Authors: Thuy Tien Nguyen Thanh Ziya Yusifov Bence Tóth Katalin Bocz Péter Márton Zoltán Hórvölgyi György Marosi Beáta Szolnoki
Polypropylene (PP) shows no charring ability in burning due to the lack of hydroxyl functional groups; thus, the flame retardant system needs an additional amount of carbonizing agent. An ammonium polyphosphate (APP)-based all-in-one intumescent flame-retardant system was prepared by the in situ polymerization of polymeric methylene diphenyl diisocyanate (pMDI) with a glycerol-based and a glycerol–sorbitol-based polyol of high OH value. The microencapsulated APP with a polyurethane shell (MCAPP) of different polyols was characterized. The MCAPP with speculated improved flame retardant performance was selected for further evaluation in the PP matrix at different loadings by means of standard flammability tests.
]]>Authors: Galya V. Klink Sergey A. Lednev Ivan N. Semenkov Maria V. Konyushkova Andrey M. Karpachevskiy Mergen M. Chemidov Svetlana S. Ulanova Natal’ya L. Fedorova Anna V. Sharapova Sergey A. Bogun Tatyana V. Koroleva
Understanding the rate and direction of pyrogenic succession in arid ecosystems, which depends on many factors, including the intensity of grazing and the frequency of pyrogenic expo-sure, will allow for more accurate predictions of the consequences of fire onplant communities, and will assist with better fire management. We studied the vegetation on 55 sites in and near the “Chernye Zemli” Natural Biosphere Reserve that burned at different times or were not affected by fires over the past 35 years and characterized the changes in vegetation cover associated with the impact of wildfire and grazing. The descriptions were grouped into chronological stages according to the time elapsed since the last fire, or into groups according to the frequency of fires. In pairwise comparison of the projective cover of plant species between chronological stages, it correlated most strongly between successive initial stages (for stages 1 and 2, p = 0.003, r = 0.73; for stages 2 and 3, p < 0.001, r = 0.78). Species with an initially higher projective cover were more likely to grow on plots in the first year after the fire: p < 0.03. Plots with rare and frequent fires had similar projective cover of individual species (r = 0.64, p < 0.001). We conclude that in the course of pyrogenic succession, communities are gradually replaced over at least ten years. At the same time, the composition of a plant community at the initial point of succession depends on the prevalence of species in the community before the fire. No fundamental effect of the frequency of fires on the composition of plant communities has been revealed.
]]>Authors: Fanghua Wu Shiliang Shi Shuzhen Shao Yi Lu Wangxin Gu Youliang Wang Xindi Yuan
In order to study the effect of hydrated phase change materials on the suppression of spontaneous combustion in coal, a thermogravimetric experiment and a reaction activation energy analysis experiment were conducted to explore the changes in the combustion characteristic parameters, characteristic temperature, and activating energy of gas coal, long-flame coal, meagre coal, and lean coal before and after adding hydrated phase change materials. The research results indicated that hydrated phase change materials increased the characteristic temperature point of the coal samples and had effective inhibitory effects on different stages of the oxidation process. However, the effect was best at low temperatures, as hydrated phase change materials undergo phase change and absorb heat when heated at low temperatures, isolating coal from contact with oxygen. The activating energy increased by 1.138–23.048 KJ·mol−1 and the mass loss was reduced by 1.6%–9.3% after inhibition of the coal samples, indicating that the oxidation rate of the various coal samples was slowed down and, thus, spontaneous combustion can be suppressed through the use of hydrated phase change materials. At the same time, this material reduced the combustibility indices of meagre coal and lean coal, as well as the comprehensive combustion indices of long-flame coal and gas coal.
]]>Authors: Abigail Rose Croker Adriana E. S. Ford Yiannis Kountouris Jayalaxshmi Mistry Amos Chege Muthiuru Cathy Smith Elijah Praise David Chiawo Veronica Muniu
In many landscapes worldwide, fire regimes and human–fire interactions were reorganised by colonialism and continue to be shaped by neo-colonial processes. The introduction of fire suppression policies and state-centric property-rights systems across conservation areas and the intentional erasure of Indigenous governance systems and knowledge have served to decouple Indigenous fire-dependent communities from culturally mediated fire regimes and fire-adapted landscapes. This has driven a decline in anthropogenic fires while simultaneously increasing wildfire risk where Indigenous people have been excluded, resulting in widespread social–ecological vulnerabilities. Much contemporary fire research also bears colonial legacies in its epistemological traditions, in the global geographical distribution of research institutions, and the accessibility of research outputs. We report on a two-day workshop titled ‘Fire Management Across Contested Landscapes’ convened concurrently in Nairobi, Kenya, and London, UK. The workshop formed part of a series of workshops on ‘Decolonising Fire Science’ held by the Leverhulme Centre for Wildfires, Environment and Society, UK. The workshop in Nairobi invited diverse Kenyan stakeholders to engage in participatory activities that facilitate knowledge sharing, aiming to establish an inclusive working fire network. Activities included rich pictures, world café discussions, participatory art, and the co-development of a declaration to guide fire management in Kenya. Meanwhile, in London, Leverhulme Wildfires researchers explored participatory research methodologies including rich pictures and participatory video, and developed a declaration to guide more equitable research. There were opportunities throughout the workshop for participants in Nairobi and London to engage in dialogue with one another, sharing their experiences and understandings of complex fire challenges in Kenya and globally.
]]>Authors: Bensheng Yun Yanan Zheng Zhenyu Lin Tao Li
Forest is an important resource for human survival, and forest fires are a serious threat to forest protection. Therefore, the early detection of fire and smoke is particularly important. Based on the manually set feature extraction method, the detection accuracy of the machine learning forest fire detection method is limited, and it is unable to deal with complex scenes. Meanwhile, most deep learning methods are difficult to deploy due to high computational costs. To address these issues, this paper proposes a lightweight forest fire detection model based on YOLOv8 (FFYOLO). Firstly, in order to better extract the features of fire and smoke, a channel prior dilatation attention module (CPDA) is proposed. Secondly, the mixed-classification detection head (MCDH), a new detection head, is designed. Furthermore, MPDIoU is introduced to enhance the regression and classification accuracy of the model. Then, in the Neck section, a lightweight GSConv module is applied to reduce parameters while maintaining model accuracy. Finally, the knowledge distillation strategy is used during training stage to enhance the generalization ability of the model and reduce the false detection. Experimental outcomes demonstrate that, in comparison to the original model, FFYOLO realizes an mAP0.5 of 88.8% on a custom forest fire dataset, which is 3.4% better than the original model, with 25.3% lower parameters and 9.3% higher frames per second (FPS).
]]>Authors: Flavio Tiago Couto Jean-Baptiste Filippi Roberta Baggio Cátia Campos Rui Salgado
This study aimed to assess fire–atmosphere interactions using the fully coupled Meso-NH–ForeFire system. We focused on the Pedrógão Grande wildfire (28,914 ha), which occurred in June 2017 and was one of the deadliest and most damaging fires in Portugal’s history. Two simulations (control and fully coupled fire–atmosphere) were performed for three two-way nested domains configured with horizontal resolutions of 2 km, 0.4 km, and 0.08 km, respectively, in the atmospheric model Meso-NH. Fire propagation was modeled within the innermost domain with ForeFire, which solves the fire front with a 20 m resolution, producing the heat and vapor fluxes which are then injected into the atmospheric model. A simplified homogeneous fuel distribution was used in this case study. The fully coupled experiment helped us to characterize the smoke plume structure and identify two different regimes: (1) a wind-driven regime, with the smoke plume transported horizontally southward and in the lower troposphere, and (2) a plume-dominated regime, in which the simulated smoke plume extended vertically up to upper levels, favoring the formation of a pyro-cloud. The simulations were compared, and the results suggest that the change in the fire regime was caused by an outflow that affected the main fire front. Furthermore, the fully coupled simulation allowed us to explore the change in meteorology caused by an extreme fire, namely through the development of a pyro-cloud that also induced outflows that reached the surface. We show that the Meso-NH–ForeFire system may strongly contribute to an improved understanding of extreme wildfires events and associated weather phenomena.
]]>Authors: Zeqi Wu Kun Wang Lin Shao Huaitao Song Kunpeng Liu
In a long and narrow corridor, the installation of roof smoke blocking structures is a measure to slow down the spread of fire smoke. When employing multiple smoke blocking structures, the spacing between these structures is a critical parameter that needs to be considered for optimal effectiveness. This paper analyzes the smoke blocking performance of double structures at different spacing and measures the smoke flow velocity both upstream and downstream of the double structures. According to the analysis of the smoke velocity vector obtained from numerical simulation, the smoke can be divided into three zones based on the flow state of the smoke after passing through the front smoke screen structure, namely the vortex zone, surge wave zone, and steady flow zone. When the rear smoke screen is located in the surge zone, the smoke blocking effect is optimal. Analysis of the morphology of the smoke layer indicates that the length of the vortex region is directly proportional to the upstream smoke flow velocity. The numerical and experimental results both indicate that an excessively large or small spacing between the structures fails to achieve optimal smoke control effectiveness. When the spacing is within an optimal range, the smoke velocity is the lowest. Finally, using a real architectural corridor as a case background, this paper presents a design example of roof smoke blocking structures. In order to arrange as many smoke blocking structures as possible, an appropriate spacing between the structures should be slightly larger than the vortex region. The smoke control effectiveness of multiple roof structures was validated through numerical simulation. As a result, the time required for smoke to pass through the corridor increases by 110 s.
]]>Authors: Dener Silva Tiago Miguel Ferreira Hugo Rodrigues
Climate change and human interventions can boost wildfires. Although naturally happening, massive events are becoming more frequent and severe. In Portugal’s mainland, many rural settlements are populated mainly by older people, and uninhabited houses are frequently poorly conserved. This combination leaves the Wildland–Urban Interface (WUI) dangerously exposed to the fires. Pursuing the understanding of WUI areas, this study applies the Wildland–Urban Interface Index (WUIX) assessment methodology to an area severely affected by the massive 2017 wildfire of Pedrógão Grande, Leiria, Portugal. The primary objective of this study was to compare the results from WUIX with the areas burned during the fire event. As a result, maps of WUI effect were generated, visually pointing to villages with higher severity compared to the others. A statistical analysis was performed in three villages from the region to validate the results by comparing the accuracy of the results obtained to the actual damages. The results point out a high correlation between the WUIX and the real scenario despite the apparent challenges in determining the variations in different types of fire effect. Finally, the WUIX results align with the data from the Pedrógão Grande wildfire, showing that some are promising in conjunction with other wildfire indicators.
]]>Authors: Nikolay Abramov Yulia Emelyanova Vitaly Fralenko Vyacheslav Khachumov Mikhail Khachumov Maria Shustova Alexander Talalaev
This research addresses the problem of early detection of smoke and open fire on the observed territory by unmanned aerial vehicles. We solve the tasks of improving the quality of incoming video data by removing motion blur and stabilizing the video stream; detecting the horizon line in the frame; and identifying fires using semantic segmentation with Euclidean–Mahalanobis distance and the modified convolutional neural network YOLO. The proposed horizon line detection algorithm allows for cutting off unnecessary information such as cloud-covered areas in the frame by calculating local contrast, which is equivalent to the pixel informativeness indicator of the image. Proposed preprocessing methods give a delay of no more than 0.03 s due to the use of a pipeline method for data processing. Experimental results show that the horizon clipping algorithm improves fire and smoke detection accuracy by approximately 11%. The best results with the neural network were achieved with YOLO 5m, which yielded an F1 score of 76.75% combined with a processing speed of 45 frames per second. The obtained results differ from existing analogs by utilizing a comprehensive approach to early fire detection, which includes image enhancement and alternative real-time video processing methods.
]]>Authors: Ana Carvalho Stéphanie Ribeiro Maria João Gaspar Teresa Fonseca José Lima-Brito
Wildfires act as a selection force threatening the sustainability and diversity of forest genetic resources. Few studies have investigated the genetic effects of forest wildfires. Species with perennial canopy seed banks in serotinous cones and soil or with long-distance seed and pollen dispersion can preserve genetic diversity and population differentiation under normal fire regimes. To test this hypothesis, we characterised molecularly Pinus pinaster Aiton (maritime pine) seedlings produced from seeds sampled in post-fire, naturally regenerated populations that had been subject to different fire regimes in the North of Portugal using inter-simple sequence repeats (ISSRs). The sampled populations burned once (A), twice (B), or three (D) times or had no prior fire history (C, control). Given the globally low seed germination ability, only 104 plantlets regenerated and were described. These plantlets were grouped according to their origin population. Intra-group ISSR polymorphism ranged from 72.73% (B) to 89.41% (D), revealing genetic differentiation among groups originating from populations that had experienced different fire recurrence. Overall, the unaffected genetic diversity of the regenerated plantlets allowed us to accept the hypothesis. Our findings enhance our understanding of the species ability to withstand fire-induced challenges and their responses to wildfires, guiding conservation endeavours and forest management strategies to bolster ecosystem resilience.
]]>Authors: Jiří Ryšavý Jakub Čespiva Lenka Kuboňová Milan Dej Katarzyna Szramowiat-Sala Oleksandr Molchanov Lukasz Niedzwiecki Wei-Mon Yan Sangeetha Thangavel
The possibilities of pistachio shell biochar production on laboratory-scale gasification and pyrolysis devices have been described by several previous studies. Nevertheless, the broader results of the pistachio shell co-gasification process on pilot-scale units have not yet been properly investigated or reported, especially regarding the detailed description of the biochar acquired during the routine operation. The biochar was analysed using several analytical techniques, such as ultimate and proximate analysis (62%wt of C), acid–base properties analysis (pH 9.52), Fourier-transform infrared spectroscopy (the presence of –OH bonds and identification of cellulose, hemicellulose and lignin), Raman spectroscopy (no determination of Id/Ig ratio due to high fluorescence), and nitrogen physisorption (specific surface 50.895 m2·g−1). X-ray fluorescence analysis exhibited the composition of the main compounds in the biochar ash (32.5%wt of Cl and 40.02%wt of Na2O). From the energy generation point of view, the lower heating value of the producer gas achieved 6.53 MJ·m−3 during the co-gasification. The relatively high lower heating value of the producer gas was mainly due to the significant volume fractions of CO (6.5%vol.), CH4 (14.2%vol.), and H2 (4.8 %vol.), while hot gas efficiency accomplished 89.6%.
]]>Authors: Marina Gravit Vasiliy Prusakov Nikita Shcheglov Irina Kotlyarskaya
Fire protection is required to protect metal structures of oil and gas facilities from fires. Such fire protection should provide high fire resistance limits: 60, 90, 120 and more minutes. Specialists of LLC “RPC PROMIZOL ” developed a multilayer, removable type of fire protection made of superfine basalt fibre and ceramic materials for operation in Arctic conditions. Five experimental studies were carried out in standard and hydrocarbon fire regimes. The fire protection effectiveness of the products for I20 beams without load was obtained: a 50 mm thick coating provided 130 min of a standard fire regime; a 15 mm thick coating provided 60 min. The 15 mm thick coating provided 30 min of a hydrocarbon fire regime and the 50 mm thick coating provided 93 min of a hydrocarbon fire regime. The I40 beam under a load of 19.9 tf showed an R243 for the standard fire regime. The coefficients of effective thermal conductivity and specific heat capacity of fire-retardant compositions were determined by solving the inverse heat conduction problem. The problem was solved by modelling using the QuickField 7.0 software package, which implements FEM. Modelling showed that for obtaining the fire resistance limit R120 under the standard fire regime for the sample steel structure from an I40 beam, it is enough to apply fire protection with a thickness of 25 mm instead of 50 mm, which agrees with the experimental data. For the hydrocarbon regime, it is predicted that R120 can be obtained at a thickness of 45 mm instead of 50 mm.
]]>Authors: Venkatesh Kodur Ankush Jha Nizar Lajnef
This paper presents the critical egress parameters that influence emergency evacuation in a typical hospital building. A parametric study of a 20-story hospital building is conducted using a computer model “Pathfinder” to simulate the evacuation efficiency and assess the influencing parameters. The main egress parameters that influence the evacuation efficiency, including the location of stairways, number of stairways, location of the fire, exit width, and number of low-speed occupants are varied. Two scenarios are simulated: one being the regular (practice) evacuation drill and the other is the actual fire drill. The result shows that the location of stairways significantly affects the total evacuation time with the optimal stairway arrangement consisting of one stairway outside the core of the building. Similarly, the story level at which the fire occurs is another key parameter with fires at lower levels being critical to dictating the evacuation time in a hospital building. The total evacuation time when the fire occurs between the third and sixth floor is found to be 170 min which is 36% and 15% higher than fires at the top story levels (15–18th floor) and the intermediate story levels (9–12th floor), respectively.
]]>Authors: Aziza Ergasheva Farkhod Akhmedov Akmalbek Abdusalomov Wooseong Kim
The maritime sector confronts an escalating challenge with the emergence of onboard fires aboard in ships, evidenced by a pronounced uptick in incidents in recent years. The ramifications of such fires transcend immediate safety apprehensions, precipitating repercussions that resonate on a global scale. This study underscores the paramount importance of ship fire detection as a proactive measure to mitigate risks and fortify maritime safety comprehensively. Initially, we created and labeled a custom ship dataset. The collected images are varied in their size, like having high- and low-resolution images in the dataset. Then, by leveraging the YOLO (You Only Look Once) object detection algorithm we developed an efficacious and accurate ship fire detection model for discerning the presence of fires aboard vessels navigating marine routes. The ship fire detection model was trained on 50 epochs with more than 25,000 images. The histogram equalization (HE) technique was also applied to avoid destruction from water vapor and to increase object detection. After training, images of ships were input into the inference model after HE, to be categorized into two classes. Empirical findings gleaned from the proposed methodology attest to the model’s exceptional efficacy, with the highest detection accuracy attaining a noteworthy 0.99% across both fire-afflicted and non-fire scenarios.
]]>Authors: Khalid Moinuddin H. M. Iqbal Mahmud Paul Joseph Grant Gamble Brigitta Suendermann Cameron Wilkinson James Bossard
Fire is one of the most undesirable events onboard a ship. The engine room is one of the most critical spaces in the ship in terms of fire protection, as it includes machinery, hydrocarbon fuel systems, and different electrical equipment. With the phasing out of Halon 1301 as a fire suppressant over recent decades, there has been an intensive effort to explore the efficacy of water-mist spray in mitigating fires within machinery spaces. This exploration entails a comprehensive investigation through experimental and simulation studies aimed at identifying suppression mechanisms and evaluating their effectiveness. While experimental setups typically encompass measurements of gas temperature, thermal radiation heat flux, oxygen concentration, and fire extinction time, limited attention has been paid to quantifying the heat release rate (HRR), a crucial indicator of fire magnitude. Furthermore, research into shielded fire scenarios remains sparse, despite their significance in maritime fire dynamics. Addressing shielded fires with water mist proves particularly challenging due to the potential obstruction impeding the direct interaction between the fire source and the water droplets. In the existing literature, most of the computational fluid dynamics (CFD) modelling of fires and suppression was performed using a Fire Dynamics Simulator (FDS). Alternate studies were performed using FireFOAM. and very few employed FLUENT and other analogous software codes. In the majority of reported computational studies, the determination of HRR was typically relied upon for its calculation derived from the measured data of fuel mass loss rate. Moreover, certain studies were undertaken for numerical simulations without conducting thorough model validation, either by omitting validation altogether or solely validating against dry fire experiments (i.e., without water-mist suppression). This critical review of the literature has identified several notable research gaps in the context of extinguishing hydrocarbon fires utilising water-mist spray, warranting further investigations. Additionally, this review paper highlights recent advancements in both experimental and numerical investigations pertaining to the efficacy of water-mist fire-suppression systems in enclosed spaces regarding hydrocarbon fires.
]]>Authors: Brice B. Hanberry Jacob M. Seidel
Globally, in remaining wildlands, tree densities and forested cover have increased in grasslands and open forests since European settlement. In the southern Rocky Mountains of Colorado, United States, we determined tree composition and tree cover from historical (years 1875 to 1896) surveys and compared them to current (2002 to 2011) tree composition and current (year 2016) forested land cover for 500,000 ha of the Routt National Forest. Additionally, we examined whether changes in precipitation occurred. Regarding composition, pine (primarily lodgepole pine; Pinus contorta) decreased from 65% to 32% of all trees, with increased subalpine fir (Abies lasiocarpa) from 0.5% to 23% of all trees, and quaking aspen (Populus tremuloides) from 13% to 30% of all trees. According to 80% of 5175 survey points not in forests, the historical landscape was very open, comprised of grasslands, mountain meadows, and other open ecosystems. In contrast, 75% of the current landscape is covered by forests. Change points in the Palmer Modified Drought Index were within historical limits, indicating that forestation was not related to a change in water availability. Based on historical surveys and accounts, we envisioned a historical landscape that was open but embedded with dense lodgepole pine clusters and spruce stands at high elevations, which has now become a predominantly forested landscape of dense forests, similar to global forestation patterns.
]]>Authors: Paúl Arias-Muñoz Santiago Cabrera-García Gabriel Jácome-Aguirre
The uncontrolled spread of fire can have huge effects on ecosystems. In Ecuador, in 2022, wildfires caused a loss of 6566.66 hectares of vegetation cover. Ibarra is an Andean canton that has also been exposed to wildfires and their effects. The aim of this study was to map wildfire susceptibility in the Ibarra canton. Seven factors that directly affect these fires were examined: precipitation, temperature, water deficit, potential evapotranspiration, slope, proximity to roads, and land cover and land use. The variables were reclassified using Geographic Information Systems and a multicriteria analysis. The results showed that Ibarra has four susceptibility categories: very low, moderate, high, and very high. The more susceptible areas are those considered to have high and very high exposure, occupying 82% of the surface. Consequently, the most susceptible land covers are crops, pastures, shrub vegetation, and forests.
]]>Authors: Cui Ding Dou Chang Diange Sun Songling Zou
This paper numerically analyzes the influence of heat release rate (HRR) and longitudinal ventilation velocity on smoke distribution characteristics in a T-shaped roadway when the fire source was located upstream of the T-junction. The back-layering length, critical ventilation velocity, smoke temperature, and CO concentration in the main and branched roadway were investigated and analyzed. The results showed that the ventilation velocity is the key factor influencing back-layering length, while the effect of HRR on back-layering length is gradually weakened as HRR increases. The critical ventilation velocity in the T-shaped roadway is higher than in a single-tube roadway, and the predicted model of dimensional critical ventilation velocity in a T-shaped bifurcated roadway is proposed. The correlation between average temperature (Z = 1.6 m) (both in the main roadway I and the branched roadway) and ventilation velocity fits the power function, and the variation in average temperature (Z = 1.6 m) according to HRR fits the linear formula. The relation between average concentration of CO (Z = 1.6 m) (both inside the main roadway I and the branched roadway) and longitudinal ventilation velocity follows the power relation, and the variation in average concentration of CO (Z = 1.6 m) according to HRR follows the linear function.
]]>Authors: Yang Song Cangsu Xu Xiaolu Li Francis Oppong
Wildfire causes environmental, economic, and human problems or losses. This study reviewed wildfires induced by lightning strikes. This review focuses on the investigations of lightning mechanisms in the laboratory. Also, the paper aims to discuss some of the modeling studies on lightning-induced wildfires at different geographical locations using satellite-recorded lightning data and different statistical analyses. This review established that irrespective of the different models used to predict lightning wildfires, there is still a lack of understanding of the lightning-strike ignition mechanism; few experiments have been modeled to establish the dynamics of lightning-strike ignition. Therefore, further research needs to be carried out in this area to understand lightning ignition. It was ascertained from the various statistical modeling that lightning-induced wildfires are exacerbated by the abundant availability of fuel with a lower moisture content and high lightning efficiency. Moreover, because of changes in the climate and weather conditions, i.e., harsh weather and climate conditions due to anthropogenic activities, lightning-induced ignition wildfires have increased over the years, and they are expected to increase in the future if the climate and weather conditions continue to aggravate. Although various modeling studies have identified that lightning-induced wildfires have increased recently, no preventive measures have been conclusively proposed to reduce lightning-caused wildfires. Hence, this aspect of research has to be given critical attention. This review presents information that gives a profound understanding of lightning-induced wildfires, especially factors that influence lightning wildfires, and the state-of-the-art research that has been completed to understand lightning-induced wildfires.
]]>Authors: Youzhi Shi Shixiong Qian Pengju Zhao Pan Guo Zihe Gao
This research focuses on the impact of smoke exhaust volume and smoke vent layout, which are two crucial factors affecting the smoke control efficiency in tunnels, on the smoke exhaust effect in tunnel fires. Numerical simulation methods are employed to investigate the impact of changing the smoke exhaust volume and the smoke vent number on the smoke exhaust performance in a curved tunnel with a ceiling centralized smoke exhaust system. This research primarily examines the length of the smoke distribution, the smoke temperature under the ceiling, the vertical visibility, and the exhausted smoke mass flow rate. The findings indicate that, in a tunnel with a single-side ceiling centralized smoke exhaust mode, an imbalance in smoke distribution occurs between the upstream and downstream of the fire source. The upstream area experiences a higher amount of smoke, while the downstream area has thinner smoke. Increasing the smoke exhaust volume yielded positive effects on smoke control, as evident in the reduced the smoke spread range, and improved the smoke exhaust efficiency. The influence of changing smoke vent number on the smoke exhaust effect was dependent on the smoke exhaust volume. When the smoke exhaust volume was excessive, altering the number of smoke vents had a minimal impact on smoke exhaust, while in cases with small smoke exhaust volumes, changes in smoke vent numbers obviously influenced the smoke control effect. Therefore, selecting an appropriate smoke exhaust volume and raising the smoke vent number can effectively optimize the performance of the ceiling centralized smoke exhaust system.
]]>Authors: Haley K. Skinner Susan J. Prichard Alison C. Cullen
Background: Climate change is a strong contributing factor in the lengthening and intensification of wildfire seasons, with warmer and often drier conditions associated with increasingly severe impacts. Land managers are faced with challenging decisions about how to manage forests, minimize risk of extreme wildfire, and balance competing values at risk, including communities, habitat, air quality, surface drinking water, recreation, and infrastructure. Aims: We propose that land managers use decision analytic frameworks to complement existing decision support systems such as the Interagency Fuel Treatment Decision Support System. Methods: We apply this approach to a fire-prone landscape in eastern Washington State under two proposed landscape treatment alternatives. Through stakeholder engagement, a quantitative wildfire risk assessment, and translating results into probabilistic descriptions of wildfire occurrence (burn probability) and intensity (conditional flame length), we construct a decision tree to explicitly evaluate tradeoffs of treatment alternative outcomes. Key Results: We find that while there are slightly more effective localized benefits for treatments involving thinning and prescribed burning, neither of the UWPP’s proposed alternatives are more likely to meaningfully minimize the risk of wildfire impacts at the landscape level. Conclusions: This case study demonstrates that a quantitatively informed decision analytic framework can improve land managers’ ability to effectively and explicitly evaluate tradeoffs between treatment alternatives.
]]>Authors: Václav Zumr Jiří Remeš Oto Nakládal
Forest fires represent a natural element in the dynamics of forest ecosystems. This study investigated the impact of a large-scale forest fire in 2022 (ca. 1300 ha) on epigeic ground beetles (Coleoptera: Carabidae). The research was conducted in coniferous forests at six pairwise study sites: burnt and unburnt dead spruce from bark beetles, burnt and unburnt clear cut, and burnt and unburnt healthy sites. Each site was replicated in four plots, with two pitfall traps deployed within each plot. In total, 48 pitfall traps (6 × 4 × 2) were installed in April 2023. It was tested how individual sites affected the similarity of ground beetle communities, whether they contained similar life guilds, and how significantly large-scale fire affects the abundance of pyrophilous ground beetles. A total of 5952 individuals and 63 species were recorded. We observed a significant decline in abundance at clear-cut and dead spruce burnt sites (73% and 77.5%, respectively) compared to the unburnt sites. Conversely, abundance increased by 88% at the burnt healthy site compared to the unburnt healthy site. Additionally, significant differences in the number of species per trap and species richness diversity (q = 0, q = 1, q = 2) were found only between burnt and unburnt healthy sites. In general, the highest species richness in the comparison of all study sites was at unburnt clear-cut and burnt healthy sites. Communities of ground beetles responded considerably to the fire, differing significantly from unburnt sites, and demonstrating a high degree of similarity. The original healthy spruce stands had highly homogeneous communities. On the contrary, any disturbance (bark beetle calamity, clear-cut) resulted in an increase in the alpha, beta, and gamma diversities of the ground beetle communities. Burnt sites attracted pyrophilous species (Sericoda quadripunctata, Pterostichus quadrifoveolatus) at very low abundances, with the highest activity in the second half of the season. In conclusion, ground beetles demonstrated a strong short-term response to large-scale fire, forming specific communities. However, pyrophilous ground beetles were unable to occupy a large-scale fire area due to the initial low abundance. Understanding post-fire processes can provide important guidance for management in areas designated for biodiversity enhancement.
]]>Authors: Murramarang Country Jessica Davis Jack Simmons Shane Snelson Victor Channell Katharine Haynes Nicholas Deutscher Leanne Brook Anthony Dosseto
Fire management techniques play a critical role in mitigating the impact of bushfires on communities and ecosystems. In Australia, government agencies implement hazard reduction burn programs, while Indigenous communities have used fire for ecosystem management for thousands of years. The positive effect of prescribed burning goes beyond bushfire risk mitigation, with impacts also on soil and ecosystem health. This study evaluates the effects of prescribed burning on soil properties, with implications for soil and ecosystem health. Two fire management techniques were evaluated: agency-led prescribed burning and cultural burning. Both fire treatments resulted in an increase in soil moisture, showing that they positively affect the soil water balance (the greater effect seen following the agency-led burn). Both fire treatments also resulted in a decrease in soil bulk density and an increase in organic matter content, with the greater effect seen for soils affected by the Indigenous-led burn. These results show that both fire management techniques positively affect soil health, with important consequences for aboveground ecosystem health. Cultural burning is the most efficient to promote reduced soil bulk density (important for nutrient availability and microbial activity) and increase carbon and nitrogen stores.
]]>Authors: Derek J. McNamara William E. Mell
Fires resulting from antecedent fires, known as exposure fires, can manifest across diverse environments, including suburban, urban, and rural areas. Notably, exposure fires represented by structure-destroying fires within the wildland–urban interface (WUI) can extend into non-WUI suburban and urban regions, presenting significant challenges. Leveraging data from the United States National Fire Incident Reporting System (NFIRS) spanning 2002 to 2020, this study investigates 131,739 exposure fire incidents impacting 348,089 features (incidents). We analyze reported economic costs, affected feature types, and property utilization patterns for these exposure fires. We also compare these exposure fires to information documented in other databases. Finally, we examine structure separation distance at residential dwellings and describe ignition pathways for selected fires. Reported property losses for some fire incidents amounted to USD 5,647,121,172, with content losses totaling USD 1,777,345,793. Prominent fire incident categories include buildings, vehicles, and natural vegetation fires, predominantly occurring in residential, outdoor, and storage areas. While the NFIRS lacked information on most major structure-destroying WUI fires, highlighting this analysis’s lack of statistical representation, it did provide insights into less extensive exposure fires, both WUI and non-WUI, unrecorded elsewhere. Our study reveals significant distinctions in the distribution of separation distances between damaged-to-damaged structures (average separation of 6.5 m) and damaged-to-not-damaged structures (average separation of 18.1 m). Notably, 84% of the incidents in exposure fires involved fire suppression defensive actions. These defensive actions contributed to the differences in structure separation distance distributions, highlighting the often-neglected role of these measures in assessing structure responses during WUI fires. We examined ignition pathways at select exposure fires, highlighting some common features involved in fire spread and challenges in documenting these pathways. Finally, we propose a set of idealized attributes for documenting exposure fires, accentuating the inherent difficulties in collecting such data across expansive geographical areas, particularly when striving for statistical representation. Our findings yield valuable insights into the multifaceted nature of exposure fires, informing future research and database development to aid in mitigating their impact on vulnerable communities.
]]>Authors: Nilanjan Chakraborty Cesar Dopazo
The fractional change in the reaction progress variable gradient depends on the flow normal straining within the flame and also upon the corresponding normal gradients of the reaction rate and its molecular diffusion transport. The statistical behaviours of the normal strain rate and the contributions arising from the normal gradients of the reaction rate and molecular diffusion rate within the flame were analysed by means of a Direct Numerical Simulation (DNS) database of statistically planar turbulent premixed flames ranging from the wrinkled/corrugated flamelets regime to the thin reaction zones regime. The interaction of flame-normal straining with the flame-normal gradient of molecular diffusion rate was found to govern the reactive scalar gradient transport in the preheat zone, where comparable timescales for turbulent straining and molecular diffusion are obtained for small values of Karlovitz numbers. However, the molecular diffusion timescale turns out to be smaller than the turbulent straining timescale for high values of Karlovitz numbers. By contrast, the reaction and hot product zones of the flame remain mostly unaffected by turbulence, and the reactive scalar gradient transport in this zone is determined by the interaction between the flame-normal gradients of molecular diffusion and chemical reaction rates.
]]>Authors: Pu Wang Hongtai Dai Xiuhui Yu Qingbiao Wang Shun Li Chuanyang Jia
Fire is a major disaster event that can have a significant effect on public safety and social development. In a college or university, fire can seriously threaten the safety, lives, and property of those there due to the compact layout of apartment buildings and high population density. The ecological safety and sustainable development of buildings are also affected. In this study, PyroSim and Pathfinder software (version 2019) were used to simulate and analyze fire-spreading characteristics based on a multi-story university student apartment building. Additionally, the most effective safe evacuation plan from four fire evacuation drill schemes was identified by analyzing and comparing their performance. Results show that the spreading of fire smoke on different floors is significantly affected by the roof structure and the vertical and horizontal diffusion characteristics of smoke. While the smoke layer at the evacuation stairways has little effect on a safe evacuation, poor visibility due to smoke and ceiling temperatures has a significant effect. Safe evacuation becomes progressively more difficult at different floor levels from the top to the bottom of the building. The optimal safety scheme involves orderly evacuation through two open emergency exits. The number of emergency exits has a significant impact on the evacuation effectiveness. Measures and suggestions have been proposed to deal with apartment fires that address pre-event prevention, emergency loss reduction during the event, and post-event report-back. These proposals form an important theoretical reference for emergency evacuation and student apartment fire safety, providing important guidance for ecological safety protection of buildings and sustainable development.
]]>Authors: Xiuquan Li Dugang Kang Lei Zhang Jie Chen Song Huang Qunfeng Zou Ziqiang He
Microchannel burners suffer from low combustion efficiency and poor stability in applications. In order to explore the effect of wall reaction on methane/air premixed combustion performances in the microchannel, the effects of wall activity, inlet velocity, pressure, and equivalence ratio on the temperature and radical distribution characteristics were studied by CFD computational simulations. It is found that as the reaction pressure increases, there are more free-radical collisions, causing the reaction temperature to rise. The OH radicals participate in the reaction at the active near wall so that the mass fraction of the OH radical on the active wall is lower than that on the inert wall. As the equivalence ratio increases from 0.6 to 1.2, the high-temperature regions increase but the maximum temperature decreases. The mass fraction of OH radical increases with the increase of the equivalence ratio, and the increase of OH radical near the inert wall is larger than that of the active wall. As the flow rate increases, the disturbance increases, and the combustion reaction becomes more intense, resulting in an increase in the temperature and the mass fraction of OH radicals. The mass fraction of H, O, OH, and CH3 radicals in the inert wall was slightly higher than that in the active wall, in which the peak mass fraction of CH3 radical appeared at the axial position closest to the entrance, while the other three radicals reached the peak at about the same axial position. This study provides a reference for combustion stability in microcombustors.
]]>Authors: Roberto Guardo Giuseppe Bilotta Gaetana Ganci Francesco Zuccarello Daniele Andronico Annalisa Cappello
We hereby present VolcFire, a new cellular automaton model for fire propagation aimed at the creation of fire hazard maps for fires of volcanic origin. The new model relies on satellite-derived input data for the topography, land-use, fuel, and humidity information, and produces probabilistic maps of fire propagation simulating fire spread. The model contains several simplifications compared to the current state-of-the-art, limiting its usability to plan fire-fighting interventions during an event in favour of a reduced computational load. The accuracy and reliability of the model are also discussed by presenting its ability to reproduce two recent fires on Stromboli island, with good spatial fit (Brier score of 0.146±0.002 for the 3 July 2019 volcanic fire, and of 0.073±0.001 for the 25 May 2022 anthropogenic fire) and less than 1.5% variation across multiple simulations for the same event.
]]>Authors: Zeeshan Ur Rehman Laila Khan Lee Hwain Yun Chiho Bon Heun Koo
In this study, process control factors such as dipping time, heat treatment time and curing conditions were optimized to prepare N-Si network sol–gel-based coatings on a cotton fabric. The dipping time was varied from 14 h to 30 min, the heat treatment time at ~90 °C was varied between no heating conditions to 15 h and the curing was performed at 165 °C. The microstructure of the coating was analyzed using low electron scanning microscopy (LV-SEM), while a compositional study of the coated substrate was carried out using FTIR and EDS techniques. From the thermal and combustion analysis of the coated samples using thermogravimetric and vertical flame test techniques, significant resistance to the degradation process was observed, particularly in the initial stages, in addition to the highest char residue for DI-0.5 h-15~32.93%. Similarly, for DI–5 h–RT, the peak degradation temperature was around ~372 °C, accompanied by a notable char residue of approximately 31.12%. The flame spread and burning rate profile further supported the findings; DI-0.5 h-15 and DI-5 h-RT had the lowest flame spread.
]]>Authors: Xinyu Hu Feng Jiang Xianlin Qin Shuisheng Huang Xinyuan Yang Fangxin Meng
Smoke, a byproduct of forest and grassland combustion, holds the key to precise and rapid identification—an essential breakthrough in early wildfire detection, critical for forest and grassland fire monitoring and early warning. To address the scarcity of middle–high-resolution satellite datasets for forest and grassland fire smoke, and the associated challenges in identifying smoke, the CAF_SmokeSEG dataset was constructed for smoke segmentation. The dataset was created based on GF-6 WFV smoke images of forest and grassland fire globally from 2019 to 2022. Then, an optimized segmentation algorithm, GFUNet, was proposed based on the UNet framework. Through comprehensive analysis, including method comparison, module ablation, band combination, and data transferability experiments, this study revealed that GF-6 WFV data effectively represent information related to forest and grassland fire smoke. The CAF_SmokeSEG dataset was found to be valuable for pixel-level smoke segmentation tasks. GFUNet exhibited robust smoke feature learning capability and segmentation stability. It demonstrated clear smoke area delineation, significantly outperforming UNet and other optimized methods, with an F1-Score and Jaccard coefficient of 85.50% and 75.76%, respectively. Additionally, augmenting the common spectral bands with additional bands improved the smoke segmentation accuracy, particularly shorter-wavelength bands like the coastal blue band, outperforming longer-wavelength bands such as the red-edge band. GFUNet was trained on the combination of red, green, blue, and NIR bands from common multispectral sensors. The method showed promising transferability and enabled the segmentation of smoke areas in GF-1 WFV and HJ-2A/B CCD images with comparable spatial resolution and similar bands. The integration of high spatiotemporal multispectral data like GF-6 WFV with the advanced information extraction capabilities of deep learning algorithms effectively meets the practical needs for pixel-level identification of smoke areas in forest and grassland fire scenarios. It shows promise in improving and optimizing existing forest and grassland fire monitoring systems, providing valuable decision-making support for fire monitoring and early warning systems.
]]>Authors: Yining Tang Zhaofeng Tian Xiao Chen Brigitta Suendermann Grant Gamble Zefeng Huang
A numerical investigation has been conducted to analyse the effect of wind on the vertical spread of fire through a front opening in a building’s external walls. The study utilises a building geometry established from previous experimental work conducted by the National Research Council of Canada (NRCC). A horizontal projection or a vertical spandrel is introduced above the opening of the compartment of fire origin. The purpose of the projection or spandrel is to inhibit the vertical spread of the fire, following the relevant requirements in the Australian National Construction Code (NCC). A computational fluid dynamics (CFD) package for fire-driven fluid flow, namely the Fire Dynamics Simulator (FDS), is employed to simulate the fire behaviour. The FDS model is validated against the NRCC’s experimental results, and a good agreement is achieved. Winds from three horizontal directions (front wind is normal to the opening, side wind is parallel to the opening, and back wind is from behind the building) have been investigated, with speeds ranging up to 10 m/s for each wind direction. Front wind speeds below 1 m/s are found to slightly enhance the vertical spread of the fire, while speeds exceeding 1 m/s are inclined to promote horizontal spread. The impact of side wind on the vertical fire spread was also found to vary with wind speed. The increase in the speed of back wind influences flame buoyancy, resulting in an augmented vertical fire spread. Furthermore, the numerical results reveal that a vertical spandrel of 1100 mm height is less effective in preventing vertical fire spread through openings, compared to a 1100 mm deep horizontal projection. The study suggests that the fire safety design in reducing the hazard of vertical fire spread through openings in buildings’ external walls could be further improved if the effect of wind is considered.
]]>Authors: Poliana Domingos Ferro Guilherme Mataveli Jeferson de Souza Arcanjo Débora Joana Dutra Thaís Pereira de Medeiros Yosio Edemir Shimabukuro Ana Carolina Moreira Pessôa Gabriel de Oliveira Liana Oighenstein Anderson
Fires are one of the main sources of disturbance in fire-sensitive ecosystems such as the Amazon. Any attempt to characterize their impacts and establish actions aimed at combating these events presupposes the correct identification of the affected areas. However, accurate mapping of burned areas in humid tropical forest regions remains a challenging task. In this paper, we evaluate the performance of four operational BA products (MCD64A1, Fire_cci, GABAM and MapBiomas Fogo) on a regional scale in the southwestern Amazon and propose a new approach to BA mapping using fraction images extracted from data cubes of the Brazilian orbital sensors CBERS-4/WFI and CBERS-4A/WFI. The methodology for detecting burned areas consisted of applying the Linear Spectral Mixture Model to the images from the CBERS-4/WFI and CBERS-4A/WFI data cubes to generate shadow fraction images, which were then segmented and classified using the ISOSEG non-supervised algorithm. Regression and similarity analyses based on regular grid cells were carried out to compare the BA mappings. The results showed large discrepancies between the mappings in terms of total area burned, land use and land cover affected (forest and non-forest) and spatial location of the burned area. The global products MCD64A1, GABAM and Fire_cci tended to underestimate the area burned in the region, with Fire_cci underestimating BA by 88%, while the regional product MapBiomas Fogo was the closest to the reference, underestimating by only 7%. The burned area estimated by the method proposed in this work (337.5 km2) was 12% higher than the reference and showed a small difference in relation to the MapBiomas Fogo product (18% more BA). These differences can be explained by the different datasets and methods used to detect burned areas. The adoption of global products in regional studies can be critical in underestimating the total area burned in sensitive regions. Our study highlights the need to develop approaches aimed at improving the accuracy of current global products, and the development of regional burned area products may be more suitable for this purpose. Our proposed approach based on WFI data cubes has shown high potential for generating more accurate regional burned area maps, which can refine BA estimates in the Amazon.
]]>Authors: Yunlin Zhang Lingling Tian
As a cigarette butt falls onto the forest surface fuel, it first smolders the fuel, then ignites into flames, and spreads as forest fire under certain conditions. In this study, the needles under a typical stand of P. massoniana were used as the research object. Needle beds with different moisture content and packing ratios were constructed indoors. Cigarette butt-ignition experiments were conducted under different wind velocities, and 30 experiment cycles were conducted under different conditions. There was a total of 5 (packing ratio) × 4 (moisture content) × 6 (wind velocity) = 120 sets of conditions, and a total of 3600 ignition experiments were conducted. The results showed that (1) the total ignition probability of the cigarette butts was 2.36%, which only occurred when the fuelbed moisture content was <10% and the wind velocity was >1 m/s. The ignition time of cigarette butts ranged from 2.73 to 7.25 min. (2) The fuelbed moisture content and wind velocity significantly influenced the ignition probability and time. With an increase in moisture content, the ignition probability of cigarette butts decreased, while the time required for ignition showed an increasing trend. Wind velocity had a dual effect on ignition. The ignition effect was optimal at a wind velocity of 4 m/s. With an increase in wind velocity, the ignition probability first increased and then decreased, and the ignition time first decreased and then increased. (3) The packing ratio had no significant effect on the ignition probability; however, the ignition time significantly decreased as the packing ratio increased. (4) The logistic regression method (LRM), general linear method (GLM), and nonlinear regression method (NLM) were used to establish a prediction model of ignition probability. The prediction effect of GLM was the worst, followed by LRM, and the NLM had the best prediction effect. The GLM was selected to establish the ignition time model, and the error was also within the allowance range. This study elucidated the underlying mechanism of factors affecting cigarette butt-based fuel ignition. In addition, the established prediction model provides a reference for human-caused forest fires and is highly significant for forest fire prevention.
]]>Authors: Matt Young Michael Remke Julie Korb
Fire injury stresses Douglas-fir trees (Pseudotsuga menziesii) that survive a wildfire event, allowing subsequent Douglas-fir beetle (Dendroctonus pseudotsugae) infection to kill trees that may have otherwise survived. This study aimed to determine how fire injury, stand, and tree characteristics drive Douglas-fir beetle host tree selection five years post-fire. We paired 28 adjacent beetle-infected and uninfected stands (infected N = 14) and 140 Douglas-fir trees (infected N = 70) within the 416 Fire burn area in Southwest Colorado. We found no statistically significant differences between infected and uninfected stand characteristics. Individual tree height, DBH, and bark char severity index were significantly higher in infected versus uninfected trees. We created a regression decision tree model to determine the influence of fire injury and tree characteristics on the probability of infection. Trees with a height ≥ 27 m, bark char height < 2.3 m, and DBH < 80 cm had the greatest probability of attack (100%). Trees with a height < 27 m, bark char severity index < 5.5, and DBH < 49 cm had the lowest probability of attack (3.7%). Understanding the influence of fire on Douglas-fir beetle host selection allows land managers to model potential epidemic outbreaks and guide proactive management actions that may reduce beetle outbreak severity or preserve high-value trees not killed by fire.
]]>Authors: Guangyi Yang Xuelei Zhang Aijun Xiu Chao Gao Mengduo Zhang Qingqing Tong Wei Liu Yang Yu Hongmei Zhao Shichun Zhang Shengjin Xie
Open-field crop residue burning (OCRB) is a widespread agricultural practice with significant impacts on regional environments and public health. The effective management of OCRB remains a challenging task that requires timely access to various forms of monitored and forecasted information. Addressing this worldwide need, an open-source platform named AgriFireInfo v1.0, which is specifically tailored to monitoring and regulating regional OCRB activities, was developed. This technical note thoroughly illustrates the platform’s architecture, major modules, and visualization processes. Through AgriFireInfo v1.0, government agencies can access timely information about the spatial distribution of fire spots and emissions as well as meteorological conditions and air quality status. AgriFireInfo v1.0 also introduces an innovative Prevention Alarming Index, designed to identify regions prone to OCRB and promote comprehensive crop residue utilization. Furthermore, it offers the burning window and crop residue yields for controlled OCRB activities and can be used to analyze shifts in farmers’ burning behaviors and intensities. Future enhancements will focus on supplying holistic information on the burning windows and burning amounts of crop residues to further facilitate refined controlled burning activities and optimize decision-making processes. The flexibility and scalability of this platform can potentially allow users to easily customize and apply it to other regions or countries.
]]>Authors: Luke A. Scott Julie E. Korb
Birds contribute to the trophic interactions within mixed conifer ecosystems and provide a suite of services, such as nutrient transport, seed dispersal, habitat creation, and insect regulation. Avian communities vary in response to the structure and composition of their habitat, which may be drastically altered by fire, the predominant disturbance of western mixed conifer forests. We conducted avian point count surveys during the peak breeding season, five years post-fire, across four burn severities (unburned, low, moderate, and high) within the 416 Fire perimeter, a 55,000-acre mixed-severity fire that burned near Durango, Colorado in 2018. Avian communities in each burn severity were evaluated for richness, diversity, differentiation, indicator species, and functional guild composition. Species assemblages were significantly different across all burn severities, excluding the low to moderate areas comparison, with differentiation driven by live tree and snag density. Avian species’ richness and diversity were not significantly different across burn severities, highlighting the importance of utilizing multivariate community analysis. Unburned and high-burn areas had significant variation in functional guilds and numerous indicator species. This study provides evidence of avian community differentiation by burn severity, suggesting that management practices promoting heterogenous stand structure in warm–dry mixed conifer will positively influence avian biodiversity.
]]>Authors: Olga D. Mofokeng Samuel A. Adelabu Colbert M. Jackson
Grasslands are key to the Earth’s system and provide crucial ecosystem services. The degradation of the grassland ecosystem in South Africa is increasing alarmingly, and fire is regarded as one of the major culprits. Globally, anthropogenic climate changes have altered fire regimes in the grassland biome. Integrated fire-risk assessment systems provide an integral approach to fire prevention and mitigate the negative impacts of fire. However, fire risk-assessment is extremely challenging, owing to the myriad of factors that influence fire ignition and behaviour. Most fire danger systems do not consider fire causes; therefore, they are inadequate in validating the estimation of fire danger. Thus, fire danger assessment models should comprise the potential causes of fire. Understanding the key drivers of fire occurrence is key to the sustainable management of South Africa’s grassland ecosystems. Therefore, this study explored six statistical and machine learning models—the frequency ratio (FR), weight of evidence (WoE), logistic regression (LR), decision tree (DT), random forest (RF), and support vector machine (SVM) in Google Earth Engine (GEE) to assess fire danger in an Afromontane grassland protected area (PA). The area under the receiver operating characteristic curve results (ROC/AUC) revealed that DT showed the highest precision on model fit and success rate, while the WoE was used to record the highest prediction rate (AUC = 0.74). The WoE model showed that 53% of the study area is susceptible to fire. The land surface temperature (LST) and vegetation condition index (VCI) were the most influential factors. Corresponding analysis suggested that the fire regime of the study area is fuel-dominated. Thus, fire danger management strategies within the Golden Gate Highlands National Park (GGHNP) should include fuel management aiming at correctly weighing the effects of fuel in fire ignition and spread.
]]>Authors: Pengfei Ding Chunyin Zhang Qize He Lijing Wang Yun Yang
To improve our understanding of flaming, smoldering, or self-extinction in the burning of wood, it is necessary to quantify the conditions that lead to self-extinguished and self-sustained smoldering combustion. Experiments were performed in a cone calorimeter under an external irradiation of 10 to 25 kW/m2 to analyze the temperature and mass loss of self-extinguished and self-sustained smoldering. The smoldering front depth was the significant parameter used to capture the smoldering characteristic, and it was defined as the axial thickness that reaches the smoldering characteristic temperature. The critical smoldering front depth of self-extinguished smoldering was lower than 10–15 mm for 30 mm thick wood at 15.5 kW/m2 irradiation. This critical depth decreased with the increase in heat flux, from 26.5 ± 1.5 mm at 10 kW/m2 to 11 ± 1 mm at 25 kW/m2. A simple theoretical analysis is proposed to explain the smoldering thickness threshold of self-sustained smoldering propagation based on the local heat balance. The equation predicts that the critical depth decreases as the heat flux increases, from 23.9 mm at 8 kW/m2 to 7.3 mm at 25 kW/m2. The predicted critical depth and heating duration were consistent with the experimental results. This study proposes a feasible parameter to help understand the threshold of smoldering propagation and the development of biomass burners.
]]>Authors: Raúl Hoffrén María Teresa Lamelas Juan de la Riva
The exposure of Mediterranean forests to large wildfires requires mechanisms to prevent and mitigate their negative effects on the territory and ecosystems. Fuel models synthesize the complexity and heterogeneity of forest fuels and allow for the understanding and modeling of fire behavior. However, it is sometimes challenging to define the fuel type in a structurally heterogeneous forest stand due to the mixture of characteristics from the different types and limitations of qualitative field observations and passive and active airborne remote sensing. This can impact the performance of classification models that rely on the in situ identification of fuel types as the ground truth, which can lead to a mistaken prediction of fuel types over larger areas in fire prediction models. In this study, a handheld mobile laser scanner (HMLS) system was used to assess its capability to define Prometheus fuel types in 43 forest plots in Aragón (NE Spain). The HMLS system captured the vertical and horizontal distribution of fuel at an extremely high resolution to derive high-density three-dimensional point clouds (average: 63,148 points/m2), which were discretized into voxels of 0.05 m3. The total number of voxels in each 5 cm height stratum was calculated to quantify the fuel volume in each stratum, providing the vertical distribution of fuels (m3/m2) for each plot at a centimetric scale. Additionally, the fuel volume was computed for each Prometheus height stratum (0.60, 2, and 4 m) in each plot. The Prometheus fuel types were satisfactorily identified in each plot and were compared with the fuel types estimated in the field. This led to the modification of the ground truth in 10 out of the 43 plots, resulting in errors being found in the field estimation between types FT2–FT3, FT5–FT6, and FT6–FT7. These results demonstrate the ability of the HMLS systems to capture fuel heterogeneity at centimetric scales for the definition of fuel types in the field in Mediterranean forests, making them powerful tools for fuel mapping, fire modeling, and ultimately for improving wildfire prevention and forest management.
]]>Authors: Feng Xu Wenjing Chen Rui Xie Yihui Wu Dongming Jiang
Vegetation classification, biomass assessment, and wildfire dynamics are interconnected wildfire-ecosystem components. The Chongli District, located in Zhangjiakou City, was the venue for skiing at the 2022 Winter Olympics. Its high mountains and dense forests create a unique environment. The establishment of alpine ski resorts highlighted the importance of comprehensive forest surveys. Understanding vegetation types and their biomass is critical to assessing the distribution of local forest resources and predicting the likelihood of forest fires. This study used satellite multispectral data from the Sentinel-2B satellite to classify the surface vegetation in the Chongli District through K-means clustering. By combining this classification with a biomass inversion model, the total biomass of the survey area can be calculated. The biomass inversion equation established based on multispectral remote sensing data and terrain information in the Chongli area have a strong correlation (shrub forest R2 = 0.811, broadleaf forest R2 = 0.356, coniferous forest R2 = 0.223). These correlation coefficients are key indicators for our understanding of the relationship between remote sensing data and actual vegetation biomass, reflecting the performance of the biomass inversion model. Taking shrubland as an example, a correlation coefficient as high as 0.811 shows the model’s ability to accurately predict the biomass of this type of vegetation. In addition, through multiple linear regression, the optimal shrub, broadleaf, and coniferous forest biomass models were obtained, with the overall accuracy reaching 93.58%, 89.56%, and 97.53%, respectively, meeting the strict requirements for survey accuracy. This study successfully conducted vegetation classification and biomass inversion in the Chongli District using remote sensing data. The research results have important implications for the prevention and control of forest fires.
]]>Authors: Domingos Pereira Elza M. M. Fonseca Miguel Osório
The present study is focused on wall panels exposed to fire, with the construction building elements we used being made of wood and gypsum board materials. This type of configuration forms hollow core wood due to the constructive process. The aim is to present a numerical study to approach the calculation of the temperature inside hollow core wood elements and measure their fire resistance. The temperature evolution inside the cavities will be obtained with recourses to obtain the heat effect by convection and radiation through the wall elements. A numerical model, previously validated by the authors, will be used to carry out this process. The methodology includes the use of the finite element method in thermal and transient analysis with nonlinear materials to calculate temperature. To measure the fire resistance of the constructive model, the thermal insulation criterion, defined by the EN 1363-1:2020 standard, will be applied. Different results will be presented to discuss and ensure the verification of these fire-resistant elements.
]]>Authors: Hong-Seok Yun Cheol-Hong Hwang
Consideration of appropriate fire scenarios in the simulations of the Fire Dynamics Simulator (FDS) for the fire-risk assessment of buildings is a critical factor in the development of prevention and response measures. The user dependence of the FDS input parameters can threaten the reliability of the fire-risk assessment. An experimental study was conducted to establish correlations for considering appropriate fire scenarios using polymethyl methacrylate. To examine the changes in the maximum-heat-release rates (HRRs) according to the combustion environment, nine burners varying in size at 25 mm intervals were burned in open and compartment environments. The results indicated that compared with the fire phenomenon in the open environment, the maximum HRR and fire growth rate of the compartment fire were increased by factors of 3–50. Additionally, the compartment fire phenomena could be classified into three stages according to the changes in the aforementioned two physical quantities. An analysis of the experimental results revealed a correlation for predicting the maximum HRR of a compartment fire with various ventilation conditions using only the experimental results for the open environment. The maximum HRR predicted through this correlation exhibited an error of <15% relative to the values measured in the experiment.
]]>Authors: Yanlong Shan Bo Gao Sainan Yin Diankun Shao Lili Cao Bo Yu Chenxi Cui Mingyu Wang
In recent years, the influence of extreme weather patterns has led to an alarming increase in the frequency and severity of sub-surface forest fires in boreal forests. The Ledum palustre-Larix gmelinii forests of the Daxing’an Mountains of China have emerged as a hotspot for sub-surface fires, and terrain slope has been recognized as a pivotal factor shaping forest fire behavior. The present study was conducted to (1) study the effect of terrain slope on the smoldering temperature and spread rate using simulated smoldering experiments and (2) establish occurrence probability prediction model of the sub-surface fires’ smoldering with different slopes based on the random forest model. The results showed that all the temperatures with different slopes were high, and the highest temperature was 947.91 °C. The spread rates in the horizontal direction were higher than those in the vertical direction, and the difference increased as the slope increased. The influence of slope on the peak temperature was greater than that of spread rate. The peak temperature was extremely positively correlated with the slope, horizontal distance and vertical depth. The spread rate was extremely positively correlated with the slope. The spread rate in the vertical direction was strongly positively correlated with the depth, but was strongly negatively correlated with the horizontal distance; the horizontal spread rate was opposite. The prediction equations for smoldering peak temperature and spread rate were established based on slope, horizontal distance, and vertical depth, and the model had a good fit (p < 0.01). Using random forest model, we established the occurrence prediction models for different slopes based on horizontal distance, vertical depth, and combustion time. The models had a good fit (AUC > 0.9) and high prediction accuracy (accuracy > 80%). The study proved the effect of slope on the characteristics of sub-surface fire smoldering, explained the variation in peak temperature and spread rate between different slopes, and established the occurrence prediction model based on the random forest model. The selected models had a good fit, and prediction accuracy met the requirement of the sub-surface fire prediction.
]]>Authors: Yiqing Xu Jiaming Li Long Zhang Hongying Liu Fuquan Zhang
In the context of large-scale fire areas and complex forest environments, the task of identifying the subtle features and aspects of fire can pose a significant challenge for the deep learning model. As a result, to enhance the model’s ability to represent features and its precision in detection, this study initially introduces ConvNeXtV2 and Conv2Former to the You Only Look Once version 7 (YOLOv7) algorithm, separately, and then compares the results with the original YOLOv7 algorithm through experiments. After comprehensive comparison, the proposed ConvNeXtV2-YOLOv7 based on ConvNeXtV2 exhibits a superior performance in detecting forest fires. Additionally, in order to further focus the network on the crucial information in the task of detecting forest fires and minimize irrelevant background interference, the efficient layer aggregation network (ELAN) structure in the backbone network is enhanced by adding four attention mechanisms: the normalization-based attention module (NAM), simple attention mechanism (SimAM), global attention mechanism (GAM), and convolutional block attention module (CBAM). The experimental results, which demonstrate the suitability of ELAN combined with the CBAM module for forest fire detection, lead to the proposal of a new method for forest fire detection called CNTCB-YOLOv7. The CNTCB-YOLOv7 algorithm outperforms the YOLOv7 algorithm, with an increase in accuracy of 2.39%, recall rate of 0.73%, and average precision (AP) of 1.14%.
]]>Authors: Yunhao Yang Yuanyuan Zhang Guowei Zhang Tianyao Tang Zhaoyu Ning Zhiwei Zhang Ziming Zhao
Determining fire source in underground commercial street fires is critical for fire analysis. This paper proposes a method based on temperature and machine learning to determine information about fire source in underground commercial street fires. Data was obtained through consolidated fire and smoke transport (CFAST) software, and a fire database was established based on the sampling to ascertain fire scenarios. Temperature time series were chosen for feature processing, and three machine learning models for fire source determination were established: decision tree, random forest, and LightGBM. The results indicated that the trained models can determine fire source information based on processed features, achieving a precision exceeding 95%. Among these, the LightGBM model exhibited superior performance, with macro averages of precision, recall, and F1 score being 99.01%, 98.45%, and 99.04%, respectively, and a kappa value of 98.81%. The proposed method for determining the fire source provides technical support for grasping the fire situation in underground commercial streets and has good application prospects.
]]>Authors: Jose A. Ortega-Becerril Clara Suarez Daniel Vázquez-Tarrío Julio Garrote Miguel Gomez-Heras
The 2021 Navalacruz wildfire occurred in a mountainous area in the Sistema Central (Spain). Despite having an average low severity index (dNBR), the loss of vegetation cover associated with the fire was responsible for a high rate of sedimentation in the rivers and streams. Additionally, the burned area affected up to 60 cultural heritage sites, including archaeological and ethnological sites, and damage ranged from burnt pieces of wood to the burial of archaeological sites. In the present work, we document and analyze the post-fire evolution in several rivers and streams. This is based on a field survey of infiltration rates, hydrodynamic modeling, and the study of channel morphological changes. Our analysis revealed how the first post-fire rains caused the mobilization and transport of ashes. This created hydrophobicity in the soils, resulting in large amounts of materials being transported to rivers and streams by subsequent medium- and low-magnitude storms. A hydrological and hydraulic model of the study catchments under pre- and post-fire conditions suggests that these trends are a consequence of a post-fire increase in flow rates for similar rainfall scenarios. In this respect, our estimates point at a significant increase in sediment transport capacities associated with this post-fire increase in flow rates. The combination of locally steep slopes with high-severity fire patches, and a considerable regolith (derived from pre-fire weathering), resulted in a series of cascading responses, such as an exacerbated supply of sand to the drainage network and the triggering of debris flows, followed by erosion and entrenchment.
]]>Authors: Sanath Sathyachandran Kumar Brian Tolk Ray Dittmeier Joshua J. Picotte Inga La Puma Birgit Peterson Timothy D. Hatten
LANDFIRE (LF) has been producing periodic spatially explicit vegetation change maps (i.e., LF disturbance products) across the entire United States since 1999 at a 30 m spatial resolution. These disturbance products include data products produced by various fire programs, field-mapped vegetation and fuel treatment activity (i.e., events) submissions from various agencies, and disturbances detected by the U.S. Geological Survey Earth Resources Observation and Science (EROS)-based Remote Sensing of Landscape Change (RSLC) process. The RSLC process applies a bi-temporal change detection algorithm to Landsat satellite-based seasonal composites to generate the interim disturbances that are subsequently reviewed by analysts to reduce omission and commission errors before ingestion them into LF’s disturbance products. The latency of the disturbance product is contingent on timely data availability and analyst review. This work describes the development and integration of the Spatially Adaptable Filter for Error Reduction (SAFER) process and other error and latency reduction improvements to the RSLC process. SAFER is a random forest-based supervised classifier and uses predictor variables that are derived from multiple years of pre- and post-disturbance Landsat band observations. Predictor variables include reflectance, indices, and spatial contextual information. Spatial contextual information that is unique to each contiguous disturbance region is parameterized as Z scores using differential observations of the disturbed regions with its undisturbed neighbors. The SAFER process was prototyped for inclusion in the RSLC process over five regions within the conterminous United States (CONUS) and regional model performance, evaluated using 2016 data. Results show that the inclusion of the SAFER process increased the accuracies of the interim disturbance detections and thus has potential to reduce the time needed for analyst review. LF does not track the time taken by each analyst for each tile, and hence, the relative effort saved was parameterized as the percentage of 30 m pixels that are correctly classified in the SAFER outputs to the total number of pixels that are incorrectly classified in the interim disturbance and are presented. The SAFER prototype outputs showed that the relative analysts’ effort saved could be over 95%. The regional model performance evaluation showed that SAFER’s performance depended on the nature of disturbances and availability of cloud-free images relative to the time of disturbances. The accuracy estimates for CONUS were inferred by comparing the 2017 SAFER outputs to the 2017 analyst-reviewed data. As expected, the SAFER outputs had higher accuracies compared to the interim disturbances, and CONUS-wide relative effort saved was over 92%. The regional variation in the accuracies and effort saved are discussed in relation to the vegetation and disturbance type in each region. SAFER is now operationally integrated into the RSLC process, and LANDFIRE is well poised for annual updates, contingent on the availability of data.
]]>Authors: W. Dukarski I. Rykowska P. Krzyżanowski M. Gonsior
The growing interest in modern polymer materials has targeted research on complex plastic coatings and the possibilities of modifying their features and properties during manufacturing. Today’s modern coatings, including polyurea and polyurethane, are among the most modern developed resins. Compared to other polymer coatings, they are distinguished by their versatility, strength, and durability. They undoubtedly represent the next step in the evolution of coatings. Advances in coating technology have also led to the development of spray, injection, and roto-cast application equipment, improving polyurea-based elastomers’ performance. For many years, there has been much interest in increasing the flame resistance of polymers. This is dictated by safety considerations and the increasing requirements for the flammability of plastics, the area of application of which is growing every year. This text attempts to provide an overview of current research on flame retardant composites. Particular attention was paid to polyurea (PU) and polyurea-based hybrids and the application areas of polyurea coatings. The paper defines flame retardants, discusses how they work, and presents the types of flame retardants and the current trends of their usage in the production of plastics.
]]>Authors: Dengyou Xia Changlin Chen Ce Zheng Jing Xin Yi Zhu
In order to solve the problem of emergency decision-making with incomplete information and deal with the accident information in different time series at the scenes of major accidents, this paper proposes a method of sequential decision-making by utilizing the relevant knowledge of D-S evidence theory and game theory. Firstly, we took an oil tank fire accident as an example and sorted out historical cases and expert experiences to establish a logical relationship between key accident scenes and accident scene symptoms in the accident. Meanwhile, we applied the logistic regression analysis method to obtain the basic probability distribution of each key accident scene in the oil tank fire, and on this basis, we constructed an evidence set of the fire. Secondly, based on the D-S evidence theory, we effectively quantified the knowledge uncertainty and evidence uncertainty, with the incomplete and insufficient information taken as an evidence system of the development of key accident scenes to construct a situation prediction model of these accident scenes. Thirdly, based on the game theory, we viewed emergency decision-makers and major accidents as two sides of the game to compare and analyze accident states at different time points and solve the contradiction between loss costs of decision-making and information collection costs. Therefore, this paper has provided a solution for the optimization of accident schemes at different time stages, thus realizing the sequential decision-making at the scenes of major accidents. Furthermore, we combined the situation prediction model with sequential decision-making, with the basic steps described below: (1) We drew up an initial action plan in the case of an extreme lack of information; then, we (2) started to address the accident and constructed a framework of accident identification, (3) collected and dealt with the continuously added evidence information with the evolution of the accident, (4) calculated the confidence levels of key accident scenarios after evaluating different evidence and then predicted the accident state in the next stage, and (5) calculated the profit–loss ratio between the current decision-making scheme and the decision-making scheme of the next stage. Finally, we (6) repeated steps (3) to (5) until the accident completely vanished. We verified the feasibility of the proposed method with the explosion accident of the Zhangzhou P.X. project in Fujian on 6 April used as an example. Based on the D-S evidence theory, this method employs approximate reasoning on the incomplete and insufficient information obtained at the scenes of major accidents, thus realizing the situation prediction of key scenes of these accidents. Additionally, this method uses the game theory to solve the contradiction between decision-making loss costs and information collection costs, thus optimizing the decision-making schemes at different time stages of major accidents.
]]>Authors: Keiji Takeno Hikaru Kido Hiroki Takeda Shohei Yamamoto Volodymyr Shentsov Dmitriy Makarov Vladimir Molkov
A hydrogen under-expanded jet released from a high-pressure vessel or equipment into the atmosphere through a 0.53 mm diameter orifice results in a sustained lifted flame for pressures above 4 MPa and flame blow-out at pressures below 3 MPa. Knowledge of whether the leaked hydrogen creates a sustained flame or is extinguished is an important issue for safety engineering. This study aims to clarify, in detail, a mechanism of flame stabilisation and blow-out depending on the spouting pressure. The model of flame stabilisation is derived using measurements and observations at the flame base location by means of high-speed schlieren images, laser diagnostics, and electrostatic probe techniques. The sustained stable flame originating from the 0.53 mm orifice is characterised by the existence of the spherical flame structures with a diameter of about 5 to 7 mm that appear one after another at the flame base and outside the streamlines of the hydrogen jet. As the spouting pressure reduces to 3.5 MPa, the sustained lifted flame becomes quasi-steady with higher fluctuations in amplitude of the flame base (lift-off height). In addition to that, flame structures are moving further from the hydrogen jet outlet, with a further decrease of spouting pressure leading to blow-out. The existence of spherical flame formations plays an important role in flame stabilisation. Based on the measurements of OH radicals using the PLIF method and ion currents, multiple flame surfaces were found to be folded in the flame structures. The hydrogen jet generates the vortex-like flow near its outer edge, creating flamelets upon ignition, ultimately forming the observed in the experiments spherical flame structures.
]]>Authors: Yuru Fan Hao Cui Jiawen Qin Changcheng Liu Que Huang
A workshop, as a crowded place, is quite easy to cause serious casualties and economic losses once there is a fire. In this paper, Pathfinder software was used to simulate fire emergency evacuation in a workshop of a large factory with building structural symmetry. According to the simulation results, several obstacles to the evacuation were discovered and further analyzed. The results showed that the main factors affecting the evacuation were the width of exits, the distribution of occupants and the effective evacuation width of stairs. Among them, only changing the width of exits had little influence on shortening evacuation time. While changing the effective evacuation width of stairs could greatly relieve the evacuation pressure, every increase of 0.5 m in the width of the staircase could shorten the evacuation time by 30.0 s. Meanwhile, the larger the number of people in high-rise buildings, the longer the evacuation time was. Therefore, the means of restricting people from entering the high-rise buildings in batches could be used to prevent personnel from being evacuated in time when a fire incident occurs.
]]>Authors: Juliana Garcia Michael C. F. Bazzocchi Kevin Fite Juan D. Ocampo Marcias Martinez
Safety and prevention of injuries should always be considered in a firefighting environment due to the hazardous conditions experienced on the fireground. These hazardous environmental conditions lead to an increased risk of contracting job-related injuries and illnesses. This review article focuses on evaluating from a statistical perspective the potential solutions found in the literature and how they decrease the likelihood and impact of occupational firefighting injuries. Investigating, identifying, and prioritizing the most common activities leading to injury, the nature of injury, and the body parts affected is a vital step in the implementation of preventive solutions. The scientific community has conducted various studies to evaluate the main injuries and injury profiles commonly suffered by firefighters. Researchers have conducted many independent studies on firefighter communities in the United States, while others have referenced national databases from sources such as the National Fire Protection Association, the Bureau of Labor Statistics, and the National Electronic Injury Surveillance System. Unfortunately, the results of these independent studies lacked standardization in survey categories and terminology, impairing the ability to obtain a clear consensus among studies on the primary nature of injuries, the body parts injured, and the activities contributing to these injuries. Consequently, this review article performed a comparative statistical analysis of published data between 1992 and 2020 to define and rank the most common work scenarios where firefighters were likely to be injured, the most common types of injuries, the parts of the body affected, and the activities that most contribute to United States firefighter injuries as documented in both national databases and independent research surveys. The statistical analysis consisted of determining the mean, standard deviation, confidence intervals (95%), and coefficients of variation for the reported data. The present study identified that despite the preventative measures taken by many organizations in the firefighting community, strains and sprains were still the leading type of injury reported from all the databases under this analysis.
]]>Authors: Lite Zhang Yang Feng Sifan Wu Huixia Jia
A two-way coupled model between polydisperse particle phases with compressible gases and a density-based coupling implicit solution method, combining the third-order MUSCL with QUICK spatial discretization scheme and the second-order temporal discretization scheme, are constructed based on the discrete-phase model (DPM) and the stochastic wander model (DRWM) in the Eulerian–Lagrangian framework in conjunction with a unitary particulate source (PSIC) approach and the SST k-ω turbulence model. The accuracy of the numerical prediction method is verified using previous supersonic nozzle gas-solid two-phase flow experiments. Numerical simulation of a two-phase jet of dry powder extinguishing agent gas with pilot-type supersonic nozzle was performed to analyze the influence of geometrical parameters, such as the length ratio rL and the area ratio rA of the main nozzle on the two-phase flow field, as well as on the jet performance indexes, such as the particle mean velocity vp,a, velocity inhomogeneity Φvp, particle dispersion Ψp, particle mean acceleration ap,a, etc. By analyzing the parameters, we indicate the requirements for the combination of jet performance metrics for different flame types such as penetrating, spreading, and dispersing.
]]>Authors: Chad T. Hanson Tonja Y. Chi Maya Khosla Bryant C. Baker Craig Swolgaard
Giant sequoia groves, located on the western slope of the central and southern Sierra Nevada mountains in California, USA, have been experiencing regeneration failure for more than a century due to the exclusion of wildfires. Giant sequoias are serotinous conifers and have evolved a strong relationship between high-severity fire and reproduction. While this relationship is widely recognized, only one previous peer-reviewed study has directly investigated giant sequoia reproduction and fire severity, and that study used different fires for each severity class. We conducted a study of giant sequoia reproduction and fire severity in a single fire, the KNP Complex fire of 2021, within the Redwood Mountain Grove in Sequoia and Kings Canyon National Park. We found that giant sequoia seedlings are more dominant relative to other conifer species and are growing faster in a large high-severity fire area than in adjacent low/moderate-severity areas. Distance to the nearest live sequoia seed source was not a significant factor in sequoia seedling density. Our results call into question the basis for widespread plans and projects designed to prevent high-severity fires and should reevaluate moving forward with proposed tree planting activities in high-severity fire areas within giant sequoia groves.
]]>Authors: Yauhen Baranyshyn Vyacheslav Kuzmitski Oleg Penyazkov Kirill Sevrouk
Induction and reaction times of hydrogen–air mixtures (ϕ = 0.5–2) have been measured behind reflected shock waves at temperatures of 1000–1600 K, pressures of 0.1, 0.3, 0.6 MPa in the domain of the extended second explosion limit. The measurements were performed in the shock tube with a completely transparent test section of 0.5 m long, which provides pressure, ion current, OH and high-speed chemiluminescence observations. The experimental induction time plots demonstrate a clear increasing of the global activation energy from high- to low temperature post-shock conditions. This trend is strongly pronounced at higher post-shock pressures. For a high-temperature range of T > 1200 K, induction time measurements show an activation energy for the global reaction rate of hydrogen oxidation of 64–83 kJ/mole. Detected reaction times exhibit a big scatter and a weak temperature dependence. The minimum reaction time value was nearly 2 µs. Obtained induction time data were compared with calculations carried out in accordance with the known kinetic mechanisms. For current and former shock-tube experiments within a pressure range of 0.1–2 MPa, critical temperatures required for strong (1000–1100 K), transient and weak auto-ignition modes behind reflected shock waves were identified by means of the pressure and ion-probe measurements in stoichiometric hydrogen-air mixture. The transfer from the strong volumetric self-ignition near the reflecting wall to the hot spot ignition (transient) was established and visualized below <1200 K with a post-shock temperature decreasing.
]]>Authors: Anastasia Moroshkina Alina Ponomareva Vladimir Mislavskii Evgeniy Sereshchenko Vladimir Gubernov Viatcheslav Bykov Sergey Minaev
In this work, the overall activation energy of the combustion of lean hydrogen–methane–air mixtures (equivalence ratio φ = 0.7−1.0 and hydrogen fraction in methane α=0, 2, 4) is experimentally determined using thin-filament pyrometry of flames stabilised on a flat porous burner under normal conditions (p=1 bar, T = 20 °C). The experimental data are compared with numerical calculations within the detailed reaction mechanism GRI3.0 and both approaches confirm the linear correlation between mass flow rate and inverse flame temperature predicted in the theory. An analysis of the numerical and experimental data shows that, in the limit of lean hydrogen–methane–air mixtures, the activation energy approaches a constant value, which is not sensitive to the addition of hydrogen to methane. The mass flow rate for a freely propagating flame and, thus, the laminar burning velocity, are measured for mixtures with different hydrogen contents. This mass flow rate, scaled over the characteristic temperature dependence of the laminar burning velocity for a one-step reaction mechanism, is found and it can also be used in order to estimate the parameters of the overall reaction mechanisms. Such reaction mechanisms will find implementation in the numerical simulation of practical combustion devices with complex flows and geometries.
]]>Authors: Brianna Baker Yvonne Dinh Iris R. Foxfoot Elena Ortiz Alison Sells Sarah E. Anderson
As climate change increases the frequency and severity of wildfires across the Western U.S., there is an urgent need for improved wildfire preparedness and responses. Socially marginalized communities are particularly vulnerable to wildfire effects because they disproportionately lack access to the resources necessary to prepare for and recover from wildfire and are frequently underrepresented in the wildfire planning process. As an exemplar of how to understand and improve preparedness in such communities, this research identified communities in Ventura County facing heightened marginalization and risk of wildfire using spatial analysis. Researchers then deployed a county-wide survey and held focus groups in two communities identified in the spatial analysis. Research revealed that non-English speakers, women, people of color, and newer residents in Ventura County are less prepared for wildfire than other groups. Based on these findings, this paper recommends an expansion of traditional risk mitigation programs, strengthened community engagement efforts, and strategies that increase community resources and leadership to decouple marginalization and wildfire vulnerability.
]]>Authors: Mário Rui Tiago Arruda António Renato A. Bicelli Fernando Branco
This paper presents a study based on new fireproof design guidelines for dwellings against the impact of wildfires. The main objective is to present the results from the surveys of the large wildfires of 2017 in Portugal, identifying vulnerabilities in dwellings that may result in spot ignitions when exposed to wildfires. Utilizing the information gathered from these surveys, it is possible to recommend fire resistance and reaction class requirements using European indoor fire standards and adapting them to suit wildfire conditions. The study focuses on classical dwellings predominantly located in high-risk fire zones within the wildland–urban interface. These assessments have the potential to generate new fireproof construction recommendations employing traditional materials commonly found in the European construction industry.
]]>Authors: Reham Shalaby Belinda Agyapong Gloria Obuobi-Donkor Raquel da Luz da Luz Dias Vincent I. O. Agyapong
Introduction: Wildfires impact large populations worldwide with increasing frequency and severity. In Canada, the fire season has affected more areas this year with potential implications for individuals’ well-being and quality of life (QoL). Objective: This study aimed to explore data related to the well-being and QoL of individuals living in areas impacted by wildfires in two Canadian provinces. Methodology: A cross-sectional survey was used to collect data from the residents in the two provinces who subscribed to the Text4Hope mental health support service. Descriptive and inferential statistics were applied using World Health Organization Well-Being Index (WHO-5). Results: Out of 1802 Text4Hope subscribers, 298 responded to the baseline surveys, yielding a response rate of (16.5%). The mean score of QoL was (40.8/100 ± 20.7). Most respondents were from Alberta (84.2%), 40 years old or below (28.3%), females (85.2%), Caucasian (83.5%), in a relationship (56.4%), employed (63.6%), received diagnoses of depression (56.6%), and anxiety (52.9%).The overall prevalence of low QoL was (67.3%; 95% CI: 61.2–73.1%) that was mostly reported among subscribers who were from Nova Scotia (70.5%), 40 years old or younger (71.2%), other gender (83.3%), Black/Hispanic and other ethnicity (85.7% each), having high-school or less education (70.3%), not in a relationship (74.1%), and unemployed (73.6%). In terms of clinical factors, low QoL was most prevalent among those who received the diagnoses of depression (74%) and anxiety (74.3%), and those who have been receiving antidepressants (71.8%) or benzodiazepines (93.3%). Regarding wildfire-related factors, the highest prevalence of low QoL was reported among those living in a region that has recently been impacted by the wildfires (74.7%) and those who have been less frequently watching television images about the devastation caused by the recent wildfires (72.6%). The multivariate logistic regression analysis model predicting the low QoL including the various variables was statistically significant; Χ2 (df = 19; n = 254) = 31.69, p = 0.03. It was found that living in a region impacted by wildfires (37.9%) was the only significant predictor of low QoL (adjusted OR: 1.96; 95% CI: 1.05–3.65). Conclusions: The impact of wildfire on the QoL and well-being among people living in impacted regions is significant. It is empirical for the health authorities to support those who are disadvantaged by wildfire via running of screening programs to early identify mental health symptoms and addressing the living conditions of the survivors, along with the provision of innovative means of mental health support. This necessitates enhanced planning of the governments and health authorities to overcome such adverse psychological consequences of these events.
]]>Authors: Yujie Lin Anfeng Yu Yi Liu Xiaolong Liu Yang Zhang Chen Kuang Yuan Lu Wenyi Dang
The accurate determination of the potential impact radius is crucial for the design and risk assessment of hydrogen pipelines. The existing methodologies employ a single point source model to estimate radiation and the potential impact radius. However, these approaches overlook the jet fire shape resulting from high-pressure leaks, leading to discrepancies between the calculated values and real-world incidents. This study proposes models that account for both the mass release rate, while considering the pressure drop during hydrogen pipeline leakage, and the radiation, while incorporating the flame shape. The analysis encompasses 60 cases that are representative of hydrogen pipeline scenarios. A simplified model for the potential impact radius is subsequently correlated, and its validity is confirmed through comparison with actual cases. The proposed model for the potential impact radius of hydrogen pipelines serves as a valuable reference for the enhancement of the precision of hydrogen pipeline design and risk assessment.
]]>Authors: Keyu Lin Peili Zhang Jimao Duan Shuo Xiang Ting’ao Shen Chaoshan Yang
The overpressure characteristics of gasoline explosions in multi-branch pipes are caused by various factors, with flame velocity as a particularly significant determinant. Overlooking the impact of turbulent flow in the branch pipes can induce a significant discrepancy in the outcome when using laminar flame velocity to determine the maximum rate of overpressure rise. To quantify the impact of turbulent flame velocity on the rate of overpressure rise in the gasoline explosions within branch pipes, the laminar flame velocity was replaced with its turbulent counterpart. Additionally, modifications to the formula for calculating the maximum overpressure rise rate were implemented. Then, experimental data of peak explosion overpressure and overpressure rise rate under different numbers of branches were obtained. Finally, the empirical data were inputted into the modified formula to determine the maximum rate of overpressure rise, thus enabling the calculation of the turbulent flame velocity across varying numbers of branches. The findings reveal a positive correlation between the number of branches and the turbulent flame velocity during tube explosions. When the number of branch pipes increased from 0 to 4, the turbulent flame velocity was found to range from 8.29 to 13.39 m/s. The increase in the number of branches did not consistently enhance the turbulent flame velocity. As the number of branches increased from zero to three, the turbulent flame velocity rose accordingly. Differently, as the number of branches exceeds three, the turbulent flame velocity exhibits fluctuations and peaks at a level approximately 1.8 times higher. The research method of this paper can provide a reference for estimating the turbulent flame velocity in the combustion process of flammable gas explosions in multi-branch tunnels.
]]>Authors: Dimitrios Kalfas Stavros Kalogiannidis Fotios Chatzitheodoridis Nikolaos Margaritis
In forested ecosystems all over the world, usually, fire is the main disturbance, and due to global climate change, its effects are worsening in many areas. Although fire impacts have been studied for many years, integrative analyses of their effects on various ecosystem services (ES) at different scales are uncommon. This study tries to assess the ecological role of fire in a changing environment, focusing on a Mediterranean country. Data were collected by the use of an online questionnaire in Greece, where the summer fires in the last decades have had significant impacts on the environment and the economy and, in many cases, there were many human and animal victims from them. The sample size of the survey was 384 workers in the primary production sector from all over the country. The study showed that fire has several effects on animal husbandry, the quality of soil nutrients and fertility, the overall vegetation cover, and on general biodiversity. It seems that the degree to which fire has an effect on ecosystem components depends on the intensity, frequency, and length of the fires. Additionally, the frequency, intensity, and length of fire affect the impacts of fire on herbaceous plant, woody vegetation, soil physical qualities, and on the different animals’ habitats.
]]>Authors: Arun Teja Doppalapudi Abul Kalam Azad
In diesel engines, emission formation inside the combustion chamber is a complex phenomenon. The combustion events inside the chamber occur in microseconds, affecting the overall engine performance and emissions characteristics. This study opted for using computational fluid dynamics (CFD) to investigate the combustion patterns and how these events affect nitrogen oxide (NOx) emissions. In this study, a diesel engine model with a flat combustion chamber (FCC) was developed for the simulation. The simulation result of the heat release rate (HRR) and cylinder pressure was validated with the experimental test data (the engine test was conducted at 1500 rpm at full load conditions). The validated model and its respective boundary conditions were used to investigate the effect of modified combustion chamber profiles on NOx emissions. Modified chambers, such as a bathtub combustion chamber (BTCC) and a shallow depth chamber (SCC), were developed, and their combustion events were analysed with respect to the FCC. This study revealed that combustion events such as fuel distribution, unburnt mass fractions, temperature and turbulent zones directly impact NOx emissions. The modified chambers controlled the spread of combustion and provided better fuel distribution, improving engine performance and combustion rates. The SCC (63.2 bar) showed peak pressure rates compared to the FCC (63.02 bar) and BTCC (62.72 bar). This study concluded that the SCC showed better results than other chambers. This study further recommends conducting lean fuel mixture combustion with chamber modifications and optimising fuel spray, such as by adjusting the fuel injection profile, spray angle and injection timing, which has a better tendency to create complete combustion.
]]>Authors: Zhenguo Yan Zhixin Qin Jingdao Fan Yuxin Huang Yanping Wang Jinlong Zhang Longcheng Zhang Yuqi Cao
Efficient evacuation route planning during underground coal mine fires is essential to minimize casualties. This study addresses current shortcomings by proposing a real-time method that integrates a multifactor coupling analysis and the optimized multilayer perceptron regressor-shortest path faster algorithm (MSPFA). This research aims to enhance evacuation route planning by overcoming factors such as inadequate consideration, low accuracy, and information lag in existing methods. This study improves the shortest path faster algorithm (SPFA) for dynamic route planning, mitigates the impact of fixed walking speed parameters using the particle swarm algorithm, and selects the optimal model (MLPRegressor) through the Bootstrap algorithm for estimating personnel walking speeds. Validated through smoke-spread experiments, the MSPFA algorithm dynamically adjusts evacuation routes, preventing toxic passages. Visualization via drawing interchange format (DXF) successfully enhances route comprehension. The MSPFA algorithm outperforms the Dijkstra algorithm with a runtime of 78.5 msand a personnel evacuation time of 3344.74 s. This research establishes a theoretical foundation for intelligent evacuation decision making in underground fire disasters. By introducing the MSPFA algorithm, it provides crucial technical support, significantly reducing the risk of casualties during emergencies.
]]>Authors: Parham Pahlavani Amin Raei Behnaz Bigdeli Omid Ghorbanzadeh
Identifying the underlying factors derived from geospatial and remote sensing data that contribute to forest fires is of paramount importance. It aids experts in pinpointing areas and periods most susceptible to these incidents. In this study, we employ the geographically and temporally weighted regression (GTWR) method in conjunction with a refined continuous invasive weed optimization (CIWO) algorithm to assess certain spatially relevant drivers of forest fires, encompassing both biophysical and anthropogenic influences. Our proposed approach demonstrates theoretical utility in addressing the spatial regression problem by meticulously accounting for the autocorrelation and non-stationarity inherent in spatial data. We leverage tricube and Gaussian kernels to weight the GTWR for two distinct temporal datasets, yielding coefficients of determination (R2) amounting to 0.99 and 0.97, respectively. In contrast, traditional geographically weighted regression (GWR) using the tricube kernel achieved R2 values of 0.87 and 0.88, while the Gaussian kernel yielded R2 values of 0.8138 and 0.82 for the same datasets. This investigation underscores the substantial impact of both biophysical and anthropogenic factors on forest fires within the study areas.
]]>Authors: Devan Allen McGranahan Carissa L. Wonkka
This study describes spatial and temporal patterns in fire across the US Western Great Plains over the last 40 years. Although pyrogeographic studies have explored the nexus of fire patterns in relation to the bio-physical environment and socio-ecological trends, most of this research has focused on forested ecosystems and regions long known for conflict between wildfires and human development, especially at the wildland–urban interface. But evidence suggests large wildfire activity is increasing in the US Great Plains, and the Western Great Plains—a Land Resource Region comprised of four ecoregions, Northwestern Plains, High Plains, Nebraska Sandhills, and Southwestern Tablelands—not only contains some of the largest areas of rangeland in the US but also the highest concentration of public land in the Great Plains. As such, the Western Great Plains provides an opportunity to explore fire activity in primarily rural landscapes with a combination of public and private ownership, all dominated by rangeland vegetation. We combined several publicly-available datasets containing fire records between 1992 and 2020 to create two databases, one with georeferenced point data on 60,575 wildfire events in the region, and another with georeferenced perimeter data for 2665 fires. Ignition by humans was the dominant cause of fires. No ecoregion showed a statistically significant trend towards either increasing or decreasing the annual burned area. The Northwestern Plains had the most burned area and the greatest number of incidents—consistently around or above 1000 incidents per year since 1992—with the majority in July. The High Plains showed the greatest increase in annual fire incidence, never reaching more than 200–300 per year 1992–2009, and averaging above 1000 incidents per year since 2010. Few long-term trends in human population, weather, or fuel metrics appear strongly associated with fire patterns in any ecoregion, although the years 2006, 2012, and 2017 stood out for their levels of fire activity, and these years often frequently logged extreme values in wildland fuel metrics. These relationships merit much closer examination in the Western Great Plains, because like other rangeland-dominated landscapes, the fine fuels that comprise these wildland fuelbeds are much more responsive to fine-scale changes in moisture conditions. Rural Western Great Plains landscapes are a mosaic of public and private land ownership, and an increasing impact of wildfires on public grazing lands—which are often situated within other jurisdictions or ownership—will likely have an impact on rural livelihoods.
]]>Authors: Irina Turku Anti Rohumaa Tapio Tirri Lasse Pulkkinen
The enormous potential of renewable bioresources is expected to play a key role in the development of the EU’s sustainable circular economy. In this context, inexhaustible, biodegradable, non-toxic, and carbon-neutral forest-origin resources are very attractive for the development of novel sustainable products. The main structural component of wood is cellulose, which, in turn, is the feedstock of nanocellulose, one of the most explored nanomaterials. Different applications of nanocellulose have been proposed, including packaging, functional coatings, insulating materials, nanocomposites and nanohybrids manufacturing, among others. However, the intrinsic flammability of nanocellulose restricts its use in some areas where fire risk is a concern. This paper overviews the most recent studies of the fire resistance of nanocellulose-based materials, focusing on thin films, coatings, and aerogels. Along with effectiveness, increased attention to sustainable approaches is considered in developing novel fire-resistant coatings. The great potential of bio-based fire-resistant materials, combined with conventional non-halogenated fire retardants (FRs), has been established. The formulation methods, types of FRs and their action modes, and methods used for analysing fireproof are discussed in the frame of this overview.
]]>Authors: Tomáš Kytka Miroslav Gašparík David Novák Lukáš Sahula Elham Karami Sumanta Das
This study delved into the combustion properties of combined glulam bonded using polyurethane (PUR) and resorcinol-phenol-formaldehyde (RPF) adhesives. The experiment involved three distinct wood species, namely, spruce, alder, and beech, which were combined in homogeneous, non-homogeneous symmetrical, and non-homogeneous asymmetrical arrangements. These species were selected to represent a spectrum, namely, softwood (spruce), low-density hardwood (alder), and high-density hardwood (beech). The varying combinations of wood species illustrate potential compositions within structural elements, aiming to optimize mechanical bending resistance. Various parameters were measured during combustion, namely, the heat release rate (HRR), peak heat release rate (pHRR), mass loss rate (MLR), average rate of heat emission (ARHE), peak average rate of heat emission (MARHE), time to ignition (TTI), and effective heat of combustion (EHC). The findings indicate that incorporating beech wood into the composite glulam resulted in an increase in heat release, significantly altering the burning characteristics, which was particularly evident at the second peak. Conversely, the use of spruce wood exhibited the lowest heat release rate. Alder wood, when subjected to heat flux at the glued joint, displayed the highest heat emission, aligning with the results for EHC and MARHE. This observation suggests that wood species prone to early thermal decomposition emit more heat within a shorter duration. The time to ignition (TTI) was consistent, occurring between the first and second minute across all tested wood species and combinations. Notably, when subjected to heat flux, the glulam samples bonded with PUR adhesive experienced complete delamination of the initial two glued joints, whereas those bonded with RPF adhesive exhibited only partial delamination.
]]>Authors: Weiheng Li Xuan Wang Polly Yuexin Cen Qian Chen Ivan Miguel De Cachinho Cordeiro Lingcheng Kong Peng Lin Ao Li
Given the growing demand for increased energy capacity and power density in battery systems, ensuring thermal safety in lithium-ion batteries has become a significant challenge for the coming decade. Effective thermal management plays a crucial role in battery design optimization. Air-cooling temperatures in vehicles often vary from ambient due to internal ventilation, with external air potentially overheating due to vehicle malfunctions. This article highlights the efficiency of lateral side air cooling in battery packs, suggesting a need for further exploration beyond traditional front side methods. In this study, we examine the impact of three different temperature levels and two distinct air-cooling directions on the performance of an air-cooling system. Our results reveal that the air-cooling direction has a more pronounced influence compared with the air-cooling temperature. By employing an optimal air-cooling direction and ambient air-cooling temperature, it is possible to achieve a temperature reduction of approximately 5 K in the battery, which otherwise requires a 10 K decrease in the air-cooling temperature to achieve a similar effect. Therefore, we propose an empirical formula for air-cooling efficiency under various conditions, aiming to provide valuable insights into the factors affecting air-cooling systems for industrial applications toward enhancing the fire safety of battery energy storage systems.
]]>Authors: Minjie Liu Yangyang Yu Junhong Zhang Dan Wang Xueling Zhang Meng Yan
Intense burning phenomena (fire disasters) need to be prevented in the combustible gas utilization and transportation processes to ensure industrial safety. Nonmetallic spherical spacers (NSSs) have been investigated and applied in lots of explosive atmospheres to prevent explosion execution in a confined space. In this work, a novel fuzzy-based analytic hierarchy process (FAHP) is developed to take into account the uncertainty in decision-making and effectively solve the problem of factor weight allocation in multi-objective optimization. Optimal Latin Hypercube Design (Opt LHD), Chebyshev Orthogonal Polynomials (COP), and Adaptive Simulated Annealing (ASA) were combined. A multi-objective optimization method is proposed for the structural parameter optimization problem on NSSs in order to achieve conflicting multiple-objective optimization of low displacement rate and minimal deformation. That is to say, the small volume (low displacement rate) and high explosion-suppression performance (minimal deformation) of NSSs were optimized simultaneously. The results show that, compared with the original NSS model’s deformation (2.85 mm) and displacement rate (3.63%), the optimized NSSs with weight allocation had optimized the deformation by 12.98% and displacement rate by 6.1%. Compared with the optimized design model of NSSs without weight allocation with a deformation of 2.75 mm and a displacement rate of 3.48%, the deformation has been optimized by 9.82%, and the displacement rate has been optimized by 2.0%. It was verified that the proposed method is effective. At the same time, it was verified that the suppression effect of NSSs can be enhanced by changing the shape of the NSS spacer reasonably by experimental verification.
]]>Authors: Azra Israr Shujaul Mulk Khan Abdullah Abdullah Ujala Ejaz Sadia Jehangir Zeeshan Ahmad Abeer Hashem Graciela Dolores Avila-Quezada Elsayed Fathi Abd_Allah
Since the Palaeozoic era, fire as a potent driver of environmental changes, has dramatically shaped the terrestrial ecosystems. Fire affects soil structure and composition, which in turn affects the floral diversity of an area. This research work aims to examine the impact of fire on vegetation and the physicochemical nature of the soil in fire-affected and fire-free sites across the Mahaban and the surrounding forests, Swabi District, Khyber Pakhtunkhwa, Pakistan. Quadrat quantitative ecological techniques were used for vegetation sampling in fire-free and fire-affected sites. In total, 219 plant species belonging to 173 genera and 70 families were recorded. Among the 219 plant species, 173 species were recorded from fire-free sites and the remaining 122 species were from fire-affected sites. The incidence of fire results in elevated organic matter, nitrogen, phosphorus, and lower calcium carbonate concentrations in the soil. The greatest species richness and evenness were observed across the fire-free sites. Our study concludes that the influence of edaphic and topographic factors on species richness varies between fire-affected and fire-free sites. Fire has significantly altered the nutrient availability in the studied region, and this is confirmed by soil analysis and vegetation research. It is suggested that further research in the field of fire ecology can produce valuable insights.
]]>Authors: Tom J. Schiks B. Mike Wotton David L. Martell
Spatial and temporal estimates of burned areas are often used to model greenhouse gas and air pollutant emissions from fire events that occur in a region of interest and over specified time frames. However, fire behaviour, fuel consumption, fire severity, and ecological effects vary over both time and space when a fire grows across varying fuels and topography under different environmental conditions. We developed a method for estimating the progression of individual wildfires (i.e., day-of-burn) employing ordinary kriging of a combination of different satellite-based active fire detection data sources. We compared kriging results obtained using active fire detection products from the Moderate Resolution Imaging Spectroradiometer (MODIS), the Visible Infrared Imaging Radiometer Suite (VIIRS), and combined MODIS and VIIRS data to study how inferences about a wildfire’s evolution vary among data sources. A quasi-validation procedure using combined MODIS and VIIRS active fire detection products that we applied to an independent data set of 37 wildfires that occurred in the boreal forest region of the province of Ontario, Canada, resulted in nearly half of each fire’s burned area being accurately estimated to within one day of when it actually burned. Our results demonstrate the strengths and limitations of this geospatial interpolation approach to mapping the progression of individual wildfires in the boreal forest region of Canada. Our study findings highlight the need for future validations to account for the presence of spatial autocorrelation, a pervasive issue in ecology that is often neglected in day-of-burn analyses.
]]>Authors: Wei Liu Xinrong Xu Jiaqing Zhang Yu Zhong Xiang Li Yanming Ding
Fireproof sealing technology is widely used in industrial, commercial, and other public buildings, so the performance of fireproof sealing materials in high temperatures or fire environments must be taken into account as an important factor. Fireproof sealant is considered to be a highly effective adhesive for sealing and fireproofing purposes. To explore its thermal decomposition mechanism and estimate its pyrolysis behaviors, a series of thermogravimetric experiments from 10 K/min to 60 K/min coupled with Fourier transform infrared spectroscopy analysis technology were performed. The results indicated that the thermal decomposition of the fireproof sealant could be divided into three reactions: the degradation of ammonium polyphosphate, melamine, and acrylic acid. In addition, the pyrolysis behavior of the fireproof sealant was compared under two kinds of atmosphere (nitrogen and air). Furthermore, the initial kinetic parameters in the nitrogen atmosphere were calculated based on model-free methods including the Friedman, KAS, and Starink methods. The average activation energy of three reactions obtained by the three methods was 108.32 kJ/mol, 200.46 kJ/mol, and 177.10 kJ/mol, respectively, while these obtained parameters were hard to regenerate, the thermogravimetric curves were accurately based on the established pyrolysis reaction scheme, with the existence of clear deviations. Therefore, a global heuristic optimization algorithm, Shuffled Complex Evolution (SCE), was selected to optimize 14 parameters (including activation energies and the pre-exponential factors) and the optimized pyrolysis results agreed well with the experimental data, even at the extra heating rate, with the correlation coefficient for the mass loss and mass loss rate being reaching up to 0.9943 and 0.9019, respectively. The study indicated that the SCE algorithm showed an appropriate potential to estimate the pyrolysis behavior of an unknown thermogravimetric experiment group.
]]>Authors: Xinsheng Jiang Dongliang Zhou Peili Zhang Yunxiong Cai Ri Chen Donghai He Xizhuo Qin Keyu Lin Sai Wang
Horizontal oil tanks, like other oil storage containers, carry the risk of explosion when gasoline–air mixtures are ignited. With the widespread application of horizontal oil tanks in the petrochemical industry, attention to safety risks is increasing. However, currently, a limited amount of experimental research on such tanks exists. To explore the characteristics of gasoline–air mixtures combustion within the confined space of horizontal oil tanks, this study constructed a medium-scale simulated horizontal oil tank (L/D = 3, V = 1.0 m3) platform. By investigating the effects of different initial gasoline–air mixture volume fractions and ignition positions on explosion overpressure characteristic parameters, an analysis of the combustion characteristics was conducted. It was found that the most dangerous gasoline–air mixture volume fraction is 1.9% when ignited at the top position and 2.1% at the middle. It was also observed that the ignition position has a significant impact on the variation in explosion overpressure characteristic parameters, with ignition at the middle position resulting having a greater explosive force compared to ignition at the top position. Furthermore, using ignition at the middle position as an example, a study was conducted on the flame morphology characteristics at initial gasoline–air mixture volume fractions of 1.1%, 1.9%, and 2.7%. The conclusions from this research deepen our understanding of the explosion characteristics of different containers, providing theoretical insights for the safe storage and transportation of oil materials in horizontal oil tanks.
]]>Authors: Zhixin Tang Tianwei Zhang Lizhi Wu Shaoyun Ren Shaoguang Cai
Fire risk assessment is a crucial step in effective fire control, playing an important role in reducing fire losses. It has remained a significant topic in the field of fire safety. To explore the research hotspots and frontier trends in fire risk assessment and to understand its macroscopic development trajectory, a sample of 1596 papers from 1976 to 2023, extracted from the Web of Science (WoS) database, was utilized to create a knowledge map. The study employed bibliometric methods, visual analysis, and content analysis to uncover the research pulse and hotspots in the field, offering insights into its future development. The findings indicate that research in fire risk assessment has demonstrated continuous growth over the past 50 years. China and the United States are the dominant research forces in the field, while India and Australia show potential as new drivers for development. Expert groups have formed in this field, with intra-institutional cooperation being the primary focus, while inter-institutional collaboration remains limited. The research outcomes exhibit multidisciplinary crossovers, exerting a significant impact on various disciplinary domains. The research hotspots primarily revolve around investigating fire and explosion accidents, assessing the vulnerability of fire subjects, and identifying potential fire hazards. The application of artificial intelligence technology is identified as a pivotal tool for future development. However, to achieve substantial progress, it is important to enhance the importance accorded to fire risk assessment, foster multinational and cross-institutional cooperation, and prioritize research innovation.
]]>Authors: James H. Speer Darrin L. Rubino Joseph R. Robb
Fire is a disturbance that serves to maintain the diverse mosaic of vegetation in the Eastern Deciduous Forest. However, our ability to reconstruct fire occurrence from hardwood tree scars still lags far behind our expertise in reconstructing fire history from conifers in the western United States. This study examines the fidelity of fire scaring in multiple tree species in the Big Oaks National Wildlife Refuge in Indiana, which is located in the central hardwood region of the Eastern Deciduous Forest. All 15 species, except for red oak, showed evidence of past fires, and most samples recorded multiple fire events. No fire scars were recorded in the latewood of the samples. Most of the fires scars occurred in the earlywood (May) suggesting the dormant season fires are likely associated with fires in March to April before the growing season begins. No synchronous fires were recorded across all sites, but fires occurred in 1981, 1982, 1984, 1985, and 1988 across multiple sites. This suggests that these were larger spreading fires. Establishment pulses were documented in association with fire events in 1981, 1984, and 1995, suggesting that fire may benefit the establishment or root sprouting of some hardwood species. Fourteen of the fifteen species that we sampled preserved fire scars, suggesting that the diverse suite of species in the Eastern Deciduous Forest is a viable sampling pool for examining fire history across this forest type.
]]>Authors: Wei Wang Min-Chun Liao Hsy-Yu Tzeng
Fire is one of the principal factors influencing subalpine ecosystem succession. Species numbers and plant compositions are used to determine postfire disturbance, vegetation, structural change, and succession. Ecologists also integrate species diversity and mathematical models to enable researchers to obtain increasingly detailed insights into habitats during post-disturbance restoration processes. This study employed five species-abundance models, namely the niche preemption model, the broken-stick model, the log-normal model, the Zipf model, and the Zipf–Mandelbrot model, to perform fitting analysis on the abundance data of postfire species coverage in shrub grasslands near 369 Hut at Xue Mountain in Shei-Pa National Park, Taiwan. We performed the logarithmic transformation on plant-coverage areas for each period of postfire shrub-grassland succession, and then, based on histograms drawn for species–coverage distribution modes, the test results consistently showed normal distributions (p < 0.05). Species-coverage histograms measuring various periods showed that there were comparatively higher numbers of common species during postfire succession and that the numbers of rare species progressively increased. The fitting results of the five species-abundance models showed that although the most suitable abundance models for each period of postfire succession varied, the majority of these periods demonstrated decent fitting with respect to the Zipf–Mandelbrot model. These findings showed that fuel consumption provided nutrients in a manner that facilitated postfire regeneration. Moreover, dominant species, such as Yushania niitakayamensis, and Miscanthus transmorrisonensis, did not fully occupy growing spaces and resource availabilities; consequently, seeded species were able to grow.
]]>Authors: Anna Dosiou Ioannis Athinelis Efstratios Katris Maria Vassalou Alexandros Kyrkos Pavlos Krassakis Issaak Parcharidis
In 2023, Greece faced its worst wildfire season, with nine major fires causing unprecedented environmental damage of 1470.31 km2. This article uses Copernicus Land Monitoring Service and Sentinel-2 data, employing advanced remote sensing and GIS techniques to analyze spatial dynamics, map burn severity, assess fire extent, and highlight pre-fire tree density and land cover. The study focuses on the catastrophic fire in the Evros region and the damage to the National Forest Park of Dadia–Lefkimmi–Soufli. It also analyzes significant fires in Rhodes, Attica, Thessaly, Evia, Corfu, and Magnesia, emphasizing the compounded challenges posed by terrain, climate, and human factors in those areas. Additionally, the climate data for each affected area were compared with the weather conditions prevailing at the time of the fires. Copernicus Land Cover and Tree Density data are integrated to aid future management, assessment, and restoration. The analysis of maps and fire statistics underscores a notable pattern: areas with higher pre-fire tree density experienced correspondingly higher burn severity. This research underscores the crucial role of such data in assessing wildfire impact. In addition, compared with Copernicus Emergency Management Service, the burned area maps validate the accuracy and reliability of the utilized satellite data. The total burned area was assessed with a high accuracy rate of 96.28%.
]]>Authors: Rentao Guo Jilin Yan He Zheng Bo Wu
The quantitative assessment of forest fire severity is significant for understanding the changes in ecological processes caused by fire disturbances. As a novel spectral index derived from the multi-objective optimization algorithm, the Analytic Burned Area Index (ABAI) was originally designed for mapping burned areas. However, the performance of the ABAI in detecting forest fire severity has not been addressed. To fill this gap, this study utilizes a ground-based dataset of fire severity (the composite burn index, CBI) to validate the effectiveness of the ABAI in detecting fire severity. First, the effectiveness of the ABAI regarding forest fire severity was validated using uni-temporal images from Sentinel-2 and Landsat 8 OLI. Second, fire severity accuracy derived from the ABAI with bi-temporal images from both sensors was evaluated. Finally, the performance of the ABAI was tested with different sensors and compared with representative spectral indices. The results show that (1) the ABAI demonstrates significant advantages in terms of accuracy and stability in assessing fire severity, particularly in areas with large numbers of terrain shadows and severe burn regions; (2) the ABAI also shows great advantages in assessing regional forest fire severity when using only uni-temporal remotely sensed data, and it performed almost as well as the dNBR in bi-temporal images. (3) The ABAI outperforms commonly used indices with both Sentinel-2 and Landsat 8 data, indicating that the ABAI is normally more generalizable and powerful and provides an optional spectral index for fire severity evaluation.
]]>Authors: Liyue Gong Yifan Peng Jun Xu Wanli Li Tianyao Jia Junqiu Ma Haihang Li
Compared to longitudinal ventilation, there are few studies on fire source development under semi-transverse ventilation. This work studied the influence of semi-transverse ventilation on the combustion characteristics of fire sources in a scaled tunnel. The burning rate and heat transfer feedback during pool fire combustion were revealed under different longitudinal and transverse ventilation velocities. The results showed that transverse ventilation had little influence on combustion characteristics, and the burning rate was more obviously affected by longitudinal ventilation. The heat convection feedback increased monotonically with the increase of the longitudinal ventilation, which led to the increase of the total heat feedback on the fuel. The heat radiation feedback changed little, and the heat conduction feedback decreased monotonically with the increase of the longitudinal ventilation velocity. By aid of a Fire Dynamics Simulator, it was found that the flame tilted downstream and was in the flow line of the lower cold air flow coming from upstream and the upper hot smoke flow outgoing in the downstream direction. The transverse ventilation of 2 m/s or lower hardly affected the combustion field of the fire source. Therefore, semi-transverse ventilation is preferable to longitudinal ventilation from the point of view of limiting fire expansion.
]]>Authors: Sanjay Kumar Khattri Torgrim Log Arjen Kraaijeveld
Time to flashover is an important fire safety parameter. The present study investigated the effects of fuel moisture content on the time to flashover, crucial in fire safety analysis. Experiments and simulations of an ISO 9750-1 room model at 1/8 scale were performed by varying the wooden compartment boundaries’ moisture content between 5% and 16%. The results showed a linear increase in time to flashover with fuel moisture content. An empirical model to predict the time to flashover according to the moisture content was developed. The experiments showed that increasing the moisture from 6.5% to 14.4% prolonged the flashover time from 4.6 min to 8.75 min. These experimental results are consistent with computational fluid dynamics (CFD) modeling using Fire Dynamics Simulator (FDS), which also depicts a corresponding increase in the time to flashover. These findings demonstrate the critical role of fuel moisture content in fire safety analysis. The results suggest that a 1/8-scale model can be utilized for cost-effective and easily manageable education and demonstration purposes. This includes helping fire brigades and fire academy students comprehend the significance of fuel moisture content in compartment fire development. Since the FDS modeling is not restricted to a 1/8 scale, the presented results are promising regarding CFD modeling of time to flashover in full-scale compartments.
]]>Authors: Yan Zhang Guru Wang Xuehui Wang Xin Kong Hongchen Jia Jinlong Zhao
High-rise buildings (HRBs) are prone to high fire hazards due to their high occupant density, limited evacuation routes, and high fire load. The indicator system method, as a systematic evaluation method, is widely applied to assess HRB fire risk. However, the method is subjective because the determination of the indicator weights mainly relies on expert experience. In order to reduce the subjectivity of the indicator system method in assessing the fire risk of HRBs, this study proposes a new assessment method by combining the spatial Markov chain model and the indicator system method. In this new method, fire occurrence probability is calculated by the spatial Markov chain model using historical HRB fire accident data. An indicator system is built to characterize the fire consequence by the structure entropy weight method. Subsequently, HRBs in Beijing are used as a case to illustrate the practicality of this approach. Firstly, the spatial Markov chain model is trained and validated using the chi-square goodness-of-fit test based on fire accident data from 2018 to 2023 in Beijing. It was found that the best performance was achieved with the monthly period and the four-state. Then, the distribution of regional fire occurrence probability in April was predicted based on fire accident data in March 2023 in Beijing. It showed that areas with higher fire occurrence probability are mainly located in the central region, especially in the I District. Then, the indicator system was used to evaluate the HRB fire consequence in the I District. The assessment results showed that the areas with more severe fire consequences are mainly located in the II and IV Districts, due to the poor performance of the fire system or the absence of fire protection systems. Coupling the fire occurrence probability and its consequences shows that HRBs with higher fire risk are mainly located in area II and should be carefully supervised for fire management. This developed method can provide some insights into the fire safety management of HRBs and the layout of the fire stations.
]]>Authors: Kyuwon Han Soocheol Kim Hoesung Yang Kwangsoo Cho Kangbok Lee
Smoke detectors are the most widely used fire detectors due to their high sensitivity. However, they have persistently faced issues with false alarms, known as nuisance alarms, as they cannot distinguish smoke particles, and their responsiveness varies depending on the particle size and concentration. Although technologies for distinguishing smoke particles have shown promising results, the hardware limitations of smoke detectors necessitate an intelligent approach to analyze scattering signals of various wavelengths and their temporal changes. In this paper, we propose a pipeline that can distinguish smoke particles based on scattering signals of various wavelengths as input. In the data extraction phase, we propose methods for extracting datasets from time series data. We propose a method that combines traditional approaches, early detection methods, and a Dynamic Time Warping technique that utilizes only the shape of the signal without preprocessing. In the learning model and classification phase, we present a method to select and compare various architectures and hyperparameters to create a model that achieves the best classification performance for time series data. We create datasets for six different targets in our presented sensor and smoke particle test environment and train classification models. Through performance comparisons, we identify architecture and parameter combinations that achieve up to 98.7% accuracy. Ablation studies under various conditions demonstrate the validity of the chosen architecture and the potential of other models.
]]>Authors: Topendra Oli Dongsoo Ha Taejin Jang Cheolwoo Park Gihyun Kim Seungwon Kim
The development and importance of tunnels are increasing worldwide, and countries like Korea, where about 70% of the total land is covered with mountain regions, need more tunnel constructions to connect different routes of roads for safe and efficient transport. This study applied fire to the 200 mm × 200 mm × 200 mm concrete specimens, similar to the Rijkswaterstaat (RWS) fire, through an electric furnace. Thermocouples were placed inside the specimens to analyze the temperature during the occurrence of fire. Experimental and simulation thermal analysis during the occurrence of fire was analyzed. The experimental temperature at different depths agreed with the simulation results. Different international fire curves were applied to study the temperature inside the concrete through simulation by LS-DYNA. Concrete with different thicknesses of fireproof board was analyzed through simulation, and using fireproof board reduces the inside temperature during fire occurrence. Among the studied international fire curves, modified hydrocarbon fire curves had a high-temperature effect on concrete.
]]>Authors: Yanzhi Li Guohui Li Kaifeng Wang Zumin Wang Yanqiu Chen
Forest fire risk prediction is essential for building a forest fire defense system. Ensemble learning methods can avoid the problem of difficult model selection for disaster susceptibility prediction and can significantly improve modeling accuracy. This study introduces a stacking ensemble learning model for predicting forest fire risks in Yunnan Province by integrating various data types, such as meteorological, topographic, vegetation, and human activity factors. A total of 70,274 fire points and an equal number of randomly selected nonfire points were used to develop the model, with 70% of the data allocated for training and the remaining 30% for testing. The stacking model combined four diverse machine learning methods: random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), and multilayer perceptron (MLP). We evaluated the model’s predictive performance using metrics like accuracy, area under the characteristic curve (AUC), and fire density (FD). The results demonstrated that the stacking fusion model exhibited remarkable accuracy with an AUC of 0.970 on the test set, significantly surpassing the performance of individual machine learning models, which had AUC values ranging from 0.935 to 0.953. Furthermore, the stacking fusion model effectively captured the maximum fire density in extremely high susceptibility areas, demonstrating enhanced generalization capabilities.
]]>Authors: Rajeendra Godakandage Pasindu Weerasinghe Kumari Gamage Hani Adnan Kate Nguyen
Fire spread scenarios associated with concealed cavity spaces have been relatively less discussed. The variation in studies with respect to geometry, influential parameters, and protection strategies has been an obstacle to deriving more generalized solutions in terms of cavity fire in buildings. A systematic literature review was conducted following the PRISMA method to identify the conclusive fire behaviour, safety risks, and protection strategies to enable future researchers to address cavity fire scenarios effectively, avoiding catastrophic disasters. This study identified that relative to open-fire scenarios, cavity fires could result in up to 10 times higher flame spread, up to 14 times higher heat exposure, and temperature conditions 13 times higher. Increased toxicity and smoke velocity are also found with cavity fires. Fire protection strategies and their efficiency were identified for a range of cavity geometries. Altogether, cavity spaces, especially narrow ones, cannot be neglected during fire safety, and proper risk identification is required to ensure the safety of the buildings and the occupants in a fire scenario.
]]>Authors: Daniel José Vega-Nieva María Guadalupe Nava-Miranda Jaime Briseño-Reyes Pablito Marcelo López-Serrano José Javier Corral-Rivas María Isabel Cruz-López Martin Cuahutle Rainer Ressl Ernesto Alvarado-Celestino Robert E. Burgan
The knowledge of the effects of fuel dryness on fire occurrence is critical for sound forest fire management planning, particularly in a changing climate. This study aimed to analyze the monthly distributions of MODIS active fire (AF) detections and their relationships with a fuel dryness index (FDI) based on satellite-derived weather and vegetation greenness. Monthly AF distributions showed unimodal distributions against FDI, which were described using generalized Weibull equations, fitting a total of 19 vegetation types and ecoregions analyzed in Mexico. Monthly peaks of fire activity occurred at lower FDI values (wetter fuels) in more hygrophytic ecosystems and ecoregions, such as wet tropical forests, compared to higher fire activity in higher FDI values (drier fuels) for the more arid ecosystems, such as desert shrublands. In addition, the range of fuel dryness at which most monthly fire activity occurred was wider for wetter vegetation types and regions compared to a narrower range of fuel dryness for higher monthly fire occurrence in the more arid vegetation types and ecoregions. The results from the current study contribute towards improving our understanding of the relationships between fuel dryness and fire occurrence in a variety of vegetation types and regions in Mexico.
]]>Authors: Bingchuan Yan Chao Sun Qingshan Feng Jian Chen Yuke Gao Changfa Tao
This paper studies the influence of hydrogen volume fraction effects on the temperature distribution of diffusion turbulent propane jet flames. Numbers of experimental scenarios have been carried out to investigate the evolution of temperature distribution under different hydrogen volume fractions. In the continuous region, these experimental results show that the temperature distribution and the maximum temperature of diffusion of turbulent jet flames are proportional to the hydrogen volume fraction under the same heat release rate of propane. Considering the model of virtual point source and the three-stage model, the theoretical model between the hydrogen volume fraction and flame temperature has been analyzed. The relationship among the temperature distribution, hydrogen volume fraction, and heat release rate has been modified. It can provide some important references for the fire risk assessment of turbulent diffusion jet flames.
]]>Authors: Andy Indradjad Muhammad Dimyati Yenni Vetrita Erna Sri Adiningsih Rokhmatuloh Rokhmatuloh
Indonesia needs a daily monitoring system due to its frequent fires and, more importantly, to assist stakeholders in the field in taking action to mitigate disasters. Our method simplified the number of hotspots for field-based purposes and was verified by comparing the point-based (point-HS) VIIRS (Visible Infrared Imaging Radiometer Suite) 375m-derived temperature anomalies (hotspots) and clustered-based hotspots (cluster-HS, our suggested method). Using Euclidean clustering, we calculated the distance between hotspot points and applied specific criteria to reduce the number of hotspots while aligning them closely with fire incidents. We evaluated accuracy at different fire sizes, burned areas, peatlands, and distances from the reported burn center. We found that the accuracy increases at 1.5 km from the center of the fire for both point- and cluster-HS at 52% and 53%, respectively. For areas larger than 14 ha, both types of hotspots yielded superior results of 83%. Cluster-HS performs better on peatlands than non-peatlands (62% vs. 57%). Without diminishing the precision of the hotspot observation, this study indicates that our method is reliable for assisting field stakeholders in the field in taking actions. Therefore, this product could be implemented into Indonesia’s daily hotspot monitoring.
]]>Authors: Yujie Lin Xiaodong Ling Anfeng Yu Yi Liu Di Liu Yazhen Wang Qian Wu Yuan Lu
Accidental hydrogen releases from pipelines pose significant risks, particularly with the expanding deployment of hydrogen infrastructure. Despite this, there has been a lack of thorough investigation into hydrogen leakage from pipelines, especially under complex real-world conditions. This study addresses this gap by modeling hydrogen gas dispersion, jet fires, and explosions based on practical scenarios. Various factors influencing accident consequences, such as leak hole size, wind speed, wind direction, and trench presence, were systematically examined. The findings reveal that both hydrogen dispersion distance and jet flame thermal radiation distance increase with leak hole size and wind speed. Specifically, the longest dispersion and radiation distances occur when the wind direction aligns with the trench, which is 110 m where the hydrogen concentration is 4% and 76 m where the radiation is 15.8 kW/m2 in the case of a 325 mm leak hole and wind under 10 m/s. Meanwhile, pipelines lacking trenching exhibit the shortest distances, 0.17 m and 0.98 m, at a hydrogen concentration of 4% and 15.8 kW/m2 radiation with a leak hole size of 3.25 mm and no wind. Moreover, under relatively higher wind speeds, hydrogen concentration stratification occurs. Notably, the low congestion surrounding the pipeline results in an explosion overpressure too low to cause damage; namely, the highest overpressure is 8 kPa but this lasts less than 0.2 s. This comprehensive numerical study of hydrogen pipeline leakage offers valuable quantitative insights, serving as a vital reference for facility siting and design considerations to eliminate the risk of fire incidents.
]]>Authors: Yan Shi Changping Feng Liwei Zhang Wen Huang Xin Wang Shipeng Yang Weiwei Chen Wenjie Xie
As global climate change and human activities increasingly influence our world, forest fires have become more frequent, inflicting significant damage to ecosystems. This study conducted measurements of combustible materials (moisture content ratio, ignition point, and calorific value) across 14 representative sites. We employed Pearson correlation analysis to ascertain the significant differences in combustible properties and utilized entropy methods to evaluate the fire resistance of materials at these sites. Cluster analysis led to the development of four combustible models. Using BehavePlus software, we simulated their fire behaviors and investigated the effects of wind speed and slope on these behaviors through sensitivity analysis. The results revealed notable differences in the moisture content ratios among different types of combustibles, especially in sites 2, 3, 8, 9, and 13, indicating higher fire risks. It was also found that while humus has a higher ignition point and lower calorific value, making it less prone to ignite, the resultant fires could be highly damaging. The Pearson analysis underscored significant variations in the moisture content ratios among different combustibles, while the differences in ignition points and calorific values were not significant. Sites 5 and 6 demonstrated stronger fire resistance. The simulations indicated that fire-spread speed, fireline intensity, and flame length correlate with, and increase with, wind speed and slope. Sensitivity analysis confirmed the significant influence of these two environmental factors on fire behavior. This study provides critical insights into forest fire behavior, enhancing the capability to predict and manage forest fires. Our findings offer theoretical support for forest fire prediction and a scientific basis for fire management decision-making.
]]>Authors: Janine Florath Jocelyn Chanussot Sina Keller
Natural hazards such as wildfires have proven to be more frequent in recent years, and to minimize losses and activate emergency response, it is necessary to estimate their impact quickly and consequently identify the most affected areas. Volunteered geographic information (VGI) data, particularly from the social media platform Twitter, now X, are emerging as an accessible and near-real-time geoinformation data source about natural hazards. Our study seeks to analyze and evaluate the feasibility and limitations of using tweets in our proposed method for fire area assessment in near-real time. The methodology involves weighted barycenter calculation from tweet locations and estimating the affected area through various approaches based on data within tweet texts, including viewing angle to the fire, road segment blocking information, and distance to fire information. Case study scenarios are examined, revealing that the estimated areas align closely with fire hazard areas compared to remote sensing (RS) estimated fire areas, used as pseudo-references. The approach demonstrates reasonable accuracy with estimation areas differing by distances of 2 to 6 km between VGI and pseudo-reference centers and barycenters differing by distances of 5 km on average from pseudo-reference centers. Thus, geospatial analysis on VGI, mainly from Twitter, allows for a rapid and approximate assessment of affected areas. This capability enables emergency responders to coordinate operations and allocate resources efficiently during natural hazards.
]]>Authors: Keith Parker Vytenis Babrauskas
One of the primary tools used for determining the origin of a wildfire is analyzing burn patterns formed during the fire progression. These patterns, called fire pattern indicators, are interpreted and used to document the direction of fire movement at specific points, creating a directional map back to the specific area of origin. This concept was first set forth in 1978 by a U.S. governmental organization, the National Wildfire Coordinating Group (NWCG). Their recommendations are currently (2016) in the third edition, and in our study, we examine these indicators. Specifically, the objective was to perform a validation exercise where controlled burns were conducted of natural vegetation plots but augmented with 32 identical sets of staged artifacts which would provide additional opportunities for fire movement to create observable directional fire pattern indicators. Three adjacent plots were burned, each using a single point ignition, all located on level, scrubland terrain. The burns were conducted in the fall season, under low to moderate burning conditions. The research was structured as a preliminary study, since only mild terrain and weather conditions were encompassed. The actual fire movements were documented by drone videos, additional ground-based videos, and still photography. Within the three burn plots, a total of 12 data sites out of 32 data sites were selected: each one containing 7 to 12 individual artifacts. Each artifact was photographically documented post-fire, and the actual fire movement direction at that location was established. Assessment entailed the use of four experienced wildland fire investigators, with each one independently assessing the direction and type of fire spread at each artifact using the photographic site evidence. An analysis was then conducted to make a statistical comparison between the actual fire movement direction and the direction estimates provided by the experts analyzing the photographic evidence and the limited information on conditions provided. The results indicate an average error of 103°. These results indicate that additional efforts are needed to study the scientific basis of the indicators and to evolve improvements in both the indicators and in the accompanying guidance to investigators.
]]>Authors: Xin Huang Zhilei Yu Zhiming Zhan
The pool fires that occur behind obstructions in a ventilated environment are very different from other wind-blown pool fires. The pool fire formed by fuel leakage in an engine nacelle is a typical example of a pool fire influenced by cross winds and baffles. Mastering the combustion characteristics of this type of fire is of great significance for fire prevention and control. In this study, the burning rate, flame length, and flame tilt angle of heptane pool fires behind a baffle under different cross wind velocities (ranging from 0 to 5 m/s) were experimentally investigated. Square pool fires with dimension of 8 cm and 12 cm with baffle height from 4 to 12 cm and different distances between fire and baffle (0, 20, 30 cm) were tested in a wind tunnel. The experimental results show that the burning rate increases with the increase in cross wind velocity for each baffle height. As wind velocity exceeds 2 m/s, the burning rate first decreases and then increases with the increase in baffle height. The flame length initially increases and then decreases with increasing wind velocity. The upper flame tilt angle is mainly affected by the cross wind, while the bottom flame tilt angle is influenced by the combined effects of cross wind velocity, baffle height, and distance between baffle and flame. The empirical correlations under different distances between baffle and flame, with wind velocity and baffle height accounted for, are then proposed for the dimensionless heat release rate and the flame length of heptane pool fires.
]]>Authors: Fang Xu Xi Zhang Tian Deng Wenbo Xu
Due to its wide monitoring range and low cost, visual-based fire detection technology is commonly used for fire detection in open spaces. However, traditional fire detection algorithms have limitations in terms of accuracy and speed, making it challenging to detect fires in real time. These algorithms have poor anti-interference ability against fire-like objects, such as emissions from factory chimneys, clouds, etc. In this study, we developed a fire detection approach based on an improved YOLOv5 algorithm and a fire detection dataset with fire-like objects. We added three Convolutional Block Attention Modules (CBAMs) to the head network of YOLOv5 to improve its feature extraction ability. Meanwhile, we used the C2f module to replace the original C2 module to capture rich gradient flow information. Our experimental results show that the proposed algorithm achieved a mAP@50 of 82.36% for fire detection. In addition, we also conducted a comparison test between datasets with and without labeling information for fire-like objects. Our results show that labeling information significantly reduced the false-positive detection proportion of fire-like objects incorrectly detected as fire objects. Our experimental results show that the CBAM and C2f modules enhanced the network’s feature extraction ability to differentiate fire objects from fire-like objects. Hence, our approach has the potential to improve fire detection accuracy, reduce false alarms, and be more cost-effective than traditional fire detection methods. This method can be applied to camera monitoring systems for automatic fire detection with resistance to fire-like objects.
]]>Authors: Xiaowei Zang Wei Liu Dali Wu Xuhai Pan Wei Zhang Haitao Bian Ruiqi Shen
As environmental conservation and sustainability gain prominence globally, modern timber structures are receiving increased focus. Nonetheless, the combustible nature of timber raises significant fire safety concerns. This review explores the recent advancements in fire safety engineering for timber structures, emphasizing both contemporary high-rise buildings and historical timber constructions. It covers topics like inherently safer design principles, fire risk prediction, and evacuation methodologies. The review emphasizes the criticality of selecting suitable materials, structural design, firefighting systems, and advanced sensor technologies for early fire detection. Additionally, we analyze and compares various evacuation strategies, offering insights into the challenges and future directions for fire safety in modern timber structures.
]]>Authors: Joana Dias Guilherme Saad Ana Soares Maria Partidário Isabel Loupa Ramos Rute Martins Margarida B. Monteiro
BRIDGE (bridging science and local communities for wildfire risk reduction) is an action–research project developing a community-based disaster risk reduction (CBDRR) process which is being fostered through a collaborative innovation laboratory (InnoLab). BRIDGE integrates different forms of knowledge and action, linking science and local communities to reduce their vulnerability and to enhance strategies for forest fire risk reduction. Applied in Monchique, a forest-fire-prone municipality in Portugal, the InnoLab creates a space for dialogue and knowledge sharing between multiple actors that, directly or indirectly, manage forest territories. BRIDGE attempts to facilitate social learning about forest fire risks, strengthen collaborative networks and enhance adaptive capacities (socially and institutionally) for forest fire prevention. This paper shares results of the InnoLab activities, which include (i) school community activities on wildfire risk perception; (ii) participatory mapping of Monchique’s vulnerabilities and risks; (iii) participatory sessions to create the community visioning for Monchique’s territory, to define priorities and capacities to be improved, and to identify functions and responsibilities to act upon; and (iv) workshop on CBDRR strategies for action. Lessons are shared on how InnoLab can represent an innovative participatory approach to promote CBDRR processes in forest-fire-prone territories by both contributing to the recognition of local knowledge systems and encouraging the active role of forest communities through strengthened local networks for a more lasting commitment to forest fire risk reduction policy.
]]>Authors: Yongjing Wang Yong Sun Lihui Dai Kun Wang Gang Cheng
The spontaneous combustion of coal caused by oxidation often leads to catastrophic fires. However, the understanding of oxidized carbon gas as a predictor of coal’s spontaneous combustion is still in its infancy. To better study the characteristics of CO2 and CO generation during low-temperature coal oxidation, the chemical reactions and activation energies during the formation of oxidized carbon gases within coal molecules were investigated using the molecular simulation method, and the reaction characteristics at different temperatures were determined. In addition, TG was used to experimentally analyze the variations in coal weight, exothermic conditions, and gas generation patterns. The results show that the low-temperature oxidation process consists of four different phases, each of which is characterized by unique CO and CO2 generation. The results of this study are important for the prevention and prediction of the spontaneous combustion of coal.
]]>Authors: Alexander J. Heeren Philip E. Dennison Michael J. Campbell Matthew P. Thompson
In wildland–urban interface areas, firefighters balance wildfire suppression and structure protection. These tasks are often performed under resource limitations, especially when many structures are at risk. To address this problem, wildland firefighters employ a process called “structure triage” to prioritize structure protection based on perceived defensibility. Using a dataset containing triage assessments of thousands of structures within the Western US, we developed a machine learning model that can improve the understanding of factors contributing to assessed structure defensibility. Our random forest models utilized variables collected by wildland firefighters, including structural characteristics and the surrounding ignition zone. The models also used landscape variables not contained within the triage dataset that captured important information about accessibility, vegetation, topography, and structure density. We achieved a high overall accuracy (77.8%) in classifying structures as defensible or non-defensible. The presence of a safety zone was the most important factor in determining structure defensibility. Road proximity, vegetation composition, and topography were also found to have high importance. In addition to improving the understanding of factors considered by wildland firefighters, communities could also gain from this information by enhancing their wildfire response plans, focusing on targeted mitigation, and improving their overall preparedness.
]]>Authors: Hanwen Guo Zhengyuan Yang Peiyao Zhang Yunji Gao Yuchun Zhang
In this work, a number of experiments were conducted in a reduced scale bifurcation tunnel with a ratio of 1:10 to explore the influence of the position of longitudinal fires (placed in branch tunnel) on smoke temperature profile under forced ventilation. Three heat release rates, six ventilation velocities, and three fire locations were considered. The main findings are summarized below, as follows: The temperature of smoke downstream of the main tunnel decreases with the rate of ventilation and longitudinal fire location. In contrast, the smoke temperature downstream of the fire source inside the branch tunnel drops with the ventilation velocity; the maximum temperature of the flame under the ceiling of the tunnel rises with longitudinal fire location. The dimensionless longitudinal smoke temperatures downstream of the main tunnel decrease exponentially with longitudinal distance, and the same observation is found in the branch tunnel. The attenuation coefficient k in the main tunnel increases with longitudinal ventilation velocity according to a power law but does not change significantly with longitudinal fire locations. However, the exponential coefficient k′ in the branch tunnel decreases linearly with ventilation velocity, whereas it increases with longitudinal fire location inside the branch tunnel. Lastly, modified models are established for estimating the longitudinal profile of temperatures downstream of the main tunnel and branch tunnel, where the influence of the rate of ventilation and location of the fire are taken into account.
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