Fire

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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%. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article

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. Full article