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35 pages, 25548 KB

Open AccessReview

Passive Fire Prevention Intervention Mechanisms for Timber-Framed Buildings: A Systematic Review (2016–2026)

by Qingnian Deng, Jingwei Liang, Shihui Zhou, Zekai Guo, Liyan Niu, Yuhao Huang, Liang Zheng and Yile Chen

Fire 2026, 9(6), 265; https://doi.org/10.3390/fire9060265 - 22 Jun 2026

Viewed by 695

Abstract

Fire is the core safety threat to the survival and development of timber-framed buildings, and passive fire prevention intervention is the core foundation of fire protection systems for timber-framed buildings. Existing reviews suffer from limitations such as incomplete scenario coverage, insufficient breakdown of [...] Read more.

Fire is the core safety threat to the survival and development of timber-framed buildings, and passive fire prevention intervention is the core foundation of fire protection systems for timber-framed buildings. Existing reviews suffer from limitations such as incomplete scenario coverage, insufficient breakdown of intervention mechanisms, and a lack of methodological standardization. This study strictly followed the PRISMA 2020 systematic review guidelines, searching the relevant literature from January 2016 to April 2026 on the Web of Science, Scopus, and Science Direct databases. After standardized screening, 89 valid articles were finally included and a systematic study was conducted through bibliometric analysis, keyword visualization, and multi-dimensional classification coding. The results show that the number of publications in this field has been continuously increasing from 2016 to 2025, with China accounting for 31.46% of the total, ranking first globally. The study constructed a core intervention mechanism system for passive fire prevention in timber-framed buildings, covering four categories: intrinsic flame-retardant modification, isolation protection, structural optimization, and spatial control. The working principles, application effects, advantages and disadvantages, and engineering application scenarios of each mechanism were clarified. This study systematically sorts out the core intervention mechanisms of passive fire prevention in timber-framed buildings, clarifies the research status and development trends in this field, and can provide evidence-based support for the design optimization, technology development, and engineering practice of passive fire protection for timber buildings. Full article

(This article belongs to the Special Issue Current Advances in the Assessment and Mitigation of Fire Risk in Buildings and Urban Areas: 2nd Edition)

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46 pages, 1436 KB

Open AccessArticle

Pointy-Headed Fires: On the Convex Duality Between Fire Shapes and Spread Rates in Fire Growth Models

by Valentin Waeselynck and David Saah

Fire 2026, 9(6), 264; https://doi.org/10.3390/fire9060264 - 22 Jun 2026

Viewed by 663

Abstract

Background: Some widely used wildland fire behavior models, like the Fire Area Simulator (FARSITE), propagate fire fronts by computing the front-normal velocity (spread rate) as a function of local inputs and the front-normal direction. Such models are sometimes observed to cause the collapse [...] Read more.

Background: Some widely used wildland fire behavior models, like the Fire Area Simulator (FARSITE), propagate fire fronts by computing the front-normal velocity (spread rate) as a function of local inputs and the front-normal direction. Such models are sometimes observed to cause the collapse of crown fires into sharp wedge shapes that eliminate heading fire behavior. Aims: We set out to document this phenomenon and, more generally, understand the relationships between fire shapes and spread rate functions. Methods: The phenomenon is studied both mathematically and through simulation experiments. Non-smooth fire fronts are theorized mathematically by an Eikonal partial differential equation (

H (x, τ, D τ) = 1

), where the unknown

τ (x)

is the time-of-arrival function and the Hamiltonian

H (x, t, p)

is positively homogeneous and possibly non-convex in p; convex analysis is used to study viscosity solutions in constant conditions. Results: We show that a fire spread model preserves the smoothness of fire fronts if and only if it is equivalent to using the Huygens principle. Nontrivially, this is equivalent to a convexity criterion on the inverse spread rate profile, which is then the polar dual of the Huygens wavelet; this corresponds to Hamiltonian–Lagrangian duality. The relevance of smoothness-destroying models to crown fire is debated. Exact analytical formulas are derived for fire growth in constant conditions. Conclusions: Our understanding of fire spread models is improved by solving the spread equations in more general ways than previously known. In particular, the collapse of heading crown fires into sharp shapes is now explained. Smoothness-destroying spread models cannot be simulated by algorithms based on travel time like cellular automata; their general well-definedness remains an open question. Fire modelers can use these findings to guide their search for improved crown fire models, and more generally to verify the accuracy of numerical implementations. Full article

(This article belongs to the Section Mathematical Modelling and Numerical Simulation of Combustion and Fire)

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22 pages, 4690 KB

Open AccessArticle

Fire Risks over the Full Lifecycle of Low-Temperature Facilities: Characteristics, Challenges, and Hazard Identification

by Qirui Wang, Qinpei Chen, Xiaoying Zhang and Zhuoer Sun

Fire 2026, 9(6), 263; https://doi.org/10.3390/fire9060263 - 22 Jun 2026

Viewed by 550

Abstract

In recent years, the rapid expansion of low-temperature facilities—such as cold storage and indoor ice and snow venues—has underscored their pronounced vulnerability to fire, as evidenced by multiple severe incidents. Due to their distinct environmental conditions, existing theoretical frameworks, technical approaches, and standards [...] Read more.

In recent years, the rapid expansion of low-temperature facilities—such as cold storage and indoor ice and snow venues—has underscored their pronounced vulnerability to fire, as evidenced by multiple severe incidents. Due to their distinct environmental conditions, existing theoretical frameworks, technical approaches, and standards exhibit limited applicability. Consequently, the fire risk characteristics of such facilities remain insufficiently defined, and systematic methods for hazard identification and assessment are lacking. This study conducts a detailed analysis of fire incident data from representative low-temperature facilities to identify the fire risk characteristics across all lifecycle stages, including construction, renovation and expansion, operation, maintenance, and demolition. An integrated framework combining the WBS/RBS (Work Breakdown Structure/Risk Breakdown Structure) matrix and complex network (CN) methods is then proposed to establish a structured methodology for full lifecycle fire hazard identification and classification. The results address critical gaps, including the absence of clearly defined lifecycle fire risk profiles and a robust scientific basis for hazard identification, and provide a technical foundation for lifecycle fire risk management in low-temperature facilities. Full article

(This article belongs to the Section Fire Risk Assessment and Safety Management in Buildings and Urban Spaces)

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22 pages, 14528 KB

Open AccessArticle

Fire Heat and Ash Deposition Regulate Post-Fire Soil Bacterial Community Recovery and Predicted Function Potential

by Yu Sun, Zi-Hao Deng, Yao-Quan Yang, Xiao-Chao Pu, Li-Wei Li, Rong She and Xiao-Yan Yang

Fire 2026, 9(6), 262; https://doi.org/10.3390/fire9060262 - 18 Jun 2026

Viewed by 696

Abstract

Disentangling the combined effects of heat and ash in natural forest fires is challenging, hindering understanding of soil microbial post-fire responses. A 90-day simulated fire experiment with 16S rRNA sequencing monitored bacterial communities and functional potential in topsoil (0–10 cm) and subsoil (10–20 [...] Read more.

Disentangling the combined effects of heat and ash in natural forest fires is challenging, hindering understanding of soil microbial post-fire responses. A 90-day simulated fire experiment with 16S rRNA sequencing monitored bacterial communities and functional potential in topsoil (0–10 cm) and subsoil (10–20 cm) under seven treatments: blank control/BC, dry ash/DA, wet ash/WA, low-intensity heating/LH, high-intensity heating/HH, charcoal smoldering combustion/CSC, and Fire, with samples collected every ten days. Results: (1) α diversity declined mainly in the topsoil, with reductions of 12.04–19.82% for Shannon, 1.23–2.86% for Simpson, and 16.03–31.34% for the Chao index. Subsoil only declined under CSC. (2) Both heating and ash treatments increased the relative abundance of low-abundance and endemic taxa. Heating significantly enriched thermotolerant, xerotolerant, and oligotrophic taxa, such as Ramlibacter. (3) Topsoil heating treatments separated from BC (p ≤ 0.01), ash clustered with BC; pH and water content drove differentiation (p ≤ 0.05). (4) Topsoil predicted function potential showed early suppression (0–20 d), mid recovery (30–60 d), and late enhancement (70–90 d) for most treatments, except WA with sustained suppression. Heat determines disturbance depth and initial bacterial loss, while ash reshapes soil properties to influence community reassembly, acting as sequential but distinct environmental filters, providing a framework for post-fire bacterial community reorganization. Full article

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17 pages, 3513 KB

Open AccessArticle

Analysis, Characterization, and Mapping of Regional Wildfire Patterns in the Wildland–Urban Interface of the State of Tocantins, Brazil

by Izabella Downar Bakalarczyk, Mário Augusto Pires Vaz and Ygor Freitas de Almeida

Fire 2026, 9(6), 261; https://doi.org/10.3390/fire9060261 - 18 Jun 2026

Viewed by 657

Abstract

Mapping wildfire patterns in Wildland–Urban Interface (WUI) areas is a fundamental tool for fire management and prevention, particularly in regions where urban expansion occurs in close proximity to natural vegetation. This mapping approach makes it possible to identify critical zones and to support [...] Read more.

Mapping wildfire patterns in Wildland–Urban Interface (WUI) areas is a fundamental tool for fire management and prevention, particularly in regions where urban expansion occurs in close proximity to natural vegetation. This mapping approach makes it possible to identify critical zones and to support more effective interventions adapted to the specific conditions of each territory. This work analyzed wildfires in the state of Tocantins, Brazil, using detailed geospatial data and advanced analysis techniques and statistics to characterize the dynamics of burned areas. Data used for the project were retrieved from MapBiomas and the Geoprocessing Laboratory of the Public Ministry of Tocantins (LABGEO), applying logistic regression models to explore the relationship between the distance of WUIs and the frequency of wildfires. The methodology covered the spatial distribution of fires and the different dynamics observed by type and size of burned area, allowing for a more detailed analysis. The results indicated significant variations in the proportion of burned areas inside and outside the WUIs, suggesting that proximity to these interfaces plays a critical role in the occurrence pattern of fires. Notably, Palmas, the state capital, stood out as one of the municipalities with the highest concentration of impacts in WUI areas, highlighting the relevance of these zones in environmental risk management. The study emphasizes the importance of adopting regional approaches that consider local specificities in the management and prevention of wildfires. The integration of geospatial data with robust statistical methodologies can guide more effective management strategies, assisting in the planning of public policies adapted to the socio-environmental dynamics of Tocantins. Full article

(This article belongs to the Special Issue Machine Learning (ML) and Deep Learning (DL) Applications in Wildfire Science: Principles, Progress and Prospects (2nd Edition))

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19 pages, 13406 KB

Open AccessArticle

Flame Retardant Eco-Friendly Foams Derived from Partially Hydrolyzed Collagen, Ammonium Polyphosphate and Miscanthus Fibers

by Roland El Hage, Abdoulay Sadou Ahmadou Roufaou, Uriche Michael Nzouotoup, Placide Uwizeyimana and Rodolphe Sonnier

Fire 2026, 9(6), 260; https://doi.org/10.3390/fire9060260 - 16 Jun 2026

Viewed by 696

Abstract

There is growing interest in the development of sustainable thermal insulating materials from renewable resources, a strategy which can stand as an alternative to conventional petroleum-based insulating materials. In this study, bio-based porous insulating materials derived from partially hydrolyzed collagen (rabbit-skin) and containing [...] Read more.

There is growing interest in the development of sustainable thermal insulating materials from renewable resources, a strategy which can stand as an alternative to conventional petroleum-based insulating materials. In this study, bio-based porous insulating materials derived from partially hydrolyzed collagen (rabbit-skin) and containing ammonium polyphosphate (APP) as flame retardant and miscanthus fibers as reinforcement are prepared. Four freeze-dried formulations were prepared: pure partially hydrolyzed collagen (COL), partially hydrolyzed collagen with APP (COL-APP), partially hydrolyzed collagen with miscanthus particles (COL-M) and a ternary formulation that included both additives (Col-APP-M). The density, porosity, thermal conductivity, specific heat capacity, compressive mechanical properties and fire behavior were evaluated. The neat collagen foam had the lowest density (122 kg·m⁻³), highest porosity (91%), and lowest thermal conductivity (0.045 W·m⁻¹·K⁻¹). The addition of APP and/or miscanthus increased density and showed limited change in thermal conductivity, which remains comparable with insulating materials (0.0445–0.0510 W·m⁻¹·K⁻¹). Specific heat capacities of partially hydrolyzed collagen foams were also relatively high (1319–1390 J·kg⁻¹·K⁻¹) as compared to some other typical insulating materials. Mechanical experiments demonstrated that APP had considerably improved the compression stiffness and strength through the physical crosslinking and densification effects in the partially hydrolyzed collagen network. Analysis of fire behavior with both Pyrolysis Combustion Flow Calorimetry (PCFC) and cone calorimetry further indicated that the addition of APP yielded improved flame retardancy with a very low heat release. These results showed that partially hydrolyzed collagen-based foams reinforced by APP and lignocellulosic particles are sustainable thermal insulation materials with desired thermal performances, improved mechanical stability, and enhanced flame retardancy. Full article

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21 pages, 4711 KB

Open AccessArticle

An Integrated Model for Dam Evacuation Under Explosion-Induced Damage: Coupling Physical Damage and Crowd Behavior

by Hongpeng Qiu, Eric Wai Ming Lee, Lingling Hu and Xiangping Xian

Fire 2026, 9(6), 259; https://doi.org/10.3390/fire9060259 - 16 Jun 2026

Viewed by 725

Abstract

This study develops an integrated computational framework to assess the passage efficiency of a dam crest serving as a critical inter-regional corridor following a severe explosion event. The framework combines a physics-based damage model with an agent-based cellular automata (CA) approach that incorporates [...] Read more.

This study develops an integrated computational framework to assess the passage efficiency of a dam crest serving as a critical inter-regional corridor following a severe explosion event. The framework combines a physics-based damage model with an agent-based cellular automata (CA) approach that incorporates pedestrian behavioral heterogeneity. The damage model conceptualizes three concentric zones: a complete fragmentation zone (0–1.5 m) with total material disintegration, a primary damage zone (1.5–5 m) following an exponential decay in structural integrity, and a secondary damage zone (5–20 m) governed by a power-law attenuation of fragmentation effects. Pedestrian behavior is parameterized by the Allowable Conflict Coefficient (ACC), the inverse of interpersonal friction, and the Emergency Level (EL), which scales the desired velocity. Extensive simulations under stochastic and targeted impact scenarios reveal a consistent evacuation performance hierarchy: Center (C) > Bottom-Left (BL) > Top-Left (TL) > Bottom-Right (BR) ≈ Top-Right (TR). Exit-proximal damage (TR, BR) increased evacuation time by up to 85% compared with central impacts. Results demonstrate a strong coupling between physical friction and urgency: the “faster-is-faster” effect is maximized under low friction (high ACC), while high friction not only suppresses the benefits of elevated EL but can also induce “faster-is-slower” phenomena under extreme conditions. These findings underscore that optimal evacuation strategies depend critically on both impact location and crowd behavior management, providing actionable insights for emergency planning and highlighting the importance of conflict mitigation in enhancing infrastructure resilience. The proposed framework thus offers a versatile and validated simulation tool for emergency planners to proactively assess and optimize evacuation strategies under various damage scenarios. Full article

(This article belongs to the Special Issue Behavioral Research on Fire Evacuation and Decision-Making Processes)

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30 pages, 21352 KB

Open AccessArticle

Early Visible Greenness Change in Forest Burned Areas Across Burn Severity and Mountainous Topography Using UAV RGB Imagery

by Qinyan Gu, Chao Xi, Weili Kou, Zhengshen Huang, Jiangxia Ye and Qiuhua Wang

Fire 2026, 9(6), 258; https://doi.org/10.3390/fire9060258 - 16 Jun 2026

Viewed by 686

Abstract

Understanding post-fire visible greenness change is important for assessing spatial heterogeneity in mountainous burned landscapes, but satellite observations often cannot capture local variation. This study developed a workflow using Unmanned Aerial Vehicle (UAV) Red–Green–Blue (RGB) imagery for RGB-interpreted burn severity classification and Green [...] Read more.

Understanding post-fire visible greenness change is important for assessing spatial heterogeneity in mountainous burned landscapes, but satellite observations often cannot capture local variation. This study developed a workflow using Unmanned Aerial Vehicle (UAV) Red–Green–Blue (RGB) imagery for RGB-interpreted burn severity classification and Green Leaf Index (GLI)-derived visible greenness change analysis three years after fire. The workflow integrated object-based Random Forest (RF) classification, bi-temporal GLI difference (

Δ

GLI) detection, and terrain-stratified analysis under RGB-only conditions. Object-based multi-feature representation, including a 41-dimensional (41D) feature set of color, texture, and gradient metrics, supported local burn severity mapping, although performance gain over the 23-dimensional (23D) set was modest and not statistically significant. The burned area was dominated by high and moderate severity classes. GLI-derived analysis showed limited visible greenness increase (mean

Δ

GLI = 0.0058), with slightly more than half of pixels being positive; high severity areas had higher

Δ

GLI, while low severity areas showed limited or negative values.

Δ

GLI also varied across terrain, being higher on steeper slopes, mid-to-upper elevations, and east-facing aspects. The workflow provides a practical local-scale approach for post-fire analysis using high-resolution UAV RGB imagery, with results interpreted as case-specific visible greenness patterns rather than comprehensive ecological recovery. Full article

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27 pages, 4196 KB

Open AccessArticle

A Forest Fire Risk Assessment Model Integrating Multi-Source Data and Human Factors and Its Application in Beijing

by Hui Zhang, Lifu Shu, Qifei Wang, Mingyu Wang and Wanzhou Chen

Fire 2026, 9(6), 257; https://doi.org/10.3390/fire9060257 - 15 Jun 2026

Viewed by 651

Abstract

This study, based on multi-source data fusion and risk index models, has developed a comprehensive methodological system for evaluating the risk of forest fires caused by human factors. The system starts with four dimensions, i.e., exposure, hazard factors, vulnerability, and prevention and control [...] Read more.

This study, based on multi-source data fusion and risk index models, has developed a comprehensive methodological system for evaluating the risk of forest fires caused by human factors. The system starts with four dimensions, i.e., exposure, hazard factors, vulnerability, and prevention and control capabilities, and constructs an evaluation framework with 19 secondary indicators. It also establishes single-category risk index models for four types of dominant fire sources: agricultural activities, religious ceremonies, tourism, and power distribution lines. Through weighted synthesis and exponential smoothing algorithms, it achieves daily dynamic risk forecasting. The research took the typical forest areas in the Mentougou, Changping, and Yanqing districts of Beijing as the application demonstration areas, collecting meteorological data, geographic information data, risk census ledgers, online hiking trajectories, and 2530 social survey questionnaires to complete the local parameter calibration and validation of the model. The retrospective analysis of 22 typical human-caused fire cases from 2018 to 2025 shows that the risk percentile of the ignition points in all cases was above 87.8%, indicating that the model has a good risk identification capability. Based on the evaluation results, differentiated control measures for different types of fire sources were proposed. The research results have been integrated into Beijing’s forest fire risk monitoring and early warning system, providing a scientific tool for the refined management of human-caused fire sources. Full article

(This article belongs to the Special Issue Integrating AI and Remote Sensing for Monitoring and Mapping Fire Impacts on Agroforestry and Wildlife Systems)

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20 pages, 8937 KB

Open AccessArticle

A Forest Fire Risk Prediction Framework Based on Machine Learning Models in the Greater Khingan

by Heng Li, Jialong Zhang, Jingwen Yang, Chenkai Teng, Kai Luo and Kaiping Sun

Fire 2026, 9(6), 256; https://doi.org/10.3390/fire9060256 - 15 Jun 2026

Viewed by 605

Abstract

The Greater Khingan, a key cold-temperate coniferous forest region in northern China, is frequently affected by forest fires with severe ecological and economic impacts. The study investigates the influence of key environmental and anthropogenic drivers on forest fire susceptibility and evaluates multiple machine-learning [...] Read more.

The Greater Khingan, a key cold-temperate coniferous forest region in northern China, is frequently affected by forest fires with severe ecological and economic impacts. The study investigates the influence of key environmental and anthropogenic drivers on forest fire susceptibility and evaluates multiple machine-learning approaches for regional fire assessment. Using 2001–2018 fire point data and multi-source remote sensing data, we integrated 13 driving factors across four dimensions: meteorology, topography, vegetation, and human activities. Collinear variables were screened using the Variance Inflation Factor (VIF). Three machine learning models—Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM)—were constructed to assess the long-term potential risk of forest fire occurrence. Driving mechanisms were analyzed using standardized regression coefficients and the SHapley Additive exPlanations (SHAP) interpretable algorithm, and spatial distribution maps of regional forest fire risk were generated based on the optimal model. Among the three models, RF achieved the highest predictive accuracy, with an accuracy of 0.919 and an Area Under the Receiver Operating Characteristic Curve (AUC) of 0.966, significantly outperforming LR and SVM. SHAP analysis reveals that forest fires are primarily driven by climatic factors (Pres and Prec as core drivers), regulated by topographic factors, and weakly affected by human factors. The proposed framework provides an effective tool for long-term forest fire susceptibility assessment by combining robust predictive performance with interpretable model outputs. The findings provide scientific support for long-term strategic forest fire risk zoning, regional firefighting resource allocation, and the formulation of differentiated prevention and control strategies, and also offer methodological references for forest fire prediction in other cold-temperate forest regions in China. Full article

(This article belongs to the Special Issue Machine Learning (ML) and Deep Learning (DL) Applications in Wildfire Science: Principles, Progress and Prospects (2nd Edition))

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14 pages, 3727 KB

Open AccessArticle

Research on Aircraft Fire Detection Method Based on IATF-YOLO

by Wei Zhang, Kai Wang and Xiaosong Song

Fire 2026, 9(6), 255; https://doi.org/10.3390/fire9060255 - 15 Jun 2026

Viewed by 495

Abstract

Aircraft cargo compartment fires constitute a significant type of aviation fire, posing a grave threat to aviation safety. To guard against and respond to such fires, existing aircraft cargo compartments are equipped with smoke detection fire detectors, which rely on perceiving changes in [...] Read more.

Aircraft cargo compartment fires constitute a significant type of aviation fire, posing a grave threat to aviation safety. To guard against and respond to such fires, existing aircraft cargo compartments are equipped with smoke detection fire detectors, which rely on perceiving changes in smoke transmittance to determine the onset of a fire. However, these detectors offer relatively low recognition accuracy and cannot provide a direct visual representation of the fire. In this work, we introduce a fire recognition method built on image sensors and a deep learning model. In light of the irregular shapes of flames and smoke, an improved interactive triplet attention mechanism (ITAM) is integrated into the You Only Look Once version 5 (YOLOv5) model, enhancing the model’s recognition accuracy. Furthermore, the original Neck structure is replaced with an Asymptotic Feature Pyramid Network (AFPN), improving the model’s ability to recognize small targets, which is particularly useful for detecting flames and smoke early in a fire. This paper further improves the model’s recognition accuracy by introducing the Focaler-IoU loss function, which balances the feature learning of hard and easy samples. Therefore, the network model in this paper is named IATF-YOLO. Ablation experiments demonstrate that our algorithm improves accuracy by 2%, while comparative experiments with several mainstream baseline models show that our algorithm achieves a 0.7% accuracy improvement, with a final peak accuracy of 93.6%. Full article

(This article belongs to the Special Issue Relevance and Applicability of AI for Fire Engineering)

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22 pages, 6871 KB

Open AccessArticle

Thermal Damage Evolution and Structural Response of Transmission Tower Legs Under Localized Wood-Crib Fire Exposure

by Haiwen Xu, Daochun Huang, Peng Li, Xincheng Quan and Tianhao Peng

Fire 2026, 9(6), 254; https://doi.org/10.3390/fire9060254 - 14 Jun 2026

Viewed by 560

Abstract

Wildfires can threaten the safety of transmission towers by degrading galvanized coatings and reducing the load-bearing capacity of steel members exposed to elevated temperatures. This study investigates the thermal damage evolution and structural response of transmission tower legs under localized wood-crib fire exposure [...] Read more.

Wildfires can threaten the safety of transmission towers by degrading galvanized coatings and reducing the load-bearing capacity of steel members exposed to elevated temperatures. This study investigates the thermal damage evolution and structural response of transmission tower legs under localized wood-crib fire exposure through a combined experimental and numerical approach. A 1:4 scale tower-leg model was subjected to a single wood-crib fire exposure for approximately 20 min, during which temperature histories, surface damage patterns, and deformation of the fire-exposed members were recorded. The results show that the maximum measured temperature reached 803 °C and decreased approximately linearly with height, leading to distinct damage zones along the tower leg. The galvanized coating exhibited progressive degradation, including oxidation, melting, cracking, and local peeling, while the surface appearance changed from bright silver to black and finally to gray-white with reddish-brown areas in severely heated regions. A temperature-informed elastic–plastic finite element model was then used to interpret the global structural response. The analysis indicates that elevated temperature reduced the stiffness and load-bearing capacity of the fire-exposed side, causing deformation concentration and torsional distortion in diagonal members. The proposed framework provides a practical basis for post-fire damage identification and rapid structural assessment of transmission towers in wildfire-prone regions. Full article

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19 pages, 20790 KB

Open AccessArticle

Coal Spontaneous Oxidation Mechanism of Low-Molecular Compounds: Pentanol

by Tianyi Yang, Xiaobo Wang, Wenhao Deng, Sichen Liu, Hanzhong Deng and Yafei Shan

Fire 2026, 9(6), 253; https://doi.org/10.3390/fire9060253 - 13 Jun 2026

Viewed by 576

Abstract

Coal spontaneous combustion (CSC) remains a major hazard in coal mining. Research on CSC has largely focused on macromolecular structures, while the behavior of low-molecular-weight compounds remains unclear. Using B3LYP/6-311G density functional theory, this study systematically reveals thirteen microscopic reaction pathways, active sites, [...] Read more.

Coal spontaneous combustion (CSC) remains a major hazard in coal mining. Research on CSC has largely focused on macromolecular structures, while the behavior of low-molecular-weight compounds remains unclear. Using B3LYP/6-311G density functional theory, this study systematically reveals thirteen microscopic reaction pathways, active sites, and the energy barrier order of pentanol during coal spontaneous combustion. The oxidation proceeds via thirteen multi-step pathways involving bond breaking and formation, with the dominant reaction being oxygen attack on the -CH₂OH group to produce pentanal (CH₃CH₂CH₂CH₂CHO) and water as the main products. The priority order of thirteen reaction pathways between pentanol and oxygen was established as: Path 6 > Path 3 > Path 8 > Path 5 > Path 4 > Path 1 > Path 11 > Path 10 > Path 9 > Path 12 > Path 7 > Path 2. The results reveal the multi-step bond-breaking and formation mechanism at the molecular level, providing a fundamental theoretical framework for understanding the radical chain oxidation mechanism of low molecular weight compounds in CSC. Full article

(This article belongs to the Special Issue Fire Risk Management and Emergency Prevention)

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20 pages, 4061 KB

Open AccessArticle

Experimental Investigation on Liquid Film Dynamics and Fire Suppression Performance of Free Water Jets Impinging on Insulated Vertical Façades

by Chao Ji, Qi Wang, Pengfei Wang and Jingjing Li

Fire 2026, 9(6), 252; https://doi.org/10.3390/fire9060252 - 12 Jun 2026

Viewed by 579

Abstract

To improve the efficiency of jet-based fire suppression for high-rise building façade fires, this study experimentally investigates the liquid film formation characteristics and fire suppression behavior of water jets impinging on insulated vertical surfaces. The effects of operating pressure (flow rate), nozzle-to-wall distance, [...] Read more.

To improve the efficiency of jet-based fire suppression for high-rise building façade fires, this study experimentally investigates the liquid film formation characteristics and fire suppression behavior of water jets impinging on insulated vertical surfaces. The effects of operating pressure (flow rate), nozzle-to-wall distance, and jet inclination angle on liquid film spreading morphology, wetted area, and effective water supply rate are systematically analyzed. The results show that increasing the flow rate significantly enlarges the wetted area, while reducing the effective water supply rate. As the nozzle-to-wall distance increases, the liquid film gradually develops a “top-wide and bottom-narrow” morphology. Although increasing the jet inclination angle decreases the wetted area, it enhances the continuity and stability of wall-adhering liquid film flow, thereby improving cooling efficiency near the flame root region. During the fire suppression experiments, low-flow-rate jets exhibit insufficient suppression stability, whereas high-flow-rate horizontal jets are capable of suppressing the flame to a residual burning state near the bottom of the façade. Further increasing the jet inclination angle enables complete flame extinguishment. This study reveals the relationship between jet parameters, liquid film behavior, and fire suppression performance, providing experimental evidence for the optimization of jet-based façade fire suppression strategies. Full article

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28 pages, 43455 KB

Open AccessArticle

Thermal Protection and Combustion Behavior of Intumescent-Coated Cross-Laminated Timber in Encapsulated Sandwich Wall Assemblies Under Medium-Scale Radiant Exposure

by Ľudmila Tereňová, Andrea Majlingová, Eva Mračková, Iveta Mitterová and Viktória Barna

Fire 2026, 9(6), 251; https://doi.org/10.3390/fire9060251 - 12 Jun 2026

Viewed by 489

Abstract

Cross-laminated timber (CLT) is increasingly used in multi-story timber construction, but its combustible nature requires reliable fire protection, particularly in layered wall assemblies with concealed cavities. This study compares two medium-scale cross-laminated timber (CLT) sandwich wall assemblies exposed to radiant heat flux of [...] Read more.

Cross-laminated timber (CLT) is increasingly used in multi-story timber construction, but its combustible nature requires reliable fire protection, particularly in layered wall assemblies with concealed cavities. This study compares two medium-scale cross-laminated timber (CLT) sandwich wall assemblies exposed to radiant heat flux of 20 kW/m² for 90 min: an uncoated reference assembly and an assembly with PROMADUR^® intumescent coating applied to the CLT surfaces. Both specimens consisted of a 90 mm three-ply CLT panel encapsulated with 12.5 mm gypsum-fiber boards fixed to a wooden stud frame forming a 40 mm installation cavity. Fire-test observations were supplemented by simultaneous thermal analysis (STA), i.e., thermogravimetry (TG)/differential thermogravimetry (DTG)/differential scanning calorimetry (DSC), of uncoated and coated CLT specimens under oxidative conditions. During the applied medium-scale radiant exposure, the unexposed-face temperatures of both assemblies remained below the insulation temperature-rise limits defined in STN EN 1363-1; however, these limits were used only as a comparative benchmark and the test does not represent a formal fire-resistance classification. The coated assembly showed improved thermal protection during the early and intermediate stages of exposure, delaying a critical thermal event near the wooden stud by approximately 35 min. However, flaming combustion of the stud occurred at about 75 min and led to degradation of the intumescent char within the cavity. In contrast, the uncoated assembly reached higher early CLT surface temperatures but showed no flaming combustion during the test. STA results supported the fire-test interpretation: the coated specimen showed a 37% reduction in peak DTG rate, a higher residual mass at the end of the test, and substantially greater mass loss in the 150–280 °C range, consistent with intumescent activation and volatile release. The results indicate that, under the tested medium-scale exposure, the intumescent coating improved early and intermediate thermal protection of the CLT surface, but did not prevent late-stage cavity flaming involving the wooden stud. Therefore, the behavior of intumescent-coated CLT in partially enclosed cavities with combustible framing should be validated under replicated, standardized and larger-scale fire exposure. Full article

(This article belongs to the Special Issue Advances in Structural Fire Engineering)

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24 pages, 4987 KB

Open AccessArticle

Towards Sustainable Internal Combustion Engines: Optimization of Cobalt Oxide Nano-Additive Microalgae Biodiesel Blends for Emission Mitigation and Performance Enhancement

by Arif Savaş, Samet Uslu, Oğuzhan Der, Gonca Uslu and Ramazan Şener

Fire 2026, 9(6), 250; https://doi.org/10.3390/fire9060250 - 12 Jun 2026

Viewed by 679

Abstract

This study investigates the effects of Cobalt Oxide (Co₃O₄) nanoparticles on engine performance as well as emission characteristics under various engine load situations in test fuel (MB10). Response Surface Methodology (RSM) was used to examine the experimental results to [...] Read more.

This study investigates the effects of Cobalt Oxide (Co₃O₄) nanoparticles on engine performance as well as emission characteristics under various engine load situations in test fuel (MB10). Response Surface Methodology (RSM) was used to examine the experimental results to assess the impact of nanoparticle concentration (0–150 ppm) on combustion behavior. Brake thermal efficiency (BTE) and brake specific fuel consumption (BSFC) were performance metrics, and CO, HC, CO₂, and NO_x were emission characteristics. The findings demonstrated that the inclusion of nanoparticles and biodiesel had a major impact on emission behavior and performance. Because biodiesel contains more oxygen than diesel fuel, it reduces CO emissions while increasing CO₂ and NO_x emissions. By boosting heat transmission, the use of nanoparticles increased combustion efficiency; however, fuel atomization was adversely affected by high concentrations. With error rates under 10% for every response, RSM models showed excellent prediction accuracy. To achieve 21% BTE, 458.21 g/kWh BSFC, and minimum emission levels of 0.048% CO, 9.478 ppm HC, 5.415% CO₂, and 601.09 ppm NO_x, the optimization study identified the optimal operating condition with a 1.31 kW engine load and 80.36 ppm Co₃O₄ addition. The results verify that the proper dosage of nanoparticles can enhance the combustion performance of biodiesel while preserving acceptable emission levels. Full article

(This article belongs to the Special Issue Combustion Process, Emission Control, and Energy Generation in Internal Combustion Engines)

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27 pages, 3268 KB

Open AccessReview

From Combustion Emissions to Neurotoxicity: Brain Health Risks of Military Burn Pits Exposure

by Katherine M. Eggers, Zoe A. Keller, Paul Barach, Julie M. Tomáška, Joshua P. Nixon, Janeen H. Trembley and Tammy A. Butterick

Fire 2026, 9(6), 249; https://doi.org/10.3390/fire9060249 - 11 Jun 2026

Viewed by 1791

Abstract

Military burn pits used during post-9/11 U.S. military deployments functioned as uncontrolled combustion systems and were widely utilized to dispose of large volumes of outdoor waste by burning. Burn pits involved heterogeneous waste materials burned under variable temperature and oxygen conditions. These combustion [...] Read more.

Military burn pits used during post-9/11 U.S. military deployments functioned as uncontrolled combustion systems and were widely utilized to dispose of large volumes of outdoor waste by burning. Burn pits involved heterogeneous waste materials burned under variable temperature and oxygen conditions. These combustion environments generated complex, toxic, multipollutant airborne emission mixtures that included particulate matter (PM_2.5), polycyclic aromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs). This narrative review synthesizes epidemiologic, experimental, and mechanistic evidence linking burn pit emissions to disruption of the lung–brain axis and adverse neurological outcomes. We specifically aim to address a critical gap in understanding how combustion-derived toxicants impact brain health and are associated with unfavorable neuropsychiatric outcomes, including increased risk of post-traumatic stress disorder (PTSD) and depression. Combustion-related exposures promote pulmonary inflammation and system-wide immune signaling that propagate to the central nervous system, contributing to neuroinflammation and dysregulation of the hypothalamic–pituitary–adrenal (HPA) axis. These interconnected mechanisms are associated with toxic encephalopathy and related cognitive and mood disturbances, underscoring the need to integrate fire science with military and environmental health services research to better define the systemic and neurological consequences of acute and chronic fire-derived inhalation exposures. Full article

(This article belongs to the Section Fire Research at the Science–Policy–Practitioner Interface)

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15 pages, 703 KB

Open AccessArticle

Properties and Depth-Related Changes in Moderately Fire-Affected Pedunculate Oak Wood

by Lukáš Sahula, Kateřina Hájková, Tomáš Holeček, Aleš Zeidler, Monika Barbara Gach, Radosław Radoń, Krzysztof Słowiński, Bartłomiej Bednarz, Krzysztof Michalec and Piotr Romanek

Fire 2026, 9(6), 248; https://doi.org/10.3390/fire9060248 - 11 Jun 2026

Viewed by 749

Abstract

Wildfires significantly affect wood properties and usability, yet their impact on hardwood species remains insufficiently understood. This study presents an exploratory characterization of moderately fire-affected pedunculate oak (Quercus robur L.) wood, combining physical, mechanical, chemical, and thermal analyses to evaluate depth-related changes [...] Read more.

Wildfires significantly affect wood properties and usability, yet their impact on hardwood species remains insufficiently understood. This study presents an exploratory characterization of moderately fire-affected pedunculate oak (Quercus robur L.) wood, combining physical, mechanical, chemical, and thermal analyses to evaluate depth-related changes within outer stem zones. Samples were collected from bark and from wood originating approximately 1 cm and 1–2 cm beneath the cambial region to evaluate radial variation associated with moderate surface fire exposure. The oven-dry density of fire-affected wood reached 720 kg·m⁻³, corresponding to values marginally below the literature reference ranges reported for unaffected oak wood. Bending strength decreased to 85.56 MPa, while compressive strength remained within or marginally above the literature reference (71.16 MPa), and Brinell hardness (42.75 MPa) stayed within the typical range for oak. Chemical and elemental analyses revealed degradation of polysaccharides and carbon enrichment in surface layers. FTIR and DSC analyses suggested partial hemicellulose degradation, structural modification of cellulose, and reduced thermal reactivity in outer stem regions. Despite these changes, the higher heating value (19.09–19.56 MJ·kg⁻¹) remained within the literature reference ranges reported for oak wood. The results suggest that under moderate surface fire conditions, fire-induced changes were primarily concentrated in outer stem layers, while inner wood retained properties comparable to the literature reference values for unaffected oak wood. These findings indicate that moderately fire-affected oak wood may remain suitable for selected material or energy-related applications following appropriate quality assessment and removal of thermally altered surface zones. Full article

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15 pages, 11338 KB

Open AccessArticle

Wildfire Perimeters Align with Topographic Ridge Lines: A Null Model Benchmark for Fire-Spread Modelling in 118 Korean Wildfires (2018–2025)

by JuGyeong Choi and HeeMun Chae

Fire 2026, 9(6), 247; https://doi.org/10.3390/fire9060247 - 10 Jun 2026

Viewed by 485

Abstract

Topographic ridges are widely used in wildfire interpretation, suppression planning, and potential control-line design, but the claim that final fire boundaries preferentially follow ridge crests is rarely tested against local terrain availability. Remote-sensing-based burn mapping and DEM-derived terrain metrics now make this question [...] Read more.

Topographic ridges are widely used in wildfire interpretation, suppression planning, and potential control-line design, but the claim that final fire boundaries preferentially follow ridge crests is rarely tested against local terrain availability. Remote-sensing-based burn mapping and DEM-derived terrain metrics now make this question testable at cohort scale, although most Korean wildfire studies have focused on ignition, occurrence probability, or fire-risk prediction rather than final-perimeter geometry. We therefore tested whether 118 final wildfire perimeters in the Republic of Korea (2018–2025) were non-randomly associated with ridge lines derived independently from a 30 m SRTM DEM. Sentinel-2 pre- and post-fire imagery and official fire metadata were used to generate burn masks and perimeters, which were sampled every 20 m and compared with ridge networks using a proximity endpoint (R30) and a joint distance-orientation endpoint (Aθ) under a local translate-and-rotate null model. Most fires were both more ridge-proximal and more strongly ridge-aligned than their local null perimeters, and the directional signal was the stronger of the two (mean enrichment 2.3, versus 1.5 for proximity alone). A valley-inclusive comparator showed no comparable pattern, indicating an association specific to ridges rather than to terrain lines in general. The directional signal was robust to ridge continuity, spatial scale, null design, and the exclusion of road-adjacent ridges. Because the analysis uses final mapped perimeters rather than time-resolved fire fronts, it documents a ridge-specific geometric association rather than proof that ridges stopped individual fires. These results provide an observational benchmark for terrain representation in fire-spread models. Full article

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20 pages, 10264 KB

Open AccessArticle

Human Activities and Wildfires: The Impact of Forest Roads, Trails, and Forest Management on Wildfire Occurrence

by Youn Yeo-Chang, Se-Eum Lee, Soo-Jin Lee and Hyo-Rin Kim

Fire 2026, 9(6), 246; https://doi.org/10.3390/fire9060246 - 9 Jun 2026

Viewed by 436

Abstract

The risk of wildfires is increasing due to high temperatures and dry weather conditions caused by climate change. Outbreaks and spread of wildfires are usually conditioned by weather, topography, and fuel characteristics. In the Republic of Korea (hereafter, the ROK), most wildfires are [...] Read more.

The risk of wildfires is increasing due to high temperatures and dry weather conditions caused by climate change. Outbreaks and spread of wildfires are usually conditioned by weather, topography, and fuel characteristics. In the Republic of Korea (hereafter, the ROK), most wildfires are caused by anthropogenic factors rather than natural ones. However, the current forest fire forecasting system being operated in the ROK does not account for anthropogenic factors. To analyze the impact of human and physical factors on wildfire occurrence, a binary logistic regression model was constructed using data from the Gangwon and Gyeongbuk provinces from January 2022 to August 2025. The dependent variable was defined as the occurrence of a wildfire, while the independent variables comprised meteorological, seasonal, stand, and anthropogenic factors. To address multicollinearity, variables with high correlation coefficients were excluded from the independent variables, which were selected by three estimating approaches, including logistic regression and two machine learning techniques (namely, Random Forest and XGBoost). With machine learning, the variables with high feature importance were identified. The explanatory power of the logistic regression analysis with independent variables selected by the machine learning models was about 1.3 times higher than that of the model using variables adjusted solely for multicollinearity. The results of logistic regression analysis revealed that weather and coniferous forests are the most important factors fostering wildfires, while the mean stand age was the most significant factor in hindering wildfires. Among the anthropogenic factors, forest road density acted as a suppressor of wildfire spread rather than a promoter of occurrence. Conversely, trail density tends to increase the risk of wildfire occurrence. Among forest management activities, plantation forests may increase the risk of forest fires, although this remains uncertain. These findings suggest that preventing wildfires requires a paradigm shift in forest resource management policies, including extending forest rotation ages and converting coniferous forests to broadleaf forests. Meanwhile, it also indicates the need to restrict the expansion of hiking trails and improve regulations regarding hiker access and behavior to prevent wildfires. Full article

(This article belongs to the Special Issue Fire Patterns, Driving Factors, and Multidimensional Impacts Under Climate Change and Human Activities)

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27 pages, 4224 KB

Open AccessArticle

Are Phase Change Material–Concrete Assemblies in Building Envelopes Fire Safe? Experimental Validation and Numerical Modelling

by Ajitanshu Vedrtnam and Nelson Soares

Fire 2026, 9(6), 245; https://doi.org/10.3390/fire9060245 - 8 Jun 2026

Viewed by 442

Abstract

Phase change materials (PCMs) are increasingly incorporated into façades and wall systems to enhance passive thermal regulation; however, their fire safety remains poorly understood. While PCMs effectively reduce cooling loads, limited data exist on their behaviour under real fire exposure. In this study, [...] Read more.

Phase change materials (PCMs) are increasingly incorporated into façades and wall systems to enhance passive thermal regulation; however, their fire safety remains poorly understood. While PCMs effectively reduce cooling loads, limited data exist on their behaviour under real fire exposure. In this study, the thermal response of PCM-integrated concrete panels was investigated through two-dimensional finite element modelling using an apparent heat-capacity formulation that accounts for phase change, latent-heat absorption, and encapsulation softening. Simulations were performed under the ISO 834 standard fire curve and constant furnace exposures between 200 °C and 800 °C for 60 min to evaluate insulation performance and encapsulation stability. Results show that PCM melting at approximately 31 °C provides a 20–25 min delay in rear-face temperature rise under moderate fire exposure (≤400 °C), maintaining the rear-face temperature increase below 180 °C for one hour. Beyond 500 °C, the acrylonitrile butadiene styrene (ABS) encapsulation softens near 95 °C, suppressing latent-heat storage and leading to rear-face temperatures between 260 °C and 360 °C. Comparative analyses indicate that organic PCMs lose effectiveness rapidly unless protected by at least a 25 mm concrete cover, whereas inorganic PCMs exhibit superior stability owing to their non-combustibility and endothermic dehydration behaviour. The results identify performance trends, thermal limitations, and design considerations for the investigated PCM–ABS–concrete assembly under the studied fire exposure conditions. The validated experimental–numerical framework provides insight into the thermal response of PCM-integrated concrete assemblies and supports future development of fire-resilient building-envelope components. Full article

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31 pages, 11252 KB

Open AccessArticle

A Novel Robust HL-Based Transformer Approach for Predicting Electrical Fire Risks

by Guozhong Huang, Yaohui Shen, Ciai Tang, Qiuhang Wu, Huiling Jiang and Xuehong Gao

Fire 2026, 9(6), 244; https://doi.org/10.3390/fire9060244 - 7 Jun 2026

Viewed by 543

Abstract

Accurate prediction of electrical fire risk is important for early warning, but real-world monitoring data are often affected by sensor noise, transient anomalies, and non-Gaussian interference. This study proposes an HL-Transformer that incorporates an HL-Pooling layer based on the Hodges–Lehmann estimator into the [...] Read more.

Accurate prediction of electrical fire risk is important for early warning, but real-world monitoring data are often affected by sensor noise, transient anomalies, and non-Gaussian interference. This study proposes an HL-Transformer that incorporates an HL-Pooling layer based on the Hodges–Lehmann estimator into the Transformer feature aggregation process. The HL-Pooling layer replaces conventional mean- or max-based pooling by using the median of pairwise averages, aiming to suppress abnormal perturbations while preserving temporal information. Experiments were conducted on a real-world electrical fire monitoring dataset and the public ETTh1 dataset, with additional robustness tests under different outlier ratios and intensities. The results show that, within the same Transformer backbone, HL-Transformer reduced the MSE by 75.4% compared with the Max-Pooling variant and achieved an R² of 0.879 on the electrical fire risk prediction task. Under injected outliers, the HL-Pooling layer showed more stable error trends, and its transfer to TCN, CNN-LSTM, and 1D-CNN models further improved predictive performance. These findings indicate that HL-Pooling is a robust and portable alternative to conventional pooling for time-series forecasting in noisy monitoring environments. Full article

(This article belongs to the Special Issue Building Fire Safety and Intelligent Protection Technologies)

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19 pages, 24427 KB

Open AccessArticle

Integrating Multi-Source Data for Forest Fire Risk Assessment: A Case Study of Liangshan, China

by Wenyi Liu, Yanmeng Shang, Yun Shen and Guanying Huang

Fire 2026, 9(6), 243; https://doi.org/10.3390/fire9060243 - 6 Jun 2026

Viewed by 584

Abstract

Forest fires pose significant threats to ecological security, human settlements, and sustainable regional development, particularly in mountainous regions with complex environmental and anthropogenic conditions. Previous studies have yet to construct a forest fire risk assessment framework that integrates multi-source data, which limits the [...] Read more.

Forest fires pose significant threats to ecological security, human settlements, and sustainable regional development, particularly in mountainous regions with complex environmental and anthropogenic conditions. Previous studies have yet to construct a forest fire risk assessment framework that integrates multi-source data, which limits the comprehensiveness and accuracy of existing assessments. To address this gap, taking Liangshan Prefecture in China as a case study, this research selected eight risk factors to characterize vegetation conditions, topographic features, climatic conditions, and human activities. A combined weighting approach integrating the mandatory determination method and the coefficient of variation method was employed to determine the weights of different indicators. Forest fire risk probability was calculated using a weighted comprehensive evaluation model, and spatial autocorrelation analysis based on global Moran’s I and local indicators of spatial association (LISA) was further conducted to investigate spatial clustering characteristics. The results indicate that high-risk and very high-risk areas are mainly concentrated in southeastern Liangshan, particularly in Xichang, Jinyang, Ningnan, Huili, and Huidong, where warmer climatic conditions, dense vegetation coverage, mountainous terrain, and intensive human activities jointly contribute to elevated forest fire risk. The global Moran’s I value of 0.219175 indicates significant positive spatial autocorrelation in forest fire risk distribution. Validation using historical fire-scar data from 2010 to 2020 showed that 83.66% of the fire scars were distributed within medium-, high-, and very high-risk areas, suggesting that the proposed assessment framework provides a reasonable representation of forest fire risk patterns in Liangshan. The findings of this study can support regional forest fire prevention planning, targeted resource allocation, and risk management in mountainous areas. Full article

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14 pages, 2383 KB

Open AccessArticle

Experimental and Numerical Study on the Pyrolysis Pathways of C₇H₄F₁₂O in a Simulated Battery Immersion System

by Ming Hu, Xuewen Geng, Wei Wang, Xingjian Kang, Yang Guo and Biao Zhou

Fire 2026, 9(6), 242; https://doi.org/10.3390/fire9060242 - 5 Jun 2026

Viewed by 469

Abstract

Lithium-ion batteries have become crucial energy carriers in multiple core fields owing to their excellent comprehensive performance. Nevertheless, as battery energy and power densities continue to rise and operating conditions grow increasingly complex, thermal safety issues have become increasingly prominent. Immersion liquid cooling [...] Read more.

Lithium-ion batteries have become crucial energy carriers in multiple core fields owing to their excellent comprehensive performance. Nevertheless, as battery energy and power densities continue to rise and operating conditions grow increasingly complex, thermal safety issues have become increasingly prominent. Immersion liquid cooling technology has attracted widespread attention in academic and engineering fields for its outstanding heat transfer and temperature uniformity performance. As a core component of this technology, the selection of liquid coolants is of vital importance. Various coolants investigated in existing studies generally suffer from limitations to varying degrees. Against this backdrop, intrinsically safe fluorocarbon C₇H₄F₁₂O (3F-135) serves as an ideal liquid cooling medium for lithium-ion batteries, thanks to its high thermal stability, superior electrical insulation and environmental friendliness (zero ODP, extremely low GWP). However, its decomposition mechanism and reaction pathways under extreme thermal runaway conditions of batteries remain unclear. In this study, a tube furnace was adopted to simulate high-temperature environments induced by thermal runaway, and gas chromatography–mass spectrometry (GC-MS) was employed to analyze decomposition products and decomposition ratios of 3F-135. Subsequently, density functional theory (DFT) calculations were utilized to construct the pyrolysis reaction network of 3F-135. Ultimately, the dominant pyrolysis pathways in different temperature ranges were clarified, providing theoretical support for the application and selection of intrinsically safe liquid coolants. Full article

(This article belongs to the Special Issue Next-Generation Fire Suppressants: From Molecular Mechanisms to System Compatibility and Environmental Safety)

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22 pages, 1705 KB

Open AccessEssay

Selection of Appropriate Clean Fire Suppression Agents in Aircraft Cargo Compartments by Ranking System

by Xiaotong Huang, Xuhong Jia, Tao Hu, Wanki Chow and Ziqi Zhao

Fire 2026, 9(6), 241; https://doi.org/10.3390/fire9060241 - 5 Jun 2026

Viewed by 587

Abstract

Appropriate Halon-free fire suppression agents for aircraft cargo compartments are important in civil aviation safety. There are many products available and selecting an appropriate agent for civil aircraft cargo compartments under specific requirements is important and will be discussed. An in-depth analysis of [...] Read more.

Appropriate Halon-free fire suppression agents for aircraft cargo compartments are important in civil aviation safety. There are many products available and selecting an appropriate agent for civil aircraft cargo compartments under specific requirements is important and will be discussed. An in-depth analysis of the technical characteristics and updated research achievements of clean fire suppression agents are reviewed first. Advantages, limitations, and application feasibility of clean fire suppression agents for cargo compartments are included with quantitative evaluation of their comprehensive attributes. A ranking system is proposed to select appropriate suppressants by considering their environmental impact, fire extinguishment efficiency, airworthiness, and safety. Two approaches were introduced with the first quantitatively evaluating all four performance areas of agents through weight allocations. The second approach excludes environmental performance as Halon is to be substituted. Only the remaining three areas are included and compared with Halon. The integrated application of a ranking system provides a reference example for selecting fire suppression agents for aircraft cargo compartments. Based on the above selected approaches, the optimal substitute suppression agents are Novec 1230/N₂, 2-BTP/CO₂, and Novec 1230/(CF₃CF₂)₃N for this example. Future development will also be guided by the dynamically updatable ranking system, which provides a pathway from technical screening to engineering design. Theoretical guidance for selecting suitable clean fire suppression agents can be achieved for aircraft cargo compartments. Full article

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17 pages, 6884 KB

Open AccessArticle

Characterization of Log-Normal Distribution of Vehicle Spacing in Highway Tunnels with Implications for Evacuation Safety

by Dingli Liu, Yantong Chen, Rongwei Bu, Jingya Wang, Junqi Liu, Lu Wu, Weijun Liu and Yao Huang

Fire 2026, 9(6), 240; https://doi.org/10.3390/fire9060240 - 5 Jun 2026

Viewed by 527

Abstract

Timely and efficient evacuation is crucial for tunnel fire safety. Previous studies often assumed fixed vehicle spacing and vehicle type ratios, which did not reflect real traffic conditions. Based on high-resolution satellite imagery of congested scenarios nationwide, 1703 sets of static vehicle spacing [...] Read more.

Timely and efficient evacuation is crucial for tunnel fire safety. Previous studies often assumed fixed vehicle spacing and vehicle type ratios, which did not reflect real traffic conditions. Based on high-resolution satellite imagery of congested scenarios nationwide, 1703 sets of static vehicle spacing data were obtained. Descriptive statistical analysis and the K–S test were conducted. As a result, a log-normal distribution model of vehicle spacing was established, with an average spacing of 2.23 m, a logarithmic mean of 0.707, and a logarithmic standard deviation of 0.439. Analysis of 11,211 vehicle samples further revealed an uneven distribution of vehicle types across lanes. Based on the statistical data, a random vehicle arrangement algorithm was developed for highway tunnels, incorporating the log-normal characteristics of vehicle spacing. Using this algorithm, non-uniform vehicle layouts were generated for tunnel evacuation modeling. A total of 120 simulations across 12 different scenarios were then conducted to analyze the impact of log-normal vehicle spacing on evacuation time. Results showed that evacuation time was 2–5% longer under a log-normal distribution than under a uniform distribution. Therefore, future tunnel evacuation simulations should account for the log-normal distribution of vehicle spacing and the actual vehicle type ratio. Full article

(This article belongs to the Special Issue Advances in Decision Support for Urban Fire Risk Management and Policy Formulation)

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26 pages, 3247 KB

Open AccessArticle

Fire Performance Prediction of Naturally Ventilated Double-Skin Façades Using CFD and Machine Learning

by Mehmet Akif Yıldız and Merve Ertosun Yıldız

Fire 2026, 9(6), 239; https://doi.org/10.3390/fire9060239 - 4 Jun 2026

Viewed by 489

Abstract

Double-skin façade (DSF) systems are important for energy efficiency because they effectively utilize natural ventilation and daylight. However, the uninterrupted vertical gaps in these systems may pose safety risks in the event of a fire by causing the rapid spread of smoke and [...] Read more.

Double-skin façade (DSF) systems are important for energy efficiency because they effectively utilize natural ventilation and daylight. However, the uninterrupted vertical gaps in these systems may pose safety risks in the event of a fire by causing the rapid spread of smoke and hot gases. This study presents a hybrid approach that combines computational fluid dynamics (CFD)-based simulations and machine learning (ML) techniques to predict heat flow and fire-room control-volume heat release rate (FR-HRR). Within the scope of the study, 400 different scenarios were modeled with different combinations of basic natural ventilation design parameters consisting of gap width, gap height, window opening area, and air inlet and outlet area. The data obtained were evaluated with different ML models, including Fine Tree, Bagged Tree, Support Vector Machine, and Artificial Neural Network models; in particular, the Fine Tree model gave the most successful results with high accuracy rates (R² = 0.99 for FR-HRR; R² = 0.91 for heat flow). The analysis showed that DSF gap width provided a dominant model-based contribution within the investigated CFD-generated dataset. This approach provides a preliminary CFD-informed ML framework for the rapid comparative assessment of fire-related responses in open-boundary naturally ventilated DSF configurations during the early design stage. Full article

(This article belongs to the Special Issue Fire Safety in the Built Environment)

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26 pages, 9359 KB

Open AccessArticle

Effects of Equivalence Ratio on Emission Characteristics of Ammonia–Hydrogen Dual-Fuel Engine

by Zhongcheng Wang, Jie Zhu, Xiaoyu Liu, Ron Wu, Jiale Du, Shenwei Weng and Jingjun Zhong

Fire 2026, 9(6), 238; https://doi.org/10.3390/fire9060238 - 4 Jun 2026

Viewed by 574

Abstract

Ammonia–hydrogen dual-fuel engines are regarded as a promising clean-energy power system, but nitrogen-based pollutants (NH₃, NO, N₂O, and NO₂) emitted during their operation restrict their popularization and application. To clarify the influence of equivalence ratio on the [...] Read more.

Ammonia–hydrogen dual-fuel engines are regarded as a promising clean-energy power system, but nitrogen-based pollutants (NH₃, NO, N₂O, and NO₂) emitted during their operation restrict their popularization and application. To clarify the influence of equivalence ratio on the emission characteristics of ammonia–hydrogen dual-fuel engines, the emission laws and formation mechanisms of nitrogen-based pollutants under different equivalence ratios were studied and the evolution of the in-cylinder cross-sectional mole fraction of NO, N₂O and NO₂ was analyzed. The results show that equivalence ratio has a significant regulatory effect on in-cylinder temperature, combustion efficiency and pollutant formation. Unburned NH₃ emission first decreases and then increases, reaching the minimum at an equivalence ratio of 1.05. NO emission peaks at 0.74 due to high temperature and combustion efficiency and is nearly zero at 1.48 under fuel-rich conditions. N₂O emission is highest at 0.5–0.62 and is inhibited at high equivalence ratios. NO₂ is mainly generated under low equivalence ratios and disappears when the equivalence ratio exceeds 0.74. This study reveals the influence mechanism of equivalence ratio on nitrogen-based pollutants of ammonia–hydrogen dual-fuel engines and provides a theoretical basis and experimental support for the optimization of engine emission-control strategies. Full article

(This article belongs to the Special Issue Advancements in Hydrogen Internal Combustion Engine Technology: Combustion, Performance, and Environmental Impact)

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17 pages, 26220 KB

Open AccessArticle

Oxidation Mechanisms of Low Molecular Valeric Acidic Compounds in Coal Spontaneous Combustion

by Shaobo Qu, Xiaobo Wang, Tianyi Yang, Wenhao Deng, Sichen Liu, Hanzhong Deng, Yafei Shan and Hongguang Ji

Fire 2026, 9(6), 237; https://doi.org/10.3390/fire9060237 - 3 Jun 2026

Viewed by 484

Abstract

Coal spontaneous combustion seriously threatens the safety of coal mine production, and studies on low molecular compounds in coal spontaneous combustion are limited. The chemical reaction process of low molecular compound valeric acid in coal spontaneous combustion was studied using B3LYP/6-311G quantum chemical [...] Read more.

Coal spontaneous combustion seriously threatens the safety of coal mine production, and studies on low molecular compounds in coal spontaneous combustion are limited. The chemical reaction process of low molecular compound valeric acid in coal spontaneous combustion was studied using B3LYP/6-311G quantum chemical density functional theory. The mechanism of valeric acid in coal spontaneous combustion was disclosed, which is the process of chemical bond formation and breakage. The findings implied that the active sites of valeric acid during combustion are C1, C5, C8, and C11 atoms. Twelve reaction channels have also been theoretically determined in the following order: Path6 > Path3 > Path8 > Path5 > Path4 > Path1 > Path11 > Path10 > Path9 > Path12 > Path7 > Path2. This is significant for developing low molecular spontaneous combustion inhibitors and preventing coal spontaneous combustion. Full article

(This article belongs to the Special Issue Fire Risk Management and Emergency Prevention)

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23 pages, 42425 KB

Open AccessArticle

Analysis of Syngas Inlet Position for Optimization of Flameless Combustion in a Biomass Pyrolyzer

by Andre Amba Matarru and Donghoon Shin

Fire 2026, 9(6), 236; https://doi.org/10.3390/fire9060236 - 2 Jun 2026

Viewed by 578

Abstract

A new biomass pyrolyzer, named Biochar Oven, has been developed using flameless combustion technology, which provides uniform high temperature in the pyrolysis reactor. A computational fluid dynamics (CFD) model of flameless combustion was developed to analyze how the fuel inlet depth controls the [...] Read more.

A new biomass pyrolyzer, named Biochar Oven, has been developed using flameless combustion technology, which provides uniform high temperature in the pyrolysis reactor. A computational fluid dynamics (CFD) model of flameless combustion was developed to analyze how the fuel inlet depth controls the reaction and heat transfer to a vertical biomass pyrolysis reactor. The combustor was modeled using the k–ε turbulence model, the discrete ordinates radiation model, and species transport with the reaction. The fuel nozzle relative depth ratios (RDR) of chamber height and equivalence ratios (ER) were varied to obtain optimal combustion and heat transfer performance. The internal recirculation ratio (Z) was calculated to evaluate the flameless combustion condition, with maximum values generally found at RDR 0.73 for each ER. Increasing depth strengthens the mixing zone closer to the reactor wall. With an ER of 0.9 and RDR of 0.73, the wall heat flux is up to 16.36 kW m⁻², the average wall reactor temperature is up to 900 °C, and the heat transfer efficiency is up to 59.79%. These flow patterns and chamber–reactor results indicate that deeper nozzle insertions (RDR 0.73) provide better overall performance by improving recirculation intensity, wall heat flux, and heat transfer efficiency with lower CO emissions. Full article

(This article belongs to the Special Issue Low Carbon Fuel Combustion and Pollutant Control)

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