Simultaneous high speed (5 kHz) Fuel-PLIF, OH-PLIF and stereo PIV imaging of pressurized swirl-stabilized flames using liquid fuels

This paper describes implementation of simultaneous, high speed (5 kHz) stereo PIV, OH and fuel-PLIF in a pressurized (up to 5.2 atm), liquid fueled, swirl stabilized flame, representative of a gas turbine combustor. The experiments were performed to characterize the flowfield, qualitative heat release and fuel spray distributions, and flame dynamics. Acquiring high speed OH-PLIF in pressurized, liquid fuel systems is difficult due to the fuel’s absorption and emission spectra strongly overlapping that of the OH fluorescence spectrum. To overcome the fuel emission polluting the OH signal, the OH and fuel fluorescence signals were partially separated by using two cameras with differing spectral filters and data acquisition timing, as the emission from OH and fuel differ both in spectral width and time. The first camera captured only fuel-PLIF, while the second captured fuel-PLIF and OH-PLIF. The fuel-PLIF images were used to compute two intensity thresholds, separating each image into regions of no fuel, fuel only and an intermediate region. In the region of no fuel, OH was detected in the second camera. In the intermediate region there was a mix of fuel and OH. Instantaneous and time-averaged results are discussed showing the flow field, flame position and dynamics, and spray distribution from the fuel signal for two different multi-component liquid fuels (Jet-A and C-5), at two inlet temperatures of 450 and 570 K, and three pressure of 2.1, 3.5 and 5.2 bar. The flame shape in some cases is described as M-shaped, existing both inside and outside of the annular swirling jet produced by the nozzle, while in other cases no reaction is apparent on the inside. The spray penetration and distribution, and flame position are sensitive to the various conditions, while the flow field topology is qualitatively insensitive. Furthermore, elevated pressure as expected sharpens all spatial gradients in the data.