An Improved Flame Volume Mixing Method for Lean Blowout Prediction of Sustainable Aviation Fuels

This study investigates the fuel discrimination capability of the flame volume mixing method (FV mixing method) in predicting the lean blowout (LBO) limits of different fuels. Conventional FV-based models exhibit limited sensitivity to variations in fuel properties, especially under lean conditions and for sustainable aviation fuels. In this work, an improved FV mixing method is proposed by replacing the classical droplet evaporation treatment with the Abramzon–Sirignano droplet evaporation model, which accounts for fuel-dependent liquid properties, Stefan flow, and coupled convective heat and mass transfer between the gas phase and droplets. As a result, the proposed method shows enhanced sensitivity to fuel variability and improves the prediction accuracy of the LBO limit for the sustainable aviation fuel Cat-C1. The model performance is validated through numerical simulations and compared with experimental data. The results indicate that, compared with the baseline FV mixing method, the proposed approach reduces the LBO prediction error by 5.7%. The improved FV mixing method provides a more robust framework for LBO prediction, with potential applications in fuel characterization and combustion optimization.

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Publication Details

Journal
Energies
Published
2026-03-16
DOI
https://doi.org/10.3390/en19061479
Primary Topic
Combustion and flame dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

An Improved Flame Volume Mixing Method for Lean Blowout Prediction of Sustainable Aviation Fuels

Xinqi Yang, Tian Deng, Yaobo Li, Pengjing Du
Energies
Combustion and flame dynamics
article

An Improved Flame Volume Mixing Method for Lean Blowout Prediction of Sustainable Aviation Fuels

Xinqi Yang, Tian Deng, Yaobo Li, Pengjing Du
article en

Abstract

This study investigates the fuel discrimination capability of the flame volume mixing method (FV mixing method) in predicting the lean blowout (LBO) limits of different fuels. Conventional FV-based models exhibit limited sensitivity to variations in fuel properties, especially under lean conditions and for sustainable aviation fuels. In this work, an improved FV mixing method is proposed by replacing the classical droplet evaporation treatment with the Abramzon–Sirignano droplet evaporation model, which accounts for fuel-dependent liquid properties, Stefan flow, and coupled convective heat and mass transfer between the gas phase and droplets. As a result, the proposed method shows enhanced sensitivity to fuel variability and improves the prediction accuracy of the LBO limit for the sustainable aviation fuel Cat-C1. The model performance is validated through numerical simulations and compared with experimental data. The results indicate that, compared with the baseline FV mixing method, the proposed approach reduces the LBO prediction error by 5.7%. The improved FV mixing method provides a more robust framework for LBO prediction, with potential applications in fuel characterization and combustion optimization.

EnergiesVol. 19(6)
Civil Aviation University of China (CN)
Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 17%
Combustion and flame dynamics
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