Single-shot CARS Imaging of Near-Wall Turbulent Reacting Flows

Abstract

In practical combustion devices featuring high power densities, the interaction between flames and walls may have a significant impact on the thermodynamic efficiency and the formation of pollutants (e.g. unburned hydrocarbons and carbon monoxide). The common understanding is that at the region near the wall ~ 1 mm, where the solid metal surface is generally much cooler than the impinging flames, steep temperature gradients exist which may result in incomplete combustion and local quenching of the flame. This has been investigated experimentally, by CARS monitoring of temperature- and major species profiles from premixed methane/air flames impinging against a cooled steel side-wall, performed at well-characterized quasi-stationary laminar conditions [1].
In these new experiments, we have employed the same generic burner and CARS imaging system [2], but now operating at significantly enhanced turbulence intensities induced by a turbulence generator grid (blockage ratio 45%, turbulence level 푢푢′/푢푢ത = 6-7%). The complex interplay between the laser diagnostic and the turbulent reacting flow in the near-wall region has been overcome, for instance, with the balanced detection between CARS signals originating from unreacted- and reacted mixtures imaged on the same detector frame, the removal of the laser beams reflecting from the surface, and the suppression of background flame luminosity within the clear aperture of the coherent imaging system. A quick-fitting routine enabling rapid convergence of two-beam femtosecond/picosecond CARS signal analysis has been developed. Correlated statistics have been produced, for instance, on the instantaneous temperature gradients near the wall (position with magnitude). This temperature data supports the recent findings of velocity measurements [3], and adds to the database on this burner system which can be used as a benchmark to improve the fidelity of numerical simulation on near-wall turbulent reacting flows.