Fire

Understanding the dynamics of fire propagation is essential in improving predictive models and developing effective fire management strategies. This study applies computer vision techniques to complement traditional fire behaviour modelling. We employ the Segment Anything Model to achieve the accurate segmentation of experimental fire videos, enabling the frame-by-frame segmentation of fire perimeters, quantification of the rate of spread in multiple directions, and explicit analysis of slope effects. Our laboratory experiments reveal that the ROS increases exponentially with slope, but with coefficients differing from those prescribed in the Canadian Fire Behaviour Prediction System, reflecting differences in field conditions. Complementary field data from prescribed burns in coniferous fuels (C-7) further demonstrate that slope effects vary under operational conditions, suggesting field-dependent dynamics not fully captured by existing deterministic models. Our experiments show that, even under controlled laboratory conditions, substantial variability in spread rate is observed, underscoring the inherent stochasticity of fire spread. Together, these findings highlight the value of vision-based perimeter extraction in generating precise spread data and reinforce the need for probabilistic modelling approaches that explicitly account for uncertainty and emergent dynamics in fire behaviour. Full article

To conduct an in-depth analysis of safety risks in small-scale business premises, this study employed field research to examine small restaurants, small supermarkets, convenience stores, and small hotels within a certain urban area. The investigation identified several critical safety issues across different types of establishments. In small restaurants, major concerns included inadequate emergency response capabilities among responsible personnel, insufficient fire separation between kitchen areas with open flames and public dining zones, as well as missing or malfunctioning emergency lighting and evacuation signage. Small supermarkets and convenience stores exhibited non-compliant electrical wiring installations and absent or defective fire extinguishing equipment. In small hotels, prevalent risks involved the lack of emergency escape respirators in guest rooms, the failure to install fire-rated doors in linen storage areas, and obstructed evacuation pathways due to clutter. Based on these findings, the study proposes practical countermeasures and recommendations aimed at enhancing safety standards in such premises. Full article

There is an urgent and constant need for land reclamation and to restore self-sustaining, stable, and resilient ecosystems. It is necessary to enhance the frequency, consistency, and success rates of applying native plant seed for ecological restoration. Smoke-water can affect seed germination of plants, regardless of whether they occur in fire-prone ecosystems. Germination trials of 18 native species of Indigenous value in the southern interior grasslands of British Columbia, Canada were conducted using a smoke aqueous solution. Locally sourced parent plant material was burned to produce smoke-water. Seeds were collected from multiple populations of the species across a wide geographic range within the B.C. southern interior to increase the genetic diversity of the seed stock. Seeds were soaked in smoke aqueous solution in various concentrates, including 0% (control), 1% (1:100), 10% (1:10), 20% (1:5), and 100%. The results indicate that germination rates in the presence of smoke-water are species-specific. Five species showed an increase in germination with smoke-water (Erythronium grandiflorum, Calochortus macrocarpus, Arnica latifolia, Lomatium nudicaule, and Shepherdia canadensis); four species showed no change (Rosa woodsii, Crataegus douglasii, Lewisia rediviva, and Prunus virginiana); and nine species showed some level of decrease (Fritillaria affinis, Fritillaria pudica, Berberis aquifolium, Claytonia lanceolata, Gaillardia aristate, Balsamorhiza sagittata, Allium cernuum, Amelanchier alnifolia, and Lomatium macrocarpum). Smoke-water also affected germination rate by plant form (herbs > shrubs), plant phenology (spring ephemeral and protracted > summer quiescent and summer mature) and plant dispersal mechanism (wind > animal). The treatments applied to encourage the germination of seeds from interior grassland forbs and shrubs have demonstrated that smoke-water can effectively break dormancy and enhance the germination rate from certain native plant species. Full article

Soundproof enclosures are essential components in ultra-high voltage converter transformer equipment. However, conventional designs pose considerable fire risks, as they may impede fire suppression efforts in case of equipment failure. This study adopted a multi-technique experimental strategy to systematically evaluate the influence of flexibilizer content on the thermal and combustion properties of soundproof enclosures. The methodology combined scanning electron microscopy and thermogravimetric analysis, cone calorimetry and thermal deformation tests. Subsequently, the entropy method was applied to quantify comprehensive fire risk based on the experimental data. The results showed that incorporation of a flexibilizer reduced thermal stability, evidenced by a decrease in the initial pyrolysis temperature from 570 K to 505–545 K at a heating rate of 5 K/min. As flexibilizer content increased, the activation energy (E_α) exhibited a pattern of initial decrease, followed by an increase, and then a subsequent decrease, with most samples exhibiting Eα values below 250 kJ/mol. Simultaneously, flexibilizer addition improved critical fire safety parameters, including reduced heat release rate, total heat release, smoke production, CO₂ release rate, mass loss rate, thermal deformation temperatures, and increased CO release rate. The comprehensive fire risk score decreased significantly from 0.2801 to a range of 0.1147–0.2522 after the addition of the flexibilizer. Thus, this study provides a quantitative assessment of fire safety in ultra-high voltage converter transformer equipment through risk evaluation, offering valuable insights for developing safer enclosure materials. Full article

Forest fire risk assessment methodologies vary considerably, presenting challenges for adaptation to specific local contexts. This study provides a systematic analysis of forest fire assessment approaches across the Mediterranean basin, American, African, and Asian regions through a comprehensive review of 112 peer-reviewed studies published from 2015 to 2025. Statistical significance testing (Chi-square tests, p < 0.05) confirmed significant regional variation in methodological preferences and indicator usage patterns. Key findings revealed that Multi-Criteria Decision Analysis dominates the field (44% of studies, n = 49), with Analytical Hierarchical Process being the most utilized method (39 studies). Machine learning approaches represent 25% (n = 28), with Random Forest leading significantly (22 applications). The analysis identified 67 indicators across seven major categories, with topographic factors (slope: 105 studies) and anthropogenic indicators (road networks: 92 studies) showing statistically significantly highest usage rates (p < 0.001), representing a statistically significant critical gap in vulnerability assessment (p < 0.01). Organizational factors remain severely underrepresented (a maximum of 14 studies for any factor), representing a statistically significant critical gap in risk assessments (p < 0.01). Statistical analysis revealed that while Mediterranean approaches excel in integrating historical and cultural factors, American methods emphasize advanced technology integration, while Asian approaches focus on socio-economic dynamics and land-use interactions. This study serves as a foundation for developing tailored assessment frameworks that combine remote sensing analysis, ground-based surveys, and community input while accounting for local constraints in data availability and technical capacity. The study concludes that effective forest fire risk assessment requires a balanced integration of global best practices with local environmental, social, and technical considerations, offering a roadmap for future forest fire risk assessment approaches in different regions worldwide. Full article

The assessment of the economic vulnerability of natural disasters is a necessary step in the evaluation of any risks. This study proposes the approach implemented under the H2020 FirEurisk project to value the economic damage of wildfires on a European scale. Economic damage is assessed as the net value change in natural (agricultural and forestry resources and their ecosystem services) and manufactured assets under simulated fire intensity, taking into consideration the time necessary for natural capital to recover to the pre-damaged conditions. We show minimum, maximum, and average damage for European countries and map the critical areas. Damages to provisioning-ecosystem services are more pronounced in Central Europe because of the lower resilience of ecosystems compared to the Mediterranean, suggesting that mitigation measures (such as managing vegetation to reduce fuel; improving access to fire services; and engaging communities through education, agriculture, and forest management participation) must be enforced. We are confident that the approach proposed may stimulate further research to test the goodness of the estimates proposed and suggest where it is more appropriate to invest in fire prevention. Full article

Modular Integrated Construction (MiC) has been strongly promoted in many dense urban areas, including the Greater Bay Area. There might be an explosion risk if leaked flammable clean refrigerants accumulate in a confined unit. Experimental and modeling studies on the explosion of flammable refrigerant propane in an MiC unit were carried out with a rectangular unit model to explore well-covered or partially covered conditions, representing the scenario of an MiC unit with its door open or closed. The experimental results were used in developing an analytical model to predict the flame surface and pressure change, with acceptable results. This study could be used as a reference for estimating pressure changes and designing ventilation systems to prevent deflagration in MiC units. Full article

Conventional wildfire assessment products emphasize regional-scale ignition likelihood and potential spread derived from fuels and weather. While useful for broad planning, they do not directly support boundary-aware, scenario-specific decision-making for localized threats to communities in the Wildland–Urban Interface (WUI). This limitation constrains the ability of fire managers to effectively prioritize mitigation efforts and response strategies for ignition events that may lead to severe local impacts. This paper introduces WUI-BTI—a scenario-based, simulation-driven boundary-threat index for the Wildland–Urban Interface that quantifies consequences conditional on an ignition under standardized meteorology, rather than estimating risk. WUI-BTI evaluates ignition locations—referred to as Fire Amplification Sites (FAS)—based on their potential to compromise the defined boundary of a community. For each ignition location, a high-resolution fire spread simulation is conducted. The resulting fire perimeter dynamics are analyzed to extract three key metrics: (1) the minimum distance of fire approach to the community boundary ($D_{min}$) for non-breaching fires; and for breaching fires, (2) the time required for the fire to reach the boundary ($T_p$), and (3) the total length of the community boundary affected by the fire ($L_c$). These raw outputs are mapped through monotone, sigmoid-based transformations to yield a single, interpretable score: breaching fires are scored by the product of an inverse-time urgency term and an extent term, whereas non-breaching fires are scored by proximity alone. The result is a continuous boundary-threat surface that ranks ignition sites by their potential to rapidly and substantially compromise a community boundary. By converting complex simulation outputs into scenario-specific, boundary-aware intelligence, WUI-BTI provides a transparent, quantitative basis for prioritizing fuel treatments, pre-positioning suppression resources, and guiding protective strategies in the WUI for fire managers, land use planners, and emergency response agencies. The framework complements regional hazard layers (e.g., severity classifications) by resolving fine-scale, consequence-focused priorities for specific communities. Full article

Wildfires pose a regularly increasing threat to ecosystems and critical infrastructure. The severity of this threat is steadily increasing. The growing threat necessitates the development of technologies for rapid and accurate early detection. However, the prevailing fire point detection algorithms, including several deep learning models, are generally constrained by the inherent hard threshold limitations in their decision-making logic. As a result, these methods lack adaptability and robustness in complex and dynamic real-world scenarios. To address this challenge, the present paper proposes an innovative two-stage, semi-supervised anomaly detection framework. The framework initially employs a Transformer-based autoencoder, which serves to transform raw fire-free time-series data derived from satellite imagery into a multidimensional deep anomaly feature vector. Self-supervised learning achieves this transformation by incorporating both reconstruction error and latent space distance. In the subsequent stage, a semi-supervised XGBoost classifier, trained using an iterative pseudo-labeling strategy, learns and constructs an adaptive nonlinear decision boundary in this high-dimensional anomaly feature space to achieve the final fire point judgment. In a thorough validation process involving multiple real-world fire cases in Yunnan Province, China, the framework attained an F1 score of 0.88, signifying a performance enhancement exceeding 30% in comparison to conventional deep learning baseline models that employ fixed thresholds. The experimental results demonstrate that by decoupling feature learning from classification decision-making and introducing an adaptive decision mechanism, this framework provides a more robust and scalable new paradigm for constructing next-generation high-precision, high-efficiency wildfire monitoring and early warning systems. Full article

In this study, a McKenna burner made for calibration is used to generate the laminar flame with the equivalence ratio of 0.78~2.0. The effect of the downward water mist spray on the extinction of the methane–air premixed laminar flame is investigated using hydroxide planar laser-induced fluorescence (OH-PLIF). The variation of the water flow rate for flame extinction is analyzed by the hydroxyl radical concentration distribution and the effective water mist flow rate. The required water flow rate for flame extinction is higher in the cases of rich fuel mixtures. The maximum critical extinguishing water flow rate for the methane–air premixed laminar flame is about 9.55 L/min under the conditions of water mist spray with a 45° solid cone spray angle and a 24 μm droplet size. Furthermore, the evolution of OH-PLIF flame behavior revealed that the stability of the hydroxyl radical concentration at the base of the flame mainly contributed to the flame extinction. This study provides a theoretical reference for the critical extinguishing conditions of water mist in the application of an active fire suppression system. Full article

This study develops, implements, and evaluates the Firebrand Spotting parameterization within the WRF-Fire coupled fire–atmosphere modeling system. Fire spotting is an important mechanism characterizing fire spread in wind-driven events. It can accelerate the rate of spread and enable the fire to spread over streams and barriers such as highways. Without the capability to simulate fire spotting, wind-driven fire simulations cannot accurately represent fire behavior. In the Firebrand Spotting parameterization, firebrands are generated with a set of fixed properties, from locations vertically aligned with the leading fire line. Firebrands are transported using a Lagrangian framework accounting for particle burnout (combustion) through an MPI-compatible implementation within WRF-Fire. Fire spots may occur when firebrands land on unburned grid points. The parameterization is verified through idealized simulations and its application is demonstrated for the 2021 Marshall Fire, Colorado. The simulations are assessed using the observed fire perimeter and time of arrival at multiple locations identified from social media footage and official documents. All simulations using a range of ignition thresholds outperform the control without spotting. Simulations accounting for fire spots show more accurate fire arrival times (i.e., reflecting a better fire rate of spread), despite producing a generally larger fire area. The Heidke Skill Score (Cohen’s Kappa) for the burn area ranges between 0.62 and 0.78 for simulations with fire spots compared to 0.47 for the control. These results show that the parameterization consistently improves the fire forecast verification metrics, while also underscoring future work priorities, including advancing the generation and ignition components. Full article

Assessing the energy flux delivered to ecosystem components by wildfires is hard because of technical and safety problems in performing measurements during such events. Here, we present a laboratory and field experimental assessment of a new method of evaluating a wildfire energy flux; our approach is based on the fact that different types of trash deform at different temperatures. We produced deformed trash in a laboratory environment using an iCone calorimeter to deliver a range of heat fluxes over a range of durations. We followed this by placing trash in instrumented prescribed fires. We show that finding melted or heat-altered plastic bottles and aluminium cans in the aftermath of wildfires can provide useful information about the heating that they received during the fire: plastic bottles are a useful indicator for areas that received less than 2 MJ/m² with a maximal temperature of <200 °C, while aluminium cans may be applied to higher-energy sites 100 MJ/m² that experienced a temperature above 600 °C. We provide a semi-quantitative proxy guide as to what different observed deformations may indicate in terms of energy flux and hope that this may allow scientists and forest managers to easily and cheaply assess the energy flux delivered to ecosystems and semi-quantitatively compare different wildfires. Full article

The accurate computation of the thermophysical properties of gases and gas mixtures is critical for combustion analysis but remains challenging due to the precision and numerical stability required across wide temperature ranges. In this study, we present Thermophy, a computational framework based on Chebyshev polynomial fitting, developed to calculate thermal conductivity, viscosity, and binary diffusion coefficients for pure gases and multicomponent mixtures. Unlike conventional tools that rely on low-order polynomial approximations, Thermophy applies Chebyshev fitting over defined temperature intervals, enabling higher accuracy, improved numerical stability, and computational efficiency. Thermophy is validated through four case studies involving pure gases, binary mixtures, and ternary mixtures relevant to combustion applications. For pure gases and air, deviations in thermal conductivity and viscosity were found to be 1.22–4.25% and 0.11–4.71%, respectively. For ternary mixtures, viscosity deviations ranged from 0.11 to 0.24%, while binary mixtures showed deviations of 2.60% and 0.20% for viscosity and thermal conductivity, respectively. Binary diffusion coefficients exhibited an overall deviation of approximately 3.35%. The combination of flexible input handling, extensibility, and high-fidelity calculations positions Thermophy as a robust and efficient alternative for integration into combustion modeling and other gas-phase simulation frameworks, including gasification, pyrolysis, global carbon cycle analysis, environmental systems, and fire modeling. Full article

Grassland fire risk perception constitutes a fundamental element of fire risk assessment and underpins the evaluation of response capacities in grassland regions. This study examines Qinghai Province, the fourth-largest pastoral region in China, as a case study to develop an evaluation index system for assessing residents’ perceptions of grassland fire risk. Using micro-level survey data, the study quantifies these perceptions and applies a quantile regression model to investigate influencing factors. The results indicate that: (1) the average grassland fire risk perception index among residents in Qinghai Province’s grassland areas is 0.509, with response behaviors contributing the most and response attitudes contributing the least; (2) Residents in agricultural areas perceive higher risks than those in semi-agricultural/semi-pastoral or purely pastoral areas, and individuals in regions with moderate dependency ratios and moderate fire-susceptibility conditions demonstrate the highest performance, whereas those in pastoral and high-susceptibility zones exhibit signs of “risk desensitization”; (3) risk communication and information dissemination are the primary drivers of enhanced perception, followed by climate variables, whereas individual characteristics of residents attributes exert no significant effect. It is recommended to monitor the impacts of climate change on fire risk patterns, update risk information dynamically, address deficits in residents’ cognition and capabilities, strengthen behavioral guidance and capacity-building initiatives, and foster a transition from passive acceptance to active engagement, thereby enhancing both cognitive and behavioral responses to grassland fires. Full article

Against the background of the accelerating global transition towards a low-carbon energy system, the lithium-ion battery (LIB) industry has witnessed a rapid development. Concurrently, fire accidents in LIB application scenarios have occurred frequently, with safety issues becoming increasingly prominent. Thermal runaway of LIBs is the direct cause of such fires. During the thermal runaway process of LIBs, lithium salts in the electrolyte undergo thermal decomposition reactions with carbonate-based electrolytes, releasing a large amount of heat and fire gases. Among them, the thermal decomposition reactions of LiPF₆ with electrolytes are coupled and superimposed, exhibiting a significant synergistic effect. This paper employs quantum chemical calculation methods to investigate the thermal decomposition reaction mechanisms between PF₅ and POF₃, which generated from the thermal decomposition of LiPF₆ and carbonate-based electrolytes (EC, DMC, and DEC) during the thermal runaway process of LIBs; and presents detailed chemical reaction mechanism models. The P atoms in PF₅ or POF₃ combine with the O atoms of the ether oxygen groups in carbonates, while the F atoms combine with the C atoms adjacent to the ether oxygen groups. This promotes the ring-opening or chain scission of carbonate molecules, reduces the energy required for the reaction, and accelerates the thermal decomposition reaction and the generation of fire gases. Modification of EC, DMC, and DEC through fluorination can effectively inhibit the catalytic effect of PF₅ and POF₃ and improve the oxidation resistance and thermal stability of the electrolytes. Full article

In order to provide fire-scene parameters for fire protection design and data support for fire safety management of waiting halls in high-speed railway stations, this study systematically investigated the combustion characteristics of single, two, and three massage chairs using an industrial calorimeter. The results showed the following: The change in heat release rate in the growth stage of the massage chairs’ combustion tests was consistent with the t² fast fire (with a growth coefficient of 0.04689). The maximum HRR was 1.2 MW for the single-massage-chair combustion test, 2.5 MW for the two-massage-chairs combustion test, and 3.5 MW for the three-massage-chairs combustion test. In the full-scale massage chairs combustion test, setting a 6.0 m fire isolation zone could effectively serve the functions of fire prevention and heat insulation. Considering a certain safety margin, and with a safety factor of 1.5 adopted, it is recommended that a fire isolation zone with a width of 9.0 m be used in the waiting halls of high-speed railway stations, which provides a direct, actionable design basis for engineering practice. Full article

Sandwich panels are widely used in industrial roofing due to their lightweight and thermal insulation properties; however, their structural fire resistance remains insufficiently understood. This study presents a data-driven approach to predict the mid-span deformation of glass wool-cored sandwich roof panels subjected to ISO 834-5 standard fire tests. A total of 39 full-scale furnace tests were conducted, yielding 1519 data points that were utilized to develop deep learning models. Feature selection identified nine key predictors: elapsed time, panel orientation, and seven unexposed-surface temperatures. Three deep learning architectures—convolutional neural network (CNN), multilayer perceptron (MLP), and long short-term memory (LSTM)—were trained and evaluated through rigorous 5-fold cross-validation and independent external testing. Among them, the CNN approach consistently achieved the highest accuracy, with an average cross-validation performance of $R^2=0.91(\mathrm{mean}\mathrm{absolute}\mathrm{error}\left(\mathrm{MAE}\right)=4.40;\mathrm{root}\mathrm{mean}\mathrm{square}\mathrm{error}\left(\mathrm{RMSE}\right)=6.42)$, and achieved $R^2=0.76(\mathrm{MAE}=6.52,\mathrm{RMSE}=8.62)$ on the external test set. These results highlight the robustness of CNN in capturing spatially ordered thermal–structural interactions while also demonstrating the limitations of MLP and LSTM regarding the same experimental data. The findings provide a foundation for integrating machine learning into performance-based fire safety engineering and suggest that data-driven prediction can complement traditional fire-resistance assessments of sandwich roofing systems. Full article

Fire has had a profound impact on Australia’s landscapes and biodiversity since the late Tertiary. Indigenous (Aboriginal) people have lived in Australia for at least 65,000 years and fire is an integral part of their culture and cosmology. In 2015, an Indigenous cultural burn was undertaken by Banbai rangers at Wattleridge Indigenous Protected Area, New England Tablelands, NSW. We compared the impact of this burn on the composition, cover, abundance, and species richness of dry sclerophyll vegetation and fuel hazard, with a hazard reduction burn at nearby Warra National Park, using a Before-After-Control-Impact experimental design. Our study found that the low-severity cultural burn and moderate-severity hazard reduction burn reduced fuel loads but did not have a significant impact on the composition of the vegetation overall or the herb layer. The hazard reduction burn had a significant impact on shrub and juvenile tree (woody species) cover, while the abundance of woody species was significantly affected by both fires, with a mass germination of ‘seeder’ species, particularly after the cultural burn. The long unburnt fire regime at Wattleridge may have made the vegetation more responsive to fire than the more frequently burnt vegetation at Warra, through accumulation of seed in the seed bank, so that the patchy cultural burn had a greater impact on woody species abundance. In terms of ecological and bushfire management outcomes, this study provides evidence to support claims that Indigenous cultural burning decreases fuel loads, stimulates regeneration of shrubs and trees, and manages at a local, place-based scale. We recommend cultural burning as a key management tool across Indigenous Protected Areas and other land tenures, with its implementation monitored and adaptively managed through two-way science, to foster fire regimes that are both culturally and ecologically beneficial. This is a vital element of our resilience in the Pyrocene and a significant step toward decolonizing science and land management. Full article

A unified WebGIS platform for wildfire simulation and visualization is presented, integrating three coupled physical models: HDWind for wind field computation, PhyFire for wildfire spread, and PhyNX for smoke plume dispersion. The system includes preprocessing and postprocessing scripts that enable the efficient integration of meteorological and cartographic data and support the visualization of outputs such as burned areas, wind and smoke fields, and emission estimates. The platform is deployed through a WebGIS interface that supports both decoupled and coupled simulations, providing operational flexibility and reducing computational demands when needed. A real wildfire scenario is simulated to demonstrate system capabilities. The case study highlights the platform’s applicability in operational contexts, reinforcing its potential to evolve into an accessible and user-oriented environmental decision support system for wildfire management. Full article