Fire Behavior Research Articles

Estimating fuel load for wildfire risk assessment at regional scales using earth observation data: A case study in Southwestern Australia

The risk of wildfires is increasing globally and models are critical to reducing this risk. Such models require information on fuel load, a crucial factor of fire behaviour, which is generally determined using a combination of fuel age and fuel accumulation models. Traditionally, estimating fuel load relies on manually compiled fire history data (MCFH). In this paper, we introduce an approach to estimate fuel load using readily available earth observation (EO) data, MODIS MCD64A1. The approach is applied to a wildfire-prone region in Southwestern Australia from 2001 to 2021. Results suggest that MODIS produces more accurate and reliable estimates of fuel load compared with MCFH. It is effective in maintaining spatially and temporally complete records of fires, as it reports 11,019 more hectares of burned areas associated with wildfires over the study period. MODIS performs better in capturing wildfires than prescribed burns, as the spatial overlapping ratio is higher for wildfires (0.63) than prescribed burns (0.42). The high agreement between the two datasets for fuel load estimation (weighted kappa of 0.91) results from grassland covering the majority of the landscape. However, the agreement is reduced for other vegetation types — 0.24 for pine, 0.36 for mallee heath, 0.39 for shrubland, and 0.58 for forest. MODIS has lower effectiveness in detecting small and under-canopy fires such as prescribed burns, suggesting the value in combining EO and manually compiled data to obtain improved estimates of fuel load. Due to the scope of objectives, the integration of EO and MCFH has not been fully explored in this study, which will be included in our future research. This study highlights the potential of earth observation data in assessing wildfire risk as the data are easily accessible and reliable, as well as efficient and cost-effective, and they provide the opportunity to develop mitigation strategies at regional scales.

Small scale pool fires: The case of toluene

Industrial applications adopting toluene as a solvent have been largely extended in recent years, including solutions within the framework of the energy transition and energy storage technologies. The potential use of this flammable compound in a different set of operative conditions and compositions requires a comprehensive and complete knowledge of its fire behaviour and combustion kinetic. To this scope, an innovative experimental procedure applicable to liquid reactive systems was developed for this scope and implemented at different boundary conditions. More specifically, the specimen was exposed to air and heat fluxes between 7 and 50 kW/m2, at a constant sample surface of 0.01 m2, an initial sample thickness of 0.01 m, and a distance between the sample and the horizontally oriented conical-shaped heater of 0.025 m. Measurements were compared with data from the current literature, when available, demonstrating the robustness and validity of the adopted procedure. Although an increase in the external flux leads to growing mass burning rates (i.e., from 0.47 g/s to 0.85 g/s), negligible effects on the ignitability were observed. Conversely, a peak in the heat release rate at 35 kW/m2 was measured. The observed reduction at higher external heat fluxes was attributed to less effective combustion, demonstrating that the maximum expected heat flux cannot be considered as an aprioristic worst-case scenario for the evaluation of pool fires. The collected data were, then, further utilized to obtain insights on the formation of the main products, including soot tendency. Based on the collected data a simplified kinetic model suitable for the computational fluid dynamics was proposed to reproduce the chemistry of the system.

Multi-factor coupled forest fire model based on cellular automata

The risk of forest fires is substantial due to uneven precipitation distributions and abnormal climate change. This study employs cellular automata principles to analyze forest fire behavior, taking into account meteorological elements, combustible material types, and terrain slopes. The Wang Zhengfei model is utilized to compute fire spread speed, and a multifactor coupled forest fire model is developed. Comparisons with experimental data show a mean calculated fire spread speed of 0.69 m/min, which is consistent with the experimental results. Using the forest fire in Anning city, Yunnan Province, as a case study with a mean burned area of 2281 ha, the burned area, rate of change in burned area, and burning area demonstrated an increasing trend, with fluctuating states in the rate of change of the burning area. Employing the controlled variable method to examine forest fire spreading patterns under varying factors such as wind speed, vegetation type, and maximum slope reveals that under wind influence, the fire site adopts an elliptical shape with the downwind direction as the major axis. Quantitatively, when the wind speed increases from 2 m/s to 10 m/s, the burned area expands by a factor of 1.37. The ratio of the combustible material configuration coefficient to the burned area remains consistent across the different vegetation types, and the burned area increases by a factor of 1.92 when the maximum slope increases from 5° to 25°.

Unveiling the Role of Climate and Environmental Dynamics in Shaping Forest Fire Patterns in Northern Zagros, Iran

Wildfires present a major global environmental issue, exacerbated by climate change. The Iranian Northern Zagros Forests, characterized by a Mediterranean climate, are particularly vulnerable to fires during hot, dry summers. This study investigates the impact of climate change on forest fires in these forests from 2006 to 2023. The analysis revealed significant year-to-year fluctuations, with notable fire occurrence in years 2007, 2010, 2021, and 2023. The largest burned area occurred in 2021, covering 2655.66 ha, while 2006 had the smallest burned area of 175.27 ha. Climate variables such as temperature, humidity, precipitation, wind speed, heat waves, and solar radiation were assessed for their effects on fire behavior. Strong correlations were found between higher average temperatures and larger burned areas, as well as between heat waves and increased fire frequency. Additionally, higher wind speeds were linked to larger burned areas, suggesting that increased wind speeds may enhance fire spread. Multiple linear regression models demonstrated high predictive accuracy, explaining 84% of the variance in burned areas and 69.6% in the variance in fire frequency. These findings document the growing wildfire risk in the Northern Zagros region due to climate change, highlighting the urgent need to integrate scientific research with policies to develop effective wildfire management strategies for sustainable forest management.

Effect of diammonium hydrogen phosphate coated with silica on flame retardancy of epoxy resin.

Epoxy resin has become one of the most widely used polymers owing to their excellent comprehensive properties. However, the inherent inflammability of epoxy resin (EP) has seriously limited its application in a range of fields with high fire safety requirements. Herein, a novel shell-core hierarchy architecture (DAP@SiO2) was prepared, composed of diammonium hydrogen phosphate (DAP) and in situ grown silica, and its structure and morphology were characterized by electron microscopy and infrared spectroscopy. The results indicated that silica particles were uniformly coated onto the surface of DAP. The modified DAP was used to reinforce the epoxy resin. The thermal stability of the EP blends was studied with the use of thermogravimetric analysis. The diammonium phosphate in DAP@SiO2 flame retardant produces pyrolysis gases such as NH3 and N2 during decomposition, diluting the concentration of oxygen and flammable volatile products around the flame. Secondly, silica migrates to the surface of epoxy resin to form a shielding layer, forming compounds containing Si-O-Si and O-Si-C structures, which can be cross-linked with other condensed phase products, greatly improving the thermal stability of the carbon layer. Fire behavior was evaluated using the limiting oxygen index (LOI), vertical burning test, and the cone calorimetry, and the flame retardancy mode of action was explained. With 12% of DAP@SiO2 involved, the EP blend passes UL-94 V-0 level, and its limiting oxygen index (LOI) reaches 33.2%. The incorporation of DAP@SiO2 in an EP matrix showed a slight reduction in the heat release and smoke production. The flame retardant mode of the EP polymer shows that its flame retardant and smoke suppression characteristics are related to the interaction of flame retardants in the gas phase and condensed phase. The mechanical properties test results illustrated that the tensile strength, elastic modulus and impact strength of EP/3%DAP@SiO2 are improved compared with pure EP. This is due to the crosslinking reaction between a large number of amino groups on the surface of DAP@SiO2 and the epoxy group on the epoxy resin, which significantly enhances the interfacial compatibility between DAP@SiO2 and epoxy resin, making the combination of DAP@SiO2 and epoxy resin closer.

Experimental study on the transitional behavior of the room fire under sub-atmospheric pressures

Fuel diffusion combustion and flame behavior within a confined space is a fundamental scientific problem in the energy and combustion field, it involves complicated chemical reaction, fire behavior, thermal dynamics, heat transfer, room-opening flowing and sub-processes of over-ventilated and under-ventilated room fire. However, previous classical knowledges and models about it are usually at standard atmospheric pressure (100 kPa), no work considers the fire evolution and flame behavior within the room for various sub-atmospheric pressures. In this paper, the experiment is carried by utilizing a 0.3 m × 0.3 m × 0.3 m reduced-scale cubic room with an opening of various dimensions, and using propane as fuel to simulate fuel combustion inside, which was placed at the Low Pressure Chamber creating various atmospheric pressures. The flame behavior and temperature evolution within the room was recorded and measured with 693 experimental conditions. The experimental results show that, (1) the air inflowing rate through opening into room and heat release rate within the room increase with atmospheric pressure; (2) the flame extinction or reaching well-mixed condition are more easily occurred for lower atmospheric pressure and opening dimension. These characteristic parameters and fire behaviors could be well described by new corrected opening ventilation factor involving effect of atmospheric pressure and the opening dimension. The research work fills the gap in basic scientific research of building fire at sub-atmospheric pressures, which also has important practical applicability of urban building fire protection design code (such as the materials in wall) in different altitudes, room fire suppression, and protecting urban safety.

An experimental study of fire development under varying ventilation conditions during the depressurization process in pressurized buildings

Hermetic pressurized buildings are a new type of building in high-altitude areas that efficiently addresses issues such as high-altitude reactions. The indoor pressure is higher than the external pressure under working conditions, and pressure relief must be carried out first during emergencies. The emergency pressure relief process during a fire may lead to complex fire behavior that is different from that in regular buildings. In this study, we focus on the impact of ventilation conditions and the status of doors in such buildings on fire evolution and smoke plume characteristics through experiments. The temperature variation in the fire room and corridor is measured under different ventilation power, ventilation time, and door opening width conditions. This shows that the width of the door has the greatest impact on fire development. A smaller gap in the door opening restricts air circulation between the interior and exterior of the room, resulting in a rapid decrease in the oxygen concentration within the fire room and a decrease in the combustion reaction rate of wood fires. The ventilation power exerts the most significant influence on the temperature variation in the corridor. These findings provide empirical data and a basis for fire science studies in high-altitude hermetic pressurized buildings and can guide existing fire protection design and management for improved safety.

Fire resistance of square double-skin concrete-filled steel tubular columns and concrete-filled double steel tubular columns

Square double-skin concrete-filled steel tubular (DSCFST) columns and concrete-filled double steel (CFDST) columns possess excellent load-carrying capacity and ductility. However, there has been limited research on the responses of DSCFST and square CFDST columns exposed to fire. This paper presents a series of tests on such columns loaded concentrically to determine the effects of the steel tube thickness, the strength of materials, load ratio, and boundary conditions on their fire resistance. Additionally, finite element (FE) models are established using ABAQUS, in which the concrete’s transient creep strain is considered through the development of the user-subroutine UEXPAN. A parametric study is undertaken by simulating 156 FE models to further study the behavior of DSCFST and CFDST columns under fire exposure. The fire test and numerical results suggest that both the load ratio and strengths of the internal tube and concrete core play significant roles in determining the fire resistance of DSCFST and CFDST columns. The developed FE models are demonstrated to capture well the fire behavior of loaded DSCFST and CFDST columns. The proposed design model predicts the ultimate loads of DSCFST columns with good accuracy; therefore, it can be employed in the practical design of DSCFST columns.

Advanced fire emergency management based on potential fire risk assessment with informative digital twins

Modern large complex buildings, with their vast expanses and multipurpose usability, present diverse fire-spread scenarios, necessitating precise awareness of fire situations. Despite numerous studies integrating building information models with IoT and AI technologies to provide contextual information, there may be limitations in recognizing potential risks under dynamic fire behaviors during urgent situations. This paper presents a fire emergency management system based on an informative digital twin (IDT) to provide instantaneous fire situational information. Utilizing IDT, the system gathers building-specific fire scenario knowledge for immediate fire recognition. Leveraging this knowledge, the IDT assesses building fire risks and shares safety information on egress routes and zones with fire-related applications. A simulation case study revealed a fire recognition processing time of 0.88 s, acceptable for fire emergencies. Additionally, the IDT’s risk assessment reduced the total evacuation time by 65 s and potential injuries by 406, demonstrating the system’s effectiveness in fire emergency management.

Can green firebreaks help balance biodiversity, carbon storage and wildfire risk?

Green firebreaks (strategically placed plantings of low-flammability vegetation) are designed to reduce the rate of fire spread and thereby increase the suppressibility of fires. Successful examples have led to some fire-prone regions investing heavily in the establishment of green firebreaks as a method of reducing fire risk while improving biodiversity and carbon storage. However, beyond small-scale case studies there has been little research quantitatively exploring the interactions among biodiversity, carbon, and wildfire risk in relation to green firebreaks. Here, we combine a Bayesian Network (BN) analysis, and fire simulations in PHOENIX RapidFire (hereafter Phoenix), to identify planting designs that reduce wildfire risks while also providing positive biodiversity and carbon outcomes. Using a BN analysis, we prioritised optimal planting designs as the combination of elements (e.g., stem density, distance from houses, shrub design, age etc.) that delivered the greatest increase in biodiversity and carbon while reducing fire risk to people and property for eight sites across south-eastern Australia. We ranked combinations of planting designs, prioritising house, and life loss first, to identify optimal designs. Optimal planting designs varied among sites, although the design elements that best reduced risk to houses and lives were consistent. These elements included ‘scattered’ shrubs and planting densities of trees consistent with an open forest structure. Estimated fuel loads for the optimal planting design at each site were used to create a simulated revegetation area in Phoenix. We simulated fire behaviour in Phoenix across a grid of ∼1000 ignitions for each site, and for up to 54 historic weather conditions for a 'current fuel’ scenario (no green firebreaks present) compared with a ‘green firebreak fuel’ scenario. We found that the establishment of a green firebreak did not result in significant changes to fire behaviour at most sites. In some cases, it reduced risk to people and property, and where fire behaviour did change in terms of intensity, frequency, ember attack and overall risk, the differences relative to the current fuel scenario were less than two percent. Overall, simulated green firebreaks in most cases were found to provide biodiversity and carbon benefits without increasing fire risk. These findings illustrate their potential as an effective nature-based solution for managing multiple priorities; however, further testing of real plantings is required to evaluate this potential as an at-scale solution.

Adaptive wildfire spread prediction for complex terrain: modeling the effectiveness of sprinkler systems

BackgroundBecause the threat of wildfires to global ecosystems and society continues to rise, this study provides an experimental simulation framework that assesses the spread and reduction of wildfires to evaluate the effectiveness of adaptation methods in reducing their impact. The process entails selecting a vulnerable wildfire area and adaptation method, then generating the computational fluid dynamics (CFD) model. Monitoring data are then used to configure the model, set boundary conditions, and simulate the fire. The effectiveness of the adaptation method in minimizing damage in the area of interest is evaluated by comparing simulations with and without the chosen adaptation method. Our focus area was a natural recreational forest in Wonju, Gangwon-do, Korea, and our adaptation method was a water sprinkler system.ResultsOur framework provides aims to provide an experimental means of assessing the wildfire spread path and spread area based on exogenous variables of wind speed, wind direction, relative humidity, and more. The sprinkler adaptation had a reduction effect of 20% in the wildfire spread rate for the 10-h period, which refers to the time limit of the simulation after ignition. We revealed that at higher wind speeds, the fire primarily follows the wind direction; whereas at lower wind speeds, the fire is more influenced by the topography. Additionally, 60 min after ignition, the adaptation methods can suppress wildfire spread by > 70%. Notably, sprinklers reduce smoke concentrations by up to 50% (ppm) over the affected area.ConclusionsThis study demonstrates the potential effectiveness of a comprehensive CFD model in mitigating wildfire spread using sprinkler systems as an experimental analysis. Key results include a 20% reduction in wildfire within 10 h of ignition, significant influence of wind speed on spread patterns, and a reduction of smoke concentrations, improving air quality. These findings highlight the potential of CFD-based frameworks to enhance wildfire response strategies. However, it is important to note that this study’s limitations include the lack of experimental or measured fire behavior data, which should be considered when interpreting the effectiveness of the CFD model.

Simulated fire video collection for advancing understanding of human behavior in building fires.

The goal of the present research was to develop a video collection of simulated fires to investigate how people perceive growing building fires. In fire safety science, a critical factor to occupant responses to building fires is the pre-movement period, determined by how long it takes an individual to initiate taking protective action with an incipient fire. Key to studying the psychological processes that contribute to the duration of the pre-movement period is presenting human subjects with building fires. One approach used in previous research is to present videos of building fires to individuals via scenarios. The numerical simulations used to model fire dynamics can be used to render videos for these scenarios. However, such simulations have predominantly been used in fire protection engineering to design buildings and are relatively inaccessible to social scientists. The present study documents a collection of videos, based on numerical simulations, which can be used by researchers to study human behavior in fire. These videos display developing fires in different types of rooms, growing at different rates, different smoke thickness, among other characteristics. As part of a validation study, participants were presented with subsets of the video clips and were asked to rate the perceived risk posed by the simulated fire. We observed that ratings varied by the intensity and growth rate of the fires, smoke opacity, type of room, and where the viewpoint was located from the fire. These effects aligned with those observed in previous fire science research, providing evidence that the videos could elicit perceived risk using fire simulations. The present research indicates that future studies can utilize the video library of fire simulations to study human perceptions of developing building fires as situational factors are systematically manipulated.

Fractional-order heterogeneous neuron network based on coupled locally-active memristors and its application in image encryption and hiding

Synaptic crosstalk significantly influences neural firing in the brain. Locally-active memristors can effectively emulate neural network synapses and have a significant importance in neural network research. This paper designs a tristable locally-active memristive model and presents a novel fractional-order (FO) heterogeneous neuron network. This neural network consists of Hindmarsh-Rose (HR) neuron and FitzHugh-Nagumo (FHN) neuron, which are connected by coupling FO locally-active memristors. The research found that changes in the order of different dimensions have a significant effect on the neural network firing through the three-parameter bifurcation diagram. Moreover, it is found that the locally-active memristor as a synapse can affect the coexistence firing behavior of the network. The complex dynamics have been studied numerically by using phase diagrams, Lyapunov exponent spectrum, bifurcation diagram and extreme multistability can be found. In particular, the system can generate a complex bursting behavior in the presence of an external current. In order to verify the accuracy of the simulation, the phase diagram of FO heterogeneous neuron network is implemented by STM32 microcontroller, and results of the experiments are in great agreement with results of the numerical simulations. Finally, an image encryption and hiding method based on FO heterogeneous neuron network and discrete wavelet transform (DWT) is proposed. The experimental results demonstrate that the encryption and hiding scheme has excellent security and strong robustness.

Modulation of CB1 cannabinoid receptor alters the electrophysiological properties of cerebellar Purkinje cells in harmaline-induced essential tremor

Essential tremor (ET) is one of the most common motor disorders with debilitating effects on the affected individuals. The endocannabinoid system is widely involved in cerebellar signaling. Therefore, modulation of cannabinoid-1 receptors (CB1Rs) has emerged as a novel target for motor disorders. In this study, we aimed to assess whether modulation of cannabinoid receptors (CBRs) could alter the electrophysiological properties of Purkinje cells (PCs) in the harmaline-induced ET model. Male Wistar rats were assigned to control, harmaline (30 mg/kg), CBR agonist WIN 55,212–2 (WIN; 1 mg/kg), CB1R antagonists AM251 (1 mg/kg) and rimonabant (10 mg/kg). Spontaneous activity and positive and negative evoked potentials of PCs were evaluated using whole-cell patch clamp recording. Findings demonstrated that harmaline exposure induced alterations in the spontaneous and evoked firing behavior of PCs, as evidenced by a significant decrease in the mean number of spikes and half-width of action potential in spontaneous activity. WIN administration exacerbated the electrophysiological function of PCs, particularly in the spontaneous activity of PCs. However, CB1R antagonists provided protective effects against harmaline-induced electrophysiological changes in the spontaneous activity of PCs. Our findings reinforce the pivotal role of the endocannabinoid system in the underlying electrophysiological mechanisms of cerebellar disorders and suggest that antagonism of CB1R might provide therapeutic utility.

A comprehensive taxonomy for forest fire risk assessment: bridging methodological gaps and proposing future directions.

Forest fire risk assessment plays a crucial role in the environmental management of natural hazards, serving as a key tool in the prevention of forest fires and the protection of various species. As these risks continue to evolve with environmental changes, the pertinence of contemporary research in this field remains undiminished. This review constructs a comprehensive taxonomic framework for classifying the existing body of literature on forest fire risk assessment within forestry studies. The developed taxonomy categorizes existing studies into 8 primary categories and 23 subcategories, offering a structured perspective on the methodologies and focus areas prevalent in the domain. We categorize a sample of 170 articles to present recent trends and identify research gaps in forest fire risk assessment literature. The classification facilitates a critical evaluation of the current research landscape, identifying areas in need of further exploration. Particularly, our review identifies underrepresented methodologies such as optimization modeling and some advanced machine learning techniques, which present routes for future inquiry. Moreover, the review underscores the necessity for model development that is tailored to specific regional data sets but also adaptable to global data resources, striking a balance between local specificity and broad applicability. Emphasizing the dynamic nature of forest fire behavior, we advocate for models that integrate the burgeoning field of machine learning and multi-criteria decision analysis to refine predictive accuracy and operational effectiveness in fire risk assessment. This study highlights the great potential for new ideas in modeling techniques and emphasizes the need for increased collaboration among research communities to improve the effectiveness of assessing forest fire risks.

Moderating effects of past wildfire on reburn severity depend on climate and initial severity in Western US forests.

Rising global fire activity is increasing the prevalence of repeated short-interval burning (reburning) in forests worldwide. In forests that historically experienced frequent-fire regimes, high-severity fire exacerbates the severity of subsequent fires by increasing prevalence of shrubs and/or by creating drier understory conditions. Low- to moderate-severity fire, in contrast, can moderate future fire behavior by reducing fuel loads. The extent to which previous fires moderate future fire severity will powerfully affect fire-prone forest ecosystem trajectories over the next century. Further, knowing where and when a wildfire may act as a landscape-scale fuel treatment can help direct pre- and post-fire management efforts. We leverage satellite imagery and fire progression mapping to model reburn dynamics within forests that initially burned at low/moderate severity in 726 unique fire pair events over a 36-year period across four large fire-prone Western US ecoregions. We ask (1) how strong are the moderating effects of low- to moderate-severity fire on future fire severity, (2) how long do moderating effects last, and (3) how does the time between fires (a proxy for fuel accumulation) interact with initial fire severity, day-of-burning weather conditions, and climate to influence reburn severity. Short-interval reburns primarily occurred in dry- and moist-mixed conifer forests with historically frequent-fire regimes. Previous fire moderated reburn severity in all ecoregions with the strongest effects occurring in the California Coast and Western Mountains and the average duration of moderating effects ranging from 13 years in the Western Mountains to >36 years in the California Coast. The strength and duration of moderating effects depended on climate and initial fire severity in some regions, reflecting differences in post-fire fuel accumulation. In the California Coast, moderating effects lasted longer in cooler and wetter forests. In the Western Mountains, moderating effects were stronger and longer lasting in forests that initially burned at higher severity. Moderating effects were largely robust to fire weather, suggesting that previous fire can mediate future fire severity even under extreme conditions. Our findings demonstrate that low- to moderate-severity fire buffers future fire severity in historically frequent-fire forests, underlining the importance of wildfire as a restoration tool for adapting to global change.

The Use of Fire Dynamics System (NIST) in Determining The Architecture of Educational Spaces for Children and Young People

Objective: This study aims to investigate the potential of the Fire Dynamics Simulator (FDS) software, developed by the National Institute of Standards and Technology (NIST), as a tool to assess and improve Fire Safety (FS) in educational environments, specifically in the classrooms of CEFET in Araxá (MG), Brazil. Theoretical Framework: The research is based on the importance of fire safety in educational environments, highlighting the vulnerability of children and young people. Concepts of fire behavior, smoke propagation, and thermal conditions in buildings are addressed. Method: The methodology adopted for this research involves detailed computer simulations using FDS to analyze different fire scenarios. The simulation results were validated with the PyroSim software. Data collection was conducted through these simulations, generating robust empirical data that support the review and development of specific regulations. Results and Discussion: The results indicate that FDS is an important ally in promoting fire safety in educational buildings. The simulations showed the effectiveness of FDS in predicting fire behavior, smoke propagation, and thermal conditions, helping to prevent and minimize potential damages. The discussion contextualizes these results, highlighting the need for accurate empirical data to strengthen Brazilian fire safety legislation. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied to positively influence legislation, optimize architectural designs, and promote safety guidelines in educational institutions in Brazil. Originality/Value: This study significantly contributes to the advancement of knowledge and practices in FS. The originality of the research lies in the application of FDS for simulations in educational environments, offering a robust tool for evaluating and improving fire safety.

Evaluating crown scorch predictions from a computational fluid dynamics wildland fire simulator

BackgroundCrown scorch—the heating of live leaves, needles, and buds in the vegetative canopy to lethal temperatures without widespread combustion—is one of the most common fire effects shaping post-fire canopies. Despite the ability of computational fluid dynamic models to finely resolve fire activity and buoyant plume dynamics including heterogenous 3D distributions of forest canopy heating, these models have had only limited use in simulating fire effects and have not been used to evaluate crown scorch. Here, we demonstrate a method of evaluating crown scorch using a computational fluid dynamics model, FIRETEC, and validate this approach by simulating the experiments that were used to develop Van Wagner’s 1973 crown scorch model.ResultsThe average scorch height prediction from FIRETEC compares well with the empirical model derived by Van Wagner, which is the most widely used empirical model for crown scorch. We further find that the 3D buoyant plume dynamics from a steady and homogeneous idealized heat source on the ground results in a spatially heterogenous crown scorch pattern reflecting complex heating dynamics that are best represented by percent scorch rather than height of scorch.ConclusionsThe ability of the computational fluid dynamics model to capture variation in crown scorch due to 3D buoyant plume dynamics provides direct links between forest structure, fire behavior, and fire effects that can be used by forest managers and researchers to better understand how fires result in crown damage under various environmental and management scenarios.

Study on the window spill fire plume trajectory of over-ventilated intermediate-scale compartment fires

The fire plume behavior of over-ventilated compartment fire is believed to be related with the façade fire. When the fire plume is reattached to the façade wall, the combustible materials over building wall are potential to be ignited soon. To investigate the window spill fire plume trajectory of over-ventilated intermediate-scale compartment fires, a modeling of fire plume trajectory is set up by using the energy conservation equation and spread theory. The temperature history of over-ventilated compartment fire is conducted by using a 1.35 m (L) × 1.35 m (H) × 1.35 m (W) compartment with window opening aspect varied from 1.12 to 4.44 and HRR differed from 200 kW to 1000 kW. The temperature of fire plume is recorded by the thermocouple mesh and the IR camera. It shows that the modelling theory could be used to predict the shape of fire plume. It agrees well with experimental result. The heat release rate of compartment fire is found to impact little influence on the shape of fire plume regarding a fixed opening dimension. It could provide a reasonable method for fire plume trajectory prediction of the intermediate-scale enclosure fire under an over-ventilated condition.

Immediate effect of local vibration on motor unit firing behavior and muscle strength in healthy young adult males

PurposeThe aim of this study was to examine the effect of vibration on motor unit (MU) firing behavior and physical performance of antagonist muscles in healthy young adult males.MethodsFourteen males (age = 24.3 ± 3.6 years) were included in this study. There were two conditions, one in which participants received 80 Hz vibration in the distal tendon of the hamstring for 30 s and the control condition (no vibration). High-density surface electromyography (HD-SEMG) signals and maximal voluntary contraction (MVC) of knee extensor muscles were evaluated before and after the respective conditions and recorded from the vastus lateralis muscle during submaximal ramp-up and sustained contractions at 30% MVC. Convolution blind source separation was used to decompose the HD-SEMG signals into individual MU firing behaviors.ResultsIn total, 739 MUs were detected (control; 360 MUs and vibration; 379 MUs), and a total of 312 matched MUs were identified across both submaximal contraction conditions (control: 150 MUs; vibration: 162 MUs). Vibration significantly increased the discharge rate (p = 0.047) and decreased the recruitment threshold before and after intervention (p = 0.001) but not in the control condition. Furthermore, the recruitment threshold is a factor that influences discharge rate. Significant correlations were observed between the recruitment threshold and both the ∆ discharge rate and the ∆ recruitment threshold under the vibration condition (p < 0.001).ConclusionVibration increased in the discharge rate and decreased the recruitment threshold of the antagonist muscle. These findings suggested that vibration contributes to immediate changes in the neural control of antagonist muscles.