Experimental and numerical investigation of burning characteristics of Australian pine trees for wildfire modelling
Gupta, Siddharth ORCID: https://orcid.org/0000-0002-1373-9491, Sharaf, Mohamed
ORCID: https://orcid.org/0000-0002-3952-0367, Arun, Malavika M
ORCID: https://orcid.org/0000-0001-9996-9070, Guerrierri, Maurice
ORCID: https://orcid.org/0000-0001-7916-7003 and Moinuddin, Khalid
ORCID: https://orcid.org/0000-0002-1831-6754
(2025)
Experimental and numerical investigation of burning characteristics of Australian pine trees for wildfire modelling.
Fire Safety Journal, 157.
ISSN 0379-7112
Abstract
Crown fires, which spread rapidly and with high intensity, present a significant challenge in wildfire management, particularly in wildland–urban interface (WUI) areas. A fundamental aspect of understanding crown fire behaviour is the combustion dynamics of individual trees, which serve as building blocks for larger-scale fire spread. This study aims to investigate the burning characteristics of Australian pine trees through both experimental and numerical methods, focusing on heat release rate (HRR), mass loss rate (MLR), total mass loss (ML), and heat flux. Experimental measurements were obtained by burning Australian pine trees under a 1.5 MW calorimeter hood, with key thermal parameters recorded. These results were compared to similar data from other tree species. A fully physics-based model was validated against experimental results. Two approaches for defining the heat of combustion in the physical simulations were explored: one based on reaction properties and the other on material properties. The study found that both approaches could effectively reproduce HRR, MLR, and ML, though discrepancies were noted in heat flux predictions due to assumptions regarding vegetation distribution. Notably, this research represents the first experimental-numerical comparison of HRR data for any tree combustion and provides a valuable contribution to understanding fire dynamics. The findings have important implications for enhancing wildfire prediction models and improving fire safety strategies in the WUI.
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| Item type | Article |
| URI | https://vuir.vu.edu.au/id/eprint/50157 |
| DOI | 10.1016/j.firesaf.2025.104500 |
| Official URL | https://doi.org/10.1016/j.firesaf.2025.104500 |
| Subjects | Current > FOR (2020) Classification > 4005 Civil engineering Current > Division/Research > Institute for Sustainable Industries and Liveable Cities |
| Download/View statistics | View download statistics for this item |
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