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Numerical simulation of the heterogeneous combustion of dust clouds containing polydisperse porous iron particles

Authors: Kun Hong; Mehdi Vahabzadeh Bozorg; Qingang Xiong; Nader Karimi; Nader Karimi; Yu Guan; Larry K.B. Li; +1 Authors

Numerical simulation of the heterogeneous combustion of dust clouds containing polydisperse porous iron particles

Abstract

In this study, heterogeneous combustion of dust clouds containing polydisperse porous iron particles was numerically investigated. The main aim was to develop a discrete three-dimensional model to quantify the effects of particle size, porosity, cloud concentration, and polydispersity on flame propagation speed. The developed numerical model was validated against experimental data to show its promising accuracy. The modeling results show that increasing the cloud concentration increases flame propagation speed significantly, regardless of the particle size distribution, by about 3 times. Increasing the particle porosity can increase flame propagation remarkably, i.e., for particle sizes in the range of 1−3, 1−10, and 1−30 um, flame propagation speed was elevated by up to 24.2%, 36.7%, and 22.6%, respectively, when particle porosity increases from 0 to 0.1. However, increasing the particle size itself was found to decrease flame propagation speed as larger particles tend to be more difficult to ignite. For example, when the particle size distribution changes from 1−3 to 1−30 um, flame propagation speed decreases by a factor of 3.6. These findings serve to improve our understanding of heterogeneous combustion of dust clouds containing polydisperse porous iron particles.

Countries
China (People's Republic of), United Kingdom, China (People's Republic of), China (People's Republic of)
Keywords

Iron powder, Flame propagation, Heterogeneous combustion, Numerical simulation, Polydispersity, Porosity, 620

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    7
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    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
Green
bronze