Abstract

Lean blowout is one of the major challenges faced when the gas turbine combustors are operated with lean fuel–air mixture to meet the emission norm. We experimentally study the flame behavior and the dynamics of heat release rate fluctuations during a transition to lean blowout. The study comprising flame visualization and estimating several measures to predict lean blowout for both premixed and partially premixed flames (using fuel ports F1 to F5) in a swirl stabilized dump combustor. To that end, we acquire unsteady heat release rate in terms of CH* chemiluminescence obtained through a photomultiplier tube with a narrow band-pass filter. For evaluating different statistical measures, we use National Instrument Labview software while acquiring the heat release rate oscillations. For premixed and partially premixed flames, such measures and the flame behavior show a different and, in some cases, even opposite trends as lean blowout is approached. However, in both premixed and partially premixed flames, the mean and root mean square values of the heat release rate fluctuation decrease as we decrease the equivalence ratio. Further, we show that the value of mean frequency calculated using Hilbert transform of the heat release rate fluctuations is a good indicator of lean blowout. Apart from the early prediction of lean blowout, different statistics of heat release rate oscillations, such as kurtosis and skewness, are shown to identify only the occurrence of lean blowout for premixed (F1 and F2) and flames with lower level of premixing (F3). They are not useful for the flames with high levels of unmixedness like F4 and F5. On the other side, probability density function is seen useful for both premixed and partially premixed flames. In short, we present the relative importance of different measures stated earlier for the identification and early prediction of lean blowout for both premixed and partially premixed flames.

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