Simulation study of grass fire using a physics-based model: striving towards numerical rigour and the effect of grass height on the rate of spread

Abstract

Grid-independent rate of spread results from a physics-based simulation are presented. Previously, such a numerical benchmark has been elusive owing to computational restrictions. The grid-converged results are used to systematically construct correlations between the rate of spread (RoS) and both wind speed and grass height, separately. The RoS obtained from the physics-based model is found to be linear with wind speed in the parameter range considered. When wind speed is varied, the physics-based model predicts faster RoS than the Mk III and V (McArthur) models (Noble et al. 1980) but slower than the CSIRO model (Cheney et al. 1998). When the grass height is varied keeping the bulk density constant, the fire front changes from a boundary layer flame mode to plume flame mode as the grass height increases. Once the fires are in plume mode, a higher grass height results in a larger heat release rate of the fire but a slower RoS.

The effect of fuel bed height in grass fire spread: addressing the findings and recommendations of Moinuddin et al. (2018)

“…The present analysis used fire spread measurement data from two outdoor experimental burning studies in grass fuels where an explicit control of fuel height was imposed to verify the realism of their results. It was found that a reduction in grass height, with or without removal of the cut fuel and regardless of the Froude number, led to a significant reduction in rate of fire spread, a result opposite to the simulations obtained by Moinuddin et al (2018).…”

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A recent numerical simulation study by Moinuddin et al (2018) determined that over a specific range of Froude numbers defined by them as 'plume mode', grass fuel height has a strong inverse effect on the rate of fire spread in grasslands. They then suggested that a relationship for effect of fuel height derived from their simulation results could be used to support fire management decision-making.

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Mathematical Modeling of Heat Transfer in an Element of Combustible Plant Material When Exposed to Radiation from a Forest Fire

“…The methodology for forest fire risk assessment can be based on developments in the field of complex risk assessment, which is used in industry [83,84]. Program tools developed on the basis of the considered mathematical model can be applied for different problems in forest fire management, such as forest fire danger and spread prediction [85], classification and mapping of wildland fuels [86], analysis of fire regime [87], operation in global vegetation models [88], and prediction of grass mortality [89].…”

Physics-Based Simulation of Heat Load on Structures for Improving Construction Standards for Bushfire Prone Areas

“…The lack of a flame angle model may also be a critical flaw; it has been established for some time that there are two modes of fire propagation in wild, industrial, and building fires (Apte et al, 1991;Morvan and Frangieh, 2018). Grassfires have been characterized as wind dominated and buoyancy dominated fires (Dold and Zinoviev, 2009;Moinuddin et al, 2018;Morvan and Frangieh, 2018). In the wind dominated mode the shearing fluid flow (that is, the wind) dominates over the buoyant flow (the updraft from the fire plume).…”

“…FDS has been carefully validated for the simulation of grassfires. Both Mell et al (2007) and Moinuddin et al (2018) have compared simulation results to experimental results from Cheney et al (1998). The simulations were shown to reproduce the measured rate-of-spread.…”