Fire, Volume 7, Issue 6 (June 2024) – 38 articles

Fire is considered a common hazard for civil structures. Public and administrative buildings are commonly designed by considering the standard fire rating and, in many cases, contain large compartments with central domes, in which fire growth can be significant. Moreover, tanks and underground fortified structures may be constructed as domes to support the heavy soil above. This paper numerically addressed such a case. First, an axisymmetric finite element model was developed and validated to predict the dome’s transient, thermal, structural, and thermal-structural behavior. Next, the model was used to conduct a parametric study to investigate the effects of the dome ring reinforcement, thickness, stiffness, central angle, base restraints, load type (external pressure or gravitational), and load ratio on the fire endurance of the dome. Design recommendations to increase the fire endurance of concrete domes were formulated based on the parametric study. Full article

Wildfire spread models are an essential tool for mitigating catastrophic effects associated with wildfires. However, current operational models suffer from significant limitations regarding accuracy and transferability. Recent advances in the availability and capability of Earth observation data and artificial intelligence offer new perspectives for data-driven modeling approaches with the potential to overcome the existing limitations. Therefore, this study developed a data-driven Deep Learning wildfire spread modeling approach based on a comprehensive dataset of European wildfires and a Spatiotemporal Graph Neural Network, which was applied to this modeling problem for the first time. A country-scale model was developed on an individual wildfire time series in Portugal while a second continental-scale model was developed with wildfires from the entire Mediterranean region. While neither model was able to predict the daily spread of European wildfires with sufficient accuracy (weighted macro-mean IoU: Portugal model 0.37; Mediterranean model 0.36), the continental model was able to learn the generalized patterns of wildfire spread, achieving similar performances in various fire-prone Mediterranean countries, indicating an increased capacity in terms of transferability. Furthermore, we found that the spatial and temporal dimensions of wildfires significantly influence model performance. Inadequate reference data quality most likely contributed to the low overall performances, highlighting the current limitations of data-driven wildfire spread models. Full article

Optimizing Resource Allocation in Fire Departments (RAFD) is crucial for enhancing Fire Protection Services (FPS) and ultimately saving lives. Efficient RAFD ensures that fire departments have the necessary resources to respond effectively to emergencies. This paper presents a method for optimizing RAFD based on performance assessment results, examining its impact on Fire Department (FD) efficiency in Portugal. Evaluating data from 353 FDs, two RAFD optimization methods were assessed: one adhering to Portuguese regulations and constraints, such as budget allocation limitations, and another without such constraints. Integrating a slack-based data envelopment analysis model and mixed-integer linear programming, the study found that incorporating FD efficiency scores in RAFD improved overall efficiency at national, district, and FD levels. While adherence to Portuguese regulations led to balanced resource allocation and a 4% performance improvement at the national level, relaxing constraints yielded an 8% improvement, albeit with potential performance deterioration in some FDs. The detailed budget and efficiency metric analysis provided in this paper offers actionable insights for fire protection services enhancement. This underscores the importance of diverse optimization strategies to enhance FD efficiency, with implications for decision-makers at the Portuguese National Authority for Emergency and Civil Protection and similar organizations globally. Full article

The study of forest fire prediction holds significant environmental and scientific importance, particularly in regions like South Carolina (SC) with a high incidence rate of forest fires. Despite the limited existing research on forest fires in this area, the application of machine learning and neural network techniques presents an opportunity to enhance forest fire prevention and control efforts. Utilizing data of forest fire from the SC Forestry Commission for the year 2023, prediction models were developed incorporating various factors such as meteorology, terrain, vegetation, and infrastructure—key drivers of forest fires in SC. Feature importance analysis was employed to construct the final fire prediction model using different machine learning and neural network approaches including Decision Tree (DT), Random Forest (RF), Logistic Regression (LR), Artificial Neural Network (ANN), Support Vector Machine (SVM), and Convolutional Neural Network (CNN). Correlation coefficients analysis was employed to construct the final fire hazard map using a correlation test. The evaluation of predictive performance based on accuracy scores revealed that the DT model achieved the highest accuracy of 90.58%, surpassing other models. However, based on the kernel density map of the fire data from 2000 to 2023, the correlation test gave the better fire hazard map compared to any other machine learning or neural network approach that utilized feature importance. Nonetheless, all models achieved prediction accuracies exceeding 80%. This finding directed us to the approach based on the correlation coefficients rather than to those just based on feature importance. The overlap between fire locations and carbon hotspots provided the immediate need to mitigate the carbon loss due to fire in those locations. These results serve as a valuable resource for forest fire prediction in SC, demonstrating the efficacy of the correlation test, providing a theoretical foundation and data support for future forestry applications in the region, and showing the outperforming capability of this method compared to other approaches based on feature importance and the importance to prioritize areas to mitigate the climate change impact based upon fire prediction. Full article

Carbon stocks provide information that is essential for analyzing the role of forests in global climate mitigation, yet they are highly vulnerable to wildfires in Mediterranean ecosystems. These carbon stocks’ exposure to fire is usually estimated from specific allometric equations relating tree height and diameter to the overall amount of aboveground carbon storage. Assessments of vulnerability to fire additionally allow for specific fire resistance (bark thickness, crown basal height) and post-fire recovery traits (cone mass for regeneration, and fine branches or leaves mass for flammability) to be accounted for. These traits are usually considered as static, and their temporal dynamic is rarely assessed, thus preventing a full assessment of carbon stocks’ vulnerability and subsequent cascading effects. This study aimed to measure the pools of carbon stocks of individual trees varying between 30 and 96 years old in the Djbel Mansour Aleppo pine (Pinus halepensis) forest in semi-arid central Tunisia in the southern range of its distribution to fit a sigmoid equation of the carbon pools and traits recovery according to age as a vulnerability framework. Allometric equations were then developed to establish the relationships between fire vulnerability traits and dendrometric independent variables (diameter at breast height, height, and live crown length) for further use in regional vulnerability assessments. The total carbon stocks in trees varied from 29.05 Mg C ha⁻¹ to 92.47 Mg C ha⁻¹. The soil organic carbon stock (SOC) at a maximum soil depth of 0–40 cm varied from 31.67 Mg C ha⁻¹ to 115.67 Mg C ha⁻¹ at a soil depth of 0–70 cm. We could identify an increasing resistance related to increasing bark thickness and basal crown height with age, and enhanced regeneration capacity after 25 years of age with increasing cone biomass, converging toward increasing vulnerability and potential cascading effects under shorter interval fires. These results should be considered for rigorous forest carbon sequestration assessment under increasing fire hazards due to climate and social changes in the region. Full article

The well-known phenomenon of attracting untypical animals to disturbed territories has been poorly investigated in the polar mountains. We studied arthropod diversity in self-healing industrial clear-cuts and burn areas in the Khibiny Mountains, Kola Polar region. Fieldworks were conducted at four sites, including a control mountain taiga forest and its three transformed variants: burnt forest, uncleared clear-cut, and twice-disturbed burnt clear-cut. Arthropods were collected using formalin traps 2–3, 5–6, and 8–9 years after industrial deforestation in 2012 and an extensive grass-roots fire in 2013. Out of 124 identified species (spiders—61; ground beetles—41; and rove beetles—22), 79 (or 64%) were collected in disturbed, primarily burned areas and were absent in control forest. We note ten species of rove beetles, nine species of ground beetles, and eight species of spiders for the first time in the well-studied arthropod fauna of the Khibiny Mts. We found that grass-root fires transform the soil vegetation covers in the polar mountain forests more powerfully in comparison with extensive deforestation and attract a greater diversity of arthropods with different preferences, enriching the fauna of the polar mountains and the Subarctic region as a whole. The attraction effect persists for, at least, a decade after the violations. Full article

The natural wind velocities in tunnels under different natural conditions are distinct, and the longitudinal ventilation velocity significantly impacts the evacuation environment. This paper examines the evacuation conditions and strategies under varying wind velocities in bifurcated tunnels. Using Fire Dynamics Simulator (FDS) and Pathfinder software, the fire development and evacuation of three distinct longitudinal positions in a bifurcated tunnel are simulated. The simulation results demonstrate that the evacuation conditions for disparate fire sources at varying wind velocities are markedly disparate. In consideration of the construction cost and the maximization of evacuation capacity, the width of the evacuation doors at the three locations should be set to 2 m, 1.5 m, and 1.5 m, respectively. Furthermore, an analysis of the safety of individual personnel through Fractional Effective Dose (FED) revealed that directing evacuees towards the upstream of the fire after the fire is detected can significantly reduce individual personnel injuries while ensuring the overall success of the evacuation. Full article

Wildfires cause great losses to the ecological environment, economy, and people’s safety and belongings. As a result, it is crucial to establish wildfire susceptibility models and delineate fire risk levels. It has been proven that the use of remote sensing data, such as meteorological and topographical data, can effectively predict and evaluate wildfire susceptibility. Accordingly, this paper converts meteorological and topographical data into fire-influencing factor raster maps for wildfire susceptibility prediction. The continuous convolutional neural network (CCNN for short) based on coordinate attention (CA for short) can aggregate different location information into channels of the network so as to enhance the feature expression ability; moreover, for different patches with different resolutions, the improved CCNN model does not need to change the structural parameters of the network, which improves the flexibility of the network application in different forest areas. In order to reduce the annotation of training samples, we adopt an active learning method to learn positive features by selecting high-confidence samples, which contributes to enhancing the discriminative ability of the network. We use fire probabilities output from the model to evaluate fire risk levels and generate the fire susceptibility map. Taking Chongqing Municipality in China as an example, the experimental results show that the CA-based CCNN model has a better classification performance; the accuracy reaches 91.7%, and AUC reaches 0.9487, which is 5.1% and 2.09% higher than the optimal comparative method, respectively. Furthermore, if an accuracy of about 86% is desired, our method only requires 50% of labeled samples and thus saves about 20% and 40% of the labeling efforts compared to the other two methods, respectively. Ultimately, the proposed model achieves the balance of high prediction accuracy and low annotation cost and is more helpful in classifying fire high warning zones and fire-free zones. Full article

The fire heat release rate (HRR) is a crucial parameter for describing the combustion process and its thermal effects. In recent years, some studies have employed fire scene images and deep learning algorithms to predict real-time fire HRR, which has led to the advancement of HRR prediction in terms of both lightweightness and real-time monitoring. Nevertheless, the development of an early-stage monitoring system for fires and the ability to predict future HRR based on current moment data represents a crucial foundation for evaluating the scale of indoor fires and enhancing the capacity to prevent and control such incidents. This paper proposes a deep learning model based on continuous fire scene images (containing both flame and smoke features) and their time-series information to predict the future transient fire HRR. The model (Att-BiLSTM) comprises three bi-directional long- and short-term memory (Bi-LSTM) layers and one attention layer. The model employs a bidirectional feature extraction approach, followed by the introduction of an attention mechanism to highlight the image features that have a critical impact on the prediction results. In this paper, a large-scale dataset is constructed by collecting 27,231 fire scene images with instantaneous HRR annotations from 40 different fire trials from the NIST database. The experimental results demonstrate that Att-BiLSTM is capable of effectively utilizing fire scene image features and temporal information to accurately predict future transient HRR, including those in high-brightness fire environments and complex fire source situations. The research presented in this paper offers novel insights and methodologies for fire monitoring and emergency response. Full article

In recent decades, wildfires have become common disasters that threaten people’s lives and assets, particularly in wildland–urban interfaces (WUIs). Developing an effective evacuation strategy for a WUI presents challenges to emergency planners because of the spatial variations in biophysical hazards and social vulnerability. The aim of this study was to map priority WUIs in terms of evacuation. The factors considered were the seriousness of the risk of wildfire exposure, and the population centres whose greatest constraints on the evacuation process stemmed from the nature of the exposed population and the time required to travel to the nearest shelter/refuge. An integrated framework linking wildfire hazard, social vulnerability, and the time taken to travel by foot or by car to the nearest refuge/shelter was applied. The study area includes two municipalities (Lousã and Sertã) in the mountainous areas of central Portugal that are in high-wildfire-risk areas and have very vulnerable and scattered pockets of exposed population. The combination of wildfire risk and travelling time to the nearest shelters made it possible to identify 20% of the WUIs that were priority areas for evacuation in the case of Sertã. In the case of Lousã, 3.4% were identified, because they were highly exposed to wildfire risk and had a travelling time to the nearest shelter of more than 15 min on foot. These results can assist in designing effective pre-fire planning, based on fuel management strategies and/or managing an effective and safe evacuation. Full article

In Southern Mediterranean regions, the issue of summer fires related to agriculture practices is a periodic recurrence. It implies a significant increase in carbon dioxide (CO₂) emissions and other combustion-related gaseous and particles compounds emitted into the atmosphere with potential impacts on air quality and global climate. In this work, we performed an analysis of summer fire events that occurred on August 2021. Measurements were carried out at the permanent World Meteorological Organization (WMO)/Global Atmosphere Watch (GAW) station of Lamezia Terme (Code: LMT) in Calabria, Southern Italy. The observatory is equipped with greenhouse gases and black carbon analyzers, an atmospheric particulate impactor system, and a meteo-station for atmospheric parameters to characterize atmospheric mechanisms and transport for land and sea breezes occurrences. High mole fractions of carbon monoxide (CO) and carbon dioxide (CO₂) coming from quadrants of inland areas were correlated with fire counts detected via the MODIS satellite (GFED-Global Fire Emissions Database) at 1 km of spatial resolution. In comparison with the typical summer values, higher CO and CO₂ were observed in August 2021. Furthermore, the growth in CO concentration values in the tropospheric column was also highlighted by the analyses of the L2 products of the Copernicus SP5 satellite. Wind fields were reconstructed via a Weather Research and Forecasting (WRF) output, the latter suggesting a possible contribution from open fire events observed at the inland region near the observatory. So far, there have been no documented estimates of the effect of prescribed burning on carbon emissions in this region. This study suggested that data collected at the LMT station can be useful in recognizing and consequently quantifying emission sources related to open fires. Full article

To investigate resistance change in the fire area of a roadway caused by roadway fires, a mathematical calculation model for thermal resistance is developed. Theoretical research is conducted to analyze the factors influencing resistance change through theoretical derivation, revealing that temperature is a key factor contributing to the change in thermal resistance. By leveraging the correlation between changes in CO concentration and temperature on the downwind side of the roadway within the fire zone, researchers developed mathematical models to predict temperature increases at various points downwind of the fire source. These models were then used to determine the mathematical relationship governing the change in thermal resistance. The accuracy of the numerical simulation software was validated using Fluent numerical simulation software and scaled-down model experiments. Full-scale numerical simulation experiments were conducted to investigate the fire characteristics of roadway fires and validate the thermal resistance mathematical model. The results indicate that the thermal resistance in the numerical simulation is 7.55 Pa at 20m from the fire source and 5.54 Pa at the end of the roadway. The decrease in resistance is linear. The minimum error between the thermal resistance calculated by the mathematical model and the gradient of the pressure drop in the numerical simulation is 0.03 Pa, approximately 2.3%. Furthermore, the fitting degree of the pressure drop in each section is as high as 97.7%. The calculation model demonstrates high accuracy and offers a theoretical foundation for investigating fire resistance in tunnel fire. Full article

Numerous studies in management and leadership indicate that one’s decision-making style is reflective of one’s leadership style. In the context of civil protection and the fire service, the ability of the fire officers to adopt the best style of decision-making and leadership in each situation represents a critical factor of success. Therefore, the present study was designed to examine the relationship between decision-making and the leadership style of fire officers. For this study, a quantitative method was used, with the application of questionnaires with closed questions. A sample of 346 officers of Portuguese fire stations answered the questionnaire. Correlations between styles are consistent with findings from other studies. Decision-making styles directly influence the leadership styles adopted. Fire officers prioritize people and social concerns, involving teams in decision-making. Research shows positive correlations between participants’ roles, conceptual decision-making, and relation-focused leadership. Higher academic degrees are associated with relationship-focused leadership. Behavioral decision-making mediates the impact of education on leadership styles. Full article

This paper presents a specific 3D computational fluid dynamics model to quantify the effects of the combustion of asphalt road pavement on user safety in the event of a fire in a bi-directional road tunnel. Since the consequences on tunnel users and/or rescue teams might be affected not only by the tunnel geometry but also by the type of ventilation and traffic flow, the environmental conditions caused by the fire in the tunnel under natural or longitudinal mechanical ventilation, as well as congested traffic conditions, were more especially investigated. The simulation results showed that the combustion of the asphalt pavement in the event of a 100 MW fire, compared to the case of a non-combustible road pavement, caused (i) an increase in smoke concentrations; (ii) a greater number of users exposed to the risk of incapacity to escape from the tunnel; (iii) a more difficult situation for the firefighters entering the tunnel upstream of the fire source in the case of natural ventilation; (iv) a higher probability of the domino effect for vehicles queued downstream of the fire when the tunnel is mechanically ventilated. Full article

This study analyzes the thermo-mechanical behavior of a brick vault and the effect of a fire on its dynamic characteristics. Based on the results of an experimental test of a real barrel vault with a net span of 161 cm and a net rise of 46.5 cm, an accurate numerical model to simulate the behavior of the brick-and-mortar structure under thermo-mechanical stresses has been implemented. The comparison of the evolution of the displacement in the keystone and the temperatures at various points of the vault allows us to affirm that the adopted micro-modeling approach presents a good accuracy and a feasible computational effort. Finally, this study shows, from a numerical point of view, how the variation in the structure’s eigenfrequencies can be predicted for extreme situations, such as fire damage. This aspect can be critical to develop effective intervention and prevention strategies, which can be useful for the preservation of our valuable cultural and historic resources. Full article

Repurposing agricultural and forestry by-products not only is beneficial for the environment but also follows the principles of the circular economy. In southeastern Spain, the Canary Island palm tree (Phoenix canariensis W.) is widely used in urban landscapes. Plantations affected by the red weevil, a pest, generate an abundance of plant waste that must be crushed and transferred to authorized landfills. The aim of this study was to manufacture boards using particles from trunks of the Canary Island palm tree without adding any binders in order to obtain an ecological and fire-resistant product. In order to manufacture the boards, three particle sizes (<0.25, 0.25–1, and 1–2 mm), a temperature of 110 °C, a pressure of 2.6 MPa, and a pressing time of 7 min were used. The boards were pressed in a hot plate press for 7 min up to four times (7 min, 7 + 7 min, 7 + 7 + 7 min, and 7 + 7 + 7 + 7 min). The resulting boards showed good thermal performance, and the board´s reaction-to-fire performance was classified as Bd0 (an Fs value of 70.3 mm). This study also showed that boards with a particle size smaller than 0.25 mm that underwent four pressing cycles of 7 min each in the press can be categorized as grade P2 according to the European Standards (MOR of 20 N/mm², MOE of 2589.8 N/mm², and IB of 0.74 N/mm²). Therefore, these manufactured particleboards could be used as a flame-retardant material for the interior enclosures of buildings (vertical and horizontal) without the need for coatings. Full article

Obtaining thermal infrared images with prominent details, high contrast, and minimal background noise has always been a focal point of infrared technology research. To address issues such as the blurriness of details and low contrast in thermal infrared images, an enhancement algorithm for thermal infrared images based on multi-scale guided filtering is proposed. This algorithm fully leverages the excellent edge-preserving characteristics of guided filtering and the multi-scale nature of the edge details in thermal infrared images. It uses multi-scale guided filtering to decompose each thermal infrared image into multiple scales of detail layers and a base layer. Then, CLAHE is employed to compress the grayscale and enhance the contrast of the base layer image. Then, detail-enhancement processing of the multi-scale detail layers is performed. Finally, the base layer and the multi-scale detail layers are linearly fused to obtain an enhanced thermal infrared image. Our experimental results indicate that, compared to other methods, the proposed method can effectively enhance image contrast and enrich image details, and has higher image quality and stronger scene adaptability. Full article

This work primarily focuses on a three-dimensional model of flame propagation and stable combustion in a scramjet chamber. The one-equation LES turbulence model is adopted to close the sub-grid-scale turbulent viscosity terms. The finite-rate combustion model, along with the Jachimowski detailed hydrogen reaction mechanism with eight components and nineteen steps, is used to analyze the flame propagation characteristics of hydrogen combustion in the scramjet combustion chamber. Initially, based on the combustion chamber model, the effect of different injection locations and equivalence ratios on flame kernel formation and the flame propagation process is analyzed. The relationship between different fuel injection conditions and the oxygen consumption rate of the combustion chamber, as well as the total pressure recovery coefficient changes, is investigated. The research focuses on changes in equivalence ratios and injection hole distributions, with injection holes arranged upstream, downstream, and inside of the cavity. The result indicated that when the injection holes were arranged downstream of the cavity, there was a phenomenon of flame backflow into the cavity, which was related to the size of the injection pressure. For this work, the pressure causing flame backflow was approximately 2 MPa. When the injection hole was arranged inside the cavity, the relative distance difference between the injection hole and the upper wall of the cavity led to the formation of two reaction zones in the combustion chamber. When the injection hole was arranged upstream of the cavity, different injection equivalence ratios affected the final stable position and structure of the flame. Therefore, the injection position, injection pressure, and injection equivalence ratio all had a certain impact on the flame kernel formation and flame propagation process. Full article

The traditional concept of compartmentation guaranteed by fire resistance is mainly concerned with the problem of destructive internal spread potential. External convective spread potential pertains to the loss of compartmentation associated with windows and facade systems. As such, it is assumed that internal fire spread occurs following mechanisms of excessive heat conduction and/or successive failure of the compartment boundaries, which can be, in most cases, conservatively characterised using traditional methods of performance assessment such as fire resistance. Nevertheless, external fire spread represents a potentially more effective route by which fire can spread through the convective advancement of flames and hot gases. This is particularly important in cases such as timber construction, where the presence of exposed timber can result in increased convective spread potential and where loss of compartmentation can result in disproportionate consequences. A simplified compartment fire model is proposed with the objective of quantifying the fuel contribution of exposed timber elements to the compartment fire and determining the impact of variable percentages of exposed timber on the convective spread potential. The overall results show that the convective fire spread potential increases with the increasing percentage of available timber. Full article

Power-to-gas technology can be used to convert excess power from renewable energies to hydrogen by means of water electrolysis. This hydrogen can serve as “chemical energy storage” and be converted back to electricity or fed into the natural gas grid. In the presented study, a leak in a household pipe in a single-family house with a 13 kW heating device was experimentally investigated. An admixture of up to 40% hydrogen was set up to produce a scenario of burning leakage. Due to the outflow and mixing conditions, a lifted, turbulent diffusion flame was formed. This led to an additional examination point and expanded the aim and novelty of the experimental investigation. In addition to the fire safety experimental simulation of a burning leakage, the resulting complex properties of the flame, namely the lift-off height, flame length, shape and thermal radiation, have also been investigated. The obtained results of this show clearly that, as a consequence of the hydrogen addition, the main properties of the flame, such as lifting height, flame temperature, thermal radiation and total heat flux densities along the flame, have been changed. To supplement the measurements with thermocouples, imaging methods based on the Sobel gradient were used to determine the lifting height and the flame length. In order to analyze the determined values, a probability density function was created. Full article

This paper presents a research program called CP2DIMG conducted at the Federation of Environment and Society Research at the University of Corsica. The goal of CP2DIMG is to better understand the influence of emotions on operational personnel’s decision-making, aiming to test training systems dedicated to individuals facing high stress during their professional activities. This type of training system is intended to enhance emotional and mental resilience, thereby improving decision-making ability in uncertain situations under the influence of emotions related to the event. For implementation, the method will be tailored to the specificities of two categories of operational personnel: firefighters and municipal police officers. The expected results will address significant demands from operational professionals in the Mediterranean region for firefighting safety but also for large-scale or highly complex interventions. This study fully integrates into the challenges of the Mediterranean region: forest management, risk prevention plans, and preparedness of local actors responsible for crisis management. Furthermore, individuals responsible for crisis management, including local government officials and risk management and security personnel, will be able to use the obtained results for effective decision-making. Full article

Mine fire accidents frequently constitute a major threat to mining safety, and their potential consequences are extremely severe, which highlights the urgency of fire prevention and control research. In this study, the CiteSpace software was used to conduct a metrological analysis of 717 relevant studies in the field of mine fire prevention and control (MFPC), aiming to reveal the research trends and trends in this field. This analysis found that the annual number of MFPC articles showed a significant upward trend, indicating that it is in rapid development during the active period. China, the United States, and Australia are the main contributors in this field, and the institutional contribution of China University of Mining and Technology is particularly outstanding, reflecting the regional concentration of research activities. The analysis of cooperation networks reveals the close cross-regional collaboration among European countries. The inhibition effect and evaluation criteria and the inhibition technology under different coal characteristics have become the focus of research. Activation energy, release, and quantum chemistry have become recent hot spots, reflecting the research on the mechanism of forward physicochemical synergistic inhibition and the in-depth exploration of the molecular level. It indicates that future research will focus on the development of temperature-responsive retardant materials, the application of quantum chemistry theory, and the exploration of the microscopic mechanism of coal spontaneous combustion through molecular simulation technology to further optimize the fire prevention strategy. In summary, the findings of this study not only provide a comprehensive picture of current research activities in the MFPC field but also indicate potential directions for future research and have important guiding significance for promoting the development of this field. Full article

With the development of the social economy and the improvement of electrification, cables and wires play an important role in people’s lives and industrial development. Meanwhile, the large-scale laying of cables has also made them a fire hazard that cannot be ignored in land construction such as residential buildings, utility tunnels, nuclear power plants, refineries, marine systems such as submarines and ships, and airborne systems such as spacecrafts and aircrafts. In this work, studies on fire the characteristics of cables and wires over the last decades have been reviewed. Based on different experimental forms and objects (laboratory wires and commercial cables), this paper summarizes the theories of the fire dynamics in wire combustion, including the models of ignition and flame propagation, the criteria for blowing off and quenching, and the critical conditions for dripping behavior. The effects of materials, layouts, and environments on wire combustion phenomena such as airflow, ambient pressure, oxygen, gravity, and orientation angle have been discussed in detail according to the theories of heat transfer and combustion. In addition, test standards and studies on the fire behavior and release of toxic gases of commercial cables have also been fully described. Through the summary of the above content, it is expected to build a preliminary theoretical framework and future research directions for researchers in the field of cable fires. Full article

Detailed numerical analyses of pulverised solid fuel flames are computationally expensive due to the intricate interplay between chemical reactions, turbulent multiphase flow, and heat transfer. The near-burner region, characterised by a high particle number density, is particularly influenced by these interactions. The accurate modelling of these phenomena is crucial for describing flame characteristics. This study examined the reciprocal impact between the discrete phase and the continuous phase using Reynolds-averaged Navier–Stokes (RANS) simulations. The numerical model was developed in Ansys Fluent and equipped with user-defined functions that adapt the modelling of combustion sub-processes, in particular, devolatilisation, char conversion, and radiative heat transfer under oxyfuel conditions. The aim was to identify the appropriate degree of detail necessary for modelling the interaction between discrete and continuous phases, specifically concerning mass, momentum, energy, and turbulence, to effectively apply it in high-fidelity numerical simulations. The results of the numerical model show good agreement in comparison with experimental data and large-eddy simulations. In terms of the coupling schemes, the results indicate significant reciprocal effects between the discrete and the continuous phases for mass and energy coupling; however, the effect of particles on the gas phase for momentum and turbulence coupling was observed to be negligible. For the investigated chamber, these results are shown to be slightly affected by the local gas phase velocity and temperature fields as long as the global oxygen ratio between the provided and needed amount of oxygen as well as the thermal output of the flame are kept constant. Full article

Interactions between urban and wildfire pollution emissions are active areas of research, with numerous aircraft field campaigns and satellite analyses of wildfire pollution being conducted in recent years. Several studies have found that elevated ozone and particulate pollution levels are both generally associated with wildfire smoke in urban areas. We measured pollutant concentrations at two Utah Division of Air Quality regulatory air quality observation sites and a local hot spot (a COVID-19 testing site) within a 48 h period of increasing wildfire smoke impacts that occurred in Salt Lake City, UT (USA) between 20 and 22 August 2020. The wildfire plume, which passed through the study area during an elevated ozone period during the summer, resulted in increased criteria pollutant and greenhouse gas concentrations. Methane (CH₄) and fine particulate matter (PM_2.5) increased at comparable rates, and increased NO_x led to more ozone. The nitrogen oxide/ozone (NO_x/O₃) cycle was clearly demonstrated throughout the study period, with NO_x titration reducing nighttime ozone. These findings help to illustrate how the compounding effects of urban emissions and exceptional pollution events, such as wildfires, may pose substantial health risks. This preliminary case study supports conducting an expanded, longer-term study on the interactions of variable intensity wildfire smoke plumes on urban air pollution exposure, in addition to the subsequent need to inform health and risk policy in these complex systems. Full article

With more frequent and intense fires expected under future climate conditions, it is important to understand the mechanisms that control flammability in Australian forests. We followed a systematic review approach to determine which physical traits make eucalypts leaves more or less flammable. Specifically, we reviewed 20 studies that covered 35 eucalypt species across five countries and found that leaf water content, leaf area (LA), and specific leaf area (SLA) are the main drivers of leaf flammability. These traits are easy and straightforward to measure, while more laborious traits (e.g., volatile organic compounds and structural carbohydrates) are seldom measured and reported. Leaf flammability also varies with species, and, while the biochemistry plays a role in how leaves burn, it plays a minor role in fire behaviour at landscape scales. This review highlights the range of different protocols used to measure flammability and leaf water content, warranting caution when comparing traits and results between studies. As a result, we propose a standardised protocol to measure leaf water content and advocate for long-term measurements of leaf traits and flammability. This study not only contributes to the understanding of how and why eucalypt leaves burn but also encourages research into the relative importance of traits in influencing flammability and provides a guide for selecting traits that can be monitored using satellite images to inform fire management policies and strategies. Full article

Once a fire breaks out in an electric bus, it can easily lead to mass casualties and severe injuries, resulting in significant property damage and social impact. The high-temperature smoke and toxic gases in an electric bus fire are key factors that cause a large number of casualties, both of which are closely related to ventilation conditions. In view of this, this study utilized the Fire Dynamics Simulator (FDS 6) software to establish a three-dimensional experimental model of an electric bus. Numerical simulations of the fire combustion process in the electric bus under different ventilation conditions were conducted. Multiple fire scenes were established based on varying ventilation areas, different wind speeds, and diverse window opening positions. This study specifically analyzed the temperature and CO concentration variations under different fire scenes. By comparing the simulation results under different ventilation conditions, it can be concluded that when an electric bus catches fire, opening 100% of the windows, the wind speed is 8 m/s, and opening the rear window of the electric bus first can minimize the fire risk. Through the numerical simulation of electric bus fires under various conditions, this study analyzed the impact of different ventilation conditions on electric bus fires, providing a theoretical basis for firefighting and rescue efforts as well as personnel evacuation in electric bus fire incidents, with the ultimate goal of maximizing public safety. Full article

Developing mmWave radar sensors for indoor crowd motion sensing and tracking faces a critical challenge: the scarcity of large-scale, high-quality training data. Traditional human experiments encounter logistical complexities, ethical considerations, and safety issues. Replicating precise human movements across trials introduces noise and inconsistency into the data. To address this, this study proposes a novel solution: a movable platform equipped with a life-size mannequin to generate realistic and diverse data points for mmWave radar training and testing. Unlike human subjects, the platform allows precise control over movements, optimising sensor placement relative to the target object. Preliminary optimisation results reveal that sensor height impacts tracking performance, with an optimal sensor placement above the test subject yields the best results. The results also reveal that the 3D data format outperforms 2D data in accuracy despite having fewer frames. Additionally, analysing height distribution using 3D data highlights the importance of the sensor angle—15° downwards from the horizontal plane. Full article

The use of existing natural gas pipelines for the transport of hydrogen/natural gas mixtures can achieve large-scale, long-distance and low-cost hydrogen transportation. A jet fire induced by the leakage of high-pressure pure hydrogen and hydrogen-blended natural gas pipelines may pose a severe threat to life and property. Based on the Abel–Nobel equation of state and a notional nozzle model, an equivalent pipe leakage model is established to simulate high-pressure pipeline gas leakage jet fire accidents. Large-scale high-pressure hydrogen and natural gas/hydrogen mixture jet fires are simulated, showing the jet impingement process and obtaining an accurate and effective simulation framework. This framework is validated by comparing the simulated and experimental measured results of flame height, flame appearance and thermal radiation. Several combustion models are compared, and the simulated data show that the non-premixed chemical equilibrium combustion model is superior to other combustion models. The influence of the pipe pressure and the hydrogen blending ratio on the consequences of natural gas/hydrogen mixture pipeline leakage jet fire accidents is explored. It is found that when the hydrogen blending ratio is lower than 22%, the increase in the hydrogen blending ratio has little effect on the decrease in the thermal radiation hazard distance. Full article

Studies on estimating cumulative fire intensity from spreading wildland fires based on fire radiative energy density (FRED) have primarily been conducted through controlled experiments. The objective of this study was to assess the potential for estimating FRED for freely-burning wildfires at landscape scales. Airborne thermal infrared image sequences collected 8 and 9 December 2017 during the Thomas Fire were used for surface temperature derivation and FRED estimation. Sensitivity of varying ambient temperatures, and a newly developed method that adjusts for ash radiances on fire radiative flux density (FRFD) and FRED estimates were tested. Pixel-level image classification was run to identify FRFD time sequences that were complete or incomplete because of cloud obscuration and provided the basis for an obscuration gap filling technique. Variations in estimated ambient temperature used to estimate FRFD had little impact on FRED estimates, while our ash adjustment led to notable differences. An exponential decay model characterized FRFD time sequences well, providing a basis for gap filling irregular sequences caused by atmospheric obscuration. FRED estimates were regressed on rate of spread (ROS) magnitudes and found to be positively and significantly correlated. FRED magnitudes were higher on 9 December when the Thomas Fire burned under higher wind speeds and lower relative humidity levels (Santa Ana weather conditions) than on 8 December. Full article