Fluid flow characterization of high turbulent intensity compressible flow using particle image velocimetry
A high turbulent intensity combustion chamber has been designed in order to operate with compressible (0.3 < M < 0.5) and preheated (T=500K) air-methane combustion. These conditions will allow the investigation of different flame regimes; most notably the proposed ‘Thickened Flame’ regime. Initial design and flow validation has been completed in order to begin further experimentation. A 10 kHz Time Resolved Particle Image Velocimetry (TR-PIV) system and a 3 kHz Planer Laser Induced Fluorescence (PLIF) system have been integrated with the system in order to diagnose the flow field and the flame respectively. The exhaust and chamber cooling subsystems were designed to comply with safety regulations, and the control systems were set up in a way that allows automated (LabVIEW) and user controlled sequencing. This work’s main purpose is to characterize and map the flow properties at maximum flow conditions (M > 0.3) in order to map the following; flow structures, kinetic energy at different length scales, velocity fluctuations and turbulent intensity. PIV measurements are carried out for three different volumetric flow rates (V = 25 scfm, 55 scfm, and 115 scfm) and three different grid geometries for each (BR= 67%, 61%, and 54%). Upon finding that the main flow structure consisted of jets caused by the grid at higher flowrates, experiments were done with a grid BR = 67% which was thinner (50% of original thickness) than the previously used grids. The thinner grid produced structures which showed flow breakup not seen previously due to the jets, however the grid BR = 61% showed best overall flow structure. The experimental results allowed the velocity fluctuation and length scale terms to be quantified and can be used with future flame studies to determine flame regime location according to the Borghi-Peters diagram^
Quiroz-Regalado, Marco Efrain, "Fluid flow characterization of high turbulent intensity compressible flow using particle image velocimetry" (2015). ETD Collection for University of Texas, El Paso. AAI1600501.