Assessment and validation of liquid breakup models for high-pressure dense diesel sprays

Yi REN, Xianguo LI

Front. Energy ›› 2016, Vol. 10 ›› Issue (2) : 164-175.

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Front. Energy ›› 2016, Vol. 10 ›› Issue (2) : 164-175. DOI: 10.1007/s11708-016-0407-9
RESEARCH ARTICLE
RESEARCH ARTICLE

Assessment and validation of liquid breakup models for high-pressure dense diesel sprays

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Abstract

Liquid breakup in fuel spray and atomization significantly affects the consequent mixture formation, combustion behavior, and emission formation processes in a direct injection diesel engine. In this paper, different models for liquid breakup processes in high-pressure dense diesel sprays and its impact on multi-dimensional diesel engine simulation have been evaluated against experimental observations, along with the influence of the liquid breakup models and the sensitivity of model parameters on diesel sprays and diesel engine simulations. It is found that the modified Kelvin-Helmholtz (KH)–Rayleigh-Taylor (RT) breakup model gives the most reasonable predicted results in both engine simulation and high-pressure diesel spray simulation. For the standard KH-RT model, the model constant Cbl for the breakup length has a significant effect on the predictability of the model, and a fixed value of the constant Cbl cannot provide a satisfactory result for different operation conditions. The Taylor-analogy-breakup (TAB) based models and the RT model do not provide reasonable predictions for the characteristics of high-pressure sprays and simulated engine performance and emissions.

Keywords

breakup model / diesel engine / high-pressure injection / simulations

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Yi REN, Xianguo LI. Assessment and validation of liquid breakup models for high-pressure dense diesel sprays. Front. Energy, 2016, 10(2): 164‒175 https://doi.org/10.1007/s11708-016-0407-9
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Acknowledgements

This work is supported financially by the Ontario Research Fund-Research Excellence (ORF-RE) program via contract # RE-02-019 and the Natural Sciences and Engineering Research Council of Canada (NSERC) via a Discovery Grant. Convergent Science is gratefully acknowledged for providing their ConvergeTM CFD code for the study described in this paper.

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2016 Higher Education Press and Springer-Verlag Berlin Heidelberg
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