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Comparison of Two Acoustic Analogies Applied to Experimental PIV Data for Cavity Sound Emission Estimation
Author(s) -
V. Koschatzky,
Jerry Westerweel,
Bendiks Jan Boersma
Publication year - 2010
Publication title -
28th aiaa/ceas aeroacoustics 2022 conference
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2514/6.2010-3812
Subject(s) - acoustics , sound (geography) , acoustic emission , computer science , estimation , physics , engineering , systems engineering
The aim of the present study is to compare two different acoustic analogies applied to time-resolved particle image velocimetry (PIV) data for the prediction of the acoustic far-field generated by the flow over a rectangular cavity. Recent developments in laser and camera technology allow the possibility to extend PIV to the study of aeroacoustic phenomena in air flows at moderate speed (up to V=20m/s, Ma=0.08). We make use of these new possibilities to obtain estimates of the acoustic emission from time-resolved PIV data. We consider the model problem of the sound radiating from an open, two dimensional, shallow cavity with an aspect ratio between its length and depth of 2 at a Reynolds number of 3:0£104 based on the cavity length. The study is carried out combining high speed two dimensional PIV imaging and sound measurements. The emitted sound is then calculated using Curle’s analogy and vortex sound theory. The prediction of the acoustic fields obtained by applying the two methods are analyzed and compared with the measured sound. Results show that both the analogies estimate the overall sound pressure level quite well and within a few dB of each other. Vortex sound theory seems to provide a better estimate for the amplitude of the tonal component and its harmonics, but suffers from higher broadband noise compare to Curle’s analogy. This is due to the higher smoothing of the data involved in the computation of the source term in Curle’s analogy, which reduces noise but also smoothes out the signal. Results show that great care must be taken in the treatment of the experimental PIV data, especially in the techniques used for spatial and temporal differentiation. The data sets obtained by PIV measurements can be, in fact, quite noisy while the spatial and temporal resolution are still limited

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