Fire | May 2025 - Browse Articles

13 pages, 2144 KiB

Open AccessArticle

Enhancing Diesel Engine Performance Through Hydrogen Addition

by Sahbi Ben Abdelwahed, Fakher Hamdi, Mehrez Gassoumi, Ilham Yahya, Noomen Moussa, Nashmi H. Alrasheedi, Ridha Ennetta and Borhen Louhichi

Fire 2025, 8(5), 206; https://doi.org/10.3390/fire8050206 - 20 May 2025

Viewed by 486

Abstract

This study evaluates the potential of hydrogen as a clean additive to conventional diesel fuel. Experiments were carried out on a single-cylinder, air-cooled diesel engine under half- and full-load conditions, across engine speeds ranging from 1000 to 3000 rpm. Hydrogen, produced on site [...] Read more.

This study evaluates the potential of hydrogen as a clean additive to conventional diesel fuel. Experiments were carried out on a single-cylinder, air-cooled diesel engine under half- and full-load conditions, across engine speeds ranging from 1000 to 3000 rpm. Hydrogen, produced on site via a proton exchange membrane electrolyser, was supplied to the engine at a constant flow rate of 0.5 L/min. Compared to pure diesel, the hydrogen–diesel blend reduced specific fuel consumption by 10% and increased brake thermal efficiency by 10% at full load. Emissions of carbon monoxide and carbon dioxide decreased by 13% and 17%, respectively, at half load. Additionally, nitrogen oxide emissions dropped by 17%. These results highlight the potential of hydrogen to improve combustion efficiency while significantly mitigating emissions, offering a viable transitional solution for cleaner power generation using existing diesel infrastructure. Full article

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16 pages, 4937 KiB

Open AccessArticle

AI-Driven Boost in Detection Accuracy for Agricultural Fire Monitoring

by Akmalbek Abdusalomov, Sabina Umirzakova, Komil Tashev, Jasur Sevinov, Zavqiddin Temirov, Bahodir Muminov, Abror Buriboev, Lola Safarova Ulmasovna and Cheolwon Lee

Fire 2025, 8(5), 205; https://doi.org/10.3390/fire8050205 - 20 May 2025

Viewed by 290

Abstract

In recent years, agricultural landscapes have increasingly suffered from severe fire incidents, posing significant threats to crop production, economic stability, and environmental sustainability. Timely and precise detection of fires, especially at their incipient stages, remains crucial to mitigate damage and prevent ecological degradation. [...] Read more.

In recent years, agricultural landscapes have increasingly suffered from severe fire incidents, posing significant threats to crop production, economic stability, and environmental sustainability. Timely and precise detection of fires, especially at their incipient stages, remains crucial to mitigate damage and prevent ecological degradation. However, conventional detection methods frequently fall short in accurately identifying small-scale fire outbreaks due to limitations in sensitivity and response speed. Addressing these challenges, this research proposes an advanced fire detection model based on a modified Detection Transformer (DETR) architecture. The proposed framework incorporates an optimized ConvNeXt backbone combined with a novel Feature Enhancement Block (FEB), specifically designed to refine spatial and contextual feature representation for improved detection performance. Extensive evaluations conducted on a carefully curated agricultural fire dataset demonstrate the effectiveness of the proposed model, achieving precision, recall, mean Average Precision (mAP), and F1-score of 89.67%, 86.74%, 85.13%, and 92.43%, respectively, thereby surpassing existing state-of-the-art detection frameworks. These results validate the proposed architecture’s capability for reliable, real-time identification, offering substantial potential for enhancing agricultural resilience and sustainability through improved preventive strategies. 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, 6214 KiB

Open AccessArticle

Inner Thermal Structure Evolution of Fire-Resistant Medium-Voltage Cable Under External Heat Flux with Varying Conductor Radius

by Moayad S. M. Sedahmed and Mohmmed Mun ELseed Hassaan

Fire 2025, 8(5), 204; https://doi.org/10.3390/fire8050204 - 20 May 2025

Viewed by 315

Abstract

Ensuring the fire resistance and thermal stability of power cables is crucial for their reliable performance in fire environments, essential for sustainable power distribution, and allowing for more time to extinguish fires and for evacuation. This study utilises numerical simulation to analyse the [...] Read more.

Ensuring the fire resistance and thermal stability of power cables is crucial for their reliable performance in fire environments, essential for sustainable power distribution, and allowing for more time to extinguish fires and for evacuation. This study utilises numerical simulation to analyse the thermal behaviour of fire-resistant medium-voltage cable, focusing on the impact of conductor radius and material properties under external heat flux. A heat transfer model of cables with conductor radii of 3 mm, 5 mm, and 7 mm under a localised external heat flux of 750 °C was developed. The results show that smaller conductors stabilise faster (reaching the steady state at 45 min for 3 mm vs. 79 min for 7 mm) but experience higher thermal stress, with conductor temperatures peaking at 692.5 °C. Larger conductors enhance axial heat conduction, reduce steady-state temperature by up to 25%, and improve heat dissipation by over 360%. The 5 mm conductor radius provided balanced performance, lowering the temperature by 65 °C compared to 3 mm, although it remained 20.1% hotter than the 7 mm. The ceramic layer played a crucial role in reducing heat flux in the heat source section. Optimised polyethylene insulation and ceramic material improved heat retention and surface temperature control in non-heat source sections. Also, thermal resistance analysis decreased from 1.00 K/W (3 mm) to 0.65 K/W (7 mm). Among material properties, increasing ceramic thermal conductivity had a more significant impact on reducing core temperature than improving insulation. These findings provide practical recommendations for optimising conductor geometry and material properties for more fire-resistant cables. Full article

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15 pages, 2057 KiB

Open AccessArticle

A Study on the Flame and Pressure Characteristics of Ultrafine Calcium Carbonate (CaCO₃) Powder in Suppressing Gas Explosions

by Guiyuan Li, Zuohui Xu, Sihan Ji, Jingde Xu, Yang Hu, Junhai Liu and Zhie Wang

Fire 2025, 8(5), 203; https://doi.org/10.3390/fire8050203 - 20 May 2025

Viewed by 326

Abstract

This study investigates the suppression effect of ultrafine CaCO₃ powder on gas explosions through a series of experiments conducted in a medium-scale explosion tube (9.6 m in length) with varying concentrations of ultrafine CaCO₃. The gas explosion suppression concentration was [...] Read more.

This study investigates the suppression effect of ultrafine CaCO₃ powder on gas explosions through a series of experiments conducted in a medium-scale explosion tube (9.6 m in length) with varying concentrations of ultrafine CaCO₃. The gas explosion suppression concentration was established at 9.5%. The results indicate that, at concentrations of 125 g/m³ and 300 g/m³, ultrafine CaCO₃ powder significantly reduced the flame propagation speed of the gas explosion. Among the concentrations that did not fully suppress the gas explosion, 20 g/m³ effectively mitigated the flame propagation speed and overpressure throughout the entire process. The concentration of 75 g/m³ demonstrated a suppression–promotion–suppression–promotion pattern regarding the flame propagation rate, with significant fluctuations observed throughout the process. While the maximum suppression rate reached 60.9%, the maximum promotion rate was 131.12%. At 10 g/m³, the flame propagation rate initially increased before decreasing, with the most effective suppression observed within the first 6.6 m, where flame propagation suppression increased rapidly from 58.13% to 74.82%, and the peak explosion overpressure was reduced by up to 62.94%. These findings contribute valuable insights for the development of effective gas explosion suppression strategies in mining environments. Full article

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13 pages, 2337 KiB

Open AccessArticle

Improvement in Fire Resistance and Smoke Leakage Performance for Existing Polyvinyl Chloride Pipes Passing Through Walls

by Ting-Yuan Li, Ying-Ji Chuang, Ching-Yuan Lin and Tseng-Wei Chao

Fire 2025, 8(5), 202; https://doi.org/10.3390/fire8050202 - 19 May 2025

Viewed by 438

Abstract

Penetration points on walls must include firestop measures to prevent the spread of fire. Countries worldwide have established standardized testing protocols for firestop methods, and firestop products must pass relevant tests before they can be used in buildings. In the present study, a [...] Read more.

Penetration points on walls must include firestop measures to prevent the spread of fire. Countries worldwide have established standardized testing protocols for firestop methods, and firestop products must pass relevant tests before they can be used in buildings. In the present study, a simple method was developed to enhance the smoke leakage performance and fire resistance of existing polyvinyl chloride (PVC) pipes passing through walls. Two sets of smoke leakage tests were performed, followed by two sets of fire tests. The smoke leakage tests were nondestructive and thus did not damage the specimens; consequently, the same specimens could be used in the smoke leakage and fire tests. The results of the smoke leakage tests indicate that the method using PVC pipes wrapped with galvanized steel sleeves outperforms the method without such wrapping. Moreover, the results of the fire tests suggest that galvanized steel sleeves considerably improve thermal insulation and safety. This finding is explained as follows: PVC pipes may burn and break apart at high temperatures, compromising fire compartmentation. A galvanized steel sleeve can retain a burning, broken pipe piece, thereby preventing injuries and stopping the detached pipe from continuing to burn on the ground. Full article

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

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14 pages, 4635 KiB

Open AccessArticle

Fire Resistance and Mechanical Properties of Wooden Dou-Gong Brackets in Chinese Traditional Architecture Exposed to Different Fire Load Levels

by Zhenzhong Lai, Xin Li, Miaotian Long, Long Yan and Zhisheng Xu

Fire 2025, 8(5), 201; https://doi.org/10.3390/fire8050201 - 17 May 2025

Viewed by 333

Abstract

Dou-Gong brackets, the distinctive structural element in ancient Chinese architecture, fulfill critical roles in load transfer, span reduction, and decoration, making its preservation vital for safeguarding wooden heritage buildings. This study investigates the combustion performance and residual load-bearing capacity of key Dou-Gong bracket [...] Read more.

Dou-Gong brackets, the distinctive structural element in ancient Chinese architecture, fulfill critical roles in load transfer, span reduction, and decoration, making its preservation vital for safeguarding wooden heritage buildings. This study investigates the combustion performance and residual load-bearing capacity of key Dou-Gong bracket components—Zuo-dou, Zheng-xin-gua-gong, and Qiao—exposed to varying fire conditions. The results reveal that an increasing fire load elevates heating rates and peak temperatures of wood substrates, resulting in a significant degradation of structural integrity. At a fire load of 55 kW, the peak temperatures at the bottom, joint edge, and top of the Dou-Gong brackets reach 755.3 °C, 489.9 °C, and 620.7 °C, respectively, representing increases of 2%, 65%, and 38%, respectively, compared to those observed at a fire load of 20 kW. Moreover, the charring rate of Dou-Gong bracket increases from 0.22–0.26 mm/min at a fire load of 20 kW to 0.50–0.56 mm/min at a fire load of 55 kW, accompanied by an increase in mass loss rate from 28.5% to 36.9%. These findings highlight the significant impact of fire conditions on the fire characteristic and structural integrity of Dou-Gong brackets, providing the first quantitative evidence of their degradation under fire exposure. By addressing this vulnerability, the study contributes to the scientific preservation of ancient wooden architecture under contemporary fire risk scenarios. Full article

(This article belongs to the Special Issue Fire Prevention and Flame Retardant Materials)

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16 pages, 2789 KiB

Open AccessArticle

Experimental Investigation on Thermal and Ignition Characteristics of Direct Current (DC) Series Arc in a Lab-Scale Photovoltaic (PV) System

by Zhilong Wei, Lin Liu, Wenxiao Huang, Yun Yang, Haisheng Zhen and Yu Lin

Fire 2025, 8(5), 200; https://doi.org/10.3390/fire8050200 - 16 May 2025

Viewed by 185

Abstract

This study investigates the thermal behavior and ignition dynamics of DC series arcs in a lab-scale photovoltaic (PV) system. The impacts of current magnitude, dynamic current variations, and electrode gap on electrode surface temperatures are analyzed, while ignition characteristics of common electrical materials [...] Read more.

This study investigates the thermal behavior and ignition dynamics of DC series arcs in a lab-scale photovoltaic (PV) system. The impacts of current magnitude, dynamic current variations, and electrode gap on electrode surface temperatures are analyzed, while ignition characteristics of common electrical materials (PC, PVC, XLPO, PPE, etc.) are investigated by analyzing critical time thresholds during the arc-induced combustion. Results show that electrode surface temperatures rise with increased current or larger electrode gaps, driven by the enhanced DC arc energy release. Dynamic current variations (increasing/decreasing) shift the balance between heat accumulation and dissipation, resulting in the nonlinear temperature evolution. Additionally, the peak temperature of the anode is about 50% higher than that of the cathode due to the electron flow-driven heat transfer and particle collisions. Notably, general electrical materials can be ignited successfully by stable DC arcs. The anode can ignite flame-retardant materials within 3 s, while the cathode takes a relatively long time to ignite, approximately 20 to 30 s. Besides, enlarged electrode gaps can induce a mutual reinforcement between arcs and flames, resulting in further stabilized arcs and intensified flames. This highlights potential elevated fire hazards as the connector gap increases due to the DC arc erosion. Full article

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18 pages, 5799 KiB

Open AccessArticle

AH-YOLO: An Improved YOLOv8-Based Lightweight Model for Fire Detection in Aircraft Hangars

by Li Deng, Zhuoyu Wang and Quanyi Liu

Fire 2025, 8(5), 199; https://doi.org/10.3390/fire8050199 - 15 May 2025

Viewed by 342

Abstract

As high-specification structures, civil aircraft hangars face significant fire risks, including rapid fire propagation and challenging rescue operations. The structural integrity of these hangars is compromised under high temperatures, potentially leading to collapse and making aircraft parking and maintenance unfeasible. The severe consequences [...] Read more.

As high-specification structures, civil aircraft hangars face significant fire risks, including rapid fire propagation and challenging rescue operations. The structural integrity of these hangars is compromised under high temperatures, potentially leading to collapse and making aircraft parking and maintenance unfeasible. The severe consequences of fire in such environments make effective detection essential for mitigating risks and enhancing flight safety. However, conventional fire detectors often suffer from false alarms and missed detections, failing to meet the fire safety demands of large buildings. Additionally, many existing fire detection models are computationally intensive and large in size, posing deployment challenges in resource-limited environments. To address these issues, this paper proposes an improved YOLOv8-based lightweight model for fire detection in aircraft hangars (AH-YOLO). A custom infrared fire dataset was collected through controlled burn experiments in a real aircraft hangar, using infrared thermal imaging cameras for their long-range detection, high accuracy, and robustness to lighting conditions. First, the MobileOne module is integrated to reduce the network complexity and improve the computational efficiency. Additionally, the CBAM attention mechanism enhances fine target detection, while the improved Dynamic Head boosts the target perception. The experimental results demonstrate that AH-YOLO achieves 93.8% mAP@0.5 on this custom dataset, a 3.6% improvement over YOLOv8n while reducing parameters by 15.6% and increasing frames per second (FPS) by 19.0%. Full article

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14 pages, 9504 KiB

Open AccessArticle

Experimental and Numerical Simulation Study of the Influence of Fe(C₅H₅)₂-SiO₂ Composite Dry Powders on Characteristics of Hydrogen/Methane/Air Explosion

by Zhiqian Zheng, Huiqian Liao, Hongfu Mi, Kaixuan Liao, Haoliang Zhang, Yi Li, Yanhui Ren, Zhijun Li, Nanfang Li and Wei Xia

Fire 2025, 8(5), 198; https://doi.org/10.3390/fire8050198 - 15 May 2025

Viewed by 224

Abstract

In order to ensure the safety of methane/hydrogen, regular SiO₂ powder was modified. Fe(C₅H₅)₂/SiO₂ composite dry powder (CDP) was selected as the explosion-suppression material. Explosion-suppression experiments and numerical simulations were adopted to investigate the inhibition [...] Read more.

In order to ensure the safety of methane/hydrogen, regular SiO₂ powder was modified. Fe(C₅H₅)₂/SiO₂ composite dry powder (CDP) was selected as the explosion-suppression material. Explosion-suppression experiments and numerical simulations were adopted to investigate the inhibition effect of 0% (

X_{H_{2}}

= 0%) and 20% (

X_{H_{2}}

= 20%) hydrogen doping ratios. The flame structure, flame propagation speed, and maximum explosion pressure are depicted to compare the inhibition effect of different mass fractions (X_Fe(C5H5)2 = 0–6%). The results showed that CDP significantly reduced the flame propagation velocity and maximum explosion pressure of

X_{H_{2}}

= 0%. The best effect was observed when 6% Fe(C₅H₅)₂ was added, with the velocity reduced to 9.241 m/s. The maximum explosion pressure was reduced to 0.518 MPa, and the effect was relatively weak for

X_{H_{2}}

= 20%, with the maximum pressure reduced to 0.525 MPa. In addition, the key radical production and temperature sensitivity showed that Fe(C₅H₅)₂ altered the molar fractions of the major species and increased the consumption of •H, •O, and •OH. As the mass fraction of Fe(C₅H₅)₂ increased, the steady-state concentrations of •H, •O, and •OH in the system showed a significant decreasing trend. This phenomenon originated from the two-step synergistic mechanism of Fe(C₅H₅)₂ inhibiting radical generation and accelerating radical consumption. This study provides insight into the process of Fe(C₅H₅)₂/SiO₂ composite dry powder inhibition and renders theoretical guidance for the explosion protection of methane/hydrogen. Full article

(This article belongs to the Special Issue Clean Combustion and New Energy)

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23 pages, 6938 KiB

Open AccessArticle

A Hybrid Attention Framework Integrating Channel–Spatial Refinement and Frequency Spectral Analysis for Remote Sensing Smoke Recognition

by Guangtao Cheng, Lisha Yang, Zhihao Yu, Xiaobo Li and Guanghui Fu

Fire 2025, 8(5), 197; https://doi.org/10.3390/fire8050197 - 14 May 2025

Viewed by 239

Abstract

In recent years, accelerated global climate change has precipitated an increased frequency of wildfire events, with their devastating impacts on ecological systems and human populations becoming increasingly significant. Satellite remote sensing technology, leveraging its extensive spatial coverage and real-time monitoring capabilities, has emerged [...] Read more.

In recent years, accelerated global climate change has precipitated an increased frequency of wildfire events, with their devastating impacts on ecological systems and human populations becoming increasingly significant. Satellite remote sensing technology, leveraging its extensive spatial coverage and real-time monitoring capabilities, has emerged as a pivotal approach for wildfire early warning and comprehensive disaster assessment. To effectively detect subtle smoke signatures while minimizing background interference in remote sensing imagery, this paper introduces a novel dual-branch attention framework (CSFAttention) that synergistically integrates channel–spatial refinement with frequency spectral analysis to aggregate smoke features in remote sensing images. The channel–spatial branch implements an innovative triple-pooling strategy (incorporating average, maximum, and standard deviation pooling) across both channel and spatial dimensions to generate complementary descriptors that enhance distinct statistical properties of smoke representations. Concurrently, the frequency branch explicitly enhances high-frequency edge patterns, which are critical for distinguishing subtle textural variations characteristic of smoke plumes. The outputs from these complementary branches are fused through element-wise summation, yielding a refined feature representation that optimizes channel dependencies, spatial saliency, and spectral discriminability. The CSFAttention module is strategically integrated into the bottleneck structures of the ResNet architecture, forming a specialized deep network specifically designed for robust smoke recognition. Experimental validation on the USTC_SmokeRS dataset demonstrates that the proposed CSFResNet achieves recognition accuracy of 96.84%, surpassing existing deep networks for RS smoke recognition. Full article

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20 pages, 12721 KiB

Open AccessArticle

Evaluation of Topographic Effect Parameterizations in Weather Research and Forecasting Model over Complex Mountainous Terrain in Wildfire-Prone Regions

by Yonghan Jo, Seunghee Kim, Yungon Lee, Changki Kim, Jinkyu Hong, Junhong Lee and Keunchang Jang

Fire 2025, 8(5), 196; https://doi.org/10.3390/fire8050196 - 14 May 2025

Viewed by 265

Abstract

Recent trends of intense forest fires in the Korean Peninsula have increased concerns about more extreme burning in the future under a warming climate. Accurate and reliable fire weather information has become more critical to reduce the risk of forest-related disasters over complex [...] Read more.

Recent trends of intense forest fires in the Korean Peninsula have increased concerns about more extreme burning in the future under a warming climate. Accurate and reliable fire weather information has become more critical to reduce the risk of forest-related disasters over complex terrain. In this study, two parameterizations reflecting complex topographic effects were implemented in the Weather Research and Forecasting (WRF) model. The model performance was evaluated over the mountainous region in Gangwon-do, South Korea’s most significant forest area. The simulation results of the wildfire case in 2019 show that subgrid-scale orographic parameterization considerably improves model performance regarding wind speed, with a lower root mean square error (RMSE) and bias by 53% and 57%, respectively. Another parameterization, reflecting slope and shading, effectively reflected sunrise and sunset effects. The second parametrization produced little effect on the daily averages of meteorological elements. However, thermodynamic components such as temperature and heat flux show more realistic values during sunset or sunrise when the solar altitude angle is low. The results imply that applying topographic parameterizations is required in numerical simulations, especially for hazardous weather conditions over complex terrain in mountainous regions. Full article

(This article belongs to the Special Issue Dynamics of Wind-Fire Interaction: Fundamentals and Applications)

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23 pages, 12531 KiB

Open AccessArticle

Detailed Numerical Simulation of Planar Liquid Sheet Atomization: Instability Dynamics, Ligament Formation, and Self-Destabilization Mechanisms

by Ziting Zhao, Chenglin Zhou, Jianfeng Zou, Jiaqi Sun and Yufeng Yao

Fire 2025, 8(5), 195; https://doi.org/10.3390/fire8050195 - 13 May 2025

Viewed by 249

Abstract

The primary atomization of planar liquid sheets near nozzle exits plays a critical role in the study of pressure-swirl atomizers, yet its intrinsic destabilization and breakup mechanisms remain insufficiently characterized due to the multi-scale nature of gas–liquid interactions, significantly limiting the predictive capacity [...] Read more.

The primary atomization of planar liquid sheets near nozzle exits plays a critical role in the study of pressure-swirl atomizers, yet its intrinsic destabilization and breakup mechanisms remain insufficiently characterized due to the multi-scale nature of gas–liquid interactions, significantly limiting the predictive capacity of current widely adopted atomization models. This study utilizes three-dimensional direct numerical simulations (DNSs) with adaptive mesh refinement and the Volume-of-Fluid (VOF) method to examine the instability and disintegration of a spatially developing planar liquid sheet under operating conditions representative of aero-engine combustors (thickness

h = 100 μ m

,

W e = 2544

,

R e = 886

). Adaptive grid resolution (minimum cell size

2.5 μ m

) enables precise resolution of multi-scale interface dynamics while maintaining mass conservation errors below 0.1‱. High-fidelity simulations reveal distinct atomization cascades originating from the jet tip, characterized by liquid sheet roll-up, interface expanding, interface tearing, and ligament/droplet formation. Through extraction and surface characterization of representative shed liquid ligaments, we quantify temporal and spatial variations between ligaments propagating toward and away from the jet core region. Key findings demonstrate that ligament impingement on the liquid core serves as the dominant mechanism for surface wave destabilization, surpassing the influence of initial gas–liquid shear at the nozzle exit. Spectral analysis of upstream surface waves reveals a pronounced correlation between high-wavenumber disturbances and the mean diameter of shed ligaments. These results challenge assumptions in classical atomization models (e.g., LISA) by highlighting self-destabilization mechanisms driven by droplet–ligament interactions. This work provides critical insights for refining engineering atomization models through physics-based ligament diameter prediction criteria. Full article

(This article belongs to the Special Issue Turbulent Spray Combustion: Mechanism Research and Modeling)

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10 pages, 7894 KiB

Open AccessArticle

A Study on Prevention of Fire Proliferation in Building-Type Solar Modules

by Yong Chan Jung, Min Ji Song, Hee Kyung Park, Min Chul Lee and Soo Yeol Lee

Fire 2025, 8(5), 194; https://doi.org/10.3390/fire8050194 - 12 May 2025

Viewed by 299

Abstract

To prevent the vertical spread of fire from flammable components in Building-Integrated Photovoltaic (BIPV) modules during building fires, we applied a fire-resistant (FR) coating technology to the surface of BIPV modules, which are commonly used in Zero Energy Buildings (ZEBs). By applying an [...] Read more.

To prevent the vertical spread of fire from flammable components in Building-Integrated Photovoltaic (BIPV) modules during building fires, we applied a fire-resistant (FR) coating technology to the surface of BIPV modules, which are commonly used in Zero Energy Buildings (ZEBs). By applying an acrylic FR coating to the BIPV module, we quantitatively evaluated the influence of heat damage before and after the FR coating, the average propagation rate of flames, and the module failure time in a combustion environment. The results demonstrate that the flame-blocking function and fire diffusion prevention effect of the FR coating are excellent in all combustion environments. Particularly, flame damage is minimized under the condition of an FR coating with a thickness of at least 50 μm. The current work suggests fire resistance mechanisms in various combustion environments and provides the applicability of FR coating technology on BIPV modules for fire non-proliferation. Full article

(This article belongs to the Special Issue Photovoltaic and Electrical Fires: 2nd Edition)

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13 pages, 5017 KiB

Open AccessArticle

Effect of Initial Temperature on Flame Spread over a Sand Bed Wetted with Transformer Oil

by Jiaqing Zhang, Yubiao Huang, Yi Guo and Guocheng Ding

Fire 2025, 8(5), 193; https://doi.org/10.3390/fire8050193 - 10 May 2025

Viewed by 275

Abstract

A series of experiments were conducted on quartz sand beds wetted with transformer oil under initial temperatures of 80–140 °C and fuel–sand mass ratios of 1:4–1:8. The flame spreading process over the fine sand bed wetted with limited liquid fuel can be divided [...] Read more.

A series of experiments were conducted on quartz sand beds wetted with transformer oil under initial temperatures of 80–140 °C and fuel–sand mass ratios of 1:4–1:8. The flame spreading process over the fine sand bed wetted with limited liquid fuel can be divided into the development and quasi-steady stages. Experimental results reveal that the flame spread rate in the quasi-steady stage increases with the initial temperature and fuel–sand mass ratio. The effect of sand bed width on flame spread depends on the initial temperature. The flame spread rate is insensitive to the sand bed width at low initial temperatures; however, it increases with sand bed width at an initial temperature close to the flash point of liquid fuel. This discrepancy mainly results from the enhanced capillary effect due to the decreased viscosity at high initial temperatures. The capillary effect is the dominant factor determining fuel vaporization and, thus, the flame spread rate, and flame radiation plays an increasing role with increasing initial temperature. The maximum flame height is sensitive to sand bed width and fuel–sand mass ratio but changes little with initial temperature. A dimensionless model was proposed to predict the normalized flame height. Full article

(This article belongs to the Special Issue Dynamics of Wind-Fire Interaction: Fundamentals and Applications)

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28 pages, 11453 KiB

Open AccessArticle

Risk Analysis of Fuel Leakage and Explosion in LNG-Powered Ship Cabin Based on Computational Fluid Dynamics

by Yuechao Zhao, Yubo Li, Weijie Li, Yuan Gao, Qifei Wang and Dihao Ai

Fire 2025, 8(5), 192; https://doi.org/10.3390/fire8050192 - 10 May 2025

Viewed by 368

Abstract

In order to analyze the explosion risk of the engine room, this paper uses CFD software to simulate the LNG leakage process in the engine room of the ship, and uses the combustible gas cloud obtained from the leakage simulation to simulate the [...] Read more.

In order to analyze the explosion risk of the engine room, this paper uses CFD software to simulate the LNG leakage process in the engine room of the ship, and uses the combustible gas cloud obtained from the leakage simulation to simulate the explosion, analyzing its combustion and explosion dynamics. On the basis of previous studies, this paper studies the coupling of leakage and explosion simulation to ensure that it conforms to the real situation. At the same time, taking explosion overpressure, explosion temperature, and the mass fraction of combustion products as the breakthrough point, this paper studies the harm of explosion to human body and the influence of ignition source location on the propagation characteristics of LNG explosion shock wave in the engine room, and discusses the influence of obstacles on gas diffusion and accumulation. The results show that the LNG leakage reaches the maximum concentration in the injection direction, and the obstacles in the cabin have a significant effect on the diffusion and accumulation of gas. In the explosion simulation based on the leakage results, it can be determined that the shape of the pressure field generated by the explosion is irregular, and the pressure field at the obstacle side has obvious accumulation. Finally, in order to reduce the explosion hazard, the collaborative strategy of modular layout, directional ventilation, and gas detection is proposed, which provides ideas for the explosion-proof design of the cabin. Full article

(This article belongs to the Special Issue Confined Space Fire Safety and Alternative Fuel Fire Safety)

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22 pages, 10463 KiB

Open AccessArticle

The Effect of Toxicity, Physical and Thermal Properties of Fire Blanket Made of Glass Fiber on Its Quality as Small Fire Suppression Tool

by Mohamed A. Hassan, Mohamed M. AlSofian, Ahmed Al Zharani, Mohammed R. AlOtaibi, Sami Al Saeed and Naif Al Anazi

Fire 2025, 8(5), 191; https://doi.org/10.3390/fire8050191 - 9 May 2025

Viewed by 305

Abstract

The use of fiberglass blankets as fire suppression blankets to extinguish accidental cooking fires has been regulated and widely used, especially in homes and small firms and laboratories. Understanding the properties, which have significant effect on their performance, is essential for ensuring effective [...] Read more.

The use of fiberglass blankets as fire suppression blankets to extinguish accidental cooking fires has been regulated and widely used, especially in homes and small firms and laboratories. Understanding the properties, which have significant effect on their performance, is essential for ensuring effective fire control and improving the quality of these blankets in fire suppression. This study examines key properties including toxicity, physical characteristics, thermal behavior, and fire suppression capabilities. Novel properties such as air permeability and spectroscopic structural analysis are explored, areas previously under-researched. The sample number S4 had Warp/weft count 21/12 with comparison to air permeability; it gave the lowest value among the selected samples. Thermal properties, including heat transfer and temperature dynamics, are also analyzed to understand how fire spreads through the material. The optimal performance of air permeability was observed to be below 650 L/m²/s. Blankets demonstrated over 45% heat blocking efficiency at low heat flux and more than 78% at high heat flux. Temperature rise within the first minute of fire exposure is a key determinant, with effective blankets maintaining temperatures below 300 °C after one minute and ensuring that the final temperature after three minutes does not exceed 390–400 °C. Additionally, a new classification system based on the toxicity of gases emitted during combustion was introduced, enhancing the safety profile of fiberglass blankets and improving their suitability for practical use. This research contributes valuable insights into both the performance and safety of fiberglass fire blankets Full article

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36 pages, 12494 KiB

Open AccessArticle

Structural and Fire Performance of Cold-Formed Steel Columns Subjected to Cavity Fire in Modular Buildings

by Rajeendra Godakandage, Kumari Gamage, Pasindu Weerasinghe, Satheeskumar Navaratnam and Kate T. Q. Nguyen

Fire 2025, 8(5), 190; https://doi.org/10.3390/fire8050190 - 9 May 2025

Viewed by 368

Abstract

Fire safety is one of the critical concerns for the design and construction of modular structures. The lack of understanding of cavity fire spread in modular construction could create variations in the fire performance of structural members. This study aimed to assess the [...] Read more.

Fire safety is one of the critical concerns for the design and construction of modular structures. The lack of understanding of cavity fire spread in modular construction could create variations in the fire performance of structural members. This study aimed to assess the impact of cavity fire spread in modular buildings initiated by a room fire using validated fire dynamics and structural numerical models. A comprehensive parametric study was conducted to identify critical thermal conditions affecting adjacent structural members under plausible cavity fire scenarios. The identified critical cavity fire thermal conditions were used to examine the structural performance of cold-formed steel intermediate column specimens while varying geometric configurations, material properties, and boundary conditions. The results highlighted two distinct phases of restrained thermal expansion and lateral deformations under material yielding and buckling, resulting in the loss of structural integrity. The restrained thermal expansion significantly increased axial/restraint forces, reaching up to 155% of the initial load. This behavior decreased axial load capacity by 2.4% to 35% of the ambient capacity. Further, the study identifies a requirement for designing the intermediate columns and the connected intermodular connections for increased design action equivalent to 56% of the service load. Full article

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

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17 pages, 25082 KiB

Open AccessArticle

Wildfire Mitigation and Evaluation of Firebreaks Through FlamMap Simulations in High-Susceptibility Areas of the Metropolitan District of Quito

by Juan Gabriel Mollocana-Lara, Katiuska Jajaira Obando-Proaño and Betsy Germania Córdova-Luspa

Fire 2025, 8(5), 189; https://doi.org/10.3390/fire8050189 - 8 May 2025

Viewed by 435

Abstract

Wildfires represent a growing concern worldwide, and their frequency has increased due to climate change and human activities, posing risks to biodiversity and human safety. In the Metropolitan District of Quito (DMQ), the combination of flammable vegetation and steep slopes increases the wildfire [...] Read more.

Wildfires represent a growing concern worldwide, and their frequency has increased due to climate change and human activities, posing risks to biodiversity and human safety. In the Metropolitan District of Quito (DMQ), the combination of flammable vegetation and steep slopes increases the wildfire susceptibility. Although there are no formally designated firebreaks in these areas, many natural and artificial elements, such as roads, water bodies, and rocky terrain, can effectively function as firebreaks if properly adapted. This study aimed to evaluate the wildfire behavior and assess the effectiveness of both adapted existing barriers and proposed firebreaks using FlamMap simulations. Geospatial and meteorological data were integrated to generate landscape and weather inputs for simulating wildfires in nine high-susceptibility areas within the DMQ. Fuel vegetation models were obtained by matching the national land-cover data with Scott and Burgan fuel models, and OpenStreetMap data were used to identify the firebreak locations. The simulation results show that adapting existing potential firebreaks could reduce the burned area by an average of 42.6%, and the addition of strategically placed firebreaks could further reduce it by up to 70.2%. The findings suggest that implementing a firebreak creation and maintenance program could be an effective tool for wildfire mitigation. Full article

(This article belongs to the Section Fire Science Models, Remote Sensing, and Data)

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26 pages, 8246 KiB

Open AccessArticle

An Investigation into the Rescue-Path Planning Algorithm for Multiple Mine Rescue Teams Based on FA-MDPSO and an Improved Force-Directed Layout

by Qiangyu Zheng, Peijiang Ding, Zhixin Qin and Zhenguo Yan

Fire 2025, 8(5), 188; https://doi.org/10.3390/fire8050188 - 8 May 2025

Viewed by 285

Abstract

It is noted that existing mine emergency-rescue algorithms have overlooked the requirement for multi-route sharing at critical nodes and have offered limited network visualisation. Consequently, a multi-team rescue-path-planning algorithm based on FA-MDPSO (Firefly Algorithm-Multiple Constraints Discrete Particle Swarm Optimisation) was proposed, and a [...] Read more.

It is noted that existing mine emergency-rescue algorithms have overlooked the requirement for multi-route sharing at critical nodes and have offered limited network visualisation. Consequently, a multi-team rescue-path-planning algorithm based on FA-MDPSO (Firefly Algorithm-Multiple Constraints Discrete Particle Swarm Optimisation) was proposed, and a graph-structure optimisation method combining a Force-Directed Layout with Breadth-First Search was introduced for node arrangement and visualisation. Methodologically, the superiority of the improved DPSO (Discrete Particle Swarm Optimisation) in route-planning precision was first validated on the DIMACS dataset. Subsequently, the hyperparameters of MDPSO (Multiple Constraints Discrete Particle Swarm Optimisation) were optimised by means of four intelligent algorithms—ACO (Ant Colony Optimization), FA (Firefly Algorithm), GWO (Grey Wolf Optimizer) and WOA (Whale Optimization Algorithm). Finally, simulations of one to three rescue-team deployments were conducted within a mine-fire scenario, and node-importance analysis was performed. Results indicated that FA-MDPSO achieved comprehensive superiority in route precision, search efficiency and convergence speed, with FA-based hyperparameter optimisation proving most effective in comparative experiments. The graph-structure optimisation was found to substantially reduce crossings and enhance hierarchical clarity. Moreover, the three-team deployment yielded the shortest equivalent path (56,357.02), and node-visitation frequency was observed to be highly concentrated on a small number of key nodes. This not only significantly improves the collaborative rescue efficiency but also provides intuitive and practical technical support for intelligent mine rescue operations. It lays an important foundation for optimising mine emergency rescue plans, ensuring the safety of underground personnel, and promoting the intelligent development of mines. Full article

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17 pages, 4666 KiB

Open AccessArticle

Lightweight YOLOv5s Model for Early Detection of Agricultural Fires

by Saydirasulov Norkobil Saydirasulovich, Sabina Umirzakova, Abduazizov Nabijon Azamatovich, Sanjar Mukhamadiev, Zavqiddin Temirov, Akmalbek Abdusalomov and Young Im Cho

Fire 2025, 8(5), 187; https://doi.org/10.3390/fire8050187 - 8 May 2025

Viewed by 458

Abstract

Agricultural fires significantly threaten global food systems, ecosystems, and rural economies, necessitating timely detection to prevent widespread damage. This study presents a lightweight and enhanced version of the YOLOv5s model, optimized for early-stage agricultural fire detection. The core innovation involves deepening the C3 [...] Read more.

Agricultural fires significantly threaten global food systems, ecosystems, and rural economies, necessitating timely detection to prevent widespread damage. This study presents a lightweight and enhanced version of the YOLOv5s model, optimized for early-stage agricultural fire detection. The core innovation involves deepening the C3 block and integrating DarknetBottleneck modules to extract finer visual features from subtle fire indicators such as light smoke and small flames. Experimental evaluations were conducted on a custom dataset of 3200 annotated agricultural fire images. The proposed model achieved a precision of 88.9%, a recall of 85.7%, and a mean Average Precision (mAP) of 87.3%, outperforming baseline YOLOv5s and several state-of-the-art (SOTA) detectors such as YOLOv7-tiny and YOLOv8n. The model maintains a compact size (7.5 M parameters) and real-time capability (74 FPS), making it suitable for resource-constrained deployment. Our findings demonstrate that focused architectural refinement can significantly improve early fire detection accuracy, enabling more effective response strategies and reducing agricultural losses. 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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31 pages, 4948 KiB

Open AccessArticle

Forest Fires, Vulnerability, and Exposure: The Evaluation of What Was Salvaged in the 2023 Fire in Tenerife (Spain)

by Jordan Correa, Lucie Boulat and Pedro Dorta

Fire 2025, 8(5), 186; https://doi.org/10.3390/fire8050186 - 7 May 2025

Viewed by 413

Abstract

Forest fires are one of the risks with the greatest socio-territorial impact in island areas with Mediterranean precipitation characteristics. Regions such as the Canary Islands, densely populated and where there is no clear differentiation between land uses, regularly suffer major forest fires that [...] Read more.

Forest fires are one of the risks with the greatest socio-territorial impact in island areas with Mediterranean precipitation characteristics. Regions such as the Canary Islands, densely populated and where there is no clear differentiation between land uses, regularly suffer major forest fires that devastate a large part of their forest mass and endanger the lives and property of thousands of people. This paper characterizes the forest fire that occurred on the island of Tenerife during the month of August 2023—defined as the most severe in Spain during that year—from a double perspective: on the one hand, analysis of the exposure and vulnerability of the buildings located in the surroundings of the fire and, on the other hand, economic quantification of the assets salvaged thanks to the intervention of the means and resources deployed by the authorities. The conclusion is that the analyzed buildings exhibit moderate vulnerability and exposure, being high in aspects such as their poor accessibility, their proximity to forest areas and, specifically, to dangerous fuel models, as well as the slope of their surroundings and their proximity to ravines. In terms of the evaluation of what was salvaged, the losses avoided are estimated at EUR 187 million, which would have been added to the actual losses—EUR 164 million—especially thanks to the interventions carried out around the nearby buildings and agricultural areas. Full article

(This article belongs to the Special Issue Building Fires, Evacuations and Rescue)

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20 pages, 5225 KiB

Open AccessArticle

Study of Temperature Distribution in U-Shaped Underwater Tunnel Fires Under the Influence of Induced Airflow

by Yuhang Zhou, Guoqing Zhu, Yuyang Ming, Xinyu Wang, Xuming Li and Liang Wang

Fire 2025, 8(5), 185; https://doi.org/10.3390/fire8050185 - 7 May 2025

Viewed by 173

Abstract

Compared to a single horizontal or inclined tunnel, a U-shaped underwater tunnel combines both types. If such tunnels catch fire, the resulting scenarios will lead to varying intensities of induced airflow, which significantly impact the internal heat transfer mechanisms. This study numerically simulated [...] Read more.

Compared to a single horizontal or inclined tunnel, a U-shaped underwater tunnel combines both types. If such tunnels catch fire, the resulting scenarios will lead to varying intensities of induced airflow, which significantly impact the internal heat transfer mechanisms. This study numerically simulated the effects of varying induced airflow strengths on the heat transfer proportion and temperature distribution within the tunnel. Key variables including the inclination angle of tunnel sections, the heat release rate (HRR) of the fire source, and its distance to the tunnel opening were systematically investigated. The results indicate that when the fire is in the horizontal tunnel section, the primary factor affecting the temperature field distribution is the HRR of the fire. As the fire source moves toward the inclined tunnel section, a transition to strong induced airflow occurs above the corner at low angles of inclination. As the slope increases, the transition position shifts downstream, toward the lower side of the corner. At this point, the tunnel is affected by strong induced airflow. Using dimensionless analysis, models were developed for temperature field distribution under strong and weak induced airflow, guiding underwater tunnel spray activation temperature and firefighting and rescue efforts. Full article

(This article belongs to the Special Issue Modeling, Experiment and Simulation of Tunnel Fire)

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15 pages, 7056 KiB

Open AccessArticle

Numerical Investigation of the Wan’an Bridge Fire and the Protection Effect of Intumescent Flame-Retardant Coatings

by Huiling Jiang, Jie Teng, Dong Wang, Liang Zhou and Yirui Chen

Fire 2025, 8(5), 184; https://doi.org/10.3390/fire8050184 - 7 May 2025

Viewed by 158

Abstract

The Wan’an Bridge, the longest wooden lounge bridge in China with a history of more than 900 years, was devastated by a catastrophic fire in 2022. This tragic event underscores the susceptibility of historical wooden structures to fire damage. In this article, the [...] Read more.

The Wan’an Bridge, the longest wooden lounge bridge in China with a history of more than 900 years, was devastated by a catastrophic fire in 2022. This tragic event underscores the susceptibility of historical wooden structures to fire damage. In this article, the bridge’s intricate structure and the development of the fire incident are introduced in detail. To gain a deeper insight into the patterns of fire propagation across the bridge and assess the reliability of fire simulations in predicting fire spread in historical wooden structures, we utilized the Fire Dynamics Simulator (FDS), with a sophisticated pyrolysis model and thermal response parameters specifically tailored to ancient fir wood. The modeling results reveal that the FDS simulation reflects the actual fire spread process well. Both the investigation and simulation findings indicate that once the flame reaches above the bridge deck, it enters a rapid three-dimensional propagation phase that is exceptionally challenging to control. Furthermore, the modeling results suggest that the application of intumescent fire-retardant coatings can significantly delay fire spread, reduce heat release rates, and suppress smoke production, thereby making them an effective fire prevention measure for historical wooden buildings. Full article

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23 pages, 8831 KiB

Open AccessArticle

YOLOv8n-SMMP: A Lightweight YOLO Forest Fire Detection Model

by Nianzu Zhou, Demin Gao and Zhengli Zhu

Fire 2025, 8(5), 183; https://doi.org/10.3390/fire8050183 - 3 May 2025

Viewed by 423

Abstract

Global warming has driven a marked increase in forest fire occurrences, underscoring the critical need for timely and accurate detection to mitigate fire-related losses. Existing forest fire detection algorithms face limitations in capturing flame and smoke features in complex natural environments, coupled with [...] Read more.

Global warming has driven a marked increase in forest fire occurrences, underscoring the critical need for timely and accurate detection to mitigate fire-related losses. Existing forest fire detection algorithms face limitations in capturing flame and smoke features in complex natural environments, coupled with high computational complexity and inadequate lightweight design for practical deployment. To address these challenges, this paper proposes an enhanced forest fire detection model, YOLOv8n-SMMP (SlimNeck–MCA–MPDIoU–Pruned), based on the YOLO framework. Key innovations include the following: introducing the SlimNeck solution to streamline the neck network by replacing conventional convolutions with Group Shuffling Convolution (GSConv) and substituting the Cross-convolution with 2 filters (C2f) module with the lightweight VoV-based Group Shuffling Cross-Stage Partial Network (VoV-GSCSP) feature extraction module; integrating the Multi-dimensional Collaborative Attention (MCA) mechanism between the neck and head networks to enhance focus on fire-related regions; adopting the Minimum Point Distance Intersection over Union (MPDIoU) loss function to optimize bounding box regression during training; and implementing selective channel pruning tailored to the modified network architecture. The experimental results reveal that, relative to the baseline model, the optimized lightweight model achieves a 3.3% enhancement in detection accuracy (mAP@0.5), slashes the parameter count by 31%, and reduces computational overhead by 33%. These advancements underscore the model’s superior performance in real-time forest fire detection, outperforming other mainstream lightweight YOLO models in both accuracy and efficiency. Full article

(This article belongs to the Special Issue Intelligent Forest Fire Prediction and Detection)

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18 pages, 2105 KiB

Open AccessArticle

Effectiveness of Self-Contained Breathing Apparatus: An Observational Study on Exposure to Polycyclic Aromatic Hydrocarbons and Associated Respiratory Risks

by Joana Teixeira, Cristina Delerue-Matos, Alice Santos-Silva, Francisca Rodrigues and Marta Oliveira

Fire 2025, 8(5), 182; https://doi.org/10.3390/fire8050182 - 2 May 2025

Viewed by 335

Abstract

Background: An effective risk assessment and management methodology is essential to minimize/mitigate health risks associated with firefighting activities. The use of a self-contained breathing apparatus (SCBA) is mandatory during structure fires to protect firefighters from hazardous fire effluents, yet the protectiveness of the [...] Read more.

Background: An effective risk assessment and management methodology is essential to minimize/mitigate health risks associated with firefighting activities. The use of a self-contained breathing apparatus (SCBA) is mandatory during structure fires to protect firefighters from hazardous fire effluents, yet the protectiveness of the SCBA system has rarely been evaluated. Objective: This study characterizes, for the first time, the levels of 18 polycyclic aromatic hydrocarbons (PAHs) inside the SCBA facemask, during 7 structure-firefighting exercises and estimates associated respiratory risks. Methods: Cotton disk samples were collected via passive air sampling and analyzed using liquid chromatography with fluorescence and UV–Vis detection. Results: Levels of total PAHs (∑PAHs: 9.17–29.6 ng/m³) and ∑PAHs_carcinogenic (0.41–5.73 ng/m³) were below the occupational limits defined by governmental agencies. The low-molecular-weight PAHs were predominant (79.5–91.4%), and the (possible/known) carcinogenic naphthalene (0.26–2.00 ng/m³), anthracene (0.088–0.31 ng/m³), chrysene (0.046–0.39 ng/m³), benzo(b+j)fluoranthene (0.18–0.40 ng/m³), and benzo(a)pyrene (0.041–0.18 ng/m³) were detected in all samples. The respiratory health risk analysis demonstrated negligible risks associated with the inhalation of PAHs. A health principal component analysis could identify firefighters at increased respiratory risk. Conclusions: The effectiveness of SCBA was demonstrated, reinforcing the need to ensure its correct use during all the phases of structure fires, including during overhaul. Full article

(This article belongs to the Special Issue Advances in Industrial Fire and Urban Fire Research: 2nd Edition)

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11 pages, 4528 KiB

Open AccessTechnical Note

Comparative Study of Temperature Distribution Characteristics of Ceiling Jets at Center and Edge Regions in Corridors

by Yunseong Kim, Youngjin Kwon, Hyun Kang and Ohsang Kweon

Fire 2025, 8(5), 181; https://doi.org/10.3390/fire8050181 - 30 Apr 2025

Viewed by 205

Abstract

This study analyzed the temperature characteristics of ceiling jets in corridor spaces by conducting experiments with varying heat release rates and ceiling heights and comparing the results with predictive equations based on the energy conservation equation. The smoke layer formed at a lower [...] Read more.

This study analyzed the temperature characteristics of ceiling jets in corridor spaces by conducting experiments with varying heat release rates and ceiling heights and comparing the results with predictive equations based on the energy conservation equation. The smoke layer formed at a lower height than in open spaces, and the ceiling jet temperature near the wall was higher than that along the central axis. Predictions were generally accurate at a ceiling height of 3.0 m but were overestimated at 1.5 m and underestimated at 4.5 m. The temperature attenuation trend aligned with Oka’s equations, though the temperature near the wall remained higher. Full article

(This article belongs to the Section Fire Science Models, Remote Sensing, and Data)

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19 pages, 6509 KiB

Open AccessArticle

Optimized Faster R-CNN with Swintransformer for Robust Multi-Class Wildfire Detection

by Sugi Choi, Sunghwan Kim and Haiyoung Jung

Fire 2025, 8(5), 180; https://doi.org/10.3390/fire8050180 - 30 Apr 2025

Viewed by 281

Abstract

Wildfires are a critical global threat, emphasizing the need for efficient detection systems capable of identifying fires and distinguishing fire-related from non-fire events in their early stages. This study integrates the swintransformer into the Faster R-CNN backbone to overcome challenges in detecting small [...] Read more.

Wildfires are a critical global threat, emphasizing the need for efficient detection systems capable of identifying fires and distinguishing fire-related from non-fire events in their early stages. This study integrates the swintransformer into the Faster R-CNN backbone to overcome challenges in detecting small flames and smoke and distinguishing complex scenarios like fog/haze and chimney smoke. The proposed model was evaluated using a dataset comprising five classes: flames, smoke, clouds, fog/haze, and chimney smoke. Experimental results demonstrate that swintransformer-based models outperform ResNet-based Faster R-CNN models, achieving a maximum mAP50 of 0.841 with the swintransformer-based model. The model exhibited superior performance in detecting small and dynamic objects while reducing misclassification rates between similar classes, such as smoke and chimney smoke. Precision–recall analysis further validated the model’s robustness across diverse scenarios. However, slightly lower recall for specific classes and a lower FPS compared to ResNet models suggest a need for further optimization for real-time applications. This study highlights the swintransformer’s potential to enhance wildfire detection systems by addressing fire and non-fire events effectively. Future research will focus on optimizing its real-time performance and improving its recall for challenging scenarios, thereby contributing to the development of robust and reliable wildfire detection systems. Full article

(This article belongs to the Special Issue Advanced Approaches to Wildfire Detection, Monitoring and Surveillance)

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20 pages, 9095 KiB

Open AccessArticle

Applying a Fire Exposure Metric in the Artificial Territories of Portugal: Mafra Municipality Case Study

by Sidra Ijaz Khan, Jennifer L. Beverly, Maria Conceição Colaço, Francisco Castro Rego and Ana Catarina Sequeira

Fire 2025, 8(5), 179; https://doi.org/10.3390/fire8050179 - 30 Apr 2025

Viewed by 669

Abstract

Portugal’s increasing wildfire frequency has led to home destruction, large areas burned, ecological damage, and economic loss, emphasizing the need for effective fire exposure assessments. This study builds on a Canadian approach to wildfire exposure and evaluates wildfire exposure in the Portuguese municipality [...] Read more.

Portugal’s increasing wildfire frequency has led to home destruction, large areas burned, ecological damage, and economic loss, emphasizing the need for effective fire exposure assessments. This study builds on a Canadian approach to wildfire exposure and evaluates wildfire exposure in the Portuguese municipality of Mafra, using artificial territories (AT) as a proxy for the wildland–urban interface (WUI) and integrates land use land cover (LULC) data with a neighborhood analysis to map exposure at the municipal scale. Fire exposure was assessed for three fire transmission distances: radiant heat (RH, <30 m), short-range spotting (SRS, <100 m), and longer-range spotting (LRS, 100–500 m) using fine resolution (5 m) LULC data. Results revealed that while AT generally exhibited lower exposure (<16% “very high” exposure), adjacent hazardous LULC subtypes significantly increase wildfire hazard, with up to 51% of LULC subtypes classified as “very high exposure”. Field validation confirmed the accuracy of exposure maps, supporting their use in wildfire risk reduction strategies. This cost-effective, scalable approach offers actionable insights for forest and land managers, civil protection agencies, and policymakers, aiding in fuel management prioritization, community preparedness, and the design of evacuation planning. The methodology is adaptable to other fire-prone regions, particularly mediterranean landscapes. Full article

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

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27 pages, 11723 KiB

Open AccessArticle

A Near-Real-Time Operational Live Fuel Moisture Content (LFMC) Product to Support Decision-Making at the National Level

by Akli Benali, Giuseppe Baldassarre, Carlos Loureiro, Florian Briquemont, Paulo M. Fernandes, Carlos Rossa and Rui Figueira

Fire 2025, 8(5), 178; https://doi.org/10.3390/fire8050178 - 30 Apr 2025

Viewed by 1313

Abstract

Live fuel moisture content (LFMC) significantly influences fire activity and behavior over different spatial and temporal scales. The ability to estimate LFMC is important to improve our capability to predict when and where large wildfires may occur. Currently, there is a gap in [...] Read more.

Live fuel moisture content (LFMC) significantly influences fire activity and behavior over different spatial and temporal scales. The ability to estimate LFMC is important to improve our capability to predict when and where large wildfires may occur. Currently, there is a gap in providing reliable near-real-time LFMC estimates which can contribute to better operational decision-making. The objective of this work was to develop near-real-time LFMC estimates for operational purposes in Portugal. We modelled LFMC using Random Forests for Portugal using a large set of potential predictor variables. We validated the model and analyzed the relationships between estimated LFMC and both fire size and behavior. The model predicted LFMC with an R² of 0.78 and an RMSE of 12.82%, and combined six variables: drought code, day-of-year and satellite vegetation indices. The model predicted well the temporal LFMC variability across most of the sampling sites. A clear relationship between LFMC and fire size was observed: 98% of the wildfires larger than 500 ha occurred with LFMC lower than 100%. Further analysis showed that 90% of these wildfires occurred for dead and live fuel moisture content lower than 10% and 100%, respectively. Fast-spreading wildfires were coincident with lower LFMC conditions: 92% of fires with rate of spread larger than 1000 m/h occurred with LFMC lower than 100%. The availability of spatial and temporal LFMC information for Portugal will be relevant for better fire management decision-making and will allow a better understanding of the drivers of large wildfires. Full article

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

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27 pages, 3258 KiB

Open AccessArticle

Urban Fire Spatial–Temporal Prediction Based on Multi-Source Data Fusion

by Haiyu Xiang, Lizhi Wu, Zidong Guo and Shaoyun Ren

Fire 2025, 8(5), 177; https://doi.org/10.3390/fire8050177 - 30 Apr 2025

Viewed by 278

Abstract

Urban fire incidents pose significant risks to public safety and infrastructure, necessitating precise spatiotemporal prediction to enhance fire prevention and emergency response strategies. However, predicting fire occurrences remains a complex task due to the intricate interplay between spatial and temporal factors, including dynamic [...] Read more.

Urban fire incidents pose significant risks to public safety and infrastructure, necessitating precise spatiotemporal prediction to enhance fire prevention and emergency response strategies. However, predicting fire occurrences remains a complex task due to the intricate interplay between spatial and temporal factors, including dynamic environmental conditions, historical dependencies, and inter-regional correlations. Temporal variables, such as past fire incidents and external influences like meteorological conditions, significantly impact fire risk, while spatial attributes, including regional characteristics and cross-regional interactions, further complicate predictive modeling. This study introduces UFSTP, an innovative framework for Urban Fire Spatial–Temporal Prediction that integrates multi-source data for enhanced predictive accuracy. UFSTP employs a neural region state representation to capture both intrinsic and extrinsic temporal dependencies, alongside a spatiotemporal propagation mechanism to model inter-regional correlations. Key environmental and historical features are extracted from real-world datasets to construct a comprehensive fire risk representation, facilitating the precise forecasting of fire occurrence in both time and space. Extensive evaluations on real-world datasets from Anci and Guangyang Districts demonstrate that UFSTP achieves a 16.2% average reduction in Mean Absolute Error (MAE) for time prediction and a 3.3% average improvement in top-1 hit rate for regional prediction over state-of-the-art baselines. The proposed framework offers a robust and interpretable approach to urban fire risk assessment, providing critical insights to optimize fire prevention measures and emergency resource allocation. Full article

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

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