Empirical Modeling of Fire Spread Rate in No-Wind and No-Slope Conditions

Rossa, Carlos G.; Fernandes, Paulo M.

doi:10.1093/forsci/fxy002

Cited by 25 publications

(22 citation statements)

References 30 publications

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“…R 0 does not significantly depend on w [29,34,51], which is mathematically explained in [52]. That is not the case of R U , since w (an input to Equation 2) influences the mechanisms of fire spread by affecting the flame tilt caused by wind.…”

Section: Model Formulation and Fire Spread Mechanismsmentioning

confidence: 97%

“…Fuel beds were line-ignited and were 1-m wide and 5-8 m long. Because R 0 measurements were not available in [33], R 0 estimates were obtained using the model in [34], applicable to a general fuel bed, and R 0 was computed from:…”

Section: Laboratory Testingmentioning

confidence: 99%

“…where S v and ρ p are fuel particle surface area-to-volume ratio and fuel particle density, respectively. Equation 7was developed and validated in [34]: fitting was based in a dataset of 225 laboratory R 0 experiments and validation resorted to a comprehensive group of 106 field fires in very diverse fuel complexes.…”

Section: Laboratory Testingmentioning

confidence: 99%

“…Because it was not practical to obtain S m values for such a wide range of fuel species, we used a simplified version of Equation 7to estimate R 0 . This simplified R 0 model is equivalent to using Equation 7with S m = 7.7 m 2 •kg −1 and was shown to yield good results for a wide range of foliage-dominated fuel complexes [34]. Because w accounts for foliage fuels only and shrubs can have a significant amount of fine woody fuels thicker than foliage, the fine fuel load (FFL) of elements <2.5 mm was used as a surrogate for w and was estimated as 0.583 for Total FFL 0.854 [42].…”

Section: Field Testingmentioning

confidence: 99%

“…It may be surprising that h/H f of field fires could be roughly predicted based on M only, since flame geometry is expected to depend on other variables, such as fuel amount, but one must have in mind that some characteristics of natural vegetation vary within limited ranges around a mean value [34]. As a consequence, even when fuel characteristics are known to influence fire behavior metrics, sometimes they can be disregarded to obtain approximate estimates of a given fire behavior parameter.…”

Section: Model Formulation and Fire Spread Mechanismsmentioning

confidence: 99%

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An Empirical Model for the Effect of Wind on Fire Spread Rate

Rossa

Fernandes

2018

Fire

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Predicting wind-driven rate of fire spread (RoS) has been the aim of many studies. Still, a field-tested model for general use, regardless of vegetation type, is currently lacking. We develop an empirical model for wind-aided RoS from laboratory fires (n = 216), assuming that it depends mainly on fire-released energy and on the extension of flame over the fuel bed in still air, and that it can be obtained by multiplying RoS in no-wind and no-slope conditions by a factor quantifying the wind effect. Testing against independent laboratory and field data (n = 461) shows good agreement between observations and predictions. Our results suggest that the fuel bed density effect detected by other work may be a surrogate for the amount of fuel involved in combustion, which depends on fuel load. Because RoS under windless conditions is unaffected by fuel load, the involved mechanisms differ from wind-aided propagation. Compared to shallow fuel beds, the wind effect is usually modest in deep vegetation, because tall fuel complexes are dominated by live fuels (high moisture content) and flames extend less above the vegetation when fuel moisture is high. The present work warrants further inspection in a broader range of field conditions.

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