Abstract Lean Blow-Out (LBO) is critical to operational performance of combustion systems in propulsion and power generation. Current predictive tools for LBO are based on decades old empirical correlations that have limited applicability for modern combustor design. According to the Lefebvreʼs model for LBO and flame volume concept, an FV (Flame Volume) model was proposed by authors in the early experimental study. The FV model adds two key parameters of α and β that represent the fraction of dome air and the dimensionless flame volume defined as the ratio of flame volume ( V f ) and combustor volume ( V c ). Due to the flame volume ( V f ) is obtained from the experimental image, FV model could only be used in LBO analysis instead of predictions. In the present study, a method named Fuel Iterative Approximation (FIA) is proposed based on FV model for LBO limit predictions. In FIA, α and β contained in FV model are estimated from the numerical simulation results of combustors, and an iterative relationship between fuel flow rate and flame volume is established to make the prediction of LBO fuel/air ratio ( q LBO ). Comparing with the experimental LBO data for 17 combustors, the q LBO obtained by FIA show much better agreement than that obtained by Lefebvreʼs model. The maximum prediction uncertainties of FIA and Lefebvreʼs model are ± 20 % and ± 50 % , respectively. The time cost of the LBO prediction using FIA for each case is about 6 hours with computer equipment of CPU × 4 and 4 GB memory, showing that the FIA is reliable and efficient, and could be used for the performance evaluation of combustors, even the so-called “paper combustors” in the primary design stage.


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    Title :

    FIA method for LBO limit predictions of aero-engine combustors based on FV model


    Contributors:
    Hu, Bin (author) / Huang, Yong (author) / Wang, Fang (author)

    Published in:

    Publication date :

    2013-01-11


    Size :

    12 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English