Fire Spotting Effects in Wildland Fire Propagation

Pagnini, Gianni

doi:10.1007/978-3-319-06953-1_20

Cited by 4 publications

(6 citation statements)

References 15 publications

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“…The proposed approach is based on the idea to split the motion of the front position into a drifting part and a fluctuating part [35,36,37,38,39,40,53,54]. This splitting allows specific numerical and physical choices which can be useful to improve the algorithms and the models.…”

Section: Random Effects Formulationmentioning

confidence: 99%

“…This formulation can be implemented into existing wildfire models as a post-processing scheme at each time step without calling for any major changes in the original framework. The efficacy of this formulation by using a LSM based fire propagation model has already been shown [35,36,38,39,40].…”

Section: Introduction and Motivationsmentioning

confidence: 99%

“…The present authors in a number of their recent works [35,36,37,38,39,40] have proposed a new approach to include the effects of random processes in some operational wildfire propagation models. They derive a formulation to modify the modelled position of the fire-front to include random processes.…”

Section: Introduction and Motivationsmentioning

confidence: 99%

“…In this study, the authors proceed with their preliminary attempt [41] to include the proposed formalism for random processes (turbulence and fire-spotting), already discussed and implemented into an Eulerian LSM based wild-land fire simulator [35,36,37,38,39,40], into a Lagrangian DEVS based wild-land fire simulation model: ForeFire (https://github.com/forefireAPI/firefront) [13].…”

Section: Introduction and Motivationsmentioning

confidence: 99%

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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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Section: Random Effects Formulationmentioning

confidence: 99%

Section: Introduction and Motivationsmentioning

confidence: 99%

Section: Introduction and Motivationsmentioning

confidence: 99%

Section: Introduction and Motivationsmentioning

confidence: 99%

See 2 more Smart Citations

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

Kaur

Mentrelli

Bosseur

et al. 2016

Communications in Nonlinear Science and Numerical Simulation

Self Cite

View full text Add to dashboard Cite

show abstract

“…To better characterize these nonlinear processes, there is a need to develop new submodels including the effects of random processes such as turbulence and fire-spotting in operationally-oriented wildfire spread models. This is one of the objectives of the work proposed in [54,53,55,29], which introduces a randomized representation of the fireline. A novel family of reaction-diffusion equations have been developed to link front models to reaction-diffusion ones and thereby integrate the effects of random processes in fire models.…”

Section: Introductionmentioning

confidence: 99%