Uncertainty quantification for the aeroacoustics of rotating blades in the time domain

Uncertainty quantification for the aeroacoustics of rotating blades in the time domain Aeroacoustics has received great attention in the past decade, owing to the ever stricter noise regulations. Despite the stochastic nature of most aeroacoustic systems, non-deterministic investigations in regards to computational aeroacoustics (CAA) are limited. In this paper, uncertainty quantification has been achieved for the noise propagation stage of hybrid CAA, and also on the noise prediction of a non-lifting helicopter rotor in hover. Analytical and computational fluid dynamics test cases have been analyzed, with uncertainties propagated through these systems using non-intrusive polynomial chaos methods. It is shown here that the source of the uncertainty in the noise is dominated by the major characteristic properties of the simulations, such as the mean flow Mach number and blade tip Mach number. Only at a low tip Mach number uncertainties in the blade thickness may contribute significantly to the noise uncertainty. Apart from this, it is seen to be unlikely that small uncertainties in the geometry, ambient conditions and observer properties will contribute significantly to the noise uncertainty. A peak pressure uncertainty of up to 20% is seen in the hovering helicopter test case, from small, realistic uncertainties. This highlights the importance of considering uncertainties in CAA investigations. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Applied Acoustics Elsevier

Uncertainty quantification for the aeroacoustics of rotating blades in the time domain

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Publisher
Elsevier
Copyright
Copyright © 2018 Elsevier Ltd
ISSN
0003-682X
eISSN
1872-910X
D.O.I.
10.1016/j.apacoust.2018.04.012
Publisher site
See Article on Publisher Site

Abstract

Aeroacoustics has received great attention in the past decade, owing to the ever stricter noise regulations. Despite the stochastic nature of most aeroacoustic systems, non-deterministic investigations in regards to computational aeroacoustics (CAA) are limited. In this paper, uncertainty quantification has been achieved for the noise propagation stage of hybrid CAA, and also on the noise prediction of a non-lifting helicopter rotor in hover. Analytical and computational fluid dynamics test cases have been analyzed, with uncertainties propagated through these systems using non-intrusive polynomial chaos methods. It is shown here that the source of the uncertainty in the noise is dominated by the major characteristic properties of the simulations, such as the mean flow Mach number and blade tip Mach number. Only at a low tip Mach number uncertainties in the blade thickness may contribute significantly to the noise uncertainty. Apart from this, it is seen to be unlikely that small uncertainties in the geometry, ambient conditions and observer properties will contribute significantly to the noise uncertainty. A peak pressure uncertainty of up to 20% is seen in the hovering helicopter test case, from small, realistic uncertainties. This highlights the importance of considering uncertainties in CAA investigations.

Journal

Applied AcousticsElsevier

Published: Oct 1, 2018

References

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