Fire behavior in chaparral–Evaluating flame models with laboratory data

Weise, David R.; Fletcher, Thomas H.; Cole, Wesley; Mahalingam, Shankar; Zhou, Xiangyang; Sun, Lulu; Li, Jing

doi:10.1016/j.combustflame.2018.02.012

Cited by 17 publications

(5 citation statements)

References 60 publications

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“…Agreement between the observed and predicted values of flame height and flame tilt was quantified using the measures identified in Cruz and Alexander (2013) and Weise et al (2018b). These error analysis schemes have been previously used in analyzing results from wildland fire behavior studies (Cruz and Alexander, 2013).…”

Section: Error Analysismentioning

confidence: 99%

“…Moreover, a numerical analysis of flame tilt angle and height, in a spreading shrub fire was presented by Morvan (2007). Recent work by Weise et al (2018b) compared predictions from flame models to results from experimental circular and line fire configurations of chaparral fire. Model predictions of flame height and flame tilt angle, were compared against experimental values in work by Nelson et al (2012).…”

Section: Introductionmentioning

confidence: 99%

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On the Use of Semi-empirical Flame Models for Spreading Chaparral Crown Fire

et al. 2019

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Flame geometry plays a key role in shaping fire behavior as it can influence flame spread, radiative heat transfer and fire intensity. For wildland fire, thorough characterizations of flame geometry can help advance the derivation of comprehensive models of wildfire behavior. Within the fire community, a classical flame modeling approach has been to develop semi-empirical models. Many of these models have been derived for surface fuels or for pool fire configurations. However, few have sought to model flame behavior in chaparral crown fires. Thus, the objective of this study is to assess the applicability of semi-empirical models on observed chaparral crown fire behavior. Semi-empirical models of flame tilt, flame height, and flame length from the literature are considered. Comparison with experimental observation of flame height in the crown fuel layer, showed good agreement between the 2/5th power law that relates flame height to heat release rate. Two new power-law correlations relating flame tilt angle to Froude number are proposed. The coefficients for new models are obtained from regression analysis.

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Section: Error Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On the Use of Semi-empirical Flame Models for Spreading Chaparral Crown Fire

et al. 2019

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“…The direction of the thermal plume was in the same direction as of the wind but as the flame approached the field of view, the thermal plume was more aligned with the direction of the flame due to the strong buoyancy force. Even though the Byram's convective number (Nelson 1993;Weise et al 2018a) for this case was calculated to be 67, which indicates the presence of high radiation power, BOS visualized a strong convective flow ahead of the flame. After 141 seconds from ignition, as the flame passed the field of view, the wind was visualized.…”

Section: Visualization Of the Thermal Plume Of Propagating Flamementioning

confidence: 74%

Using Background-Oriented Schlieren to Visualize Convection in a Propagating Wildland Fire

Aminfar

Cobian-Iñiguez

Ghasemian

et al. 2019

Combustion Science and Technology

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Heat and mass transfer are important processes associated with wildland fire. Both radiant and convective heat transfer are important processes with convection often being the dominant mechanism. Unlike radiation, there is no direct method of measuring convection. Since convective heat transfer is governed by the fluid flow, understanding the fluid flow provides good understanding on the convective heat transfer. In fluid mechanics, flow visualization is a common methodology used to understand flow characteristics. Schlieren imagery is a common flow visualization technique which captures changes in fluid density such as the ones occur around a fire. Background-Oriented Schlieren (BOS) is a flow visualization technique that uses a background image with various patterns to visualize the density gradient caused by density fluctuations in a fluid. We applied BOS to measure the flow associated with laboratory-scale line fires. The reproducible fires were spreading in pine needle fuel beds in a wind tunnel with and without imposed wind. This initial application of BOS in a fire environment successfully visualized the flow around the flame. The visualized flow underwent a secondary process to produce the velocity field of the flow. Results indicate that even in conditions where the fire is known to be dominated by radiation, wind carried the thermal plume ahead of the flame front and expanded the thermal plume. In contrast, in the no wind condition, the thermal plume remained vertical above the fire. Using the BOS imagery, a new model for estimation of convective heat transfer was introduced. In addition to estimation of the convective heat transfer ahead of the fire, this new model enables visualization of convective motion.

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“…In fact, fireline intensity is a function of rate of spread, which in turn is a function of a different I R , resulting in two different reaction intensities for the same fuel bed. Studies have shown that the fireline intensityflame length relationship produces better approximations for low-intensity fires, such as observed in prescribed burns in light grass and pine needle fuel beds (Byram 1959;Alexander and Cruz 2012;Weise et al 2018).…”

Section: Discussionmentioning

confidence: 99%

Reaction intensity partitioning: a new perspective of the National Fire Danger Rating System Energy Release Component

Fujioka

Weise

Chen

et al. 2021

Int. J. Wildland Fire

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The Rothermel fire spread model provides the scientific basis for the US National Fire Danger Rating System (NFDRS) and several other important fire management applications. This study proposes a new perspective of the model that partitions the reaction intensity function and Energy Release Component (ERC) equations as an alternative that simplifies calculations while providing more insight into the temporal variability of the energy release component of fire danger. We compare the theoretical maximum reaction intensities and corresponding ERCs across 1978, 1988 and 2016 NFDRS fuel models as they are currently computed and as they would be computed under the proposed scheme. The advantages and disadvantages of the new approach are discussed. More study is required to determine its operational implications.

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Fire behavior in chaparral–Evaluating flame models with laboratory data

Cited by 17 publications

References 60 publications

On the Use of Semi-empirical Flame Models for Spreading Chaparral Crown Fire

On the Use of Semi-empirical Flame Models for Spreading Chaparral Crown Fire

Using Background-Oriented Schlieren to Visualize Convection in a Propagating Wildland Fire

Reaction intensity partitioning: a new perspective of the National Fire Danger Rating System Energy Release Component

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