This paper studies the spontaneous radiant energy emitted by a trapped vortex flame, focusing on the intermittent occurrence of the flame blowout during thermoacoustic oscillation. We tackle this issue by a wavelet-based auto-conditioning technique, that on the grounds of an energy criterion, performs an objective detection and selection of those events whose energy content exceeds a proper threshold. The result is the time history of a signal containing extinction-reignition events only. As further outcomes, the detected intermittent events are statistically characterized in terms of shape, amplitude, time lag, and timescales. Moreover, intermittent events are found to be in phase with the tonal component of the radiant energy signal, whereas they occur randomly in time. Although the wavelet auto-conditioning technique is a well-established method in fluid dynamics and aeroacoustics, we apply it in the combustion field, where alternative methods, based on wavelet transforms, have already been successfully applied. Additional information about intermittency in the flame is inferred from the chaotic analysis: Recurrence plot (RP) of radiant energy shows that the time of boundary crisis is much larger than the characteristic timescale of extinction-reignition event. Furthermore, cross-conditioning of RPs with intermittent events found by wavelet transform results in a characteristic "pike-like"pattern, which identifies an intermittent state different from the most common intermittency types already described in the literature.
|Titolo:||Wavelet and recurrence analysis for lean blowout detection: An application to a trapped vortex combustor in thermoacoustic instability|
|Data di pubblicazione:||2020|
|Appare nelle tipologie:||1.1 Articolo in rivista|