Experimental and numerical investigation of burning characteristics of Australian pine trees for wildfire modelling

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Gupta, Siddharth ORCID logoORCID: https://orcid.org/0000-0002-1373-9491, Sharaf, Mohamed ORCID logoORCID: https://orcid.org/0000-0002-3952-0367, Arun, Malavika M ORCID logoORCID: https://orcid.org/0000-0001-9996-9070, Guerrierri, Maurice ORCID logoORCID: https://orcid.org/0000-0001-7916-7003 and Moinuddin, Khalid ORCID logoORCID: 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
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