Fire, Volume 7, Issue 2 (February 2024) – 27 articles

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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%. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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 r_L and the area ratio r_A of the main nozzle on the two-phase flow field, as well as on the jet performance indexes, such as the particle mean velocity v_p,a, velocity inhomogeneity Φ_vp, particle dispersion Ψ_p, particle mean acceleration a_p,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. Full article

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. Full article

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. Full article

In this work, the overall activation energy of the combustion of lean hydrogen–methane–air mixtures (equivalence ratio $\phi$ = 0.7−1.0 and hydrogen fraction in methane $\alpha =0$, 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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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 (NO_x) 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 NO_x 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 NO_x 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. Full article