Numerical Simulation of the Dynamics of Turbulent Swirling Flames

Response of Premixed Flames to Velocity Disturbances
surements at the burner exit at two different frequencies to identify the varied
propagations speeds of the perturbations and the variations of swirl number
produced by them. The impact of the variations of swirl number and by the
phase between perturbations on the flame response was analyzed. It was observed
that when the axial and tangential velocity fluctuations were almost
out of phase, swirl number fluctuations were present, inducing variations on
the flame angle. Under these conditions, a destructive interaction mechanism
is produced, which decreases the amplitude of the flame describing function.
On the other hand, when both perturbations were almost in phase, the amplitude
of the swirl number fluctuation decreased, and a constructive interaction
mechanism is produced, showing a peak amplitude in the flame describing
function. The investigations mentioned before demonstrate that the position
of the swirler has a strong impact on the flame response.
Finally, non-linearity is also an important issue on the studies of flame dynamics.
It appears from a saturation response of the flame to the increase of
the amplitude of the fluctuation. This topic is not investigated in the present
study as it is focus on the use of tools in the linear regime as linear system
identification with finite impulse response filters and network models using
linearized Navier-Stokes equations. Thus the flame was excited to amplitudes
in the linear regime of the flame [96]. While experimental and analytical investigations
has been extensively carried out in the investigation of non-linear
effects, the development of non-linear system identification tools for thermoacoustics
systems [157, 182, 183] is in its early stages, showing that a much
complex process needs to be carried out for the identification compared to
the linear identification tools.
3.4 Model of Impulse and Frequency Responses to Axial Velocity
and Swirl Fluctuations
Various models have been proposed to describe the flame response as mentioned
in section 3.2. Some of these models are based on time lag distributions.
A model for the flame dynamics was proposed by Komarek and Po-
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