Proper Orthogonal Decomposition Method for the Prediction of Fan Broadband Interaction Noise
Proper Orthogonal Decomposition Method for the Prediction of Fan Broadband Interaction Noise
The turbulent wake generated by a rotor interacting with outlet guide vanes (OGVs) is one of the dominant broadband noise sources in a turbofan engine. An accurate representation of the rotor wake turbulence is therefore important for the reliable prediction of the rotor–OGV interaction noise. This paper presents a turbulence synthesis method based on a spectral proper orthogonal decomposition (POD) representation of the turbulent wake that aims to reproduce the desired velocity cross-spectrum along the OGV leading edges where noise is emitted due to turbulence–OGV interaction. The method is first developed in the frequency domain based on a superposition of vortical modes with the appropriate amplitudes. Fourier modes and POD modes are proposed to represent the two-point velocity spectrum. The POD modes will be shown to be highly efficient in reconstructing the flowfield near the tip region where a large-scale coherent structure is present. An extension of the POD synthetic turbulence method to the time domain is also presented by means of a white noise filtering technique to allow the generation of time-varying velocity signals with the desired cross-spectral characteristics. The results show that both the one- and two-point statistics can be closely reproduced. The proposed frequency-domain POD synthetic turbulence method for fan broadband noise prediction for a realistic fan–OGV configuration is illustrated by the use of a frequency-domain linearized Navier–Stokes solver to predict the sound power radiation due to each vortical mode. Overall sound power levels at a number of discrete frequencies are predicted and compared against measured noise data. Agreement is found to be within the uncertainty of the noise sound power measurement.
5336-5356
Liu, Xiaowan
85bbaeb6-7fb2-429b-8f29-3a889480d2fd
Paruchuri, Chaitanya
5c1def64-6347-4be3-ac2d-b9f6a314b81d
Joseph, Phillip
9c30491e-8464-4c9a-8723-2abc62bdf75d
September 2022
Liu, Xiaowan
85bbaeb6-7fb2-429b-8f29-3a889480d2fd
Paruchuri, Chaitanya
5c1def64-6347-4be3-ac2d-b9f6a314b81d
Joseph, Phillip
9c30491e-8464-4c9a-8723-2abc62bdf75d
Liu, Xiaowan, Paruchuri, Chaitanya and Joseph, Phillip
(2022)
Proper Orthogonal Decomposition Method for the Prediction of Fan Broadband Interaction Noise.
AIAA Journal, 60 (9), .
(doi:10.2514/1.J061176).
Abstract
The turbulent wake generated by a rotor interacting with outlet guide vanes (OGVs) is one of the dominant broadband noise sources in a turbofan engine. An accurate representation of the rotor wake turbulence is therefore important for the reliable prediction of the rotor–OGV interaction noise. This paper presents a turbulence synthesis method based on a spectral proper orthogonal decomposition (POD) representation of the turbulent wake that aims to reproduce the desired velocity cross-spectrum along the OGV leading edges where noise is emitted due to turbulence–OGV interaction. The method is first developed in the frequency domain based on a superposition of vortical modes with the appropriate amplitudes. Fourier modes and POD modes are proposed to represent the two-point velocity spectrum. The POD modes will be shown to be highly efficient in reconstructing the flowfield near the tip region where a large-scale coherent structure is present. An extension of the POD synthetic turbulence method to the time domain is also presented by means of a white noise filtering technique to allow the generation of time-varying velocity signals with the desired cross-spectral characteristics. The results show that both the one- and two-point statistics can be closely reproduced. The proposed frequency-domain POD synthetic turbulence method for fan broadband noise prediction for a realistic fan–OGV configuration is illustrated by the use of a frequency-domain linearized Navier–Stokes solver to predict the sound power radiation due to each vortical mode. Overall sound power levels at a number of discrete frequencies are predicted and compared against measured noise data. Agreement is found to be within the uncertainty of the noise sound power measurement.
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Accepted/In Press date: 3 June 2022
e-pub ahead of print date: 11 July 2022
Published date: September 2022
Additional Information:
Funding Information:
This work was partly supported by Aerospace Technology Insti-tute–funded program ACAPELLA and EU 2020–funded TurboNoi-seBB (Grant Agreement No. 690714) at the University of Southampton. The authors would like to thank Anecom and Turbo-NoiseBB for providing the data. The authors would also like to thank Rolls-Royce for technical support.
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© 2022 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
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Local EPrints ID: 469740
URI: http://eprints.soton.ac.uk/id/eprint/469740
ISSN: 0001-1452
PURE UUID: d5768044-362a-49cc-8da3-ee4559187294
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Date deposited: 23 Sep 2022 17:13
Last modified: 16 Mar 2024 21:58
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Xiaowan Liu
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