Active control for statistically stationary turbulent premixed flame simulations

Abstract

The speed of propagation of a premixed turbulent flame correlates with the intensity of the turbulence encountered by the flame. One consequence of this property is that premixed flames in both laboratory experiments and practical combustors require some type of stabilization mechanism to prevent blow-off and flashback. The stabilization devices often introduce a level of geometric complexity that is prohibitive for detailed computational studies of turbulent flame dynamics. Furthermore, the stabilization introduces additional fluid mechanical complexity into the overall combustion process that can complicate the analysis of fundamental flame properties. To circumvent these difficulties we introduce a simple, heuristic feedback control algorithm that allows us to computationally stabilize a turbulent premixed flame in a simple geometric configuration. For the simulations, we specify turbulent inflow conditions and dynamically adjust the integrated fueling rate to control the mean location of the flame in the domain. We outline the numerical procedure, and illustrate the behavior of the control algorithm on methane flames at various equivalence ratios in two dimensions. The simulation data are used to study the local variation in the speed of propagation due to flame surface curvature.

Turbulence‐Flame Interactions in Type Ia Supernovae

“…Defining the local speed in this way has the property that the global burning speed is the integral of s l T over the isosurface. For additional details about construction of the elements , see Bell et al (2006) and Day et al (2008). Figure 8 compares instantaneous temperature and carbon isosurfaces for case (b) and is colored by the integrated fuel consumption rate, s l T .…”

Turbulence effects on cellular burning structures in lean premixed hydrogen flames

“…Diffusion and chemical kinetics, which occur on time scales faster than advection, are treated time-implicitly. An automatic feedback control algorithm [25,34] adjusts the inflow velocity to stabilize the flame in the computational domain. This integration scheme is embedded in a parallel adaptive mesh refinement framework based on a hierarchical system of rectangular grid patches [35].…”

“…Example laminar fluid-flame interaction studies include experimental validation and analyses of the interaction of single vortical structures with a rich methane-air flame [37]. In [25,38], the control algorithm discussed above was presented and used to explore the response of methaneair flames in the presence of turbulence, based on the detailed chemistry and transport models in the GRI-Mech 3.0 mechanism [39]. A two-dimensional controlled hydrogen flame in the turbulence/chemistry regime of the present work was analyzed extensively in [26].…”

“…The fluctuations are chosen to match (in terms of integral scale and intensity) those observed in related laboratory experiments. For this study, the mean inflow velocity is adjusted dynamically using an automatic control algorithm [25] to hold the mean position of the flame a fixed distance above the inflow face. The procedure allows the simulation of a weakly turbulent flame in a quasi-steady configuration without the need to simulate a pilot or some geometric stabilization device.…”

An Explicit Runge-Kutta Iteration for Diffusion in the Low MachNumber Combustion Code

“…The fine grid resolution is therefore 78.125 (micron). The flame evolves over 0.05 (sec) during which it is steadied at y = 2.0 (cm) using the control algorithm discussed in [1]. Figure 1 displays the mole fractions of the species with respect to distance along the y axis.…”