Experimental validation of a numerical model for the transport of firebrands

Kortas, S.; Mindykowski, Pierrick; Consalvi, Jean-Louis; Mhiri, Hatem; Porterie, B.

doi:10.1016/j.firesaf.2009.08.001

Cited by 32 publications

(19 citation statements)

References 17 publications

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“…from the atmospheric boundary layer to the fire-induced flow, is assumed to be parameterised by the turbulent diffusion coefficient D T only. The determination of the PDF of the downwind distribution of firebrands has been studied by numerical solution of balance equations (Sardoy et al, 2008;Kortas et al, 2009). Sardoy et al (2008) found that the phenomenon follows a bimodal distribution, but only the firebrands with shortdistance landing were considered important for the analysis of danger related to fire spotting, since they have the potential to ignite a new fire, while those with a long-distance landing reach the ground in a charred oxidation state.…”

Section: Model Discussionmentioning

confidence: 99%

“…In fact, extremely important phenomena in wildland fire propagation are turbulent hot-air transport due to the turbulent nature of the atmospheric boundary layer that can consequently affect fire-atmosphere interactions (Clark et al, 1996;Potter, 2002Potter, , 2012aLinn and Cunningham, 2005;Sun et al, 2006;Filippi et al, , 2011Sun et al, 2009;Mandel et al, 2011;Forthofer and Goodrick, 2011), as well as the fire spotting phenomenon (Sardoy et al, 2007(Sardoy et al, , 2008; Kortas et al, 2009;Perryman, 2009;Bhutia et al, 2010;Koo et al, 2010;Wang, 2011;Morgante, 2011;Perryman et al, 2013). Both processes have a random character; therefore, the fire front motion turns out to be random.…”

Section: Introductionmentioning

confidence: 99%

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Modelling wildland fire propagation by tracking random fronts

Pagnini

Mentrelli

2014

Nat. Hazards Earth Syst. Sci.

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Abstract. Wildland fire propagation is studied in the literature by two alternative approaches, namely the reactiondiffusion equation and the level-set method. These two approaches are considered alternatives to each other because the solution of the reaction-diffusion equation is generally a continuous smooth function that has an exponential decay, and it is not zero in an infinite domain, while the levelset method, which is a front tracking technique, generates a sharp function that is not zero inside a compact domain. However, these two approaches can indeed be considered complementary and reconciled. Turbulent hot-air transport and fire spotting are phenomena with a random nature and they are extremely important in wildland fire propagation. Consequently, the fire front gets a random character, too; hence, a tracking method for random fronts is needed. In particular, the level-set contour is randomised here according to the probability density function of the interface particle displacement. Actually, when the level-set method is developed for tracking a front interface with a random motion, the resulting averaged process emerges to be governed by an evolution equation of the reaction-diffusion type. In this reconciled approach, the rate of spread of the fire keeps the same key and characterising role that is typical of the level-set approach. The resulting model emerges to be suitable for simulating effects due to turbulent convection, such as fire flank and backing fire, the faster fire spread being because of the actions by hot-air pre-heating and by ember landing, and also due to the fire overcoming a fire-break zone, which is a case not resolved by models based on the level-set method. Moreover, from the proposed formulation, a correction follows for the formula of the rate of spread which is due to the mean jump length of firebrands in the downwind direction for the leeward sector of the fireline contour. The presented study constitutes a proof of concept, and it needs to be subjected to a future validation.

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Section: Model Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modelling wildland fire propagation by tracking random fronts

Pagnini

Mentrelli

2014

Nat. Hazards Earth Syst. Sci.

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“…This convective and radiative transfer of heat causes a rapid ignition of the unburned fuel bed and leads to a faster spread of the fire. Turbulence can also facilitate the generation of spot fires when the firebrands are transported away from the main fire due to advection [26,27,28,29,30]. The effect of such random phenomena can range from subdued to catastrophic depending upon the concurrent weather conditions and fuel characteristics.…”

Section: Introduction and Motivationsmentioning

confidence: 99%

Turbulence and fire-spotting effects into wild-land fire simulators

Kaur

Mentrelli

Bosseur

et al. 2016

Communications in Nonlinear Science and Numerical Simulation

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This paper presents a mathematical approach to model the effects of phenomena with random nature such as turbulence and fire-spotting into the existing wildfire simulators. The formulation proposes that the propagation of the fire-front is the sum of a drifting component (obtained from an existing wildfire simulator without turbulence and fire-spotting) and a random fluctuating component. The modelling of the random effects is embodied in a probability density function accounting for the fluctuations around the fire perimeter which is given by the drifting component. In past, this formulation has been applied to include these random effects into a wildfire simulator based on an Eulerian moving interface method, namely the Level Set Method (LSM), but in this paper the same formulation is adapted for a wildfire simulator based on a Lagrangian front tracking technique, namely the Discrete Event System Specification (DEVS). The main highlight of the present study is the comparison of the performance of a Lagrangian and an Eulerian moving interface method when applied to wild-land fire propagation. Simple idealised numerical experiments are used to investigate the potential applicability of the proposed formulation to DEVS and to compare its behaviour with respect to the LSM. The results show that DEVS based wildfire propagation model qualitatively improves its performance (e.g., reproducing flank and back fire, increase in fire spread due to pre-heating of the fuel by hot air and firebrands, fire propagation across no fuel zones, secondary fire generation, \dots). Though the results presented here are devoid of any validation exercise and provide only a proof of concept, they show a strong inclination towards an intended operational use. The existing LSM or DEVS based operational simulators like WRF-SFIRE and ForeFire respectively can serve as an ideal basis for the same.Comment: Accepted for publication in Commun. Nonlinear Sci. Numer. Simula

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“…Physics based on coupled fire-atmosphere models consider approximations of the governing equations from the fluid dynamics, the combustion, and the thermal degradation of solid fuel (see, e.g., [64][65][66]) aiming to preclude the use of existing simplified empirical wildfire models because they do not predict general fire behaviour; however the high-resolution and the high-fidelity combustion are not currently appropriate because of their computational cost. Several physics based on coupled fire-atmosphere studies have been conducted (see [67][68][69][70][71][72]) and some of these studies have been applied to the fire spotting problem. Among them [71] has considered particle combustion of cylindrical and disk-shaped firebrands for several geometrical parameters.…”

Section: Introductionmentioning

confidence: 99%

Calculation of Spotting Particles Maximum Distance in Idealised Forest Fire Scenarios

Pereira

Leite

et al. 2015

Journal of Combustion

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Large eddy simulation of the wind surface layer above and within vegetation was conducted in the presence of an idealised forest fire by using an equivalent volumetric heat source. Firebrand’s particles are represented as spherical particles with a wide range of sizes, which were located into the combustion volume in a random fashion and are convected in the ascending plume as Lagrangian points. The thermally thin particles undergo drag relative to the flow and moisture loss as they are dried and pyrolysis, char-combustion, and mass loss as they burn. The particle momentum, heat and mass transfer, and combustion governing equations were computed along particle trajectories in the unsteady 3D wind field until their deposition on the ground. The spotting distances are compared with the maximum spotting distance obtained with Albini model for several idealised line grass or torching trees fires scenarios. The prediction of the particle maximum spotting distance for a 2000 kW/m short grass fire compared satisfactorily with results from Albini model and underpredicted by 40% the results for a high intensity 50000 kW/m fire. For the cases of single and four torching trees the model predicts the maximum distances consistently but for slightly different particle diameter.

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Experimental validation of a numerical model for the transport of firebrands

Cited by 32 publications

References 17 publications

Modelling wildland fire propagation by tracking random fronts

Modelling wildland fire propagation by tracking random fronts

Turbulence and fire-spotting effects into wild-land fire simulators

Calculation of Spotting Particles Maximum Distance in Idealised Forest Fire Scenarios

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