Numerical simulations of flame spread in pine needle beds using simple thermal decomposition models
Computational fluid dynamics (CFD) models have increased in use for studying scenarios relevant to wildland fires, such as examination of the driving processes in flame spread in vegetative fuels. However, these tools utilize a complex set of submodels which require a large number of input parameter...
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Veröffentlicht in: | Fire safety journal 2023-12, Vol.141, p.103886, Article 103886 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Computational fluid dynamics (CFD) models have increased in use for studying scenarios relevant to wildland fires, such as examination of the driving processes in flame spread in vegetative fuels. However, these tools utilize a complex set of submodels which require a large number of input parameters. Often the full set of fuel-specific parameters are not well-quantified and the user must rely upon the best available information. In this study, we examine the implications of using different simple models for thermal decomposition when simulating flame spread through a bed of dead pine needles in quiescent conditions. Model results using one set of common literature values are compared to those using data from milligram-scale characterizations of the fuel. An updated model for char oxidation is also implemented and tested. It was found that the literature values over-predicted mass loss rate by a factor of 2.4, while the fuel-specific values yielded predictions within the experimental uncertainty. A simple approach to decomposition modeling was also shown to be useful for investigating the role of bed structure on flame spread and the heat flux within the fuel bed.
•A multiphase CFD model was used to simulate flame spread in pine needles in still air.•Fitting the pyrolysis model with fuel species specific data impacted burning rate.•An updated char oxidation model was shown to provide reasonable results.•The model was able to capture fuel structure effects on spread and heat transfer. |
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ISSN: | 0379-7112 |
DOI: | 10.1016/j.firesaf.2023.103886 |