An Experimental Study Evaluating the Burning Dynamics of Pitch Pine Needle Beds Using the FPA

Jan C. Thomas, A. Simeoni, Michael R. Gallagher, N. Skowronski
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引用次数: 12

Abstract

Pine needle litters, a key fuel in coniferous forest systems, are highly porous fuel beds. They provide a source of continuous fuel medium that can be easily ignited and will sustain flame spread on the ground during forest fires. This work represents an experimental study that is focused on the influence of the fuel moisture content on the burning dynamics and the flammability characteristics of forest fuel beds. The FM Global Fire Propagation Apparatus was utilized to obtain time to ignition, heat release rate, total heat released and CO/CO2 concentration data. The methodologies applied in previous studies were improved with new modifications. The results were analyzed with respect to the sample’s fuel moisture content as well as other test conditions, such as airflow condition (wind), sample holder openness and external heat flux. The importance of the fuel moisture content is critical to understand as the majority of fuels present in the natural environment have elevated moisture content compared to dead dry fuel. Samples studied are representative of wet ground fuels as well as live fuels which do burn when crowning conditions develop. The results presented here are a building block for developing an experimental database that can be used to understand the influence of environmental conditions on the flammability of porous forest fuels and assess the risks that comes with a wildfire. Furthermore, the data can also be used for fire behavior model validation.
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用FPA评价沥青松针床燃烧动力学的实验研究
松针凋落物是针叶林系统的重要燃料,是高度多孔的燃料床。它们提供了一种连续的燃料介质,可以很容易地点燃,并在森林火灾期间维持火焰在地面上的蔓延。本文主要研究了燃料含水率对森林燃料床燃烧动力学和可燃性特性的影响。利用FM全球火焰传播仪获得点火时间、放热率、总放热量和CO/CO2浓度数据。在以往的研究中应用的方法得到了改进,并进行了新的修改。分析了样品的燃料含水率以及其他测试条件,如气流条件(风)、样品支架开度和外部热通量。理解燃料水分含量的重要性是至关重要的,因为与完全干燥的燃料相比,存在于自然环境中的大多数燃料的水分含量较高。所研究的样品既有湿地燃料的代表,也有在形成顶盖条件时燃烧的活燃料的代表。这里提出的结果是开发一个实验数据库的基础,该数据库可用于了解环境条件对多孔森林燃料可燃性的影响,并评估野火带来的风险。此外,这些数据还可以用于火灾行为模型的验证。
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