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Prediction of lean blowout performance of gas turbine combustor based on flow structures

Published online by Cambridge University Press:  21 December 2017

E. Ahmed*
Affiliation:
Collaborative Innovation Centre of Advanced Aero-Engines, National Key Laboratory of Science and Technology on Aero-Engines, School of Energy and Power Engineering, Beihang University, Beijing, China
H. Yong
Affiliation:
Collaborative Innovation Centre of Advanced Aero-Engines, National Key Laboratory of Science and Technology on Aero-Engines, School of Energy and Power Engineering, Beihang University, Beijing, China

Abstract

The insufficient depth of modelling to capture the flow physics within primary combustion zone is the prime reason behind limited accuracy of semi-empirical correlations. Flame volume concept establishes a better connection between LBO performance and flame parameters, which improves the modelling depth and hence the prediction accuracy. Nonetheless, estimation of flame parameters is a challenging task. In addition, the iterative loop to approach convergence for a single geometry demands several numerical simulation runs. In this study, the association of LBO performance has been extended to flow structures, they are uniquely associated with the geometric features and can efficiently relate global LBO performance with primary zone geometry. The lean blowout phenomenon was presented as a contest between igniting and extinction forces within Reverse Flow Zone. These forces were quantified by four performance parameters including area, minimum axial velocity, average temperature, and average velocity. Selected parameters provide valuable information regarding the size of recirculation bubble, the intensity of flow reversal and the amount of entrained hot gases. For the purpose of validation, 11 combustor geometries were selected. The RANS simulation was carried out to estimate performance parameters, and predicted performance was compared against experimental data. The excellent agreement highlights the efficiency and promising future for the proposed methodology. Moreover, the association of prediction process with flow structure, instead of geometric features/dimension, makes it universal prediction methodology for wide range of combustor configurations.

Type
Research Article
Copyright
Copyright © Royal Aeronautical Society 2017 

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