Fire and Materials最新文献

Combustible dust poses a hazard to industry in two ways, i.e., reactive as a cloud or reactive as a pile. This paper deals with the smouldering behaviour of wood dust deposits initiated by hot bodies. Effects of embedded depth and airflow condition are investigated. Two sizes of wood dust are selected as test samples, namely wood powder and wood chip. The results indicate that under the same hot bodies embedded depth, wood chip combustion propagates faster than wood powder in general due to its unique flocculent structure. Due to the increased insulation effect of the wood dust layer, the temperature at the same measuring point is higher than that of the wood chip layer. In addition, under airflow conditions, the smouldering propagation of wood deposits is significantly higher than that without airflow (2.42 and 4.34 m/s) for both wood powder and wood chip samples. However, the deposited wood powder has a lower minimum ignition temperature than wood chip. Accumulated wood dust in considered to have a greater fire risk in powder form.

Ornamental vegetation constitutes the main type of natural fuel within the wildland-urban interface. Its flammability is often the criteria that fire risk managers use to promote certain species against others, with direct repercussions in fire safety. Traditionally, flammability is assessed using four parameters (ignitability, combustibility, sustainability, and consumability), through small-scale laboratory tests. Although widely used, these techniques fail to reflect the actual burning behaviour of species when they ignite. In our study, we developed an experimental method to classify ornamental vegetation's flammability based on full-scale burning behaviour. We categorise flammability into three levels: low (resists ignition), medium (acts as ladder fuel), and high (spreads fire). To evaluate this, we model normalised weight loss rate curves as Gaussian functions (flammability bells) and use metrics from these functions (maximum weight loss per second, associated time and standard deviation) as combustibility indicators. Experimental results reveal that these metrics can effectively differentiate between low, medium and high flammability. The method was developed by burning ornamental trees from four typical Mediterranean species (Leyland cypress, Arizona cypress, Northern white-cedar, and Cherry laurel) with varying spatial configurations, physiological statuses and moisture content. Our method is straightforward, robust, and affordable for implementation in appropriately equipped fire laboratories, offering meaningful insights into vegetation flammability and fire behaviour in the wildland-urban interface. These experimental results can help reduce fire risk from ornamental vegetation in human settlements.

Grassy vegetation represents a significant fuel source in multiple fire-prone regions around the globe. These fuels are a major component of surface fuel beds and are therefore typically the first layer of the wildland fuel strata that ignites. Thus, understanding the drivers of successful grassy fuel ignition is key to developing a comprehensive description of the process leading to fire spread. In the wildland-urban interface, hot metal particles produced by powerline failures or mechanical equipment operations are a leading ignition source for these types of fuels. The goal of this study is to develop improved understanding of the role of fuel species and physical characteristics on the ignition behavior of grass fuels when exposed to hot metal particles. Three common California invasive grass species were studied in their natural configuration as well as in configurations in which fuel particles have been shredded or made into a powder. Overall, it was observed that the ignition temperature was lower in fuels in their powder form than fuels in a shredded or natural form. Furthermore, the findings here align with prior works, indicating that the presence of chemical compounds such as lignin and proteins may hinder ignition. Consequently, wheatgrass fuels, which have higher lignin and protein content, consistently required higher temperatures to ignite (460°C) compared to Avena (370°C), Bromus (348°C), and excelsior fuels (350°C), which contain these compounds in lower concentrations.

In recent years, wildfires in residential regions have increasingly inflicted significant economic and social losses. Preemptive measures can reduce the damage to public infrastructure and lessen these impacts. Rapid evaluation of residential structures after wildfire is crucial for investigating the overall scope of the damage and establishing an effective disaster mitigation strategy. However, conducting these assessments involves detailed on-site examinations, which require considerable time and workforce. Furthermore, these qualitative assessments can be subjective and prone to error. To overcome these shortcomings, this study suggests a practical methodology for performing damage assessments of housing after a wildfire using deep learning technology. The applications of deep learning to three different image sources for residential areas are analyzed and compared as follows: uncrewed aerial systems imagery, aerial imagery, and satellite imagery. Notably, combinations of these image sources were considered from the training stage, and the impact of changes in training data when applied to each image source was comprehensively investigated. Key results reveal achievable accuracies depending on the various remote sensing data sources used in the training and application phases. This study is expected to provide deep learning researchers working on wildfires with a fundamental resource for the comprehensive use of remote sensing data and to provide valuable insights into the decision-making process for wildfire responders.

Tungsten delay compositions are widely utilized in ammunition, small detonators, and other devices. In this study, we first explored the changes in the burning rate of micron-sized tungsten delay compositions (W/BaCrO₄/KClO₄) when achieving zero oxygen balance under different material tube walls. Subsequently, SiO₂, CuO, BN, and shellac were added to the tungsten delay composition to investigate the burning rate variations of different samples in aluminum tubes. The experimental results reveal that the combustion rate of the tungsten delay composition decreases with an increase in the thermal conductivity of the tube wall. The content of BN exhibits a linear relationship with the combustion rate of the tungsten delay composition, the combustion rate of the tungsten delay composition decreases with the increase of the mass percentage of BN. A small amount of SiO₂, CuO, and shellac accelerates the combustion rate of the tungsten delay composition, but the combustion rate decreases as the content of these additives increases. The conclusion of this study can provide a wider range of delay times for delay devices with significant spatial limitations.

Fiber dust's flocculent structure often leads to underestimation of its potential for fire and explosion. In order to compare the fire hazards of fiber dust layers with different widths and inclination angles exposed to simulated hotspots with traditional powdered dust layers. The current research systematically studied the flame spread characteristics of flax, paper scraps, and wood dust with widths of 20, 30, 40, 50, and 60 mm at inclination angles of 0°, −10°, −20°, −30° and −40°. Studies have found that at different widths and inclination angles, flax dust has a higher flame spread velocity than wood powder, and even metal powder. Under the coupling effect of the width and inclination angle of the countercurrent flame, the inclination angle has a significant impact on the flame spread velocity of the countercurrent flame. Flax fiber dust has a significantly higher fire hazard than conventional dust. These findings should be taken into account in the industrial processes of handling flax fiber dust.

Wildfires arriving at a brush-cleared vegetation near vulnerable assets in the Wildland-Urban Interface (WUI), experience significantly reduced fire propagation, intensity, and associated risks. However, assessing the effectiveness of fuel reduction on fire behavior remains challenging due to limited understanding of ignition and propagation mechanisms in live vegetation. To fill this gap, a simplified approach was designed, focusing more on the combination of physical modeling with new empirical data rather than providing new insight in the physical process modeling. Burning experiments were conducted on cypress trees at two scales of live vegetation, the “laboratory scale” and the “real scale,” to gather data on fire behavior in cypress canopies with varying fuel moisture content (FMC) and bulk density (BD), using two ignition methods. A semi-empirical model, based on the physical model Fire Dynamic Simulator was developed, using the “laboratory scale” data as inputs, while the data recorded at “real scale” were used to validate the model. Laboratory-scale experiments showed consistent results when ignition was initiated by flame contact. In contrast, indirect radiant heat ignition was highly variable due to the influence of gaps between leaves. At the real scale, BD had a significant impact on fire behavior. The model evaluation showed it could simulate fire auto-propagation in live vegetation much more precisely compared to current physical models, leveraging the precise fire behavior data obtained at the laboratory scale.