweiger
Internal combustion engine vehicles and electric vehicles share many similarities in the event of a vehicle fire but also differ in certain aspects. While both vehicle types release pollutants typical of vehicle fires, fires involving electric vehicles also emit battery-specific emissions. To investigate hazardous-substance exposure of emergency responders, two fire tests were carried out on identical electric vehicles. In each test, one battery cell was mechanically short-circuited, resulting in thermal runaway and propagation within the battery. Gas and time-resolved aerosol measurements, wipe samples, extinguishing agent samples, and urine samples were analyzed. A primary finding was the pronounced variability between the two fire events: despite comparable test conditions, the two vehicle fires exhibited markedly different development patterns, highlighting the inherent variability of electric vehicle fire behavior. Wipe samples showed increased metal concentrations after the tests, with maximum post-extinguishing surface concentrations of 7.4 mg/m2 nickel, 17.45 mg/m2 cobalt, and 14.25 mg/m2 lithium. Extinguishing agent samples showed increased concentrations of inorganic contaminants and polycyclic aromatic hydrocarbons. Urine samples showed no indication of a systematic increase in creatinine-adjusted metal concentrations among protected participants. Toxic gases were released immediately after cell short-circuiting, with hydrogen fluoride, hydrogen cyanide, and acetylene reaching approximately 500 ppm before visible flames occurred. Aerosol measurements identified transiently elevated particle number concentrations in the exterior near-field environment and, in one test, inside the passenger compartment, where a shift towards smaller particle diameters was observed. The findings demonstrate multiple responder-relevant exposure pathways and substantial variability in electric vehicle fire events.
]]>Authors: Fernando García-Fernández Jesús Domínguez Alberto Gil-Carrera Luis Tapia Adrián Regos
The Atlantic–Mediterranean ecotone of northwestern Iberia is one of the most fire-prone regions in Europe, yet post-fire avian dynamics there remain poorly documented. To characterise short- to mid-term post-fire avian trajectories in this ecotone, we combined a 16-year fire record with six consecutive breeding seasons of annual point-count surveys. Between 2020 and 2025, we recorded 13,770 individuals of 67 bird species across 210 fixed locations in a mountain protected area of NW Spain dominated by frequent small- to medium-sized wildfires. We contextualised trajectories against both contemporary unburned reference conditions and historical baselines representing contrasting fire regimes. Community-level species richness and total abundance converged rapidly toward reference levels within 3–5 years, whereas functional-group responses showed marked divergence: shrubland and open-habitat species consistently overshot unburned reference abundances, while forest-associated guilds showed persistent deficits—most pronounced among canopy foragers. Conservation value peaked during early post-fire stages and remained above reference levels for at least 9 years. This study provides the first integrated characterisation of post-fire avian trajectories at the species, functional-group, and community levels in this Atlantic–Mediterranean transitional system, offering an empirical baseline for future mechanistic research and evidence-based fire management in fire-prone landscapes.
]]>Authors: Phillip M. Stepanian Kiley L. Yeakel Adonis F. R. Leal Jhonys Moura Timothy A. Bonin Earle R. Williams
Past field experiments have demonstrated multiple cloud seeding techniques for modifying the electrical characteristics of developing thunderstorms with the purpose of reducing or eliminating lightning strikes. One motivation for these weather modification research programs was the prospect of preventing wildfires in inaccessible locations or particularly hazardous conditions by temporarily suppressing a prolific ignition source: lightning. It has been nearly 50 years since the last large-scale field effort in lightning suppression, and the ensuing five decades of technological innovation hold the promise of supporting this novel hazard mitigation approach. This study outlines observational and forecasting requirements, as well as an associated remote sensing architecture, that would support an operational wildfire prevention program based on lightning suppression by chaff seeding clouds. Two capabilities enabled by remote sensing observations are highlighted: (1) identifying potential regions of extreme wildfire behavior based on wildland fuels, topography, and weather, and (2) predicting regions where dry lightning strikes are probable. In combination, the proposed nowcasting system would predict the most likely areas of lightning-initiated wildfire danger. Dependent on land management strategies, surrounding infrastructure, firefighting capacity, and risk to human wellbeing, this information could be used to deploy lightning suppression technology to reduce or temporarily prevent wildfire ignitions in these high-risk situations.
]]>Authors: Zelong Xia Zhouxi Zhao Guofang Zhai Yifan Zhang
Clarifying the relationships between built environment characteristics and urban fire risk is important for developing effective fire prevention and planning strategies. However, spatial dependence and nonlinear relationships between the built environment and fire risk remain insufficiently understood. Accordingly, this study presents a geographically enhanced machine learning (GE-ML) framework that incorporates spatial adjacency into machine learning models through spatially weighted feature construction. Specifically, contiguity-based spatial weight matrices were used to derive spatially weighted features from 2D and 3D built environment variables. The Optimal Parameter-based Geographical Detector (OPGD) was applied to assess scale sensitivity and compare the explanatory power and interactions of the original and spatially weighted features. Six candidate models, including Ordinary Least Squares (OLS), K-Nearest Neighbors (KNN), Multilayer Perceptron (MLP), Random Forest (RF), Light Gradient Boosting Machine (LightGBM), and eXtreme Gradient Boosting (XGBoost), were then evaluated under different feature configurations, followed by SHapley Additive exPlanations (SHAP) analysis of the selected model. Results show that: (1) spatial weighting generally increased the explanatory power of major built environment factors and their interactions, with Queen contiguity yielding higher q-values than Rook contiguity; (2) spatially weighted features improved predictive performance across different models, and GE-XGBoost achieved the highest R2 (0.7067) and lower residual spatial autocorrelation than GWR and GWRF; and (3) 2D and 3D built environment features accounted for 59.55% and 40.45% of the total SHAP importance, respectively, with Geo-TPD, Geo-BVD, Geo-PS, and Geo-LUI identified as the most important features. SHAP analysis further revealed nonlinear relationships and interactions between these features and predicted fire risk. These findings highlight the value of incorporating spatial adjacency information into fire risk modeling and support spatially differentiated fire risk management.
]]>Authors: Yueqiao Yang Mingyuan Li Yuanhong Bi Zhixiang Yuan Liang Zhao Zewen Song Gege Gai
The increasing frequency of wildfires has made large-scale collective emergency evacuation increasingly critical. However, existing studies provide limited understanding of how information structures shape the interaction between individual risk perception and collective evacuation behavior. This study develops a collective evolutionary game-based evacuation framework under ambiguous and clear information conditions. Under ambiguous information, individual heterogeneity in risk sensitivity, mobility, and resource endowment is incorporated into social interaction payoffs. Under clear information, observable evacuation consequences, including travel time, risk exposure, and congestion effects derived from route-choice interactions, are incorporated into evacuation utility. Numerical simulations examine the evolutionary characteristics of collective evacuation behavior under different information conditions and population scales. The results show that social interactions play an important role in shaping evacuation decisions under ambiguous information, while congestion effects and route-choice interactions influence evacuation utility under large-scale demand. Sensitivity analyses further demonstrate that congestion representation affects evacuation utility across different population scales. These findings highlight the importance of considering information structure, individual heterogeneity, and collective interactions in evacuation modeling. Emergency management should therefore improve risk communication, evacuation capacity, and congestion mitigation strategies. This study provides theoretical insights into collective evacuation decision-making under heterogeneous information conditions.
]]>Authors: Chaoyun Mai Panrong Chen Haipeng He Hao Xie Chongyi Huang Tianlei Wang Zhiyuan Su Hongye Li
Early-stage flame and smoke in forest fire scenes are often small, weakly textured, and easily confused with complex backgrounds, while many accurate YOLO-based detectors are difficult to deploy on resource-constrained FPGA devices. This study proposes YOLO-FSD, a lightweight detector derived from YOLOv4-tiny for FPGA-oriented deployment. It integrates inverted residual and depthwise separable structures, a lightweight semantic enhancement (LSE) block at the deep feat2 feature, a lightweight P4 detection head, and a shallow detail compensation branch. On the combined test set of the D-Fire and New Fire and Smoke datasets, YOLO-FSD achieves a mean average precision at an intersection-over-union threshold of 0.5 (mAP50) of 69.36%, with 3.951 M parameters and 1.520 G multiply-accumulate operations (MACs). Compared with YOLOv4-tiny, mAP50 increases by 2.76 percentage points, while parameters and MACs decrease by 32.76% and 55.53%, respectively. For deployment validation, batch normalization (BN) fusion and 16-bit integer (INT16) parameter conversion are followed by fixed-point forward inference on a Xilinx Zynq-7020 FPGA, with a software-side parameter-quantization sensitivity analysis used as an intermediate check. FPGA raw output evaluation achieves 69.14% mAP50, only 0.22 percentage points below the PyTorch 32-bit floating-point (FP32) model, demonstrating the feasibility of FPGA-side forward inference.
]]>Authors: Junwei Shi Ziyan Zhang Ziming Xu
Lithium-ion battery energy storage stations are being rapidly deployed for peak regulation, renewable energy integration, and emergency power supply in power systems. Their fire risk is governed by interacting factors, including cell thermal runaway, equipment failure, operating environment, personnel behavior, management systems, and information systems, and is characterized by coupling, dynamic evolution, and confined-space fire spread. Existing static risk assessment methods cannot fully represent feedback among multiple risk factors or connect risk assessment results with the physical-field evolution of fires in energy storage compartments. This study develops an integrated grey relational analysis, system dynamics, and FDS framework. Personnel, equipment, environmental, management, and information risk factors are first established, and their weights are calculated using grey relational analysis. A system dynamics model is then used to analyze the temporal evolution of overall risk and subsystem risk responses. Finally, FDS is applied to simulate fire spread in a 30 ft containerized lithium-ion battery energy storage compartment under no-suppression and water-mist suppression conditions. The results show that the central fire-source region and battery module layer are key areas of gas-phase high-temperature accumulation and potential fire spread. In the no-suppression scenario, the high-temperature region remains localized near the fire source at 3.0 s, expands along the module layer from 30.0 to 50.0 s, and approaches a relatively stable distribution after 70.0 s. Under the investigated simulation conditions, water mist reduces near-source heating, weakens smoke-layer development, and slows spatial fire spread through evaporative cooling, reduced thermal radiation feedback, and disturbance of the hot smoke layer. These findings provide a methodological reference for fire risk assessment and fire suppression design in containerized battery energy storage stations.
]]>Authors: Tadeáš Zachara Vlastimil Borůvka Tomáš Kytka Benjamín Petržela Kryštof Kubista Přemysl Šedivka
Recycled cotton fibers offer a promising route for sustainable thermal insulation, but their flammability limits wider application. This study evaluated rigid recycled cotton insulation boards bonded with a polyvinyl acetate (PVAc)–starch system and modified with kraft lignin or aluminium trihydroxide (ATH) at dosages of 10 and 15 wt.%. Board density, thermal conductivity, volumetric heat capacity, thermal diffusivity, cone-calorimeter behavior, and ignitability under single-flame exposure were assessed. Thermal conductivity remained within a narrow range of 0.071–0.075 W·m−1·K−1, indicating that the basic insulation function was preserved despite formulation changes. Greater differences were observed in volumetric heat capacity and thermal diffusivity, particularly in lignin-modified boards at higher PVAc contents. Fire behavior was strongly formulation-dependent and showed no uniform dose-dependent response. The lowest peak heat release rate (pHRR) was obtained for the formulation containing 10 wt.% ATH and 20 wt.% PVAc, while the lowest total heat release (THR) was obtained for the formulation containing 10 wt.% ATH and 18 wt.% PVAc, reaching 170.31 kW·m−2 and 62.30 MJ·m−2, respectively. Lignin produced a less consistent effect on heat release. Under single-flame exposure, edge application was generally more critical than surface application, while ATH, particularly at 15 wt.%, provided the most consistent reduction in ignition and early flame spread. Overall, ATH was the more promising fire-modifying additive, although further formulation optimization and formal reaction-to-fire classification are required.
]]>Authors: Adrian Simion Florin Ioan Bode
The reaction-to-fire class printed on the Declaration of Performance of an External Thermal Insulation Composite System (ETICS) is often the only fire performance evidence available during early design. This paper reports, specimen by specimen, twenty-three Single Burning Item tests on nominally equivalent expanded-polystyrene ETICS, performed in one notified laboratory in two campaigns about two and a half years apart. A mineral silicate render on an inert substrate gave a fire growth rate index of 77.3 W/s; a complete ETICS with 100 mm of expanded polystyrene beneath an organically bound render gave 70.6 W/s, so that within the twenty-minute exposure, and while the rendering system retained its integrity, the assembly had a fire growth rate index comparable to, and slightly below, that of the render alone; because the two configurations differ in more than the presence of the core, this bounds the core contribution rather than isolating it. Coefficients of variation between nominally identical specimens ranged from 2% to 87%, and collapse and detachment carry no weight in the class. Individual specimens of one product spanned the B/C boundary, and one assembly was classified as s1 based on a mean of 0.4 m2, below the threshold, although two of its three specimens lay above it. In the later campaign, nominally equivalent assemblies gave mean indices that were 3.7 to 7.0 times higher, with lateral flame spread in seven out of eight tests. The campaigns fall under different editions of EN 13823: the measured burner output places any residual bias of the heat-release chain opposite to the observed change, while the revised smoke correction makes cross-campaign smoke comparison indicative only. The recovered specimen-level dataset, including the time-resolved records, accompanies this paper.
]]>Authors: Kaisen Yao Songhan Yang Yi Xing Ziwei Chen Hao Wang
This review critically evaluates glass-ceramics derived from aluminosilicate solid wastes through the linked framework of raw-material chemistry, the processing route, microstructure, thermal performance, and environmental safety. Waste-derived CaO–Al2O3–SiO2 (CAS) and CaO–MgO–Al2O3–SiO2 (CMAS) systems currently provide the most developed basis for dense and porous building products, whereas evidence for other compositional systems remains less mature. Across these materials, phase assemblage, residual-glass connectivity, crystallized pore-wall integrity, and pore structure jointly govern thermal stability, heat transfer, dimensional stability, cracking behavior, and mechanical-property retention after high-temperature treatment. Bulk crystallization and powder sintering are the principal demonstrated preparation routes, although their applicability depends strongly on waste composition, glass-forming ability, and processing windows. Future studies should integrate multi-source waste design, low-energy processing, standardized thermal and mechanical characterization, long-term leaching assessment, and life-cycle analysis to establish reliable performance and environmental boundaries for practical applications.
]]>Authors: Mingming He Zelin Sun Xin Ma Hao Huang Chao Ding Yufei Dai Zheng Wang
This paper presents a numerical investigation into full-scale double-opening compartment fires. It aims to reveal the underlying mechanisms by which the relative spatial layout of the fire source and openings influences neutral plane characteristics, flow field dynamics, and the allocation of spill plume heat release. The findings indicate that asymmetric boundary constraints in corner-door configurations cause the neutral plane to deform into an “S-shape.” The average neutral plane height decreases significantly as the total heat release rate increases. Moreover, the closer the fire source is located to the door, the more pronounced the descent of the neutral plane becomes. Furthermore, complex internal vortices and momentum losses induced by asymmetric layouts cause classical mass flow rate prediction formulas to overestimate actual values. By introducing a spatial structural factor to calibrate the discharge coefficient, the theoretical calculations of the inflow mass flow rates achieve a high degree of agreement with the simulation results, reducing the relative error to approximately 15%. The results also demonstrate that variations in door and window positions have limited influence on the overall spill-plume mass flow rate. However, different opening configurations modify the spatial aerodynamic characteristics of the flow field, thereby affecting the spatial distribution of external heat release. The incoming airflow from a centrally positioned door directs the fuel gases toward the window, whereas the wall-bounded vortex induced by a corner door entrains fuel to spill out from the door. Once the fire scale exceeds the critical indoor heat release rate, the compartment enters a ventilation-limited regime. This results in increased outward transport of unburned gases and an abrupt rise in the external heat release rate.
]]>Authors: Jady Damien Smith Anthony Power Francis E. Putz Sam Van Holsbeeck
Wildfire risks are increasing due to climate change, which poses a challenge to conventional firefighting strategies. In the wildland–urban interface (WUI), people and their infrastructure are increasingly vulnerable to fire. Strategic planting of low-flammable vegetation as green firebreaks has emerged to support wildfire management in the WUI. However, under extreme heat and drought, even low-flammability plants become fuel, contributing to fire spread and intensity. This paper presents a conceptual design framework for irrigated green firebreaks (iGFBs), which does not seek fine detail, or transferability, but rather it provides the initial concept for integrating vegetation design with supplemental irrigation to maintain fuel moisture and enhance fire-regulating ecosystem services. The framework is structured around landscape contexts, priority ecosystem services, integrated design solutions, and implementation considerations. A case study in Noosa Shire, Queensland, Australia, demonstrates how urban water reuse, including greywater and rainwater, can provide the needed irrigation in a WUI landscape. The iGFB concept highlights the potential to reduce fire intensity and slow fire spread while delivering co-benefits such as localised cooling and enhanced biodiversity. While the framework is site-responsive, its underlying principles are transferable to other WUI settings. Further research is required to evaluate the effectiveness of iGFBs under different fire and climate scenarios.
]]>Authors: Marek Kvet Jaroslav Janáček Michal Kvet David Mičulka
This scholarly article focuses on a specific application of discrete optimization methods in the emergency services. The search for the optimal deployment of service centers is one of the strategic decisions made in the field of urgent pre-hospital healthcare management. Since the consequences of the decisions are important for everyone and can directly affect the availability of the emergency medical service, different opinion groups are often taken into account when formulating a mathematical model. If there are two or more different conflicting objectives, the Pareto front of solutions usually needs to be constructed. It may serve as a good basis for finding the final system design. Since the construction of the exact Pareto set is very time-consuming and requires large computing resources, the efforts of many experts are focused on the development of efficient algorithms enabling the approximation of the original Pareto frontier in a short time. This paper introduces one of such heuristics. Even if the proposed algorithm of gradual refinement follows the idea of sequential processing of the current set of non-dominated solutions item by item inspecting the neighborhood of each element for possible extension of the Pareto front approximation, it can be simply adjusted and generalized making use of several parameters. Such an adjustment naturally raises the question of their optimal settings. Therefore, we gradually tried several procedures, from simple experimental verification of suitable values up to the development of sophisticated tuning of parameters based on machine learning methods. In this way, we created a complex advanced algorithm with elements of artificial intelligence. A series of numerical experiments are carried out utilizing real-world benchmarks that have their Pareto fronts applied in order to quantify and measure the efficacy of the proposed heuristic method.
]]>Authors: Wei Li Heng Zhang Hongwei Yang Zhibo Wang Xiuhua Wu
Anthropogenic fires in agro-pastoral ecotones are understudied. Using Ordos data (1987–2020) and machine learning, we identified fire drivers and patterns. Fires clustered in eastern populated areas, increased after 2000, and peaked recently, with April seasonality. Human-related ignitions dominated. Slope, humidity, and precipitation consistently drove burned area. Fires shifted to lower, drier, cooler conditions, suggesting possible advancing fire season and increasing human influence. Ecological restoration has been associated with increased fuel continuity, and the temporal coincidence suggests a potential restoration–fire paradox, although this hypothesis requires direct testing. Management should prioritize spring vigilance and fuel integration; better data on human behavior and fine fuels are needed for early warning.
]]>Authors: Fengju Shang Jiaqing Zhang Yi Guo Xiang Liu Liangpeng Ye
A lightweight inorganic sound-absorbing panel was developed using fly ash cenospheres, sintered ceramsite, and aluminum dihydrogen phosphate binder, with particular emphasis on heat-insulation performance under controlled furnace-heating conditions. A sequential formulation design was adopted to investigate the effects of ceramsite content, cenosphere particle size, and binder content. Normal-incidence sound absorption, TG/DTG behavior, thermophysical properties, unexposed-side temperature, and apparent flexural strength were experimentally evaluated, and a three-dimensional transient heat-transfer model was used for macroscopic thermal-response analysis. The A1–A3 cenosphere-based panels exhibited frequency-dependent sound absorption, with peak coefficients approaching 1.0 in the middle- and higher-frequency ranges. The A-series specimens retained more than approximately 98.7% of their mass after heating to 1000 °C. Finer cenospheres and lower binder contents generally reduced thermal conductivity and unexposed-side temperature. B9, containing 30–50 mesh cenospheres, 10 mass parts ceramsite, and 65 mass parts binder, exhibited the lowest measured thermal conductivity of 0.127 W/(m·K) and was identified as the preferred formulation in terms of heat-insulation performance. The apparent flexural strength increased with binder content and reached 2.605 MPa, revealing different effects of binder addition on mechanical and thermal performance. Numerical predictions reproduced the experimental unexposed-side temperature trends, with RMSE values of 4.80–9.66 °C for the representative formulations. The results demonstrated the combined sound-absorption, thermal-insulation, and mechanical characteristics of the developed cenosphere-based panels.
]]>Authors: Tang Tang Xinsheng Jiang Biao He Dongliang Zhou Run Li Keyu Lin Yunxiong Cai
Vision-based fire and smoke detection must be both accurate and lightweight for edge cameras and unmanned aerial vehicles (UAVs). Most lightweight fire detectors, however, are validated on a single dataset from a single run, which leaves the accuracy–efficiency trade-off and its external validity only partially examined. Rather than a new state of the art, we take an evaluation-centered stance and study two lightweight operating points of YOLO11n: an accuracy-first variant (LFS-YOLO11-A) that adopts the Wise-IoU (WIoU) loss at no extra parameters, and a lightweight variant (LFS-YOLO11-B) that further adds GhostConv. Both are evaluated on the public D-Fire dataset, retrained on a second dataset (DFS) over eight seeds, and profiled across GPU/CPU under PyTorch and ONNX Runtime. LFS-YOLO11-A matches the baseline on D-Fire (mAP@0.5 0.760 versus 0.758), while LFS-YOLO11-B reduces parameters by 12.4% and computation by 11%, both exceeding 160 FPS end-to-end (batch = 1) on a desktop-class GPU. On DFS, WIoU yields a small, exploratory +0.6-point improvement (nominal paired p = 0.037; seed-sensitive, with a confidence interval lower bound near zero), whereas an apparent +6.1-point gain from an early, uncontrolled run proved to be train/test contamination introduced before the data pipeline was frozen, not a genuine effect. Frozen-pipeline, multi-seed, two-benchmark evaluation is therefore necessary to separate genuine effects from the artifacts of uncontrolled single runs in lightweight fire and smoke detection.
]]>Authors: Xin Wang Hao He Jianxin Zhang Min Song
Reliable optical sensing of smoke and flames in high-rise buildings is challenging due to weak early cues, vertical smoke diffusion, facade occlusions, nighttime illumination, and fire-like urban interferences. We propose CDU-YOLO, a scene-aware real-time detection framework built upon YOLOv8n. Rather than relying on indiscriminate network scaling, task-oriented integration of existing modules is introduced: dynamic point-sampling (DySample) to preserve blurred boundaries of distant micro-targets, an enlarged receptive field (UniRepLKNet) to capture large-scale vertical propagation, and a dynamic bounding-box regression loss (WIoU) to handle occlusions. Experiments on a custom high-rise fire dataset and two public datasets demonstrate 94.9% mAP@0.5 and 56.7% mAP@0.5:0.95. In a dedicated flame-only size-stratified evaluation, CDU-YOLO improves AP@0.5 for small flames from 79.6% to 91.7% and reduces their miss rate from 25.2% to 11.3% relative to YOLOv8n. Under a unified desktop protocol (RTX 3080, PyTorch FP16, 640×640, batch size 1, no TensorRT), end-to-end throughput increases from 41 FPS to 55 FPS. A separate Jetson Orin NX deployment benchmark reaches 92 FPS using TensorRT FP16. The explicit introduction of an “others” category during training contributes to reducing false positive predictions against fire-like distractors. These results support the use of CDU-YOLO as a supplementary visual sensing component for early situational awareness. Nevertheless, residual misses on small and ultra-distant flames, continuous video-stream validation, and long-term field testing remain to be addressed before safety-critical online deployment.
]]>Authors: Yanan Zhu Dmitri A. Kalashnikov Jeff Lapierre Elizabeth DiGangi Jacquelyn Ringhausen
Understanding how lightning interacts with environmental conditions to ignite wildfires is key to improving fire risk assessments. While previous studies have explored the role of lightning characteristics and environmental conditions in fire ignition on regional scales, a comprehensive analysis across the contiguous United States (CONUS) is lacking. This study investigates the influence of both lightning characteristics and environmental conditions on lightning-ignited wildfires from 2016 to 2020 using high-resolution lightning, precipitation, meteorological, and land cover datasets. By matching over 25,000 lightning-ignited wildfires (LIWs) to nearby lightning events, we distinguish between fire-initiating (FL) and non-fire lightning (NFL) and analyze key variables including lightning peak current, flash multiplicity, precipitation, fuel moisture, vapor pressure deficit, and vegetation type. Results show that fire lightning tends to have lower multiplicity and slightly higher peak current, and occurs under drier atmospheric and fuel moisture environments. Precipitation accumulated over 1 h and 24 h prior to LIWs shows the largest effect-size difference between FL and NFL, followed by fuel moisture and energy release component. Among vegetation types, evergreen needleleaf forests and grasslands show the highest relative ignition efficiency. Regional analysis across National Climate Assessment regions reveals notable variation in the relative importance of these factors, with eastern regions showing stronger sensitivity to precipitation and fuel moisture compared to western regions. We also find that holdover fires, discovered more than 24 h after ignition, occur under wetter conditions compared to promptly detected fires. These findings highlight the dominant role of environmental conditions in lightning fire ignition and emphasize the need for region-specific fire management strategies.
]]>Authors: Ivan S. Yakovenko Alexey D. Kiverin
Ultra-lean hydrogen flames under terrestrial gravity are governed by a coupled interaction among preferential diffusion, thermal diffusion, heat loss, and self-induced convection. This study numerically examines combustion in a quiescent 6 vol.% H2–air mixture using detailed chemistry and a low–Mach–number formulation. A complete set of calculations was considered, with Soret diffusion and optically thin radiative heat loss independently enabled and disabled. One-dimensional spherical calculations were used to isolate the initial post-ignition flame kernel growth, while two-dimensional planar and axisymmetric simulations described its subsequent buoyant rise, deformation, and breakup. Over the analyzed interval, the spherical flame-front radius followed an extended Rf2≈Kt regime rather than constant-speed expansion. Soret diffusion increased the effective growth coefficient K, whereas radiation reduced it. The axisymmetric calculations reproduced the experimentally measured leading-point trajectory substantially better than the planar formulation. Soret diffusion produced larger, faster-rising kernels and maintained a more nearly circular upper cap, whereas radiation had a weaker effect on trajectory but increased relative lateral flattening. In all cases, a toroidal vortex stretched the flame segment and caused local extinction and fragmentation. Soret diffusion delayed breakup, while radiation advanced it; their combined effect on breakup time was nearly compensating. The results show that Soret transport and radiation primarily alter kernel growth and resistance to vortex-induced extinction, while the qualitative breakup pathway remains hydrodynamically controlled.
]]>Authors: Jun Ma Jing Fang Ya Ni Gaoming Du Yingjian Hu Yonggang Liu Shaokun Ge
Suspension cables and main cables (collectively referred to as cables) on both sides of suspension bridges are critical load-bearing components that determine overall structural stability. Cables are directly exposed to fires when burning vehicles stop in emergency or slow lanes, so investigating the temperature response of cables under vehicle-fire scenarios is essential for fire-resistant design of suspension bridge cables. For this purpose, a 1:4 scaled fire test platform was constructed based on a real suspension bridge in Guangzhou, China, that prohibits tanker access. Nine fire tests were conducted under 0–1.65 m/s crosswind, using gasoline and polyethylene plates as fuel to simulate 50 MW and 75 MW heavy-duty truck pool fires, with cable temperatures measured for fires occurring in different lanes. The results show that flame coverage increases with heat-release rate and first increases then decreases with wind speed at a turning point of 1.0 m/s. The most adverse scenario is a 75 MW truck fire in the emergency lane at 1.0 m/s wind speed, where the maximum height of 300 °C isotherm reaches 2.0 m in the test, corresponding to 8.0 m for the full-scale bridge. It is thus recommended that the fire protection coverage height for cables shall be no less than 8.0 m. This study provides valuable reference for cable temperature evolution analysis and fire protection strategy optimization for suspension bridges.
]]>Authors: Cem Kırlangıçoğlu Gökhan Coşkun Orhan Yalçınkaya Mehmet Fatih Döker
Subway tunnels exacerbate fire hazards, revealing a critical lacuna regarding the spatio-temporal coupling of fire progression and human egress. To address this, this study proposes and validates an Integrated Spatio-Temporal Risk Assessment Model to explicitly quantify survivability thresholds under complex fire dynamics. The framework synergizes Large-Eddy Simulation (LES) based Computational Fluid Dynamics with agent-based pedestrian trajectory modeling within a 3D tunnel featuring a 2% longitudinal gradient. Evaluating 9.5 MW and 12 MW fire energies, the model assessed Single-Sided Evacuation (SSE), Double-Sided Evacuation (DSE), and Sprinkler-Assisted Single-Sided Evacuation (SSE-S) across 2160 agents. Hazards were quantified by continuously resolving Fractional Effective Dose (FED) indices, 60 °C boundaries, and 500 ppm CO fronts. Simulations reveal the gradient induces a severe stack effect, accelerating toxic dispersion and yielding temperatures exceeding 1200 °C. Consequently, SSE engendered fatal bottlenecks (FED: 15.33), whereas DSE optimized pedestrian flux, capping peak FED at 0.52. Crucially, while active suppression (SSE-S) extinguished flames within 105 s, thermodynamic cooling induced a paradoxical loss of smoke buoyancy, causing toxic layers to stratify at the breathing zone. Ultimately, while DSE and SSE-S are paramount for survivability, water-based suppression generates localized toxicological risks, necessitating the integration of low-level smoke detection and extraction architectures in future subterranean designs.
]]>Authors: Jacob Smoot Randy A. Grant Abdullatif Alsulami Thomas J. LaRocca Julie A. Moreno Luke Montrose
Wildfire smoke (WFS) is an expanding source of fine particulate matter (PM2.5) with well-documented cardiopulmonary risks, yet its impact on organismal aging and functional decline remains incompletely understood. Here we use the nematode Caenorhabditis elegans to characterize the dose-dependent impacts of simulated WFS PM2.5 exposure (0.095–1000 µg/mL) on survival and age-associated functional outcomes. Locomotion and morphology were assessed at defined time points in adulthood, after which unexposed progeny of WFS-exposed nematodes were evaluated for identical tests to detect gross intergenerational effects. Parental (P0) worms subjected to a single 24 h WFS exposure exhibited dose-dependent reductions in lifespan at high concentrations and significant impairments in neuromuscular function at lower concentrations. A single P0 WFS exposure was also sufficient to induce deficits in multiple measures of locomotion and morphology, but these readouts were almost entirely resolved in F1 progeny. Additionally, RNA-sequencing on P0 nematodes was used to provide insight into biological processes underlying our in vivo observations, revealing WFS-associated aging-like transcriptomic signatures. Taken together, these results suggest that acute WFS exposure is sufficient to induce age-associated functional decline and establish C. elegans as a scalable, low-cost in vivo platform for quantifying WFS-driven toxicity.
]]>Authors: Jianqin Ma Qingsong Zhao Xuelei Xian
In the design of local application fire extinguishing systems, nozzles sometimes cannot be installed vertically due to space constraints and must be inclined. During inclined discharging, the discharge cone coverage pattern changes, and the high-concentration area shifts toward the front of the discharge direction, resulting in insufficient concentration at the rear of the fire source and compromising extinguishing effectiveness. Therefore, the nozzle aiming point must be offset toward the nozzle installation side. This discharge offset can compensate for the concentration deficiency at the rear of the discharge direction and ensure extinguishing effectiveness. This paper takes perfluorohexanone as the research object and, for the K100 swirl-core atomizing nozzle, conducts CFD numerical simulations and 70B pan fire full-scale extinguishing validation tests on discharge offsets at different inclination angles (90°, 75°, 60°, 45°). The research shows that the nozzle installation angle should not be less than 45°, and the offset increases as the angle decreases. The offsets of the K100 nozzle at 90°, 75°, 60°, and 45° are 0 mm, 66.34 mm, 101.34 mm, and 175.86 mm, corresponding to 0, 0.08R, 0.12R, and 0.22R (R is the protection radius), respectively. Compared with carbon dioxide standards, the offset required for perfluorohexanone is much smaller than that for carbon dioxide (approximately 1/2 to 1/3 of that of carbon dioxide at the same installation angle). A calculation formula for the offset based on the protection radius R is proposed, providing a design basis for precise nozzle positioning in local application systems under confined spaces or complex installation conditions. The generalizability of the proposed offset model is further validated through additional experiments using perfluoroheptanone, a high-boiling-point agent with similar physicochemical properties to perfluorohexanone.
]]>Authors: Zhenzhen Feng Anjian Yang Kun Qin Ran Ye Xiaojing Tian Fuquan Deng
Flue gas recirculation (FGR) is an effective technique for reducing thermal nitrogen oxide (NOx) emissions of gas turbines. However, variations in inlet oxygen concentration significantly alter the internal combustion characteristics of staged swirl combustors and induce combustion instability. To clarify the coupling mechanism between oxygen content and combustion stability under diverse operating conditions, three-dimensional numerical simulations are performed on a staged swirl combustor. The effects of oxygen mass fraction ranging from 11% to 23%, together with multiple operating parameters including inlet temperature, inlet velocity and operating pressure, on flame morphology, velocity fluctuation, heat release fluctuation and pressure fluctuation, are systematically investigated. The results show that increasing the inlet temperature optimises the uniformity of heat release, compensates for the combustion inhibition under low-oxygen conditions, and effectively improves combustion stability. Oxygen content exhibits a non-monotonic regulatory effect on combustion pulsation characteristics. Appropriate reduction of oxygen content narrows the high-temperature reaction zone and suppresses pressure fluctuations, thereby improving combustion stability, whereas a moderate low-oxygen condition of 17% aggravates velocity fluctuations and deteriorates combustion stability. Although elevated oxygen content enhances the overall heat release intensity, it increases the amplitude and dominant frequency of heat release fluctuations, which triggers combustion instability. Furthermore, high inlet velocity and high operating pressure amplify the disturbance of low-oxygen environments on the flame field and further degrade combustion stability. This study clarifies the competitive and coupling relationships among oxygen concentration, operating parameters and combustion dynamic characteristics, providing a theoretical basis for the stability optimisation and low-oxygen combustion regulation of gas turbine combustors with flue gas recirculation.
]]>Authors: César García-Hernández Laura Asión-Suñer Pedro Ubieto-Artur
Fire drills are considered very useful in different professional environments and public buildings, so they could also help to train citizens in domestic fire safety. According to the last available data, 172 deaths were reported during one year in the 19,411 domestic fires that occurred in Spain. Drills could be convenient in domestic fire safety training to reduce these fatal data. This pilot study, with 20 participants, explores the integration of smoke-diving drills in a safety training programme, developed at the Citizen School for Risk Prevention, in Zaragoza (Spain), to improve citizens’ knowledge and safe behaviour in domestic settings. A fire in a small apartment was simulated and, during this experimental smoke-diving drill, participants had to successfully escape in a limited time. This drill started in a room with zero visibility (very common in domestic fires) and (breathable, non-toxic) smoke, combined with high temperature. Due to the absence of light, two thermal cameras were used to record the participants’ behaviour. Two surveys, before and after the drill, were used to assess the acquired knowledge, in addition to the analysis of the thermal videos. Results revealed both positive and negative aspects of this experimental drill, thanks to the collaboration with professional firefighters, who participated as citizen scientists.
]]>Authors: Andrea Majlingova Ľudmila Tereňová Viktória Barna Iveta Mitterová Eva Mračková
The fire response of cross-laminated timber (CLT) sandwich wall assemblies depends on interactions among the structural core, lining, cavities and secondary timber members. This study examines the thermal roles of these layers under medium-scale radiant exposure. The thermogravimetric mass change, mass-loss rate and heat-flow response were obtained for CLT, Fermacell® gypsum–fiber board and timber stud specimens by simultaneous thermal analysis. One complete, artifact-free record per material group was selected for mechanistic comparison; the data were not used to characterize material variability statistically. The degradation intervals were compared qualitatively with temperatures, visual observations and post-test damage recorded during a 90 min exposure of the wall assembly at 20 kW/m2. Fermacell® retained 77.8% of its initial mass; CLT and stud specimens retained 22.5% and 20.8%, respectively. The largest mass loss of both wood-based materials occurred at 280–430 °C, with mass-loss-rate peaks at 372.1 °C for the CLT and 359.4 °C for the stud. The lining initially delayed heat transfer. After board cracking, cavity heating was followed by the degradation and glowing of the timber stud. Layer-specific thermal analysis supports the mechanistic interpretation of the tested assembly, but it neither predicts event timing nor replaces standardized fire resistance testing or classification.
]]>Authors: Lei Wang Daochun Huang Hao Wang Ling Liao Zhangquan Rao Enze Zhou Tianhao Peng
Wildfires near overhead transmission line corridors can cause localized conductor heating, thermal elongation, increased sag, and reduced ground clearance. However, traditional sag-calculation formulas and simplified equivalent-temperature methods have difficulty accurately representing wildfire-induced nonuniform temperature rise. To address this limitation, a fluid–thermal–stress multiphysics model was developed for an LGJ 300/40 ACSR conductor. A prescribed flame-temperature field and surrounding airflow were calculated using a CFD model to obtain the conductor’s nonuniform temperature distribution, which was then transferred to a structural finite-element model to determine thermal expansion and sag deformation. The effects of fire-source location were also investigated. The results show that nonuniform temperature rise leads to sag responses significantly different from those predicted using the three-section equivalent-temperature method. When the average conductor temperature reached approximately 130 °C, the maximum sag increased to about three times the cold-state value. Changing the fire-source location resulted in maximum differences of 73.3 °C in average conductor temperature and 37.1% in maximum sag. These quantitative relationships provide a practical reference for assessing conductor-to-ground clearance and evaluating wildfire-induced sag risk of overhead transmission lines.
]]>Authors: Yasin Sevinç Yaşar Selman Gültekin Tuğba Deniz
Forest fires increasingly challenge forest governance systems by exposing institutional coordination deficiencies, operational capacity gaps, and policy fragmentation. Although wildfire research has predominantly focused on forestry agencies, the contribution of internal security organizations to wildfire management remains underexplored. This study investigates the organizational barriers to effective forest fire combat from the perspective of Gendarmerie personnel in Türkiye using a Structural Equation Modelling framework. Survey data from 304 Gendarmerie personnel operating in wildfire-prone regions of Türkiye were analyzed using exploratory and confirmatory factor analyses within a structural equation modelling framework. The analysis identified two closely related dimensions of organizational wildfire-management capacity: Gendarmerie’s Operational Capacity and Gendarmerie’s Preventive Measures and Coordination. The findings suggest that operational capacity and preventive/coordination capacity should be understood as closely interconnected dimensions of organizational wildfire-management capacity. The structural model explains the importance of strengthening institutional capacity and collaborative governance within Türkiye’s wildfire management system. The findings support the implementation of integrated training programmes, enhanced technological infrastructure, standardized inter-agency coordination protocols, and preventive governance strategies to improve organizational preparedness and strengthen national wildfire resilience.
]]>Authors: Zhenguo Yan Yanping Wang Zhixin Qin
To characterise the coupled effects of smoke dispersion, temperature rise, ventilation-driven flow and pedestrian evacuation behaviour in indoor fires, this study develops a coupled fire-evacuation simulation framework based on the lattice Boltzmann method (LBM) and the social force model (SFM). A supermarket scenario is used as the computational domain, and the text-based map is discretised into a numerical grid. A three-dimensional D3Q19-LBM scheme is adopted to describe low-Mach-number indoor ventilation flow, with temperature transport, semi-Lagrangian smoke advection and diffusion, buoyancy forcing, supply-air and exhaust boundaries, and moving-pedestrian obstacle feedback incorporated into the solver. Pedestrian motion is guided by an exit-distance potential field and accounts for interactions between pedestrians, wall repulsion, local congestion correction and speed reduction induced by smoke and heat exposure. Visibility, temperature and toxic-dose indicators are further used to quantify the influence of the fire environment on evacuation safety. Evacuation time, exposure dose, hazardous-area ratio, smoke-exhaust efficiency and population outcomes are obtained for different initial population sizes. The proposed framework therefore represents fire-environment evolution and pedestrian response within a unified computational procedure and provides a reproducible numerical basis for indoor fire-evacuation safety assessment, ventilation and smoke-exhaust optimisation, and pedestrian risk analysis.
]]>Authors: Nina Dobrinkova Kadir Alperen Coskuner
Understanding wildfire dynamics and their climatic and topographic drivers is essential for effective fire management in Southeastern Europe. This study presents the first long-term assessment of wildfire trends across different land-cover types in Bulgaria, providing a methodological framework that is applicable across the wider Balkan region using the FireCCI51 burned area dataset (2001–2022). Burned area patterns were analyzed in relation to temperature, relative humidity, precipitation, the Ångström Index, Vapor Pressure Deficit (VPD), and topographic conditions. Burned area declined across most land-cover types, particularly croplands and forests. Croplands accounted for 96.4% of the total burned area (4.9 Mha), while forests, grasslands, shrublands, and wetlands represented 3.6%. Burned area was positively correlated with temperature (r = 0.37–0.53) and VPD (r = 0.40–0.53), and negatively with relative humidity (r = −0.48 to −0.55) and the Ångström Index, highlighting the importance of atmospheric dryness for wildfire activity. Seasonal climate-fire analyses further indicated that burned-area variability was more strongly associated with climatic conditions during the peak fire season than during the pre-fire season, particularly through lower relative humidity and higher vapor pressure deficit values. Topographic analysis revealed clear partitioning across land-cover classes. Cropland and wetland fires were concentrated in flat, low-elevation landscapes (mean altitudes ~117 m and ~40 m; slopes ~3.36% and ~2.04%), while forest and grassland fires occurred in higher, steeper terrain (mean altitudes ~351 m and ~315 m; slopes ~14.25% and ~9.76%). Shrubland occupied an intermediate niche (mean altitude ~287 m; slope ~9.43%), statistically overlapping with both forest and grassland categories, and acting as a transitional zone between lowland agricultural plains and mountainous ecosystems. Fire activity showed a clear seasonal pattern, with the highest burned areas occurring in August, coinciding with maximum VPD and minimum Angström index values. These results highlight the important role of atmospheric dryness and temperature variability in shaping wildfire activity in Bulgaria and demonstrate the usefulness of long-term satellite burned-area datasets for regional fire monitoring that can be applied not only in Bulgaria but also across the Balkan region.
]]>Authors: Kuracina Richard Kosár László Szabová Zuzana Weinmann Nina
The present study focuses on the experimental evaluation of the minimum ignition temperature (MIT) of dispersed dust in a Godbert–Greenwald furnace. The aim of this article is to assess the influence of dust container design on MIT determination. Two container configurations were evaluated: a standard dust container and a modified conical dust container. Experiments were carried out using various dust types, sample masses, and dispersion air pressures. The results indicate that container geometry has a significant effect on dust cloud homogeneity, combustion stability, and the measured MIT values. Difference between MIT values is up to 30–40 K. The conical container consistently produced lower and less variable MIT values (difference up to 110 K), suggesting a more efficient and reproducible formation of dust cloud. The difference of MIT in standard dust container is up to 220 K. The observed differences are discussed in relation to the dust cloud formation within the furnace.
]]>Authors: Xu Zhang Weihao Fan Qiheng Shi Wenbiao Wang
This paper proposes a post-training structured channel pruning scheme leveraging Gradient-Weighted Class Activation Mapping (Grad-CAM) for few-class fire detection under limited computational resources. After standard training, category-specific gradient signals extracted from the detection heads are used to generate channel-wise class activation maps over multi-scale feature layers, and fire and smoke responses are fused to rank channel importance. A layer-level retention quota is further applied to implement structured channel pruning, followed by lightweight fine-tuning. The pipeline does not require additional sparsity-inducing training. We validate the method on a self-established fire and smoke dataset containing 9041 images, using YOLOv5s, YOLOv5m, and YOLOv5l as baseline detectors. In workflow-level comparisons, the proposed method achieved higher mAP@0.5 than the implemented L1-based workflow at 40% and 60% pruning, but not at 80%. At 60% pruning, the pruned YOLOv5s model contained 2.158 M parameters and required 2.901 GFLOPs. These results indicate that Grad-CAM provides a useful class-aware criterion for channel importance and offers a promising model-compression strategy for resource-constrained fire detection, although physical edge-device performance remains to be evaluated.
]]>Authors: Yunlin Zhang Zhiyang Li
Forest fire impacts increasingly reflect coupled environmental and human influences, especially in mountain regions where terrain, vegetation, hydroclimate, and accessibility vary sharply over short distances. We examined the spatiotemporal heterogeneity of forest fire burn severity and its associations with environmental and anthropogenic predictors in Guizhou Province, Southwest China, using fire events from 2003 to 2016 and event-level mean relative differenced Normalized Burn Ratio (RdNBR). The study region supports a heterogeneous subtropical forest mosaic comprising evergreen broadleaved, mixed conifer–broadleaved, subalpine coniferous, and secondary deciduous broadleaved forests. Vegetation, topographic, meteorological, anthropogenic, and socioeconomic variables were integrated, and spatial autocorrelation analysis, nested linear models, random forest modeling, and quantile regression were used to identify consistent predictors and upper-tail responses. Burn severity was right-skewed, dominated by low- and moderate-severity events, with a distinct upper tail of high-severity fires. Interannual variation was not significant, whereas monthly differences were pronounced. Spatial clustering was evident, with hotspots concentrated mainly in central-western and southwestern Guizhou. Across modeling approaches, NDVI and elevation were the most consistent predictors, indicating that vegetation condition and mountain terrain provide the underlying template for burn severity. Meteorological and human-related variables showed weaker mean effects but stronger nonlinear, scale-dependent, and heterogeneous responses. Quantile regression further indicated that high-severity fires were not simply the upper end of average fire behavior, but reflected distinct upper-tail predictor responses. These findings show that severe fire impacts in mountainous subtropical regions are spatially uneven and shaped by coupled vegetation, terrain, weather, and human influences, supporting hotspot-oriented adaptation and risk reduction in regional human–environment systems.
]]>Authors: Suhaib M. Hayajneh Jamal Naser
Wildland–urban interface (WUI) fires expose buildings to complex thermal loads arising from radiation, convection, flame contact, and hot-gas impingement, and radiation-only assessment may be insufficient when wind-driven vegetation fires interact directly with façades. This issue is increasingly relevant in Australia, where cross-laminated timber (CLT) and other mass-timber systems are increasingly used, including in bushfire-prone regions. This study quantifies the thermal exposure of a simplified two-storey CLT building subjected to wind-driven Douglas Fir plantation fires using Fire Dynamics Simulator (FDS). A previously validated Douglas Fir vegetation-fire model was coupled with the building, and a one-factor-at-a-time parametric study varied fuel load, moisture content, building separation distance, terrain slope, wind velocity, and wind direction. The analysis considered heat release rate (HRR), gas temperature, CLT wall and glazing temperature, radiative, convective, net, and incident heat fluxes, adiabatic surface temperature, convective-to-radiative heat transfer ratio, and time-to-peak response. Fuel load and terrain slope produced the strongest increases in peak HRR, whereas moisture content reduced and delayed fire development. Increasing separation distance substantially reduced local exposure. Wind velocity and direction modified plume trajectory and façade heating, demonstrating that the highest HRR did not always correspond to the highest building temperature. Convective heating dominated over radiative heating at the monitored locations. The proposed physics-based framework integrates global fire behaviour with local thermal-response metrics and provides a basis for performance-based assessment of CLT buildings exposed to WUI fires, extending approaches that rely primarily on radiant heat exposure.
]]>Authors: Shukai Jiang Jianfeng Gao Xiao Wu Yulin Yang Meng Li
This study examines how pipe bends affect the explosion behavior of premixed air–light hydrocarbon mixtures. We aim to provide a basis for safer pipeline design and explosion risk reduction in industrial systems that include bends. We used a combined experimental and computational approach: high-fidelity explosion experiments together with large eddy simulation (LES). First, we conducted baseline tests in a straight pipe with premixed gases at different equivalence ratios to find the ratio that gives the highest peak explosion pressure. We then systematically varied the double-elbow configuration, testing seven complementary angle pairs: 30°/150°, 45°/135°, 60°/120°, 90°/90°, 120°/60°, 135°/45°, and 150°/30°. By tracking flame morphology, maximum overpressure, overpressure rise rate, and flame speed, we identified how bend geometry couples with explosion dynamics. The results show that bend angle strongly influences wall-induced compression, but the effect on peak overpressure is non-monotonic due to competing mechanisms: pressure wave reflection reinforces the flame at symmetric angles, while flow dissipation weakens it in highly asymmetric configurations. Peak overpressure reaches its highest value at the symmetric 90–90° arrangement, exceeding the straight-pipe baseline by 66%. However, the largest flame surface area and fastest propagation occur in configurations with large angle differences. The maximum pressure rise rate, by contrast, increases steadily with bend angle. Flame speed increases substantially in elbow configurations, driven by stronger turbulent mixing from flow separation and vortex shedding. The 150–30° and 90–90° configurations produce the highest speeds (~100 m/s), whereas the 30–150° arrangement yields a smaller enhancement due to weak initial turbulence. Downstream of the bend, flame morphology distorts significantly: both wrinkling intensity and total flame surface area grow with bend angle, which increases the reaction rate and overall explosion intensity. These findings offer quantitative guidance for optimizing explosion prevention, positioning ignition sources, and assessing risk in bent industrial piping.
]]>Authors: Luisa F. Escobar-Alvarado Lorenza B. Fontana Telmo Ernesto Meneses António Alessandra Vannucci
Fire regimes are changing globally, yet dominant fire governance remains centred on emergency response and suppression, often neglecting fire’s ecological functions and cultural significance. Although community-based burning practices persist across many fire-dependent landscapes, particularly in Africa, they rarely receive institutional recognition or appropriate governance. Integrated Fire Management and Community-Based Fire Management frameworks have called for bottom-up approaches that integrate biological, environmental, and social dimensions while prioritising local governance and customary fire practices. However, practical mechanisms for eliciting socio-cultural values, operationalising participation, and addressing power asymmetries in fire decision-making remain limited. This article documents the application of Legislative Theatre as a participatory approach to co-develop an Integrated Fire Management plan in eastern Angola. Through 37 stories based on lived experiences and collective, performance-based exercises exploring fire-related problems across seven villages, communities articulated diverse fire uses, values, and shared norms for improving local fire governance. Our findings show that theatre-based methods enabled the expression of embodied, emotional, and experiential knowledge often overlooked by conventional engagement approaches, while supporting knowledge co-production and participant agency. We argue that Legislative Theatre and storytelling provide practical tools for strengthening the socio-cultural dimensions of Integrated Fire Management, provided they are carefully facilitated, culturally adapted, and supported through long-term engagement.
]]>Authors: Runzhi Li Yuntao Liang
This study quantitatively investigates the effects of methane concentration and sealed/vented boundary conditions on the transient pressure, temperature, and propagation characteristics of methane–air explosions in a reduced-scale goaf-like enclosure. Experiments were conducted in a 0.5 m3 rectangular chamber at methane concentrations of 8%, 10%, and 12%, with pressure and temperature measured synchronously under sealed and vented boundary conditions. Numerical simulations were further performed to examine explosion-propagation characteristics. The sealed boundary condition produced substantially greater pressure and thermal accumulation within the chamber than the vented condition. The highest measured local pressure and temperature were 0.711 MPa and 552.46 °C, respectively, at 12% methane. The maximum pressure rise rates under the sealed condition were 3.00, 3.00, and 6.25 MPa/s at 8%, 10%, and 12% methane, respectively. Under the vented condition, the pressure and temperature responses exhibited a pronounced non-monotonic dependence on methane concentration, with the strongest measured response among the tested concentrations occurring at 10% methane, close to the stoichiometric composition. At this concentration, the highest measured local pressure and temperature reached 0.341 MPa and 373.05 °C, respectively, while the representative maximum pressure rise rate at P2 reached 5.70 MPa/s. Numerical results further indicate that venting reduces pressure and thermal accumulation within the chamber but can transfer high-temperature, high-velocity explosion products into the connected airway. These findings indicate that methane-explosion hazards in goaf–roadway systems should be evaluated by considering both peak loads and transient energy-transfer characteristics under different boundary conditions.
]]>Authors: Xiaozhe Gao Yuanqi Liu Kun Liu Chuang Liu Liantong Fu Yixiao Sun Jiaji Wang
Vented hydrogen explosions in ducts can transfer flame and pressure loads to external spaces, yet how internal obstructions regulate this external hazard remains insufficiently understood. Here, a three-dimensional FLACS model was used to examine hydrogen–air explosions with in-duct blockage ratios of 0–66.8%. Results show that the internal peak overpressure and flame propagation speed increased with increasing blockage ratio. At a blockage ratio of 66.8%, the internal peak overpressure exceeded 1.75 bar, more than twice that of the unobstructed case. In contrast, the external peak overpressure decreased markedly, with a reduction of approximately 79% at 66.8% blockage. The simulated results are consistent with stronger velocity shear and a less compact released hydrogen-cloud front at high blockage, which coincided with a weaker external second explosion. The findings support comparative hazard assessment of vented narrow hydrogen-handling spaces under the tested fuel-rich condition.
]]>Authors: Hao Xiao Yi Zheng Tao Yang Guangwen Zhang Chunyu Jiang Ming Ma Chun Wang Xiangdi Zhao
The behavior of petroleum pool fires has important implications for fire safety and environmental protection due to heat release, smoke generation, and pollutant emissions. In this study, controlled pool-fire experiments were conducted using representative petroleum fuels with multiple pan diameters to investigate the coupled effects of fuel properties and geometric scale on combustion behavior and emission characteristics. Key parameters, including the heat release rate, smoke production rate, mass loss rate, major gaseous emissions, and soot characteristics, were systematically measured. The results show that increasing pan diameter accelerated fire development, increased combustion intensity, and generally enhanced cumulative gaseous emissions. Compared with kerosene, gasoline exhibited more rapid combustion and higher smoke production, whereas kerosene produced a more sustained heat-release process and higher cumulative gaseous emissions. Correlation analysis, principal component analysis, and principal component regression revealed that fuel thermophysical properties and geometric scale are the dominant factors governing combustion behavior and pollutant formation. The proposed statistical framework provides a practical approach for quantitatively relating fuel properties to heat-release characteristics. These findings improve the understanding of the coupled effects of fuel composition and fire scale on petroleum pool-fire behavior and provide experimental support for fire hazard assessment and combustion modeling.
]]>Authors: Yiming Wang Yibao Wang
Public Fire Emergency Literacy (PFEL) is a critical determinant that fundamentally shapes individual survivability and the efficacy of societal safety governance—particularly amid intensifying fire risks characterized by growing complexity and destructive potential. Traditional single-perspective or linear analytical frameworks fail to capture PFEL’s multi-causal and configurational nature. To address this gap, this study integrates the Emergency Management Life Cycle Theory with the WSR system approach to measure PFEL across 36 major Chinese cities using 3872 survey responses and explores its multidimensional attributes and generative mechanisms via multiple methods (Delphi technique, entropy weighting, GIS spatial analysis, multiple regression, fsQCA). Key findings: (1) PFEL exhibits a pronounced cognition precedes capability gap with marked demographic heterogeneity; (2) PFEL displays a distinct “Central > Northeast > East > West” hierarchical gradient and notable spatial disequilibrium—core cities in the Central region (e.g., Wuhan and Zhengzhou) outperform traditional first-tier metropolises in the East; (3) physical infrastructure, organizational management, and individual cognition jointly shape PFEL with significant regional heterogeneity—participation in emergency training emerges as the most potent driver; (4) configurational path analysis indicates that PFEL is determined by a complex conjunctive causal mechanism formed by the combined effects of physical facilities, organizational management and individual initiative. Policy implications cover strengthened public emergency response capacity, differentiated policies, and multi-factor collaborative governance. The findings offer theoretical references and practical guidance for improving public resilience systems and emergency resource allocation.
]]>Authors: Xiyuan Chen Yujia Huang Pengxiang Wang Tingyu Zhang Baisong Qiao Jianzhong Yang
In the testing of aircraft cargo smoke detectors, surrogate smoke is often used in place of fire-generated smoke to avoid the hazards of live-fire experiments. Reproducing the time-varying concentration profile of real fire smoke requires feedback control of the surrogate smoke concentration. Two obstacles arise: the turbulent smoke flow is difficult to model accurately, and the distance between the generator and detector introduces a substantial control-loop delay. This study proposes a smoke simulation method based on model-free adaptive predictive control (MFAPC). The MFAPC scheme was tested in a full-scale aircraft cargo compartment simulator, where it drove the surrogate smoke concentration to track the profile recorded from a real cargo fire. Particle image velocimetry (PIV) was used concurrently with concentration control to capture the corresponding smoke velocity field. Across all conditions, MFAPC reduced the root-mean-square error by up to 38% compared with model-free adaptive control alone. With a control-loop delay longer than 10 s, the light transmission deviation remained within 2% of the target. The PIV data show that the controlled surrogate smoke velocity field reproduces the dominant structures and evolution patterns of actual fire-generated smoke, providing fluid-mechanistic evidence that a recreated dynamic smoke environment is physically meaningful.
]]>Authors: Xinrong Du Zhicheng Yang Qiang Zeng
Coal fires are a significant source of greenhouse gas emissions and ecological pollutants, yet their emission characteristics and carbon accounting remain poorly constrained. To reveal the pollutant generation characteristics and carbon emission levels of the typical underground coal fire area in Sulabulak, Xinjiang, this study integrated laboratory simulation, multi-source remote sensing inversion, and in situ field monitoring. Thermogravimetric analysis, a high-temperature tube furnace, HSC thermodynamic simulation, and multi-source remote sensing data from Landsat-8/9 and Sentinel-1A were employed to investigate the gaseous products and heavy metal migration mechanisms at different combustion stages, and to delineate the spatial extent of different combustion states in the fire area. A coal loss model was then constructed by coupling experimentally determined carbon emission factors with remote sensing-derived areas and was compared with an emission flux model based on field measurements. The results show that the coal oxidation process proceeds through three distinct stages, with indicator gas ratios (CO2/CO and C2H4/C2H6) serving as effective indicators for combustion state identification. Heavy metal partitioning is governed by elemental volatility and redox conditions: As and Se partition predominantly into the gas phase, while Zn becomes enriched in fly ash. Remote sensing time series analysis documents continuous fire expansion accompanied by progressive surface subsidence. By cross-validating the indirect coal loss model (constrained by remote sensing area) against the direct emission flux model (constrained by field measurements), we estimate the current annual GHG emission of the Sulabulak fire area at approximately 0.65 × 104 t CO2 equivalent. This study proposes a coupled “micro-experiment–macro-remote sensing–field measurement” approach for carbon emission accounting, providing reliable data support for environmental pollution control and the development of carbon inventories for coal fires in arid regions.
]]>Authors: Cunfeng Zhang Hongyong Yuan Jinbin Yuan Longxian Guo Guoguan Lan Wanki Chow
Lithium-ion battery-powered (LIB-powered) electric bicycles (E-bicycles) are widely used in China, with many accidental fires occurring in parking facilities in high-rise buildings. E-bicycle parking areas in high-rise buildings have become fire-prone zones. There is an urgent need to establish fire codes for the parking facilities in high-rise buildings. However, only limited research has been conducted on protecting against such fires. Uncertainties also remain about appropriate methods for fire barriers and fire suppression in parking facilities. To better understand parking facility fires in high-rise buildings, four fire scenarios and a total of six experiments on LIB-powered E-bicycle fires were studied in this paper, aiming to seek principles on how to prevent serious fire accidents by isolating E-bicycles parked in parking facilities. Fire spread between the LIB-powered E-bicycles and the propagation patterns of smoke generated by E-bicycle fires within parking facilities were studied. The effectiveness of different fire extinguishing methods in suppressing LIB-powered E-bicycles fires was discussed. The reasonable fire separation distance for E-bicycles was determined. It was found that LIBs with ternary lithium-ion batteries (such as nickel-cobalt-manganese) are more prone to initiate thermal runaway. Setting appropriate separation distances could effectively minimize the spreading of E-bicycle fires in high-rise buildings. A sprinkler system with a lower hazard class is proposed to operate under lower water pressure and flow rates. Fire control methods were proposed, including fire-resistive eave and fire barrier. The results can be used in setting up fire code.
]]>Authors: Bensheng Yun Jie Shen Zhenyu Lin Xinhe Yang
Early and reliable fire and smoke detection is essential for forest-fire warning and emergency response, especially in UAV-view and complex-background imagery, where small fire spots and diffuse smoke are easily affected by illumination variations and visually similar high-brightness or cloud- and fog-like backgrounds. To address these challenges, this paper formulates early fire and smoke recognition as a bounding-box detection task and proposes a Detail–Scale–Context Detection Network, named DSC-Det. DSC-Det is designed as a lightweight one-stage detection network and introduces three task-oriented components: a Detail–Context Downsampling Module (DCDM) for reducing information loss during early feature compression, a Dynamic Dual-Branch Fusion Module (DDFM) for adaptive multi-scale feature interaction under complex backgrounds, and a Shared-Regression Asymmetric Classification Head (SACH) for improving classification adaptation across feature layers while maintaining shared regression. Experiments on a constructed forest-fire-oriented fire and smoke dataset for UAV-view and complex-background monitoring scenes show that DSC-Det achieves 90.1% mAP@0.5 and 66.9% mAP@0.5:0.95, outperforming the lightweight reference detector by 2.3% and 4.4%, respectively. The results demonstrate that DSC-Det improves early forest-fire and smoke detection with controlled model complexity.
]]>Authors: Luan Zang Mingzhou Liu Hongyan Zhu Yangyi Wu Changchun Xu Haifeng Liu
Methanol compression-ignition engines are vital for transport carbon neutrality, yet methanol’s low cetane number, corrosivity, low viscosity, and cavitation tendency compromised piezoelectric injector reliability. This study proposed systematic optimization strategies tailored to methanol’s fuel properties. A sealed thin-walled metal encapsulation, fabricated from precipitation-hardening martensitic stainless steel, was designed to isolate corrosive methanol media. The geometry of the tubular spring was optimized to meet the stiffness requirements for high-frequency injections. A monolithic nozzle without side pin holes, also upgraded to the same precipitation-hardening martensitic stainless steel, effectively suppressed stress corrosion cracking by leveraging the material’s combined high strength and excellent corrosion resistance. A dedicated return-line backpressure valve compensated for hydraulic leakage and improved fuel replenishment, and nozzle hole taper and inlet fillet radius were optimized to mitigate cavitation. Cold-motoring reliability tests showed the optimized injector maintained flow deviation within 3% after 100 million cycles, whereas the unoptimized prototype reached 8% deviation at 60 million cycles. The single-cycle injected fuel quantity coefficient of variation dropped from 4% to 1.3%. Spray characteristic comparison tests further confirmed that the optimized injector maintained stable flow consistency and atomization quality after prolonged cyclic operation. These optimizations effectively resolved corrosion, wear, and hydraulic instability caused by methanol, significantly enhancing flow consistency and durability over the service life. The results provided critical component-level technical support for advancing methanol compression-ignition engines from laboratory research to industrial application, addressing key reliability barriers that previously hindered engineering deployment of methanol-fueled powertrains.
]]>Authors: Xin Xu Guoqing Zhu Min Peng Chao Zhu Zhen Hu Yumeng Wang
High-temperature smoke remains a primary threat in tunnel fire safety. The curved walls of small-radius Urban Traffic Link Tunnels (UTLTs) significantly alter smoke flow patterns and temperature distribution. Furthermore, no quantitative model exists to assess the impact of transverse fire location variation on temperature distribution in small-radius UTLTs. To address this gap, this study integrates experimental and numerical methods to specifically investigate the influence of curvature radius and transverse fire location on ceiling temperature distribution. Key findings demonstrate: (1) Wall-adjacent fires exhibit substantially higher temperatures than non-adjacent scenarios, resulting from restricted air entrainment (increasing flame height) combined with wall thermal constraint effects. (2) Competition between centrifugal and inertial forces consistently produces a higher maximum temperature rise beneath the convex ceiling versus the concave side in curved sections. (3) A novel dimensionless parameter Rcs is derived from smoke control volume force analysis. This parameter quantifies the coupled effect of curvature radius and ventilation velocity on convex-concave ceiling temperature difference, enabling a predictive regression equation. (4) Through dimensional analysis, key governing dimensionless parameters are identified. Incorporating the Richardson number (Ri), which characterizes inertial-to-buoyant force competition, a predictive model for maximum ceiling temperature rise in small-radius UTLTs is ultimately established.
]]>Authors: Xiaokun Zhao Anyu Song Jun Ge Yafei Tian Wencai Wang Donghui Yang
Water-mist curtains act as thermal barriers to longitudinal smoke propagation in confined-space fires, but their downstream cooling remains difficult to predict with reduced-order models. This study develops a calibrated semi-analytical model that uses the incident temperature at the curtain’s upstream face and combines a one-dimensional droplet residence-time solution with a Stefan-flow heat-transfer reduction. A lumped closure coefficient, k = Aeq/A0, collectively accounts for the simplified initial velocity and trajectory, spray nonuniformity, ensemble shielding, representative properties, and boundary inputs. The coefficient is inferred from 5 MW FDS cases with D32 = 400–700 μm and is not interpreted as breakup or coalescence, which were absent from the monodisperse simulations. Cases at 2, 4, and 6 MW provide within-domain blind tests, whereas 1, 3, and 7 MW provide supplementary assessment; the maximum reconstructed relative deviation in exit temperature is 13.4%. A 1:5 experiment supplies a cross-scale trend comparison, but its geometry differs from the full-scale FDS domain, and only the 3 MW-equivalent fire has an archived mass-loss calibration. The model is therefore limited to the present calibration domain and should not be transferred directly across geometries, nozzles, or ventilation conditions.
]]>Authors: Jie Gao Ningye Jia Xinrong Du Qiang Zeng
Coal fires are disasters that occur when underground coal seams are subjected to combustion conditions induced by natural or human factors. This study investigates the eco-environmental quality of three typical coal fire areas, namely Surablak, Shuixigou, and Sikeshu. To achieve this, the previously proposed improved remote sensing ecological index for coal fire areas (RSEIds) was applied to assess and track eco-environmental quality based on multi-temporal Landsat imagery from 2000 to 2024. The GeoDetector model was then employed to identify the dominant influencing factors and their interaction effects. The findings indicate the following: (1) The RSEIds show strong applicability in coal fire areas and provide an effective assessment of eco-environmental quality, with classification results highly consistent with Google imagery. (2) From 2000 to 2024, the eco-environmental quality of all three fire areas generally underwent a process of deterioration followed by partial recovery, with improvement after 2021 mainly occurring in marginal zones rather than in the central parts of the fire areas. (3) Spatially, poor and fair eco-environmental conditions were concentrated in the core disturbance belts of the fire areas, whereas good and excellent conditions were mainly distributed in peripheral mountainous and zones with relatively good vegetation conditions. (4) The dominant driving factors exhibited clear regional differences: distance to the coal fire area and temperature were most important in Surablak, land use type and aspect in Shuixigou, and aspect and precipitation in Sikeshu, while factor interactions consistently showed stronger explanatory power than single factors. These results provide essential references for eco-environmental assessment, restoration zoning, and sustainable management in coal fire areas.
]]>Authors: Moxuan Hu Siwei Wei Changhai Li Yi Zhao Yanming Ding
The growing demand for renewable biomass energy has driven in-depth research into pyrolysis, in which particle size has emerged as a key factor influencing reaction kinetics and gas release. In this study, beech wood with four different sizes were prepared. A thermogravimetric analyzer (TGA 4000) and a Fourier transform infrared spectrometer (FTIR) were used to analyze the thermal behavior of the biomass under a high-purity N2 atmosphere at heating rates of 10, 20, and 40 K/min. Conversion rates and activation energies were calculated from the thermogravimetric data using two model-free methods, while infrared spectroscopy was employed to analyze gas composition and release characteristics. The experimental results indicate that changes in particle size significantly affect the DTG curves: as particle size increases, the maximum rate of weight loss gradually rises. In terms of pyrolysis kinetic parameters, the activation energy of the biomass samples increased from 166.42 kJ/mol to 176.07 kJ/mol. Gas release peaks also exhibited a trend of shifting toward higher temperature regions. The primary gaseous products were classified into six functional group/gas categories, with their yields ranked in descending order as follows: CO2 > CH2O > CH3OH > H2O > CH4 > CO. Except for CO2, the yields of all other components increased with increasing particle size. These research findings provide data and guidance for the recovery and reuse of biomass resources, as well as for the modeling of biomass pyrolysis reactors, and the classification, pretreatment, and process optimization of biomass materials, thereby accelerating their practical application.
]]>Authors: Hao Tang Deli Zhu Xuefeng Han
Electric vehicle (EV) fires can rapidly affect smoke and thermal conditions in underground parking garages. In this study, fifteen PyroSim/FDS cases were screened, but quantitative analysis was restricted to four prescribed-extraction cases and one baseline-matched two-device spray pair. The 0.30 m production mesh was selected using characteristic-fire-diameter, geometric-resolution, and computational-cost criteria. A matched 0.20/0.30/0.50 m check yielded non-monotonic fixed-point responses; mesh independence was not established. Extraction cases were compared using 270–300 s means and the first downward crossing of a 10 m visibility reference. At the same nominal outflow of 10 m3/s, two 5 m/s surfaces produced lower M1 gas temperature and CO and higher visibility than one 10 m/s surface. Relocating the second spray device beneath the vehicle reduced the τ = 120–150 s mean M4 underside-region gas temperature from 776.5 to 103.4 °C, while M1 visibility remained about 0.22 m. Because the model lacks a physical make-up-air path and corresponding experiments were not reproduced, these findings are limited to local prescribed-boundary comparisons. Relevant experiments support the represented mechanisms but the results do not validate the absolute point values. The simulations do not demonstrate battery extinguishment, maintained tenability, or code compliance.
]]>Authors: Shuangjie Mei Yang Cao Xuefeng Han
Battery electric vehicle (BEV) fires in road tunnels can intensify thermal, smoke transport, visibility, and CO exposure hazards under confined ventilation. This study evaluated the combined mitigation performance of water mist and semi-transverse mechanical ventilation. A three-dimensional PyroSim/FDS model of a 200 m × 10 m × 5 m tunnel was established with a 7 MW BEV design fire at the midpoint. The prescribed-source model was assessed against a reduced-scale lithium-ion battery tunnel experiment; at the representative monitoring location, the simulated temperature history reproduced the main trend, with deviations of approximately 7% and 10% at the first and second peaks. Thirty-six coupled cases examined ventilation mode, nominal opening velocity, nozzle arrangement and spacing, flow rate input, droplet diameter, and spray cone angle. Supply ventilation improved hot-smoke-layer cooling and visibility, whereas exhaust ventilation more effectively reduced the local CO volume fraction. Under the baseline weighting scheme, the highest-ranked case reduced the peak local ceiling-region and near-fire gas temperatures by 77.8% and 82.2%, increased average visibility during 200–500 s by 42.9%, and achieved a comprehensive relative mitigation index (CRMI) of 56.6%. Two supplementary nominal 10 MW simulations showed that this case retained substantial thermal control, reducing the two peak temperatures by 65.7% and 74.1%, but did not improve local visibility or CO. Thus, the thermal-mitigation trend persisted at the higher nominal input, whereas the full multi-hazard ranking was not transferable across fire sizes.
]]>Authors: Yunli Xu Guangshuai Han Jie Geng
With the rapid development of recycling and secondary utilization of end-of-life battery materials, it is crucial to clarify the impact of full-lifecycle degradation on the thermal safety limits of lithium-ion batteries. This study focuses on a 16 Ah NCM613|graphite pouch battery. First, it analyzes the evolution of capacity decay, thickness expansion, and internal resistance during cycling at room temperature (25 °C) and high temperature (45 °C). Furthermore, an adiabatic accelerated calorimeter (ARC) is employed to investigate the influence of different states of health (SOH) levels (95% and 85%) on the battery’s thermal runaway characteristics. The findings indicate that, macroscopically, batteries in all states follow similar voltage–temperature failure pathways, with mass loss rates confined to a narrow range of approximately 16%, emphasizing the low catastrophic potential of mid-nickel chemistry. However, the microscopic kinetic mechanisms exhibit significant anisotropy: although thickness and internal resistance display no apparent abrupt increase during the late stage of room temperature aging, the capacity exhibits a highly nonlinear plunge behavior. The severe internal lithium plating side reaction triggered by this phenomenon causes the self-heating onset temperature to drop rapidly from 130.0 °C in the fresh state to 79.7 °C. Concurrently, the activation energy of the exothermic side reaction, fitted using a simplified Arrhenius equation, exhibits a non-monotonic variation with aging progress. In the early stages of aging at 95% SOH, due to high temperatures promoting more significant growth of the interfacial film or moderate film formation at room temperature enhancing interfacial thermal stability, the activation energies for both aged batteries increase, and the energy barrier at high temperatures is slightly higher than at room temperature; however, during the deep aging stage at 85% SOH, due to the degradation of active material components and the emergence of lithium plating characteristics, the energy barrier significantly decreases, with high-temperature-aged batteries exhibiting a greater reduction, highlighting the cumulative negative impact of prolonged high-temperature exposure on thermal safety. The research provides a core scientific basis for establishing a battery safety early warning and dynamic health management system covering the entire lifecycle.
]]>Authors: David Novák Kateřina Hájková Vlastimil Borůvka Tomáš Kytka
Potassium silicate is used as an inorganic fire-retardant treatment for wood, but its effect on the short-term thermal response of different species under combined temperature–moisture conditions remains insufficiently described. This study investigated spruce (Picea abies (L.) H. Karst) and beech (Fagus sylvatica L.) wood impregnated with potassium silicate and exposed to temperatures representing drying, mild thermal loading and the onset of thermal degradation. The evaluation included impregnation uptake, moisture content, mass changes, heat-transfer behavior, differential scanning calorimetry (DSC), chemical composition, Fourier-transform infrared spectroscopy (FTIR) of isolated cellulose and color measurements. Spruce showed higher uptake than beech, with an average weight percentage gain (WPG) of 10.5% compared with 3.6%. The treatment increased equilibrium moisture content by 2.6 percentage points in spruce and 1.1 percentage points in beech. Heat-transfer measurements showed that temperature and moisture governed heating: higher target temperatures were reached faster, whereas air-conditioned samples heated more slowly due to water evaporation. At lower temperatures, the direct effect of impregnation on heating time was limited, whereas at higher temperatures the treatment more clearly affected the subsequent degradation response. DSC revealed lower thermal resistance of beech and increased endothermic heat absorption in impregnated samples, particularly spruce. Higher-temperature exposure caused mass loss, hemicellulose degradation, moderate cellulose structure modification and visible color changes, with ΔE* exceeding 52 in impregnated spruce after 210 °C. The elevated-temperature response was governed by wood species, uptake, moisture content and thermal exposure level.
]]>Authors: Bin Sun
This study addresses the critical need for accurate and efficient large-scale urban fire spread path prediction in dense urban areas by proposing a new gravitational framework-based theory. Its core innovation is the “characteristic attractive force” model, which mechanistically quantifies fire spread as a dynamic interaction between buildings, integrating factors like spacing, height, area and density effects to predict trajectories from the initially ignited building. This study adopts a GIS-based rapid prediction framework that circumvents the dependence on complex physical parameters. It utilizes high-precision spatial data and optimized algorithms to streamline prediction processes while retaining favorable prediction accuracy. Validated on two real-world clusters, the proposed approach enables effective visualization of dynamic propagation trajectories and pathway spectra that characterize the detailed propagation routes and ignition sequences. Notably, the framework achieves exceptional efficiency, completing predictions for large clusters in tens of seconds per scenario, making it suitable for real-time risk assessment. Overall, this work advances urban fire modeling with an innovative, efficient, and practical tool to support fire safety engineering and emergency management decision-making.
]]>Authors: Jady D. Smith Anthony Power Francis E. Putz Sam Van Holsbeeck
Climate change, altered ecosystems, and expanding development in fire-prone landscapes are increasing fire risk in the wildland–urban interface (WUI). This study uses Noosa, southeast Queensland, Australia, as a case study for a preliminary modeling assessment of irrigated green firebreaks (iGFBs). Using the AMICUS Vesta Mk2 fire-behavior model, fire spread rates and fireline intensity were compared across dry eucalypt control scenarios, non-irrigated green firebreak scenarios, and irrigated green firebreak scenarios receiving 1 and 2 mm m−2 day−1 of water. In line with future climate predictions, these scenarios were compared under progressively worsening fire-weather conditions. The drought-affected dry eucalypt control produced the highest predicted fire spread rates and fireline intensity, and although non-irrigated green firebreak scenarios reduced fire behavior, they may still exceed typical suppression thresholds under catastrophic conditions. In contrast, iGFB scenarios consistently reduced both fire spread rates and fireline intensity across all fire-weather classes. Sensitivity analysis indicated that the model outputs were most responsive to drought- and moisture-related assumptions, supporting the importance of fuel moisture in the performance of the iGFB concept. Although iGFBs are not a stand-alone solution suitable for all settings, the findings provide a preliminary region-specific proof of concept for iGFBs and support the need for further applied research.
]]>Authors: Umar Daraz Štefan Bojnec
Wildfires are increasingly recognized as environmental disturbances associated with socio-economic transformations in agrarian systems. This study examines the associations between reported wildfire exposure, land-market outcomes, and agrarian inequality in the Malakand Division of northern Pakistan, a region characterized by forest–agriculture interfaces and livelihood dependence on land. The study aims to analyze how different levels of wildfire exposure are associated with land values, ownership patterns, market transactions, inequality, and coping strategies among farming households. A quantitative cross-sectional design was employed using a sample of 400 households selected through multistage sampling. Data were collected through structured questionnaires and analyzed using ANOVA, chi-square tests, multiple and logistic regression, hierarchical regression, and principal component analysis. Results show that reported land values differed significantly across wildfire-exposure categories (F = 48.72, p < 0.001), with directly exposed households reporting the lowest values. Regression analysis identified direct wildfire exposure as the strongest negative statistical predictor of reported land value (β = −0.468, p < 0.001), while directly exposed households had substantially higher odds of reporting land sales (Exp(B) = 6.35). Chi-square results indicate a significant association between wildfire exposure and land transactions (χ2 = 64.82, p < 0.001). Retrospectively reported landholding data show an increase in the Gini coefficient from 0.41 before the reported fire period to 0.53 afterward. The addition of land-transaction variables increased the explained variance in agrarian inequality to 72%, which is consistent with a potential land-market pathway but does not constitute evidence of causal mediation. Coping strategies such as land sale, migration, and borrowing emerged as dominant reported responses among affected households. The study concludes that wildfire exposure is strongly associated with land devaluation, land sales, and greater agrarian inequality. Because the study is cross-sectional and lacks an independently observed pre-fire baseline or causal identification strategy, these findings should not be interpreted as definitive causal effects.
]]>Authors: Penghui Jia Haihui Han Xiaojuan Yan Chendi Gao Chuntao Yin Xiaoyan Chen
Identifying coal fire risk areas is essential for safe production in coal mines. Land Surface Temperature (LST) retrieval and high-temperature anomaly extraction are core techniques for coal fire risk detection. To address the insufficient evaluation of the accuracy of relevant algorithms for arid open-pit mines, this study takes the Xingsheng Open-Pit Coal Mine in Yiwu County, Xinjiang as the research object. Based on Landsat imagery and UAV thermal infrared data, we systematically compared five mainstream LST retrieval algorithms and six high-temperature anomaly extraction algorithms and determined the optimal combination for long-term monitoring. The results indicate that all five algorithms can effectively depict LST spatial distribution under normal temperature conditions. The Jiménez-Muñoz split-window algorithm performs best for small-scale coal fire identification, with a mean absolute error of 3.25 °C and a relative error of 5.53%, and its fitting slope of 0.82 proves superior stability. For high-temperature anomaly extraction methods, the gradient threshold method achieves a 100% overlap rate with actual anomalies and no omission, which is ideal for large-scale surveys; the cluster analysis method balances detection accuracy and economic benefits for pit-scale investigations. Using 52 valid Landsat images from 2013 to 2025, long-term monitoring reveals that high-temperature anomalies are most active in summer, with an average patch area of 5.65 × 105 m2, and weaken sharply in winter. According to the observed spatiotemporal evolution patterns, the dynamic changes in thermal anomalies are inferred to be mainly associated with human mining activities, with coal seam conditions as the secondary influencing factor. This study provides reliable technical references for coal mine safety management and coal fire disaster prevention.
]]>Authors: Milorad Giljača Vladan Radonjić Oto Iker Ivana Rašović Sonja Pravilović
Accurate short-term wildfire forecasting is essential for effective early warning, operational planning, and resource allocation. This study proposes the Dynamic Spatio-Temporal Fire Pressure Model (DST-FPM), a leakage-controlled forecasting framework that integrates wildfire memory, spatial connectivity, cumulative fire pressure, and seasonal variability using historical satellite-derived active fire detections. The framework combines an Active Cell Framework (ACF), Dynamic Fire Pressure (DFP), the Fire Connectivity Index (FCI), Five-Day Fire Pressure (FFP), and the Operational Fire Risk Pressure (OFRP) index within an Extreme Gradient Boosting (XGBoost) model to predict wildfire occurrence over three-day and five-day forecasting horizons, with the five-day horizon adopted as the primary operational scenario. The methodology was evaluated across Bosnia and Herzegovina, Croatia, and Montenegro using 3,591,054 grid-cell-day observations collected between January 2020 and December 2025. Independent chronological training, validation, and testing datasets were combined with temporal, spatial, and spatio-temporal validation procedures to assess model robustness. For the primary five-day forecasting horizon, the proposed framework achieved a ROC AUC of 0.773, a PR AUC of 0.147, a balanced accuracy of 0.678, and a Matthews correlation coefficient of 0.135 on the independent testing dataset, while maintaining stable performance across all validation procedures. The fitted XGBoost model consistently assigned high predictive importance to the proposed fire pressure indicators, while Top-K analysis showed that 13.5% of future wildfire occurrences were identified within only 1% of the highest-priority grid-cell-day observations. These findings indicate that integrating wildfire memory, spatial connectivity, cumulative fire pressure, and seasonal variability provide complementary predictive information for short-term wildfire forecasting while preserving interpretability, robustness, and operational applicability.
]]>Authors: Yiyu Wang Guiyun Gao Aibin Wang Ao Wang Jikun Liu
The increasing frequency and severity of wildfires pose growing challenges to ecological security in remote forest regions. In road-sparse primeval forests, wildfire prevention and ground emergency response are constrained not only by fire-prone environmental conditions, but also by limited tactical access routes. Existing wildfire susceptibility studies can identify areas with higher fire occurrence potential, whereas route planning studies often optimize access without explicitly considering where fires are more likely to occur. This study developed a GIS-based decision-support framework linking wildfire susceptibility modelling with firefighting access route planning in the northern primeval forest region of the Greater Khingan Mountains, China, to improve the efficiency of wildfire prevention and response in areas with sparse road networks. Using 887 historical fire points and nine environmental and anthropogenic predictors, Logistic Regression (LR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) models were compared to identify relatively wildfire-prone areas. High-susceptibility locations were grouped into operational management zones using K-means clustering. A generalized forest traversal cost surface was constructed by integrating terrain, vegetation, land cover, water constraints, and existing-road accessibility, and a hybrid simulated annealing and 2-opt algorithm was used to design candidate access corridors. Results show that the RF model achieved the best internal-validation performance (AUC = 0.948; overall accuracy = 0.873), and feature-importance comparison showed that land surface temperature, proximity to roads, and NDVI were the most influential predictors. In total, 386 target points extracted from the high- and extreme-susceptibility classes were grouped into 12 spatial clusters. The optimized network identified 1008.46 km of candidate corridors and reduced the mean nearest-access distance for 13 historical wildfire events by 53.7% after the planned network was incorporated. After incorporating the planned corridors into the existing road system, the road-network density increased from 0.96 to 2.015 m/hm2. These findings demonstrate that susceptibility-driven route planning can translate predicted fire-prone areas into prioritized management units and candidate access corridors, thereby reducing spatial accessibility gaps and supporting phased patrol deployment and emergency-resource allocation in road-sparse primeval forests.
]]>Authors: Yu-Tsung Ho Chung-Chyi Chou Yi-Lin Chen
Indoor positioning identifies location but does not directly indicate whether a route remains passable, how hazard exposure changes, or which alternative should be considered under deteriorating fire conditions. As a result, a geometrically shorter route may still be selected despite greater hazard exposure, blockage, or positioning uncertainty. This study proposes a dynamic hazard-aware route-risk assessment model based on Fire Positioning Infrastructure Theory (FPIT) for fireground decision support in building fires. The model converts BIM/IFC spatial semantics into a computable graph, maps normalized hazard scenario data onto graph edges, excludes edges exceeding scenario-specific hazard or blockage criteria, and evaluates the remaining feasible routes using an integrated route-risk score, hazard exposure, travel time, and positioning uncertainty. A normalized illustrative computational demonstration showed that the conventional shortest route had the lowest travel time but higher route-risk score, hazard exposure, and positioning uncertainty. The FPIT-based lower-route-risk-score alternative had lower values for these indicators but required longer travel time, while the intermediate detour provided a compromise. Pareto comparison retained the three feasible routes as non-dominated alternatives with different score–time–uncertainty characteristics. The computational demonstration illustrates the model’s internal calculability, traceability, comparability, and ability to represent route trade-offs; it does not constitute empirical validation or evidence of operational effectiveness in actual fireground environments.
]]>Authors: Weiwei Fan Mingyang Ma Fan Li Wu Wei
Based on the decoupled n-dodecane skeletal mechanism and the computational fluid dynamics (CFD) numerical framework, a multilayer feedforward neural network surrogate model was developed to predict ignition delay in a constant-volume combustion vessel. The Levenberg–Marquardt optimizer with adaptive damping coefficients was used for model training, with mean squared error as the loss function and an inherent early stopping mechanism to prevent overfitting without additional weight decay regularization. To eliminate random interference from initial parameter settings, the surrogate model underwent 1000 repeated training trials, each with random weight re-initialization. The effects of hidden neurons, data partition strategy, normalization scheme, and sample size on predictive performance were systematically examined. The optimal configuration—three hidden neurons, a 70:15:15 data split, and a 105-sample training set—showed low sensitivity to data normalization. The resulting surrogate model is concise and sample-efficient, maintaining satisfactory prediction accuracy at 800 K and 1100 K while substantially reducing computational overhead. It provides a practical and reliable tool for subsequent combustion prediction and uncertainty quantification of hydrocarbon fuels. The feedforward neural network surrogate model substantially cuts the computational overhead for fuel combustion prediction to merely 15–20 min for every batch of 60 samples.
]]>Authors: Dongyin Lai Lin Liu Juanxiu Liu Jing Zhang Xiaohui Du Ruqian Hao Xudong Wang
Early aerial smoke detection is vital for wildfire response, but deploying accurate two-stage deep detectors on resource-limited Unmanned Aerial Vehicles (UAVs) remains computationally prohibitive. Moreover, under uniform supervision, standard knowledge distillation struggles on aerial smoke data, where foreground–background imbalance is severe and smoke boundaries are visually ambiguous. To resolve this, we propose the Decoupled Topology Distance Distillation (DeTD) framework to compress two-stage smoke detectors for real-time edge inference. DeTD features three key innovations. First, a decoupling module uses ground-truth-derived binary masks to isolate smoke and background features, mitigating distillation class imbalance. Second, a topology distance distillation module projects these decoupled features onto a unit hypersphere, employing a novel Symmetric Triplet Loss. This jointly optimizes the intra-class compactness and inter-class separability of both the foreground and background relational geometry between the teacher and student networks. Third, prediction-head soft-label distillation transfers class-conditional knowledge, synergistically complementing the intermediate-feature distillation. Comprehensive experiments on the D-Fire benchmark and a custom aerial UAV dataset yield mAP50 scores of 67.4% and 70.6%, respectively. DeTD consistently outperforms thirteen recent distillation baselines, and the lightweight student attains real-time-compatible inference, narrowing the accuracy–efficiency gap and indicating feasibility for deployment on resource-constrained UAV edge hardware.
]]>Authors: Aliaksei Patsekha Robert Galler Mario Weitzer
Longitudinal ventilation is a primary smoke-control strategy in road tunnels, yet its effect on structural thermal exposure remains insufficiently quantified under full-scale conditions. This study examined whether increased airflow mitigates lining heating by lowering peak temperatures or instead redistributes thermal loading in time and space. Full-scale gasoline–diesel pool-fire experiments were conducted at the Research Centre “Zentrum am Berg” under two ventilation regimes and two fire-source elevations, while surface temperatures of protected tunnel linings were recorded continuously. Higher ventilation generally delayed peak temperatures and produced broader high-temperature plateaus, despite similar or moderately lower peak values at the lower source elevation. When the fire source was positioned closer to the tunnel ceiling, lower ventilation produced higher but shorter-lived temperature peaks, whereas stronger ventilation reduced maxima but prolonged heating. Overall, cumulative thermal exposure, quantified by a temperature–time integral, was greater under higher-airflow conditions. These results show that, within the tested range of ventilation and source-elevation conditions, peak temperature alone does not adequately represent structural fire severity and that duration-dependent exposure metrics should be included in performance-based tunnel fire design.
]]>Authors: Bo Song Bo Li Zhiyong Zhang Yun Chen Qingyang Wang Xing Zhang Zhen Cao Tao Yue Jianwu Jiang
To address the problems of small fire-spot scale, blurred boundaries, complex backgrounds, and insufficient feature representation of weak targets in Unmanned Aerial Vehicle (UAV)-based early forest fire detection, a YOLOv8n-based forest fire detection model, termed TriRHC-YOLO, is proposed. The model first introduces Reparameterized VGG (RepVGG)Block into the backbone network to enhance the extraction capability of shallow local features. Subsequently, a Hierarchical Feature Attention (HFA) module is designed to collaboratively model fire-spot features from three levels, namely directional structures, local textures, and global semantics, thereby enhancing the network’s capability to discriminate fire targets and suppressing interference from complex forest backgrounds. Finally, a Cross Stage Partial Feature Fusion with Cascade Star Block (C2f-CStar) module is designed to improve the representation capability of the model for local structural information and weak salient fire-spot features under complex backgrounds through cascaded spatial feature reconstruction and a star-shaped multiplicative gating mechanism. In addition, a UAV-specific early forest fire detection dataset is constructed based on the FLAME and FLAME_VISION datasets, and experimental validation is conducted on this dataset. The experimental results show that the proposed TriRHC-YOLO outperforms several classical YOLO algorithms, including YOLO11n, YOLO12, and YOLO26, as well as six advanced YOLO-based improved models. The Recall, mean Average Precision (mAP)@0.5, and mAP@0.5:0.95 reach 0.769, 0.848, and 0.608, respectively. The results of the ablation experiments further verify the effectiveness of the three designed modules. Moreover, the proposed model contains only 3.181 M parameters and achieves 168.251 Frames Per Second (FPS), demonstrating favorable real-time detection capability. Overall, the proposed method can effectively improve the detection accuracy of early weak fire targets and the background suppression capability under complex forest backgrounds, making it suitable for real-time UAV-based forest fire inspection tasks.
]]>Authors: Shusmita Saha Jeanette Cobian-Iñiguez
Wind gusts are known to significantly influence wildfire behavior, yet their direct role in ignition dynamics remains underexplored in laboratory settings. This study investigates how controlled wind gusts affect ignition behavior, combustion transitions, and heat re-lease characteristics of wildland fuels using a bench-scale wind tunnel. Three fuel types, Excelsior, wild oat (Avena), and Wheatgrass were exposed to heated stainless-steel par-ticles under varying wind speeds (1.0 and 2.0 m/s) and gust frequencies (0.03, 0.05, and 0.07 Hz). Key ignition parameters, including ignition temperature, ignition delay, smol-dering-to-flaming (StF) transition, burnout time, and heat release rate (HRR), were measured and analyzed. The results show that increasing gust frequency consistently impacted ignition behavior which reduces ignition and transition times across all fuels while raising ignition temperatures and HRR. For instance, StF transition times in Avena dropped from 58 to 42 s and flaming ignition temperatures rose from ~415 °C to ~498 °C as gust frequency increased from 0.03 Hz to 0.07 Hz at 2.0 m/s wind speed. Also, for the same set of experiments, HRR rose from 1674 J/s to 2372 J/s with increasing gusts. These findings indicate that gusty winds enhance convective heat transfer and oxygen availability, accelerating fire initiation and intensifying combustion. The results offer valuable insights for improving predictive fire spread models, ignition risk assessments, and wildfire mitigation strategies under transient wind conditions.
]]>Authors: Delei Kong Dong Ma Yongning Yu Yixuan Yang Fucheng Zhang Huogen Luo
Coal spontaneous combustion is a severe hazard in the goafs of shallow-buried coal seams, particularly under the condition of continuous surface air leakage. This study conducted an integrated experimental and 3D multi-field coupled numerical investigation based on the Huojitu Coal Mine. Experimental kinetic analyses revealed that the upper seam coal exhibits a significantly higher oxygen consumption rate and CO generation capacity than the lower seam coal, characterized by an earlier initial CO generation temperature of 40 °C compared to 60 °C. Subsequent simulations indicated that the flow field and oxygen distribution within the overlying goaf exhibit a distinct “U-shaped” profile governed by surface air leakage. The sequential extraction of the lower coal seam significantly expands the oxidation zone on the return side of the overlying goaf, leading to the formation of a critical high-temperature zone exceeding 100 °C near the return side of the setup entry. Guided by these findings, a three-phase foam technology was implemented in the field, effectively encapsulating the residual coal and drastically reducing the CO concentration at the upper corner from a peak of 221 ppm to a stable 5 ppm. The findings highlight the role of surface air leakage in coal mining and provide corresponding strategies to mitigate spontaneous combustion risks in shallow-buried coal seams.
]]>Authors: Shu-Chen Tsai Meng-Xin Chi Wei-Min Luo
The aim of this study is to explore the fire resilience of traditional ancient villages in Huizhou, China, and to reveal “traditional environmental planning knowledge” as a spatial survival strategy for high-density settlements. This study adopts a qualitative interpretive paradigm, combining historical geography with a literature review, field surveys, and overlay analysis. The study found that these villages, during site selection, utilized basin topography to construct a multi-level disaster mitigation system encompassing “macro-level water systems, meso-level alleyways, micro-level firewalls, and sandwich fire-extinguishing floors.” This endogenous physical technology, based on defensive awareness and community agreements, achieves a dynamic balance of resilience between humans and the environment. The cultural interpretation based on the indicators in this study primarily reflects the disaster resilience potential of traditional planning. The conclusions should be carefully interpreted within the framework of traditional environmental design. Furthermore, commercial intervention, infrastructure renovation, and population loss are leading to the neglect of this defensive space. This lack of a holistic perspective will trigger the “resilience degradation” of ancient villages. Future research urgently needs to establish a “resilience decay model” to quantitatively assess the disaster resistance capabilities remaining after damage to the surrounding buffer space, based on traditional environmental planning knowledge.
]]>Authors: Boning Li Rui Guo Zhen Cao Li Wang Qixing Zhang Xi Zhang
Concealed fires within the insulation layers of buildings, such as cold storage facilities and cinemas, present a serious fire hazard because heat generated by electrical faults can accumulate behind protective panels before ignition and then spread rapidly once combustion begins. Conventional fire detection methods have limited capability to identify these hidden thermal abnormalities at the pre-ignition stage. To address this problem, this paper proposes a deep learning method, called the Multi-Scale Cross-Modal Fusion Network (MSCMFNet), that uses multispectral images to identify abnormal heat sources beneath insulation layers before visible combustion occurs. A standardized experimental platform was developed to accurately simulate subsurface heat sources within the pre-ignition temperature range of insulation materials. Instead of relying on fixed temperature thresholds, the proposed method learns the characteristic spectral patterns produced by hidden heating. It extracts information from different spectral bands, combines these complementary features, and verifies the persistence of detected heat sources over time to reduce false alarms caused by non-fire disturbances. Experimental results demonstrate that the proposed method can effectively detect concealed thermal anomalies before ignition, providing reliable early warning and offering a promising approach to improving fire safety in buildings that make extensive use of insulation materials.
]]>Authors: Katarína Dúbravská Miroslava Mamoňová Viera Kučerová
This study investigated microstructural, optical, and thermal changes in spruce wood (Picea abies) exposed to controlled laboratory heating to identify indicators associated with the transition from progressive thermal degradation to the initial char formation. Cubic specimens measuring 20 × 20 × 20 mm were exposed to selected temperatures between 240 and 300 °C under atmospheric conditions, with a 15 min isothermal exposure period. Microstructural changes were evaluated by scanning electron microscopy (SEM) and quantitative tracheid double cell wall measurements, supported by simultaneous thermal analysis (STA) and color and reflectance analyses. Simultaneous thermal analysis (TG/DTG/DSC) was performed on separate specimens from the same wood material to provide complementary thermal evidence. The most pronounced microstructural changes were observed between 250 and 260 °C, including substantial thinning of tracheid cell walls, degradation of bordered pits, increased brittleness, and localized structural collapse. Quantitative measurements showed reductions in double cell wall thickness exceeding 50% at 260 °C. TG/DTG analysis indicated the onset of intensive thermal degradation at 254.2 ± 1.48 °C, while optical measurements showed pronounced darkening and reduced differentiation of reflectance spectra above approximately 260 °C. The combined evaluation of complementary analytical methods indicates that the 250–260 °C interval represents a condition-dependent microstructural transition associated with accelerated thermal degradation and the early development of a charred structure under the applied experimental conditions. These findings provide complementary experimental evidence for interpreting the early stages of wood charring and may support the interpretation and future refinement of heat transfer and pyrolysis models. They complement, rather than replace, the conventional 300 °C engineering char line criterion used in structural fire design.
]]>Authors: Senlin Yao Shian Jin Shaokun Ge Ya Ni Gaoming Du Yingjian Hu Yin Liang
This study evaluates high-silica fiber/silica aerogel composites (HSFACs) for the passive fire protection of bridge cables. The primary objective is to reveal the high-temperature degradation mechanism of HSFAC and quantitatively determine a reliable thickness scheme for long-term hydrocarbon-fire protection of bridge cables. HSFAC specimens were heat-treated and characterized by thermal conductivity, tensile testing, SEM/TEM, FTIR, and TG analysis. A self-built furnace was used to assess an HSFAC-based cable protection system under hydrocarbon-fire exposure. Increasing heat-treatment temperature enlarged the pore and particle sizes of HSFAC and reduced its thermal-insulation performance. During 120 min of fire exposure, the cable protected by a single 5 mm HSFAC layer reached 300 °C within 45 min, whereas the cable protected by a double-layer 5 + 5 mm HSFAC system remained below 300 °C throughout the test. Finite element simulations validated against the experimental results confirmed that increasing HSFAC thickness improved thermal protection. After 90 min, the predicted cable-surface temperatures were 556 °C and 314 °C for HSFAC thicknesses of 5 mm and 10 mm, respectively. By integrating high-temperature material characterization, HC-fire testing, and thickness-dependent numerical analysis, this study links material degradation to system-level fire performance and provides a quantitative basis for HSFAC thickness design.
]]>Authors: Eric Scheepbouwer
AI-based decision support is moving into fire practice and governance, where it is used to prioritise inspections, analyse building and community risk, examine station coverage, support evacuation planning, interpret warnings, and explore fire scenarios. These tools can extend analytical capacity, but they also create a decision role migration problem: an output developed for prediction, prioritisation, warning, simulation, or planning may later be treated as clearance, justification, or authority. Existing fire model evaluation guidance recognises that validation is use-specific; AI systems add a further challenge because outputs can migrate across dashboards, reusable software components, interfaces, and institutional procedures. This article develops a role-sensitive framework for bounded deployment of AI decision support in urban fire risk management. The framework classifies AI outputs by epistemic role, decision proximity, validation basis, temporal coupling, consequence asymmetry, and governance explicitness. Its central synthesis is that evidence sufficient to warn may be insufficient to clear. Probabilistic outputs can support screening, investigation, prioritisation, and scenario analysis; permissive or safety-proximate claims require stronger assurance, uncertainty communication, fallback rules, and explicit authority allocation. The contribution is a governance logic for keeping exploratory, advisory, policy-shaping, and safety-proximate AI roles separate in urban fire management and policy formulation.
]]>Authors: Jiangao Zhang Jing Yang Pei Zhu Zhi Sun Quan Shao
High-rise building fires pose substantial challenges to conventional firefighting operations due to restricted rescue space and the difficulty of delivering suppression resources rapidly. To improve response efficiency, this study proposes a two-stage mission planning framework for multi-station UAV-based firefighting. The proposed methodology simultaneously accounts for environmental wind, building obstacles, fire evolution, and UAV payload constraints. In the first stage, an improved particle swarm optimization (PSO) algorithm is employed to generate time-optimal flight paths satisfying both spatial obstacle-avoidance and wind-field constraints. In the second stage, based on the actual flight times derived from the first stage, the multi-UAV resource scheduling problem is formulated as a mixed-integer linear programming (MILP) model to minimize the total fire suppression mission duration. Additionally, an isochrone-based firefighting coverage circle is introduced to optimize the layout of additional fire stations. Simulation results indicate that while optimized paths remain geometrically similar under varying wind conditions, wind-induced flight time variations significantly affect UAV arrival sequences and flight times. In the scheduling stage, differences in station layouts and fire scales alter projectile release timing; under unfavorable conditions, such temporal differences can increase the total mission duration by more than 28%. Notably, the optimized addition of fire stations effectively enhances response redundancy in high-rise clusters, reducing fire suppression time in adjacent scenarios by approximately 50%. The proposed method provides theoretical support and methodological guidance for cooperative UAV firefighting and emergency resource optimization in urban environments.
]]>Authors: Izuchukwu Oscar Okafor Zifei Liu Mayowa Boluwatife George
Accurate quantification of wildfire risk is essential for balancing wildfire mitigation and prescribed fire management in grassland ecosystems, yet existing fire danger indices do not explicitly distinguish seasonal fuel dynamics from daily weather variability. This study presents a hierarchical framework for quantifying wildland fire risk by explicitly separating seasonal wildfire potential from daily weather-driven fire activity. The framework introduces the Daily Burned Area Ratio (DBAR) as a quantitative measure of realized wildfire risk and decomposes it into the Seasonal Burned Area Ratio (SBAR) and the Daily Burn Activity Index (DBAI). Wildfire records from the U.S. Forest Service Fire Program Analysis Fire-Occurrence Database, Oklahoma Mesonet weather observations, and remotely sensed vegetation data collected between 1995 and 2020 were used to develop and evaluate the framework in the Flint Hills of Kansas and Oklahoma. SBAR was modeled using grass curing and air temperature to characterize the seasonal baseline of wildfire activity, whereas DBAI was modeled using dead fuel moisture content (DFMC) and wind speed to quantify day-to-day departures from that seasonal baseline. The SBAR model accurately reproduced the characteristic bimodal wildfire regime of the Great Plains, whereas the DBAI model identified DFMC as the dominant control on daily wildfire activity, with wind speed providing an important secondary influence. Compared with the Burning Index (BI) and the Grassland Fire Danger Index (GFDI), the hierarchical framework achieved superior performance in discriminating fire days from non-fire days. Global sensitivity analysis further demonstrated that the framework provides a more balanced representation of the influences of grass curing, relative humidity, air temperature, and wind speed than the conventional indices. By explicitly separating seasonal fuel dynamics from short-term weather variability, the proposed framework provides an ecologically interpretable, locally calibratable, and operationally practical approach to wildfire risk assessment. Because the seasonal and daily components can be calibrated independently, the framework is readily transferable to other grassland ecosystems and provides a flexible foundation for adaptive wildfire and prescribed fire management under changing climatic conditions.
]]>Authors: Jingwei Liang Qingnian Deng Liyan Niu Shihui Zhou Jiahai Liang Zekai Guo Liang Zheng Yile Chen
Traditional fire detection technologies for buildings are no longer adequate for the fire prevention and control needs of complex structures, while emerging artificial intelligence technologies have become the core path to break through the bottlenecks in this industry. Existing reviews suffer from non-standardized paradigms, one-sided scopes, insufficient methodological evaluation, incomplete time coverage, and a lack of engineering orientation, failing to meet the evidence-based research needs of the field. This study strictly followed the PRISMA 2020 systematic review guidelines, selected relevant SCI papers from the Web of Science Core Collections from 1 January 2016 to 30 March 2026, in JCR Q1 and Q2, and finally included 221 valid papers; it systematically carried out bibliometric analysis and technical system sorting. The results showed that (1) the number of publications in this field showed a significant exponential upward trend, with China accounting for 52% of the research output, ranking first in the world, and (2) convolutional neural networks and YOLO series algorithms are the mainstream application technologies in the field. The study clarified the performance differences, advantages, and disadvantages, and applicable scenarios of various artificial intelligence algorithms. This study identified the existing technical and methodological limitations in the field and explored the core research directions for the future, and provided evidence-based support for the academic research and engineering implementation of artificial intelligence in the field of building fire detection and prevention.
]]>Authors: Chao Liu Ziheng Pu Wei Guo Shuai Wang Zhigang Ren
To address the discrepancy between the constant-power fire sources currently used in cable fire-related research and cable fire protection product testing and actual cable fires, this paper proposes a cable equivalent combustion simulation method based on electrical fault fires. The cable tunnel experiment platform was built and, based on energy equivalence, used an igniter to simulate a fault arc’s thermal effect and ignite the cable, obtaining the temperature rise characteristics at multiple points in the fire source area. Based on the experimental data, a simulation model for the mixed combustion of multiple cable materials was established and revised, and the heat release rate (HRR) under different fire scenarios was calculated. Then, an equivalent fire source device capable of simulating the aforementioned HRR curve was designed. The results indicate that under ignition conditions with an igniter power of 400 kW and duration of 90 s, the cable fire development exhibits nonlinear dynamic evolution, with a flame height of 0.63 m. The peak temperature rise rate and peak temperature at the measurement point reach 3.27 °C/s and 926 °C, respectively. When 39.4% of the insulation layer material of the cable participates in combustion, and the fuel molecular formula is C2.28H5.70O1.42N0.08Si0.65, the relative error between simulated and experimental temperatures during stable combustion is 3.0%. Heat release rates for mild, moderate, and severe fires stabilize near 350 kW, 420 kW, and 530 kW under this calibrated cable model. The relative error between the temperature curve from the fire source device during the stable combustion stage and that from the actual combustion experiment is 3.4%, indicating favorable equivalence.
]]>Authors: Daniel Rosales-Giron Chad M. Hoffman Rodman R. Linn Scott M. Ritter Justin P. Ziegler
Coupled fire–atmosphere models (CFAMs) are increasingly proposed as an important tool for investigating a range of scientific and management questions, including the design of fuel management strategies. Uncertainty in CFAM outputs arises from environmental and fuel inputs, and a host of user-defined simulation choices such as fire approach angle and ignition timing. In this study, we used the Wildland–Urban Interface Fire Dynamics Simulator (WFDS) to quantify uncertainty in rate of spread and canopy consumption across pre- and post-restoration ponderosa pine stands. Two ensembles were conducted: (1) varying fire approach angles across 12 rotations and (2) varying ignition time in 80 simulations (five per plot, with 0 s delay, 250 s delay, and three random intervals in between). Metrics evaluated were rate of spread and percent canopy consumption. Variability was quantified using coefficients of variation (CVs). Approach-angle variation produced a mean CV of 5.46% for rate of spread, with treated stands exhibiting reduced variability relative to untreated stands. Canopy consumption showed a mean CV of 6.16%, with treatment having no effect. Ignition-time variation produced smaller CVs (rate of spread: 2.47%; canopy consumption: 3.60%) with no differences between management conditions. These results indicate that user-defined configuration choices contribute measurable but modest uncertainty, and that structural modifications from management can reduce sensitivity of fire spread. Incorporating these sources of uncertainty into formal frameworks will improve interpretation of CFAM outputs for operational and research applications.
]]>Authors: Rubén Jiménez-Panadero Fernando Alacid Rodrigo Yáñez-Sepúlveda Vicente Javier Clemente-Suárez
Professional wildland firefighters are exposed to substantial physical, thermal, respiratory, and psychosocial demands. This cross-sectional study examined whether cardiometabolic and work-related health indicators differed among the five provinces of Castilla-La Mancha after accounting for age and sex. The analytical sample comprised 757 salaried GEACAM wildland firefighters (663 men and 94 women). Outcomes were visceral fat level, device-derived metabolic age, metabolic age gap, the Work Ability Index (WAI), the 14-item Perceived Stress Scale (PSS-14), self-rated health, and anxiety problems. Province effects were tested using heteroscedasticity-robust linear models or logistic regression, with age and sex as covariates. Adjusted pairwise provincial contrasts were corrected using Holm’s method. Province was associated with visceral fat level (F(4, 687) = 3.21, p = 0.013, partial R2 = 0.021) and PSS-14 score (F(4, 685) = 4.64, p = 0.001, partial R2 = 0.029). No adjusted provincial association was found for metabolic age, metabolic age gap, WAI, self-rated health, or anxiety problems. After Holm correction, PSS-14 scores were lower in Albacete than in Guadalajara (adjusted difference = −3.17, 95% CI −5.18 to −1.16; pHolm = 0.018) and Toledo (−3.54, 95% CI −5.36 to −1.72; pHolm = 0.001). Although the global province effect for visceral fat was significant, no individual pairwise contrast remained significant after Holm correction. Provincial heterogeneity was therefore modest and concentrated in perceived stress and, less conclusively, visceral fat. These findings support age- and sex-adjusted surveillance while precluding causal explanations based on terrain, fire exposure, workload, or recovery, none of which were measured.
]]>Authors: Rui Liu Jia Xie Hanbing Hao Taiyun Zhu Yi Guo Xiang Liu Yang He Jiaqing Zhang Tianchang Meng
Early detection of incipient fire signs, such as dilute smoke emerging at valve hall penetration seals, remains a critical challenge for fire safety in ultra-high-voltage (UHV) converter stations. This study addresses the limitation through controlled valve hall sealing simulations that systematically reproduce the complete fire evolution process—from initial dilute smoke leakage, through dense smoke accumulation, to eventual flame overflow—thereby constructing a high-fidelity dataset tailored to complex converter station environments with low-contrast and varying illumination conditions. Building on this dataset, an attention-enhanced YOLOv5s model integrating multiple attention mechanisms (GAM, CBAM, CA, and ECA) is proposed as the core of an end-to-end visual detection framework. Rigorous experiments and ablation studies validate the framework’s superiority: dilute smoke detection precision improves substantially from a baseline of 57% to 81%, with recall increasing from 61% to 84%; dense smoke and flame detection achieve accuracies of 92% and 98%, respectively. Compared with the original model, false and missed alarm rates are significantly reduced, demonstrating strong robustness against background interference and lighting variations. The proposed method enables reliable, high-precision monitoring across all fire stages, providing a novel technical pathway for early fire warning in UHV converter stations and offering extensibility to other large-scale industrial fire monitoring scenarios.
]]>Authors: Liudas Sukevicius Mindaugas Grigonis Ramune Zurauskiene
This study investigates the reaction of charred wood cladding systems to fire, focusing on the influence of wood species, charred surface treatment, flame retardant treatment, surface coating and board orientation. Nine different configurations of larch and spruce cladding samples with 20 mm thickness were investigated, which were installed into the system according to standard requirements. The samples differed by wood type, charred surface treatment, board orientation, covering with flame retardant agents and additional surface coverings. Two commercial flame retardant treatments and three commercial surface coatings were included in the experimental matrix. Fire behaviour was evaluated according to the EN 13823 Single Burning Item (SBI) method, analysing the ignition time, fire growth rate index, total heat release from the specimen in the first 600 s of exposure to the main burner flames, smoke growth rate index and total smoke production from the specimen in the first 600 s of exposure to the main burner flames as indicators. Although it was determined that the ignition time fluctuated in a relatively narrow range (from 5 min 12 s to 5 min 36 s), analyses of the additional SBI indicators revealed much clearer differences between the systems. The best results were obtained for the charred notched spruce system treated with the phosphate-, urea- and biocide-based flame retardant, which had the longest ignition time and lowest values for the investigated indicators. Meanwhile, the least favourable behaviour was observed in the notched untreated spruce system and in the horizontally oriented system, marked by higher fire spreading and smoke formation values. The obtained results show that the reaction of a wood cladding system to fire is not determined only by the type or application rate of flame retardant, but also the whole system’s structure, including the wood type, surface processing, covering combination and installation configuration.
]]>Authors: Morey J. Kolber James N. Ippolito William J. Hanney
Introduction: Approximately 50% of firefighter injuries occur in the musculoskeletal system and poor movement quality increases injury risk. Previous research suggests that corrective exercise interventions with integrated movements improve movement literacy; however, the long-term benefit of corrective exercise programming has not been established among firefighters. Purpose: To investigate, as a continuation of a previously published short-term (mean—267 days) outcome pilot study, the long-term effectiveness of auto-generated corrective exercise programming on movement literacy scores among firefighters with lower baseline scores. Methods: Nine male firefighters (mean age +/− standard deviation 40 (12)) with baseline Functional Movement System (FMS™) scores less than 14/21 were initially recruited from October 2021 to September 2022. Baseline FMS™ assessments included detailed explanations of the seven movement screens as well as five clearing procedures and scoring criteria. A certified FMS™ professional performed each test first, prior to scoring, to demonstrate what was expected and firefighters were permitted to attempt each test for a total of three times with the highest score retained. Scores ranged from 0 to 3 for each of the seven movement screens with a maximum composite score of 21. Upon completing the screenings, test scores were reviewed and a detailed report was provided to each firefighter through the FMS™PRO APP. Additionally, each participant received an auto-generated corrective exercise program from the FMS™PRO APP with exercise figures, descriptions, and videos to be performed prior to routine conditioning programs. Participants were re-evaluated an average of 813 days after baseline for the long-term follow-up (F2). Pairwise comparisons from baseline to F2, as well as from a previously reported short-term follow-up (F1) to F2, were evaluated using the Friedman and Wilcoxon signed-rank tests. A Bonferroni correction resulted in an adjusted alpha of p = 0.025. Results: Composite FMS™ scores improved from a baseline mean of 11.3/21 to 14.7/21 at F2. When F2 was compared to the F1 scores from the previously published data set, scores declined by a mean of 1.4 points. Compared with baseline, scores at F2 were significantly improved (p = 0.013) with a large effect size (r = 0.83). In contrast, score declines (r = −0.73) from F1 to F2 were not statistically significant after Bonferroni correction (p = 0.028). Conclusions: An auto-generated corrective exercise program combined with a detailed explanation of baseline performance was effective in improving overall movement literacy in a standardized movement assessment tool in a long-term follow-up exceeding 2 years. The composite score change exceeded the threshold of error based on a previously established minimal detectable change (MDC) of 2.5/21, indicating true change occurred from baseline to F2. The decline from F1 to F2 did not exceed the threshold of error based on the MDC and may represent a regression to the mean and participant acknowledgement of marginal adherence after F1. Long-term adherence to programming is necessary to prevent the tapering of improvements seen in this study. The absence of a comparison or control group is a study limitation.
]]>Authors: Yibo Zhang Weijun Pan Yanqiang Jiang Lang Lei Qinyue He
In mountainous wildfire response, unmanned aerial vehicle (UAV) emergency services depend on rapidly deployable and spatially reliable vertiports. However, existing site-selection methods insufficiently support continuous UAV operations in topographically complex terrain. This study develops a geographic information system (GIS)-based framework integrating Multi-Criteria Decision-Making (MCDM) and k-medoids clustering to shift UAV vertiport planning from individual site suitability ranking to networked deployment. The framework organizes feasible vertiport candidates into sector-based support staging nodes for coordinated multi-node wildfire response. Applied to the Xichang wildfire, the selected vertiport candidates reduced the mean first-arrival time by up to 71.4% compared with existing fire stations. Under differentiated reload-time assumptions, the staging node support mode further reduced the mean sortie cycle time by up to 56.85% and increased the mean delivery capacity from 17 to 42 fire-extinguishing bombs per UAV per hour. These results indicate that combining vertiport suitability evaluation with staging node-based logistical coordination improves the spatial organization and operational efficiency of UAV-enabled wildfire suppression. The framework offers decision support for networked UAV vertiport and staging node deployment in mountainous wildfire response.
]]>Authors: Peng Lei Yunqiang Wang Yajin Fan Jie Chen
Underground deep vertical spaces are a new form of architectural structure for the efficient use of land resources. However, their slender geometry can intensify smoke transport and thermal hazards during fires. Sealing is a potential emergency strategy, but its influence on smoke dynamics and flame extinction in deep shafts remains insufficiently quantified. This study investigates smoke transportation characteristics and flame self-extinction in a sealed deep vertical space using 1:26 reduced-scale experiments combined with CFD simulations. Across the tested conditions, sealing consistently increased the characteristic upper-shaft centerline temperature rise, with enhancements ranging from 43.2% to 374.9%. The vertical centerline temperature above the fire exhibits a segmented decay behavior: in the plume-rise region it follows a power-law trend, while the decay coefficient deviates from the ideal-plume expectation, consistent with the thermal shielding effect associated with the confined upper hot-gas layer. Under sealed conditions, a distinct “ghosting” flame behavior and eventual self-extinction were observed. The combined flame, thermal, and simulated flow-field evidence is consistent with an oxygen-limited interpretation, although this mechanism was not directly verified by gas-species measurements. Based on the reduced-scale dataset, the self-extinction time was normalized by the characteristic oxygen-consumption timescale to2, yielding texttO2=2.074h1 m−0.394Q1 kW−0.071, which provides a quantitative description of flame self-extinction under the tested sealed conditions.
]]>Authors: Samson Tan Teik Toe Teoh Paul Joseph Khalid Moinuddin
Battery Energy Storage Systems (BESS), utilising chemistries based on Nickel Manganese Cobalt (NMC) containing lithium-ion devices, often present fire safety hazards that existing qualitative risk frameworks, including NFPA 855’s 5 × 5 consequence-likelihood matrix, are insufficiently granular to quantify. This paper presents an original probabilistic risk assessment (PRA) of fire hazards associated with BESS for a 485.52 kWh NMC installation at the Equinix SG4-4A data centre in Singapore, using Monte Carlo simulation (N = 10,000 iterations) to characterise uncertainty in hydrogen fluoride (HF) gas dose, time to Immediately Dangerous to Life or Health (IDLH) concentration, cabinet-to-cabinet propagation probability, and suppression effectiveness. The HF yield is modelled as a triangular distribution (0.3–0.8 g/kWh, mode 0.5 g/kWh), ventilation activation delay as log-normal (median 90 s), and suppression effectiveness as a piecewise function of water application delay. The results demonstrated that HF dose exceeded the National Institute for Occupational Safety and Health (NIOSH) IDLH of 25 mg/m3 in 100% of simulated scenarios for both single- and two-compartment designs, thus confirming that threshold HF toxicity was essentially unavoidable for any occupant present during a full thermal runaway event, and that ventilation alone cannot achieve adequate risk reduction. The single-stage suppression effectiveness was found to be only 37.9% (mean), providing quantitative confirmation that two-stage (clean agent + water) suppression is warranted for NMC chemistry. The two-compartment design was found to reduce the peak HF dose by 50%, and also reduced the mean IDLH clearance time from 599 to 301 min, thus shifting residual risk from As Low As Reasonably Practicable (ALARP)-tolerable to broadly acceptable under UK Health and Safety Executive (HSE) criteria. The paper proposes a quantitative PRA framework as a complement to NFPA 855 Chapter 5’s qualitative Hazard Mitigation Analysis, enabling more informed engineering decisions for BESS fire safety. To the best of our knowledge, this is the first study to apply Monte Carlo simulation to HF dose modelling in a tropical data-centre BESS context and thereby address a documented gap in the literature.
]]>Authors: Zhuqing Zhang Simin Zhu
Explosive detonation is a high-speed and high-energy chemical-physical transformation process that rapidly generates high-temperature and high-pressure gases as well as shock waves. These energies are released intensely in a short time, exhibiting extremely strong destructive power. When these high-temperature and high-pressure gases and shock waves act on the surface of combustibles, they can instantly peel off the hot core on the surface, disrupting the conditions necessary for sustaining the combustion reaction and thereby achieving a fire-extinguishing effect. However, to attain this application goal, it is essential to select explosive materials with both high energy density and low sensitivity. In this study, DFTB-MD (Density Functional Tight-Binding Molecular Dynamics) and DFT (Density Functional Theory) methods were employed to systematically investigate the thermal decomposition process of benzotrifuroxan (BTF)/1,3,5-trinitrobenzene (TNB) cocrystal nanoparticles under high-temperature conditions. Our simulations reveal, for the first time, that the thermal decomposition mechanism of BTF/TNB cocrystal nanoparticles is strongly size-dependent: the 1.8 nm particles exhibit earlier ring-opening of BTF due to the higher surface-to-volume ratio, while the 2.2 nm particles show superior structural stability and lower molecular diffusivity. Meanwhile, increasing temperature from 2100 K to 2400 K shifts the dominant initial decomposition pathway from C–NO2 cleavage in TNB to ring rupture in BTF. These findings provide atomic-scale theoretical insights into the design and application of BTF/TNB cocrystal nanoparticles for explosion-based fire suppression.
]]>Authors: Grazia Pellizzaro Carla Scarpa Marcello Casula Annalisa Canu Bachisio Arca Michele Salis Valentina Bacciu
Forest fires are a recurring disturbance in Mediterranean ecosystems, but they also impact air quality and public health, particularly given recent trends towards increasingly widespread and extreme fires. This study analyzed six large fires that occurred in Sardinia, Italy, between 2009 and 2021, in order to evaluate their impact on ground-level PM10 concentrations and to investigate the influence of fire size, fuel type, and meteorological conditions. The analysis included data on fire perimeters and land cover, meteorological conditions, smoke plume trajectory simulations using HYSPLIT, satellite imagery, and PM10 concentration measurements from the regional air quality monitoring network. The six case studies differed markedly in terms of burned area, vegetation composition, duration, and weather context. The results showed that the extent of the fire is likely not the most significant factor influencing the increase in PM10 observed in the days following the fires. The most pronounced increases in PM10 concentrations were recorded during the Isili and Montiferru fires, which differed in burned area but were similar in terms of fuel composition, dominated by forest and shrubland vegetation. These factors, together with favorable atmospheric conditions for plume transport and particulate matter deposition, likely contributed to the observed increases in PM10, including exceedances of WHO and national daily limit values. By contrast, Bonorva, Ittiri, and Borore showed limited or no clear accumulation of PM10, despite large burned areas in some cases. These findings suggest that the effects of wildfires on air quality in the Mediterranean region can be influenced by several features, such as meteorological conditions, biomass burned, area burned, severity and intensity of fires. Furthermore, the observed exceedance of WHO thresholds highlights the need to integrate public health considerations into wildfire risk management in the Mediterranean basin.
]]>Authors: Lihong Zhao Ping Fang Songtao Liu Shiyao Liu Xu Zhang Xiaolin Yang Rongkun Pan Yonghao Mao
As rooftop photovoltaic (PV) systems are increasingly deployed on taller buildings and across a wider range of building applications, localized overheating or initial fires caused by electrical faults, combustible roof-covering materials, or maintenance-related ignition sources may affect PV modules and contribute to subsequent fire spread over the rooftop system. In this study, a full-scale fire experiment was conducted on a flat-laid rooftop PV system using a nominal 100 kW n-heptane pan fire as a controlled localized external fire source to investigate the fire development and escalation mechanism of the system. The results show that the fire hazard was first and primarily concentrated in the confined under-panel space: the average cavity peak temperature of the ignited array reached 684.0 °C, with a local maximum of 853.4 °C, both significantly higher than the maximum upper-surface center temperature of 370.7 °C. The involvement of the waterproofing membrane in combustion was the key amplifying mechanism driving the transition from localized heating to a sustained high-temperature event; the average cavity temperature exceeded 500 °C after 234 s and remained above this threshold for approximately 201 s, with an average cavity heat accumulation index of 178.1 × 103 °C·s. Compared with the lower upper-surface center measuring points, hazardous temperatures beneath the modules were reached earlier by 149, 193 and 247 s at the thresholds of 50, 100 and 200 °C, respectively. Under the tested configuration, these findings provide engineering insights for fire-risk identification, early monitoring, and fire-safe design of flat-laid rooftop PV systems in high-rise building applications.
]]>Authors: Yang Liu Shunbing Zhu Yue Sun Jianlong Zhang Zhengxiang Han
This experiment investigated changes in the key parameters of explosion pressure peak (Pmax) and pressure rising rate peak ((dP/dt)max) and flame propagation characteristics of wood dust explosion (pine, cypress and poplar dusts) under different wood dust diameters and concentrations using a 20 L spherical explosion apparatus. Combined with thermogravimetric analysis and Fourier transform infrared spectroscopy, the pyrolysis behavior of different wood dusts and the generation mechanism of gas-phase flammable products were elucidated. The results indicate that the type, wood dust diameter and concentration of dust had a great impact on the severity of explosion. As the dust diameter decreased, Pmax and (dP/dt)max both showed a trend of first increasing and then decreasing. Among them, the explosion pressure and Kst value of 300-mesh poplar wood were the highest, reaching 0.72 MPa and 11.6 MPa·m/s. The flame propagation characteristics were comprehensively influenced by dust morphology, volatile matter content and concentration. Among them, the peak height of flame propagation and its instantaneous velocity were obviously higher for poplar and pine wood dusts than those of cypress wood due to the high carbon and volatile matter contents. The overall quality loss rate of poplar dust in the thermogravimetric experiment was the highest, while its pyrolysis reaction rate was also the highest. The mass loss rate of 140-mesh poplar wood reached 90.5%, and the thermal decomposition reaction rate reached 19.48%/min. The large number of alkanes, aldehydes and ketones, as well as gases such as CO and CO2 generated during the pyrolysis, provided the material basis for the chain reaction of a dust explosion. This study systematically elucidated the differences in explosion parameters, flame propagation behavior, and pyrolysis processes of different wood dust, thus providing theoretical support for their explosion risk assessment and safety protection.
]]>Authors: Long Chen Xiaoxing Zhong Zhenlu Shao Tao Zhou Guofu Zhang Fei Cao Zichao Jia
Accurate localization of concealed fire sources is the fundamental prerequisite for effective coal fire control and mitigation. The self-potential method, as a passive, cost-effective geophysical technique for large-area surveys, exhibits unique advantages in coal fire detection, yet 3D inversion of self-potential data for high-precision coal fire source localization remains insufficiently studied. In this paper, a 3D iterative compact inversion algorithm based on the minimum support functional is adopted to invert self-potential data for 3D localization of underground concealed coal fire sources. The algorithm’s reliability and robustness are verified systematically via numerical simulations at both laboratory and field scales, followed by sandbox experiments with artificial battery sources and burning coal specimens, and finally validated its engineering applicability in the Sandaoba Coal Fire Area in Xinjiang. Numerical results show that the algorithm achieves high-precision inversion of source current density across multiple orders of magnitude, with a relative error below 10%. Sandbox experiments confirm that coal combustion generates a typical dipole self-potential field with distinct negative surface anomalies, whose amplitude is positively correlated with combustion intensity. Field inversion results successfully delineate the 3D boundary of the concealed fire source (buried at 40–140 m), which is highly consistent with borehole temperature measurement data. This study provides a robust technical framework for 3D detection of concealed coal fires, offering strong technical support for precise coal fire governance and hazard mitigation.
]]>Authors: Junwei Shi Ziyan Zhang Mengyao Zhang
Thermal runaway in electric vehicle power battery packs is a key risk in fire prevention and control for electric transportation. Its triggering, propagation, and failure modes are jointly affected by external thermal abuse, material insulation performance, and side reactions inside cells. To identify the temperature response and fire risk of power battery packs under different thermal abuse intensities, this study established a three-dimensional multiphysics thermal runaway simulation model in COMSOL Multiphysics 6.1, coupling solid heat transfer, electrochemical heat generation, and side-reaction heat release. A semi-quantitative risk ranking was then performed using failure mode, effects, and criticality analysis (FMECA). The model considered the low-temperature safe conditions, 120 °C, 140 °C, and 170 °C, as the main ambient temperature conditions, while also analyzing the effects of the heat transfer coefficient on trigger time and peak temperature. The results show that, under the low-temperature safe condition and the 120 °C condition, the battery module mainly exhibits slow heating and does not undergo thermal runaway. Based on the side-reaction characteristics, the temperature near 125 °C can be used as a risk warning threshold for thermal runaway. At 140 °C, the side-reaction heat source increases markedly, and the system enters the thermal runaway risk region. Because the trigger time is strongly affected by the heat transfer coefficient and monitoring position, this condition is interpreted only as a risk-acceleration stage under critical thermal abuse. Approximately 167 °C can be regarded as the critical threshold for irreversible thermal runaway. Under severe thermal abuse at 170 °C, rapid intensification of internal side reactions increases the peak module temperature to 375–385 °C. Temperature field evolution shows that heat is transferred mainly from the exterior to the interior before thermal runaway, forming an outside-high- and inside-low-temperature distribution. After the runaway stage begins, heat release from internal cell side reactions becomes dominant, and the high-temperature region concentrates inside the module, producing a gradient reversal with a higher internal temperature. The FMECA results show that the positive electrode–electrolyte reaction has the highest RPN, with a value of 405. Accelerated SEI decomposition and the negative electrode–electrolyte reaction also form key risk links in the chain heat-release pathway. This study provides a reference for thermal management, fire barrier design, and fire risk classification of power battery packs.
]]>Authors: Youhao Xie Wenjie Wei Liangyuan Qi Weiyi Xing Yuan Hu
The issue of thermal runaway in power batteries of new-energy vehicles occurs frequently, posing a serious threat to life and property safety. This study aims to develop a high-performance fire-proof coating to address this problem. Specifically, the research focused on constructing an organic-inorganic composite intumescent fire-resistant coating, with modified halloysites (Ti-HNTs) serving as the key component. In this coating system, the intumescent flame-retardant (IFR) system and Ti-HNTs were employed as the organic and inorganic components, respectively, while water-based epoxy resin emulsion was selected as the matrix material. Through the utilization of XPS, FTIR, and SEM techniques, it was verified that the Ti-HNTs were successfully modified and integrated well with the coating matrix. Following further optimization of the Ti-HNTs proportion and coating thickness, it was determined that the coating containing 4% Ti-HNTs with a designed thickness of 1.5 mm exhibited the optimal fire-proofing performance. In the fire-resistance experiment, after 10 min of testing, the temperature of this coating could reach a minimum of 215.9 °C. Compared to the control group, its heat-insulation effect was enhanced by 49.4%, with an expansion multiplier of 37.7 and a maximum smoke density of 22.55. These results were significantly superior to those of the control group without the addition of Ti-HNTs. SEM analysis indicated that the coating could form a uniform and dense carbon layer, with an inner surface featuring a honeycomb-bubble structure. This SEM-analyzed Ti-HNTs-modified fire-proof coating demonstrated excellent fire resistance and thermal-isolation effects in new-energy vehicle batteries, thus providing reliable fire protection for the batteries. Additionally, impact-resistance tests revealed that the coating could withstand a simulated battery pressure-relief impact without penetration, maintaining its structural integrity and thermal-barrier function. This further validated its reliability for battery fire protection.
]]>Authors: Katrin Kuhnen Mariana S. Andrade Mortimer M. Müller Harald Vacik
Wildfires are an increasing threat in Central Europe and pose challenges for protective forests and areas at the wildland–urban interface (WUI). Understanding, describing and predicting fire behaviour is therefore becoming more relevant for fire management. This work aims to reconstruct the fire spread behaviour of past fire events occurred under differing environmental conditions with selected fire spread models. The three fire spread models Farsite, SimtableTM and Prometheus were selected according to a list of predefined properties they were expected to fulfil. Subsequently, they were tested under different environmental conditions and evaluated against documented perimeter of past fire events. The focus of the analysis was on the spatial perimeter to quantify metrices such as over- and underestimated areas in percent, Sørensen–Dice coefficient and the Jaccard similarity coefficient. Farsite showed the best overall results in both regions. Simtable performed well in steep and complex terrain but produced underestimations in flat terrain. Prometheus lagged, likely due to inadequate parametrization of fuel data, which is a key input parameter in fire spread modelling. As Farsite is readily accessible, it has the greatest potential for further application and more in-depth research. For higher reliability, additional empirical data on fire behaviour are needed to develop custom fuel models or refine current adjustments used to simulate fire spread.
]]>Authors: Jaeun Choi Wonseok Yang Seokju Kim Ahyeon Jeong Jiwoo Baek Nanggyun Ko Chumni Jeon Eun Sang Jung
Accurate wildfire prediction increasingly determines whether emergency resources arrive before a disaster becomes uncontrollable, yet the dominant paradigm reduces the problem to binary occurrence, offering no estimate of the severity that drives suppression planning. This study develops a machine-learning framework for four-class wildfire severity prediction, conditional on ignition, from weather-station observations and calendar terms alone. We construct a composite severity index (CSI) by applying principal component analysis to five damage dimensions (burned area, suppression equipment, personnel, duration, and property loss) recorded for 868 wildfires in Gangwon Province, South Korea (2011–2022) and pair standard observations with effective humidity and six indices of the Canadian Forest Fire Weather Index (FWI) System. Under a leakage-safe protocol, the strongest tree ensembles reach a macro F1 of 0.46 to 0.50 (recommended configuration: 0.41 ± 0.03 across 20 repeated splits) against a four-class chance level of 0.25, and the recommended Random Forest attains an extreme-class recall of 0.474; the CSI target outperforms burned area by 5.5 macro-F1 points under identical inputs. A weather-only screen separates extreme from non-extreme events with an ROC AUC of 0.758, capturing 47% of extreme events at a 20% alert budget. We also quantify how oversampling misplaced before the train-test split inflates the macro F1 to 0.65–0.83, a cause for caution for the severity-prediction literature.
]]>Authors: Wisdom M. D. Dlamini
Burned-area totals are useful for national monitoring, but they do not reveal how, when or under what social and ecological conditions a landscape burns. We developed an event-based fire-regime and stewardship framework for Eswatini, a topographically compressed southern African country where protected areas, communal rangelands, cropland margins, plantation landscapes and peri-urban interfaces occur in close proximity. Global Fire Atlas event histories for 2001–2025 were organised by fire year and intersected with approximately 10 km2 hexagonal units. The burned-area rate, event frequency, recurrence, seasonality, large-fire dominance, pyrodiversity and trend were used to classify fire-regime types independently of socio-ecological predictors. An XGBoost regression model, evaluated on a 20% held-out test set, was interpreted using exact TreeSHAP diagnostics. Fire activity was strongly seasonal: July–September accounted for 78.2% of the burned area, with August alone accounting for 34.2%. Eight fire-regime types were identified, ranging from low-information and episodic units to frequent small-fire mosaics, large-fire-dominated areas and emerging burned-area intensification regimes. The burned-area-rate model performed well on held-out data (R2 = 0.71; Spearman rho = 0.75). Human modification, goat density, elevation, forest probability, fuelwood dependence and precipitation seasonality ranked among the most influential predictors, but their fitted effects were non-linear and often bidirectional. The combined diagnostics supported six adaptive management zones covering protected-area stewardship, conservation-sensitive management, settlement–livelihood interfaces, late-season risk reduction, monitoring and integrated landscape management. Although the Eswatini results are context-specific, the workflow offers a transferable way to connect fire histories, socio-ecological contexts and place-based stewardship in African mosaic landscapes.
]]>Authors: Jinrui Deng Jianfeng Li Yang Cao Bingcai Sun Yinghua Jing Shengli Chu
For gas leakage monitoring in obstacle environments such as oil and gas stations, the layout of fixed sensors directly affects the validity of monitoring data and the accuracy of subsequent leakage source localization. To achieve effective coverage of high-risk areas with a limited number of sensors and reduce deployment costs, this paper proposes a multi-objective optimization method for sensor layout based on the non-dominated sorting genetic algorithm-II (NSGA-II). Based on multi-scenario computational fluid dynamics simulation data, the peak concentration, hazardous concentration duration, and leakage probability at each monitoring point are extracted as risk characteristic indicators. The NSGA-II analytic hierarchy process is employed to determine the weight of each indicator, and a comprehensive risk classification model for the monitored area is established. This is adopted for solution seeking. Through non-dominated sorting and crowding distance calculation, the Pareto optimal front is searched in the solution space. The optimized layout scheme is applied to the leakage source term estimation based on particle filter, and the performance of different layout schemes is compared and analyzed with the source localization error as the evaluation index. Case studies show that the sensor layout optimized by the non-dominated sorting genetic algorithm achieves effective coverage of high-risk areas. With the same number of sensors, its high-risk area coverage rate outperforms that of the multi-objective particle swarm optimization algorithm (MPSOA). Following the application of the optimized layout, the localization accuracy of leakage source term estimation is significantly improved. Compared with the traditional grid and circular layouts, the source localization error is reduced by approximately 44%. Compared with the layouts optimized by the MPSOA and genetic algorithm (GA), the error is decreased by 30.4% and 33.3%, respectively. The proposed sensor layout optimization method based on the NSGA-II can effectively balance monitoring coverage and economic cost, and significantly improve the localization accuracy of gas leakage sources. This study provides a theoretical basis and technical support for the optimal deployment of fixed gas sensor networks in complex scenarios.
]]>Authors: María Alicia Arcos Ángel Balaguer-Beser Luis Á. Ruiz José L. Soriano-Sancho
Live fuel moisture content (LFMC) is a key determinant of fuel flammability and forest fire danger; however, its operational monitoring remains challenging due to the limited spatial and temporal coverage of field measurements. This study aims to assess the operational suitability of a Random Forest-based methodology for LFMC estimation by extending a previously validated local-scale approach to a regional and multi-year context. Weighted average LFMC was modeled across 67 shrubland plots in the Valencian Region (eastern Spain) from 2017 to 2025 using Sentinel-2 spectral indices and aggregated meteorological variables consistent with prior research. Model performance was evaluated under spatially independent and combined spatio-temporal training–testing scenarios designed to approximate real-world wildfire monitoring conditions. Results show that the model exhibits good spatial transferability when applied to shrubland plots not used during training within the same temporal domain, while temporal extrapolation is more limited and dependent on the stability of climatic conditions represented in the training data, with a marked decline in performance under changing temperature and precipitation regimes. These findings highlight key drivers of LFMC prediction, identify validation strategies under operational constraints, and contribute to the development of scalable monitoring approaches for wildfire danger assessment and fuel management in Mediterranean shrublands.
]]>Authors: A. Maleah Winkler Andrew R. Moore William R. Kinnaird
Firefighters often perform multiple consecutive bouts of high-intensity work in hot environments, which can lead to physiological fatigue and increased health risks. This study examined changes in core temperature, skin temperature, and heart rate during recovery periods following repeated bouts of work in recruit firefighters (n = 10) across a full day of outdoor training. Participants completed four work–rest cycles consisting of firefighting drills performed in full personal protective equipment (PPE), followed by passive recovery after PPE removal. Physiological measurements were recorded one minute prior to recovery and then at 5, 10, and 20 min throughout recovery. Skin temperature and heart rate decreased significantly (p < 0.05) within 5–10 min of recovery in most rounds. However, core temperature required at least 20 min to significantly decline (p < 0.05). These findings suggest that shorter recovery periods may be sufficient for heart rate and skin temperature to return to baseline, whereas longer recovery periods are needed for heat to dissipate from the core, especially as work intensity increases. Thus, standard rehabilitation protocols may be insufficient under more extreme working conditions and should be adjusted accordingly to ensure firefighter safety.
]]>Authors: Duckha Jeon Woodam Chung Geonho Kim Byung-Doo Lee Chun Geun Kwon Hee-Young Ahn Ye-Eun Lee Hee Han
The Republic of Korea experiences over 500 forest fires annually, consuming more than 4000 ha. Helicopters are the primary resource for initial attack, but effectively dispatching these limited resources during multiple simultaneous fires poses a significant challenge, as these incidents compete for the same pool of helicopter resources. To support real-time, operational-level helicopter dispatch decisions, an interactive decision support framework was developed that integrates information gathering, fire prioritization, and dispatch optimization. This framework employs an integer linear programming (ILP) approach to minimize the weighted sum of suppression costs and resulting burn perimeters, while allowing for uncontained fires when fire spread rates exceed the cumulative suppression capacity of available helicopters. The framework was applied to two test cases: (1) five hypothetical simultaneous fire incidents, and (2) four actual simultaneous fire incidents recorded on 22 March 2025, with the resulting solutions compared against manual dispatch decisions made by the Korea Forest Service (KFS). The results demonstrate the framework’s capability to analyze diverse fire suppression scenarios and generate a range of effective dispatch options. By integrating real-time fire behavior simulation and optimization, incorporating fire damage potential, and replicating the Republic of Korea’s unique suppression practices, this framework aims to enhance real-time helicopter dispatch decision-making, contributing to the KFS’s ongoing efforts to integrate scientific knowledge into forest fire suppression and management.
]]>Authors: Sai Yao Zilong Liang Zixuan Zhang Suqin Chen Lijing Wang Mingchao Wang Haijun Zhang
Monnex has become the most efficient dry powder extinguishing agent due to its unique fire extinguishing mechanism—the “burning fragmentation” phenomenon. To study the fire extinguishing mechanism of Monnex in detail and elucidate the process of its “burning fragmentation” phenomenon, we have examined the microstructure changes and compositions of Monnex powder during its thermal decomposition process. The results indicate that Monnex undergoes complex iterative reactions and produces explosive intermediates (NH4NO3, KCN, and KN3) when entering the fire. Upon reaching the temperature of 240 °C, the explosive substance is completely pyrolyzed and undergoes a mini- burning fragmentation, resulting in the decomposition of Monnex powder into particles and the release of a large amount of inert gases and free radicals. This is the reason why Monnex has become an optimal dry powder. Toxic substances KCN and KOCN were found during the whole pyrolysis process, so personal protection should be paid attention to in practical applications. Our research not only improves the understanding of the Monnex fire extinguisher, but also provides important scientific evidence for the development of fire extinguishing technologies and environmentally friendly fire protection materials.
]]>Authors: Jiaxu Pei Ruihuan Zhang Hualong Yan Yulu Hao Yu Huang Jin Xiao
Accurate detection in the early stages of a fire is a crucial prerequisite for the efficient implementation of fire suppression and emergency rescue operations. Its accuracy and timeliness directly affect the control of disaster loss severity. Traditional fire detection methods mainly include three categories, which are manual inspection, sensor detection, and visual recognition. However, manual inspection is restricted by labor costs and time efficiency, making it difficult to achieve large-scale, high-frequency and real-time fire monitoring. Sensor detection is easily interfered by environmental factors such as temperature, humidity, and dust, leading to frequent false alarms and missed alarms. Visual recognition technology has shortcomings in aspects such as detailed feature perception, dynamic scene modeling, and reasoning robustness in complex environments, making it difficult to meet the requirements of high-precision detection. To address these issues, this study innovatively proposes a lightweight fire and smoke detection model based on semantic enhancement and frequency domain perception modeling, which is named the SemaFire you only look once (SemaFire-YOLO) model. The model constructs a large language and vision assistant (LLaVA) semantic guidance module, which uses a large language model to understand and guide the semantic features of images, thereby enhancing the saliency representation intensity of small and weak target regions. Then, a Haar wavelet-based downsampling module is adopted, which compresses spatial information while preserving high-frequency features such as flame edges and smoke textures, improving the accuracy of target recognition. Next, the convolution modulation mechanism is introduced to replace the traditional attention mechanism, enhancing the overall modeling efficiency and reducing computational overhead. Finally, a Dynamic Tanh normalization module is adopted to replace the batch normalization module in the traditional YOLO algorithm, strengthening the model’s representation stability and reasoning robustness under unstable input distributions. Experimental results show that the SemaFire-YOLO model achieves a mean average precision (mAP@0.5) of 64.30% on the fire image dataset, which is 0.8, 2.0, 0.6, and 3.8 percentage points higher than that of mainstream models such as YOLOv5n, YOLOv8n, YOLOv11n, and YOLOv12n, respectively. It exhibits better boundary detection capability and practical deployment potential. Through visual analysis, the results indicate that the improved SemaFire-YOLO model achieves more accurate detection and higher confidence in actual complex scenarios, further verifying the model’s robustness and accuracy in complex scenarios such as low contrast and dynamic fire conditions.
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