Identification of Flap Side-Edge Two-Source Mechanism Based on Phased Arrays

Bai, Baohong; Lin, Dakai; Li, Xiaodong

doi:10.2514/1.j060377

Cited by 5 publications

(3 citation statements)

References 20 publications

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“…In this frequency range, the sound pressure levels scale with the fifth power of the flow velocity as typical edge noise sources [19]. The classical fifth-power-scaling was also used by Brooks and Marcolini [20] for Strouhal numbers smaller than 5 as well as in other studies on flap side edge noise [3,21,22] and wind turbine noise [23]. These studies focus on the scaling of the overall trailing edge noise spectrum, though, and do not contradict the current approach chosen to scale solely the tip noise contribution.…”

Section: Beaforming Resultsmentioning

confidence: 99%

Influence of end plate placement on the reduction of airfoil tip vortex formation noise

2022

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The tonal noise generated at the tip is a major contribution to the aerodynamic noise generated by three-dimensional airfoils. One way to reduce this noise is the use of end plates, which was investigated in the present study for three different circular end plate geometries applied to a cambered NACA 4412 airfoil with aspect ratio 2 and forced boundary layer transition. Microphone array measurements were performed in a small aeroacoustic wind tunnel for chord based Reynolds numbers between 75,000 and 200,000 and geometric angles of attack between 0° and 20°. The acoustic far-field noise spectra obtained for the baseline configuration show a broadband hump centered at a chord based Strouhal number of 13 that is associated with the noise generation at the tip and scales with the third power of the flow velocity. The application of end plates reduces this peak and is most effective for end plates which bound the flow on the suction side of the airfoil. Hot-wire measurements taken for one configuration show that the end plates diffuse the turbulence intensity in the relevant frequency range and reduce the fluid transfer along the pressure gradient at the tip. The suction side end plate additionally prevents the interaction of turbulent structures with the trailing edge and is therefore more effective in reducing noise. Surface flow visualizations for this configuration reveal a separation line extending along the full span up to the tip while the surface flow of the baseline and pressure configuration is strongly affected by the flow swept around the tip. Therefore, the placement of the end plate on the suction side is more effective in reducing tip noise.

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Section: Beaforming Resultsmentioning

confidence: 99%

Influence of end plate placement on the reduction of airfoil tip vortex formation noise

2022

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“…Interestingly, for all three models the inner wing trailing regions are silent, or cannot be reconstructed by CLEAN-SC due to the limited dynamic range. A major difference is the WTR I source, where there are two distinct (leading and trailing edge) sources on model A and model B [29,21,37] but only one (presumably leading, based on the aeroacoustic behavior) source on the EMBRAER. The positions of the sources remain approximately the same for varying Reynolds number and Mach number, and the slotted and closed test section.…”

Section: Spatial Occurrence Of Sourcesmentioning

confidence: 99%

Aeroacoustic testing on a full aircraft model at high Reynolds numbers in the European Transonic Windtunnel

Ahlefeldt

Ernst

Goudarzi

et al. 2023

Journal of Sound and Vibration

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“…With the increasing requirements for airworthiness and economy of commercial aircraft, aircraft noise has been a major concern to people and needs more attention. Aircraft noise consists of many sources, including jet noise, 1 fan noise, 2 landing gear noise, 3 high-lift device noise 4 and the pylon/nacelle juncture noise. 5 The ranking of these noise sources is different under different operating conditions.…”

Section: Introductionmentioning

confidence: 99%

A physics merged deep neural network-based prediction method for jet turbulent mixing noise

Bai,

Zhang,

et al. 2024

International Journal of Aeroacoustics

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Turbulent mixing noise is a vital component of jet noise, and its rapid, accurate prediction has always been persistently pursued. Recent advancement in machine learning has been applied to jet noise prediction. However, these applications are pure curve fitting and lack physical constraints. In this study, a physics-merged deep neural network (PMNN)-based prediction method was developed for turbulent mixing jet noise by merging the physics of the jet noise. This deep neural network (DNN)-based method employed recent advancements in jet turbulent mixing noise containing large- and fine-scale turbulence structures. Two simple rational functions for large- and fine-scale turbulent noise similarity spectra were proposed to replace the original complex similarity spectra functions and incorporated into the DNN-based prediction method. For comparison, we present two data-driven DNN-based prediction methods (DDNN). The first DDNN method used the sound pressure level (SPL) as the output of neural networks, directly establishing the nonlinear relationship between the input features and SPL. In the second DDNN method, the dominant modes of the jet noise spectra extracted using the proper orthogonal decomposition method were merged with DNN. These DNN-based methods were then trained using a set of experimental data over a wide range of jet operating conditions. Their performance was evaluated and compared. It was evident that all these DNN-based methods were capable of predicting turbulent mixing noise reasonably well. In contrast to the DDNN methods, the PMNN method could provide insights into the jet turbulent mixing noise components. It demonstrates that the turbulent mixing jet noise spectra at the mid polar angle is generated by the large-scale noise component at low-frequency range and by the fine-scale noise component at high-frequency range.

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Identification of Flap Side-Edge Two-Source Mechanism Based on Phased Arrays

Cited by 5 publications

References 20 publications

Influence of end plate placement on the reduction of airfoil tip vortex formation noise

Influence of end plate placement on the reduction of airfoil tip vortex formation noise

Aeroacoustic testing on a full aircraft model at high Reynolds numbers in the European Transonic Windtunnel

A physics merged deep neural network-based prediction method for jet turbulent mixing noise

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