# Investigation of aeroacoustic noise generation by simultaneous particle image velocimetry and microphone measurements

Investigation of aeroacoustic noise generation by simultaneous particle image velocimetry and... A correlation technique is tested, which enables the identification of flow structures that are involved in sound generation processes. At first, the method is applied to the problem of induced noise from flow over a cylinder. The velocity field around a circular cylinder is measured by particle image velocimetry (PIV), while the radiated sound is recorded with a microphone. Both measurements are conducted in a synchronized manner so as to enable the calculation of the cross-correlation between velocity or vorticity fluctuations and the acoustic pressure. The therewith obtained coefficient matrix provides time- and space-resolved information about the statistical dependency between flow structures and the acoustic pressure. Furthermore, a proper orthogonal decomposition (POD) is applied to the velocity field. Then the correlation between dominating modes and the acoustic pressure is computed to identify which modes are mainly involved in the sound generation. Finally, the developed method is applied to the more applied problem of the flow-field inside a leading-edge slat-cove. The results show that, in this case, the signal-to-noise ratio is too low to allow an identification of noise-relevant flow structures, as opposed to the case of the cylinder wake flow, where 5,000 PIV recordings were sufficient to identify the flow structures, which are involved in the noise-generation process. A maximum in spatial distribution of the cross-correlation coefficient is observed 1.6 diameters downstream of the cylinder; its value decreases as one moves further downstream. In this area of maximal correlation, a rapid acceleration of the released vortices takes place. The cross-correlation coefficient fluctuates over time in a sine-type oscillation with maximum values of about $$|R_{v^{\prime}p^{\prime}}| = 0.2.$$ $$R_{u^{\prime}p^{\prime}}$$ and $$R_{v^{\prime}p^{\prime}}$$ show a periodic behavior with a phase shift of π/2 with respect to each other. These regular oscillations can be explained by coherent periodic structures in the flow-field. These structures generate a sound field with the same periodicity, which is perceived as tone. Hence, the correlation between the velocity fluctuations and the acoustic pressure show oscillations identical to those of the input signals. A filtering of uncorrelated noise can be observed; this being caused by the averaging process during the cross-correlation calculation. The correlation with the eigenmodes of a POD gives correlation coefficients, which are no larger than the correlation with a local near-field quantity. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Experiments in Fluids Springer Journals

# Investigation of aeroacoustic noise generation by simultaneous particle image velocimetry and microphone measurements

, Volume 45 (6) – Jun 27, 2008
13 pages

/lp/springer_journal/investigation-of-aeroacoustic-noise-generation-by-simultaneous-4rizEK1vsX
Publisher
Springer-Verlag
Subject
Engineering; Engineering Fluid Dynamics; Fluid- and Aerodynamics; Engineering Thermodynamics, Heat and Mass Transfer
ISSN
0723-4864
eISSN
1432-1114
D.O.I.
10.1007/s00348-008-0528-y
Publisher site
See Article on Publisher Site

### Abstract

A correlation technique is tested, which enables the identification of flow structures that are involved in sound generation processes. At first, the method is applied to the problem of induced noise from flow over a cylinder. The velocity field around a circular cylinder is measured by particle image velocimetry (PIV), while the radiated sound is recorded with a microphone. Both measurements are conducted in a synchronized manner so as to enable the calculation of the cross-correlation between velocity or vorticity fluctuations and the acoustic pressure. The therewith obtained coefficient matrix provides time- and space-resolved information about the statistical dependency between flow structures and the acoustic pressure. Furthermore, a proper orthogonal decomposition (POD) is applied to the velocity field. Then the correlation between dominating modes and the acoustic pressure is computed to identify which modes are mainly involved in the sound generation. Finally, the developed method is applied to the more applied problem of the flow-field inside a leading-edge slat-cove. The results show that, in this case, the signal-to-noise ratio is too low to allow an identification of noise-relevant flow structures, as opposed to the case of the cylinder wake flow, where 5,000 PIV recordings were sufficient to identify the flow structures, which are involved in the noise-generation process. A maximum in spatial distribution of the cross-correlation coefficient is observed 1.6 diameters downstream of the cylinder; its value decreases as one moves further downstream. In this area of maximal correlation, a rapid acceleration of the released vortices takes place. The cross-correlation coefficient fluctuates over time in a sine-type oscillation with maximum values of about $$|R_{v^{\prime}p^{\prime}}| = 0.2.$$ $$R_{u^{\prime}p^{\prime}}$$ and $$R_{v^{\prime}p^{\prime}}$$ show a periodic behavior with a phase shift of π/2 with respect to each other. These regular oscillations can be explained by coherent periodic structures in the flow-field. These structures generate a sound field with the same periodicity, which is perceived as tone. Hence, the correlation between the velocity fluctuations and the acoustic pressure show oscillations identical to those of the input signals. A filtering of uncorrelated noise can be observed; this being caused by the averaging process during the cross-correlation calculation. The correlation with the eigenmodes of a POD gives correlation coefficients, which are no larger than the correlation with a local near-field quantity.

### Journal

Experiments in FluidsSpringer Journals

Published: Jun 27, 2008

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