Fire and Materials最新文献

With global warming, the wildfire season tends to get longer, causing fatalities and devastating damage to human property. Although many countries have implemented fire risk prevention measures, particularly in Wildland Urban Interfaces (WUI), this finding shows that there are weaknesses in the prevention measures. This is mainly due to a lack of knowledge about WUI fire exposure conditions. This paper presents field-scale experiments to characterise the burning of rockrose-reconstructed hedges (6 × 1 × 1 m) close to a building in order to provide experimental data on heat release rate (HRR), flame front geometry, and heat fluxes to the building. The mean horizontal flame extent was 4.4 (±0.7) m with values up to 5.5 m. These values are generally higher than the minimum distance to be maintained between vegetation and buildings in most countries. The fire intensity ranged from 283 to 3479 kW/m, resulting in maximum values at 3 m from the hedge of up to 45.4 kW/m² for the total heat flux and 38.1 kW/m² for the radiant heat flux. However, the flame duration is short, averaging 112.8 (±27.1) s. This type of exposure is far from those used to test the fire resistance worldwide. Therefore, the data obtained in this study are crucial for improving fire risk prevention methods worldwide, whether for fuel management in defensible zones or for testing building materials to make buildings more resistant to wildfires.

Smoldering combustion, often linked with forest fires in coniferous forests, pose significant health and environmental risks, particularly in densely populated countries like Germany, where these fires commonly occur in wildland–urban interface (WUI) areas. This study investigates the combustion characteristics of Pinus sylvestris soil, focusing on the underlying processes and thermal behavior. The aim is to provide a comprehensive analysis of smoldering combustion in pine forest soil, with a specific focus on fire-exposed soil horizons. The research integrates soil characterization, elemental analysis, heat of combustion determination, and thermogravimetric analysis (TGA) of pine soil fractions ranging from < 0.063 to > 4 mm, conducted under both air and nitrogen atmospheres. The derivative thermogravimetry (DTG) curves reveal that the fastest mass loss occurs during pyrolysis, with peak temperatures between 240°C and 280°C. Activation energies (E _a ) were calculated using the Kissinger–Akahira–Sunose (KAS) and Flynn–Wall–Ozawa (FWO) methods. The highest activation energies were observed between conversion rates of 0.2 and 0.4. Activation energies at peak temperatures for all fractions were determined using the Kissinger method. Residue analysis reveals significant variations in organic content, ranging from 22.6% to 92.7%. The findings demonstrate that German-typical pine soil is prone to smoldering combustion, highlighting processes determined as preheating, drying, pyrolysis, and oxidation. As part of the German Pilot of the EUs TREEADS project, this study provides essential data for numerical simulations, emphasizing the need to consider both physical and chemical properties of soil fractions to mitigate the impact of smoldering fires in pine forest ecosystems.

Accurate estimation of heating temperatures experienced by fire retardant coatings (FRCs) is crucial in identifying the ignition source during fire investigations. While traditional methods, such as spectroscopy, effectively capture the compositional changes in FRC at various heating temperatures, they are typically bulky, costly, and unsuitable for rapid field analysis. This study proposes the use of smartphone and machine learning to predict the heating temperatures of FRC. A smartphone is employed to capture short videos of FRC samples illuminated by its color-changing screen. Video frames are then decomposed into color images and converted into spectral data for further processing. Linear and nonlinear regression models are applied to identify key variables and enhance predictive accuracy. The performance of smartphone-based temperature estimation is compared to that of hyperspectral imaging and laser-induced breakdown spectroscopy. In the test phase, the coefficient of determination for smartphone-based estimation ranges from 0.946 to 0.962, often surpassing that of benchmark methods. These results indicate that smartphones can provide a low-cost, effective means for estimating heating temperatures of FRC in fire investigations.

This paper presents the results of a standard fire resistance test of a loaded steel beam in a horizontal furnace. The beam was tested in three configurations: (1) unprotected, (2) protected with a single 22 mm layer of oriented strand board, and (3) protected with a double layer of the same cladding. The study also describes the development of a model in Fire Dynamics Simulator to predict the thermal conditions in the furnace and to observe the temperature trends on the beam surface, on the cladding, and at various depths in the cladding. A comparison between calculated and measured temperatures showed good agreement for the unprotected beam. However, for the protected beams, the model underestimated temperatures after 15 and 30 min for the single-layer and double-layer protection, respectively. Several potential sources for the discrepancies are identified. The main reason lies probably in the model's inability to correctly account for the effect of gaps in the cladding joints. Future work will focus on improving the accuracy of the model by removing these identified limitations, with particular attention to the behavior of the cladding as a passive fire protection material.