Velocity Mapping of an H₂ − O₂ Exhaust Jet in Air by Means of Schlieren Image Velocimetry (SIV)

Abstract

Visualization methods have always been used to inspect flows that are invisible to the naked eye. Seedless velocimetry has been regarded as an alternative to other intrusive quantitative methods and adapted to fit many applications in the industrial or scientific field. Schlieren image velocimetry (SIV) uses the general working principle of a schlieren system to acquire flow images, while relying on a particle image velocimetry (PIV)-like algorithm to obtain quantitative data related to the studied flow. The test case of this study consists of a turbulent round exhaust jet generated by a micro-thruster that uses H2−O2 as a propellent. Mapping the local velocities of the flow is achieved by initially performing a lagrangian tracking method which makes use of a direct image correlation algorithm. These results are then compared to the velocity map obtained from a kymograph applied to a series of images. The velocity profiles obtained through SIV will be compared to the velocity profile of the jet provided by the CFD simulation. The schlieren investigation of the jet’s local velocity map is set to determine the thruster’s capabilities, and conclude if the thruster reaches the desired Mach for which it has been designed.

Keywords

• SIV
• direct image correlation
• image processing
• threshold
• kymography
• PIV