Soot modeling of counterflow diffusion flames of ethylene-based binary mixture fuels

Wang, Yu; Raj, Abhijeet; Chung, Suk Ho

doi:10.1016/j.combustflame.2014.08.016

Cited by 130 publications

(104 citation statements)

References 90 publications

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“…A method of moment with interpolative closure (MOMIC) [18] with three moment variables was used to predict soot formation, with an updated heterogeneous soot pathways following Ref. [27]. Due to the limited availabilities in experimental data, different experimental configurations were used for comparison of various observables, such as PAH, soot volume, and soot diameter.…”

Section: Discussionmentioning

confidence: 99%

“…In reference with the earlier work with heterogeneous mechanism mentioned in [27], a similar approach of surface reaction and soot dynamics approach is carried out to validate the reduced mechanism. The following section summarizes the models for soot formation pathways.…”

Section: Heterogeneous Soot Modelmentioning

confidence: 99%

“…The method of determining γ is explained by Wang et al [27], in which the baseline pure ethylene flame was simulated by adjusting γ. It was shown that a satisfactory agreement between the simulated and experimentally observed maximum soot volume fraction was obtained with γ = 0.0052.…”

Section: Soot Nucleationmentioning

confidence: 99%

“…This suggests that including only pyrene for nucleation may not be sufficient in describing the soot inception process. In fact, a recent study [27] reported that the larger PAH species have a stronger effect in the dimerization and soot inception, suggesting that higher PAH species need to be accounted for in comprehensive soot models.…”

Section: Introductionmentioning

confidence: 99%

“…The reduced mechanism is first validated against the premixed and counterflow flames, for which measured PAH concentrations are available. The mechanism is an update from the previous KAUST Mech 2 (KM2) developed for lower hydrocarbon fuels [27]. An earlier KAUST Mech 1 (KM1) was to predict higher hydrocarbon fuels [29].…”

Section: Introductionmentioning

confidence: 99%

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A computational study of ethylene–air sooting flames: Effects of large polycyclic aromatic hydrocarbons

Selvaraj

Arias

Lee

et al. 2016

Combustion and Flame

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An updated reduced gas-phase kinetic mechanism was developed and integrated with aerosol models to predict soot formation characteristics in ethylene nonpremixed and premixed flames. A primary objective is to investigate the sensitivity of the soot formation to various chemical pathways for large polycyclic aromatic hydrocarbons (PAH). The gas-phase chemical mechanism adopted the KAUST-Aramco PAH Mech 1.0, which utilized the AramcoMech 1.3 for gas-phase reactions validated for up to C2 fuels. In addition, PAH species up to coronene (C 24 H 12 or A7) were included to describe the detailed formation pathways of soot precursors. In this study, the detailed chemical mechanism was reduced from 397 to 99 species using directed relation graph with expert knowledge (DRG-X) and sensitivity analysis. The method of moments with interpolative closure (MOMIC) was employed for the soot aerosol model. Counterflow nonpremixed flames at low strain rate sooting conditions were considered, for which the sensitivity of soot formation characteristics to different nucleation pathways were investigated. Premixed flame experiment data at different equivalence ratios were also used for validation. The findings show that higher PAH concentrations result in a higher soot nucleation rate, and that the total soot volume and average size of the particles are predicted in good agreement with experimental results. Subsequently, the effects of different pathways, with respect to pyrene-or coronene-based nucleation models, on the net soot formation rate were analyzed. It was found that the nucleation processes (i.e., soot inception) are sensitive to the choice of PAH precursors, and consideration of higher PAH species beyond pyrene is critical for accurate prediction of the overall soot formation.

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Section: Discussionmentioning

confidence: 99%

Section: Heterogeneous Soot Modelmentioning

confidence: 99%

Section: Soot Nucleationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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