No abstract

The analysis of laboratory fire experiments led to the development of a reaction-diffusion model for the spread of fire across a fuel bed in windless and slopeless conditions. A method for the determination of coefficients in this model based on the dynamic features of a spreading fire is given. The numerical study of the mathematical problem proposed allows us to predict the rate of spread, the fire front perimeter and the temperature distribution for line-ignition and point-ignition fires. These results are compared with success to experimental data. Furthermore, the model allows us to estimate the acceleration of spread for a point-ignition fire in its initial stage and in the steady-state phase. Résumé Une analyse menée sur des expériences de laboratoires nous a permis de proposer un modèle de réaction-diffussion pour la propagation du feu sans vent et sans pente au travers d’une litière. Une méthode d’identification des coefficients du modèle, à partir des caractéristiques dynamiques de la propagation du feu, est donnée. L’étude numérique du problème mathématique nous permet de prédire la vitesse de propagation, le périmètre du front de feu et la température dans le domaine d’étude pour des allumages en ligne et pour des allumages ponctuels. Ces résultats sont comparés avec succés à des données expérimentales. De plus, nous sommes aussi en mesure de décrire l’accélération du front de feu dans les premiers instants suivant un allumage ponctuel.

Simulating the interaction between fire and atmosphere is critical to the estimation of the rate of spread of the fire. Wildfire's convection (i.e., entire plume) can modify the local meteorology throughout the atmospheric boundary layer and consequently affect the fire propagation speed and behaviour. In this study, we use for the first time the Méso-NH meso-scale numerical model coupled to the point functional ForeFire simplified physical front-tracking wildfire model to investigate the differences introduced by the atmospheric feedback in propagation speed and behaviour. Both numerical models have been developed as research tools for operational models and are currently used to forecast localized extreme events. These models have been selected because they can be run coupled and support decisions in wildfire management in France and Europe. The main originalities of this combination reside in the fact that Méso-NH is run in a Large Eddy Simulation (LES) configuration and that the rate of spread model used in ForeFire provides a physical formulation to take into account the effect of wind and slope. Simulations of typical experimental configurations show that the numerical atmospheric model is able to reproduce plausible convective effects of the heat produced by the fire. Numerical results are comparable to estimated values for fire-induced winds and present behaviour similar to other existing numerical approaches.

Although the modelling of the spreading of a forest fire has made considerable progress recently, there remains a lack of reliable field measurements of thermodynamic quantities. We propose in this paper a method and a set of measuring structures built in order to improve the knowledge on the fundamental physical mechanisms that control the propagation of wildland fires. These experimental apparatus are designed to determine: the fire front shape, its rate of spread, the amount of energy impinging ahead of it, the vertical distribution of the temperature within the fire plume as well as the wind velocity and direction. The methodology proposed was applied to a fire spreading across the Corsican scrub on a test site.The recorded data allowed us to reconstruct the fire behaviour and provide its main properties. Wind and vegetation effects on fire behaviour were particularly addressed.

This work presents a new modelling approach to the elaboration of a simple model of surface fire spread. This model runs faster than real-time and will be integrated in management tools. Until now, models used in such tools have been based on an empirical relationship. These tools may be efficient for conditions that are comparable to those of test-fires but the absence of a physical description makes them inapplicable to other situations. This paper proposes a physical 3D model of surface fire able to predict fire behaviour faster than real-time. This model is tested on experiments carried out across fuel beds under slope and wind conditions.