Presented to: AFRC 2017 Industrial Combustion Symposium
September 17th – 20th, 2017, Houston, TX, USA

Thomas J. Flynn, Timothy A. Fuller, and Suzana Rufener - The Babcock & Wilcox Company - Barberton, OH USA

Charles E.A. Finney and C. Stuart Daw - Oak Ridge National Laboratory - Knoxville, TN USA

ABSTRACT

Industrial boilers and furnaces occasionally suffer low-frequency vibrations generated by a dynamic feedback process between the burner (or burners) and acoustic modes in adjacent gas-filled cavities in the main combustion chamber or connecting ductwork. This occurs when pressure pulses associated with acoustic resonances propagate to the burner so that they are in phase with combustion rate fluctuations caused by turbulence and reaction dynamics. When these pressure pulses become sufficiently phase-synchronized with fluctuations in heat release from the flame, the forces that normally dissipate the pressure waves are overwhelmed and an amplifying feedback loop is created. In the literature, such oscillations are referred to as thermoacoustic oscillations or ‘rumble,’ and their basic physics have been the subject of numerous investigations for well over a century. Unfortunately, rumble amplitudes can be large enough to negatively impact thermal efficiency and emissions, and the associated mechanical vibrations they cause can even lead to structural damage. The potential for rumble poses a significant challenge to combustion engineers because it is often very difficult to predict and can be associated with a large number of design and operating factors such as fuel quality, burner swirl and staging, induction and draft fan characteristics, ducting design and combustion cavity shape. The underlying relationships involved are sufficiently complex that it is possible for two apparently identical boilers or furnaces to exhibit completely different rumble tendencies. In this study, we review the published information currently available about the causes and suppression of burner rumble and suggest possible opportunities for improving its prediction, diagnosis, and active control.