Publication Date
Spring 2023
Degree Type
Thesis
Degree Name
Master of Science (MS)
Department
Mechanical Engineering
Advisor
Ali Tohidi
Keywords
embers, firebrands, particle, transport, turbulence, wildfires
Subject Areas
Mechanical engineering
Abstract
Firebrand showers are the fastest and most complex form of wildfire spread by generating spot fires in random locations. This randomness is due to many factors, including turbulent wind and particle shape. This work seeks to understand how small-scale turbulence affects firebrand landing distribution and develop a methodology to couple firebrand transport with wildfire simulations. Understanding transport at small scales can provide knowledge on large-scale transport in wildfire simulations. The computational domain and the mesh size in wildfire simulations are very large and do not feature small-scale turbulence. High-resolution small-scale turbulent and uniform boundary layers at various turbulence intensities are used for testing plate and rod firebrand transport. Plates and rods were found to have higher travel distances in uniform flows. Plates were also found to be more sensitive to changes in turbulence intensity. Rods were found to have a high concentration of depositions in a small area, while plates had a wide range of depositions. The shape of the firebrand was found to be an important factor in where it will land due to small-scale turbulence. The firebrand transport solver was coupled with WRF-SFIRE for large-scale transport in a high-wind-speed prescribed fire and a low-wind-speed wildfire. Both plates and rods were found to travel farther distances in the low-wind-speed fire due to higher lofting by the fire plume. This work provides the first steps toward improved wildfire simulations with firebrand transport of plates and rods. Further development can help the wildfire science community better understand wildfire spread through spot fire generation by firebrands.
Recommended Citation
Cervantes, Antonio Q., "Numerical Modeling of Firebrand Transport" (2023). Master's Theses. 5394.
DOI: https://doi.org/10.31979/etd.ddm6-vzya
https://scholarworks.sjsu.edu/etd_theses/5394