A Framework to Facilitate Firebrand Characterization

Abstract

Generation of firebrands from various fuels has been well-studied in the past decade. Limited details have been released about the methodology for characterizing firebrands such as the proper sample size and the measurement process. This study focuses on (1) finding the minimum required sample size to represents the characteristics of the population, and (2) proposes a framework to facilitate the tedious measurement process. To achieve these goals, several firebrand generation tests were conducted at a boundary layer wind tunnel with realistic gusty wind traces. Firebrands were generated from burning structural fuels and collected in 46 strategically located water pans. The statistical analysis showed that the minimum required sample size based on the chosen statistical parameters (standard deviation, confidence interval, and margin of error) is 1,400 for each test. To facilitate characterizing such a large sample of firebrands, an automated image processing algorithm to measure the projected area of the firebrands was developed, which can automatically detect the edges of the background sheet, rotate the photo if its tilted before cropping, detect edges of firebrands, remove erroneous particles (e.g., ash) and finally measures the projected area. To facilitate the weighing process, a Gaussian process regression was performed to predict the mass based on projected area, traveling distance and wind speed. The model can predict the firebrand mass within 5% error compared to the measurement. This framework and model can provide a probabilistic range of firebrand characteristics over the continuous range of the collection region.

Ignitibility of structural wood products exposed to embers during wildland fires :

“…Ember size (i.e., mass and shape) controls its duration of burning and its aerodynamics during travel while its size and mass at landing determine the possible energy transfer to the substrate [8,23,78]. Distance traveled by an ember is affected by the type of vegetation, moisture content, intensity of the fire, and wind speed [79].…”

“…Wind has competing effects on the mass of the embers. Higher wind speeds can generate larger embers but can also result in a higher burning rate, thereby consuming more mass during transport [78]. Higher wind speeds could also extinguish the embers.…”

“…In most studies, the size of embers was determined by measuring holes in the polyurethane sheets on which the embers were collected or by catching embers in aluminum pans with or without water. More recently, Hedayati et al [78] developed an automated image processing algorithm to measure the projected area of the embers collected in water pans. Based on projected area, travelling distance, and wind speed the authors predicted the mass of embers.…”

Determination of Firebrand Characteristics Using Thermal Videos

“…Recently, several studies have been conducted in an attempt to solve this problem [16][17][18][19][20][21][22][23]. In order to conduct this research, a series of prescribed fire experiments within pine forests were performed to study the generation of firebrands and their properties as a function of fire behavior [16][17][18].…”

“…In order to conduct this research, a series of prescribed fire experiments within pine forests were performed to study the generation of firebrands and their properties as a function of fire behavior [16][17][18]. Hedayati et al [20] conducted experiments that were designed to generate firebrands from building materials in a wind tunnel and, upon doing so, proposed a probabilistic model for the estimation of firebrand mass/projected area/flying distance. The formation of firebrands from thermally degraded vegetative elements was also investigated in the study [19].…”