Spatio-temporal correlations of jets using high-speed particle image velocimetry

The major source of aircraft noise at take-off is jet noise. If jet noise is not adequately addressed environmental impact concerns will constrain the planned growth of the air transport system. A considerable amount of research worldwide has therefore been aimed at identifying ways to reduce jet noise including development of a predictive tool that can estimate the noise generated by new nozzle designs. Current noise prediction techniques, however, still require the input of empirically calibrated noise source models and their performance is still inadequate. In addition, development of detailed noise source identification measurements and the associated understanding of how to control (and reduce) the noise at the source has been limited. The fundamental turbulence property which acts as the source of propagating noise in shear layers is the two-point space-time velocity correlation (Rijkl). Very few measurements exist for this property to guide model development. It is therefore the aim of the work reported in this thesis to provide new experimental data that helps identify the turbulence sources located within the shear layer of jets. The technique of Partical Imaging Velocimetry (PIV) is used to capture directly the flowfield and all relevant turbulent statistics... cont'd.