Dynamics Of Fire Spread Research Articles

Analysis of the wind flow and fire spread dynamics over a sloped–ridgeline hill

This paper presents results from a computational and laboratory investigation of wind flow and fire spread over an isolated sloped-ridgeline laboratory-scale hill under various slopes with the wind blowing perpendicularly to the ridgeline. The results show two situations of unexpected or unusual fire behaviour; one is a lateral spread of the fire front over the windward face into a down-ridge direction resulting from a strong near-surface flow component parallel to the ridgeline. The other behaviour is a lateral enlargement of the fire front near the ridgeline over the leeward face in an up-ridge direction resulting from a flow parallel to the ridgeline. Comparison with reference fire spread rates and wind flow observations highlight the importance of the interaction between terrain-modified flow mechanisms and the fire in which they result in accelerated flows that drive the indicated unexpected behaviour.

A Complex Network Theory Approach for the Spatial Distribution of Fire Breaks in Heterogeneous Forest Landscapes for the Control of Wildland Fires.

Based on complex network theory, we propose a computational methodology which addresses the spatial distribution of fuel breaks for the inhibition of the spread of wildland fires on heterogeneous landscapes. This is a two-level approach where the dynamics of fire spread are modeled as a random Markov field process on a directed network whose edge weights are determined by a Cellular Automata model that integrates detailed GIS, landscape and meteorological data. Within this framework, the spatial distribution of fuel breaks is reduced to the problem of finding network nodes (small land patches) which favour fire propagation. Here, this is accomplished by exploiting network centrality statistics. We illustrate the proposed approach through (a) an artificial forest of randomly distributed density of vegetation, and (b) a real-world case concerning the island of Rhodes in Greece whose major part of its forest was burned in 2008. Simulation results show that the proposed methodology outperforms the benchmark/conventional policy of fuel reduction as this can be realized by selective harvesting and/or prescribed burning based on the density and flammability of vegetation. Interestingly, our approach reveals that patches with sparse density of vegetation may act as hubs for the spread of the fire.

Stochastic cellular automata model for wildland fire spread dynamics

A stochastic cellular automata model for wildland fire spread under flat terrain and no-wind conditions is proposed and its dynamics is characterized and analyzed. One of three possible states characterizes each cell: vegetation cell, burning cell and burnt cell. The dynamics of fire spread is modeled as a stochastic event with an effective fire spread probability S which is a function of three probabilities that characterize: the proportion of vegetation cells across the lattice, the probability of a burning cell becomes burnt, and the probability of the fire spread from a burning cell to a neighboring vegetation cell. A set of simulation experiments is performed to analyze the effects of different values of the three probabilities in the fire pattern. Monte-Carlo simulations indicate that there is a critical line in the model parameter space that separates the set of parameters which a fire can propagate from those for which it cannot propagate. Finally, the relevance of the model is discussed under the light of computational experiments that illustrate the capability of the model catches both the dynamical and static qualitative properties of fire propagation.

Numerical simulations of grass fires using a coupled atmosphere‐fire model: Dynamics of fire spread

Numerical simulations using a coupled atmosphere‐fire model (called HIGRAD/FIRETEC) are examined to investigate the dynamics of fire behavior in grasslands, focusing specifically on the relative roles and contributions of radiative and convective heat transfer and the relationships of these processes to the evolution of the solid fuel temperature; the three‐dimensional velocity fields in the vicinity of the fire; and the depletion of fuel, fuel moisture, and oxygen. The progression of the fire past a given point in these simulations is divided into a preheating period and an active burning period. The preheating period is characterized by a slowly increasing radiative heating of the fuel that evaporates fuel moisture and raises the temperature of the fuel slightly and by weak convective cooling because the gases flowing over the heated solid fuel are still cooler than the fuel itself. The active burning period is characterized by the presence of a strong pulse of convective heating and continued radiative heating, accompanied by the development of large vertical velocities and a rapid increase in fuel temperature that causes the reaction rates to increase and the fuel to begin to burn, producing heat and increasing the rates of depletion of fuel and oxygen. In all simulations, the magnitude of the convective heat transfer is greater than that of the radiative heat transfer; however, these processes and their relationships to the three‐dimensional structure and evolution of the fire are shown to depend both on the ambient wind speed and on the specific location along the fire front (e.g., at the head of the fire where the fire is spreading in the direction of the ambient wind, or on the flank of the fire where the fire is spreading in the direction almost perpendicular to the ambient wind).

Dynamics of fire spread in grasslands: Numerical simulations with a physics-based fire model

Dynamics of fire spread in grasslands: Numerical simulations with a physics-based fire model

Self-similar spatial clustering of wildland fires: The example of a large wildfire in Spain

Euclidean analytical tools for quantifying the patchiness of complex natural patterns such as wildfires in general do not recognize that measures of object densities over the landscape vary as a function of the size of the spatial elements. Therefore, improved fractal statistical methods are needed to quantify patch structures in ways that capture the spatial variation of the analysed pattern in relation to scale. The aims of this research are to show first, that remotely sensed wildfire scars are fractal objects, and second, how the resulting fractal dimension can be interpreted to give insight into the dynamics of fire spread over the landscape.