Quantifying effects on fire propagation in woody fuel models using the thin fuels assumption

Abstract

In this paper, we quantify the effects of thermally thin fuel prescriptions commonly made in numerical models that eliminate temperature gradients within a heated object. This assumption affects the modeled ignition and burn behavior but there is little research on its impact, particularly in larger fuels. We begin by comparing modeled to observed ignition times and burn rates. To control for the variability in the material properties of wood, as opposed to the modeled variability due to the thin-fuel assumption, we conduct experiments using thermogravimetric analysis (TGA) for samples of lodgepole pine. From this data, we derive material properties via optimization with genetic algorithms. We also perform burnout experiments on large, woody fuels to confirm ignition time and mass loss rates for a range of fuel specimens. These experiments are then repeated with a numerical modeling platform to validate the model. Once validated, we use the model to explore the significance of thermally thin fuel assumptions by performing the same analyses on fuels with both thermally thick and thermally thin fuel treatments. We quantify the above phenomena but also examine how the composition of fuels varies spatially and temporally.