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Predicting the fire spread rate of a sloped pine needle board utilizing pyrolysis modelling with detailed gas-phase combustion

journal contribution
posted on 2024-11-02, 07:06 authored by Timothy Chen, Anthony Yuen, Chunguang Wang, Guan Heng Yeoh, Victoria Timchenko, Chi Pok CheungChi Pok Cheung, Qing Chan, Wenjie Yang
A novel Large Eddy Simulation (LES) based fire field model that incorporates pyrolysis modelling has been developed. This model is specifically designed for flame propagation of wildland fire scenarios. It uniquely embraces the radiation heat feedback from the flame, gaseous combustion and soot products towards the fuel bed surface. It also considers the detailed chemical kinetics for combustion, primary soot incipient and oxidant for soot formation, turbulent microscopic fuel–air mixing which are fully coupled, interactive and non-linear. Numerical simulation has been performed to study the effect of slope angle on the flame propagation characteristic of pine needle fuel beds. The fire spread rate and temperature predictions are within 12% accuracy in comparison to experimental data. Owing to the unbalanced air entrainment drew by the flame combustion for the inclined slope angle cases, it can be observed from the visualised flame that it was tilted to the unburned portion of the board. This behaviour strongly promotes the radiative heat transfer from the flame onto the fuel bed, which led to a rapid increase in pyrolysis rate thus accelerated the overall flame spread on the board surface. This physical phenomenon was successfully captured by the pyrolysis model and was found to be significantly more accurate in predicting the fire spread rate for slope angles higher than 20° (error of 11.12%) when compared to empirical flame tracking methods (error of 87.19%). © 2018 Elsevier Ltd

Funding

ARC Training Centre in Fire Retardant Materials and Safety Technologies

Australian Research Council

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History

Journal

International Journal of Heat and Mass Transfer

Volume

125

Start page

310

End page

322

Total pages

13

Publisher

Elsevier

Place published

United Kingdom

Language

English

Copyright

© 2018 Elsevier Ltd. All rights reserved.

Former Identifier

2006084392

Esploro creation date

2020-06-22

Fedora creation date

2018-09-20

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