Visualising convective heat transfer in a propagating wildland fire

Bushfires are a large destructive natural hazard, intensified by climate change and increasing human activity into wildland areas. Accurate prediction of fire behaviour is essential for mitigation strategies and emergency response. While radiative heat transfer has traditionally been emphasized in bushfire modelling, recent studies reveal the significant role of convective heat transfer, especially in fine porous fuels. This thesis investigates the complex contributions of convective heating and cooling and their influence on the rate of spread (ROS) in bushfires through a combination of physics-based numerical simulations and experimental methods. Numerical simulations were conducted using the Large Eddy Simulation (LES) method in Fire Dynamics Simulator (FDS), exploring the effects of wind speed, slope angle, fuel moisture content, fuel packing ratio, and fuel height and their correlation with convective heat transfer. Parallel experimental studies employed a custom-built controllable flow sand burner, a custom-built wind tunnel, and advanced optical diagnostic techniques, including Retroreflective Shadowgraphy (RS) and Background Oriented Schlieren (BOS), to visualise and quantify heat transfer dynamics. Thermocouples, Pitot tubes, and heat flux sensors were used to capture physical measurements for validation. The results reveal that convective heating dominates in wind-driven and sloped scenarios, while convective cooling plays a critical offsetting role in radiative preheating. Derived correlations link environmental and fuel parameters to convective heat transfer, offering new insights into fire spread modelling. Notably, this work is the first to capture and quantify convective heat flux in propagating fires using the RS technique, bridging a key knowledge gap in fire science. By enhancing our understanding of convective heat transfer mechanisms in bushfires, this thesis contributes to refining fire prediction models and supports the development of more reliable fire spread prediction tools. The findings have practical implications for wildfire mitigation, especially in the face of increasingly frequent and intense fire seasons globally.

Grantor dc:publisher

UNSW, Sydney

Year dc:date

2026

Author dc:creator

• Sadeghi, Mohamad

• Visualisation
• anzsrc-for: 4017 Mechanical engineering

Statement dc:rights

• open access
• CC BY 4.0
• free_to_read

Licence

• https://purl.org/coar/access_right/c_abf2
• https://creativecommons.org/licenses/by/4.0/

Language dc:language

en

Identifier

https://doi.org/10.26190/unsworks/32182

OAI identifier oai:identifier

oai:unsworks.library.unsw.edu.au:1959.4/107462