Yannick Pizzo

Determination of Woody Fuel Flame Properties by Means of Emission Spectroscopy Using a Genetic Algorithm

Because radiation from flames is often the dominant mechanism for wildfire spread, detailed information on flame properties is required. The proposed procedure combines a spectrally resolved radiation model for simulating the line-of-sight infrared emission intensity and spectroscopy data and uses a genetic algorithm (GA) to determine a set of flame properties, allowing optimal agreement between model and outdoor experiments. GA calibration and sensitivity analysis were conducted using well-defined reference flames. The combined GA/radiation model was used with emission data to estimate the effective properties of flames from the combustion of woody fuel beds from 0.5 to 4 m in thickness. Experimental results show that the contribution of soot particles to flame emission increases with flame thickness. The GA was found to be robust and efficient in providing relevant flame properties from line-of-sight intensities on the infrared spectrum of radiation.

Fire spread and percolation in polydisperse compartment structures

In this paper, we employ a cellular automata and percolation analysis to model fire spread in polydisperse amorphous massively multi-compartmented structures (e.g. naval vessels, high-rise buildings, warehouses, or nuclear plants). Various shapes and sizes of compartments are considered. Each compartment is composed of nc equal-size cells. It is found that increasing nc increases fingering and lacunarities of fire patterns, and subsequently front roughness. However, this also increases the probability of fire propagation throughout the system as the percolation threshold presents a power-law decrease with nc −1 for small values of nc. For large polydisperse compartments, the propagation/non propagation transition seems to be size-independent. A special emphasis is put on the dynamics of fire propagation. Further study is needed to evaluate network properties that should help in developing better strategies to reduce fire consequences.