Frontiers in Mechanical Engineering (Sep 2019)

Air Permeability of the Litter Layer in Broadleaf Forests

  • Houzhi Wang,
  • Houzhi Wang,
  • Philip J. van Eyk,
  • Paul R. Medwell,
  • Cristian H. Birzer,
  • Zhao F. Tian,
  • Malcolm Possell,
  • Malcolm Possell,
  • Xinyan Huang

DOI
https://doi.org/10.3389/fmech.2019.00053
Journal volume & issue
Vol. 5

Abstract

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Fuel on the ground, such as leaves, twigs and decomposing matter, accumulate over time and account for a large percentage of the total fuel load in forests. In fire events, material on the ground is often referred to as a fuel bed. The air permeability of a fuel bed is a critical factor that influences fire behavior because it controls the amount of air or oxygen available for combustion within the fuel bed. The aim of this study is to provide a better understanding of the air permeability of the fuel beds in forests. The air permeability for different fuel beds were determined using experimental and theoretical methods. The pressure drop across the fuel bed samples were experimentally measured using a verified permeability testing rig. The air permeability was then calculated using Darcy's Law or the Forchheimer equation from the pressure drop measurements, depending on the Reynolds number. The particles in the fuel beds were characterized in terms of particle size and shape. Based on the particle characterization, the air permeability of the fuel beds was also calculated using the Kozeny-Carman equation. The results show that the experimental method is preferred when determining the air permeability for natural forest fuel beds due to the variability in the size and shape of the particles. The effect of Reynolds number on effective permeability was aslo investigated, and it was found that the transition from Darcian to non-Darcian flow occur at different Reynolds numbers for different fuel particles. For example, the transition occurs at 5 and 15 for gum bark and decomposing matter, respectively. The significance of this study is that it increases the ability to predict the air permeability of fuel beds in forests, which is essential for modeling wildland fire behaviors involving in porous fuel beds. All the samples were dried at 105°C to remove moisture in the samples.

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