Airfoil trailing-edge noise source identification using large-eddy simulation and wavelet transform
Seongkyu Lee, Donghun Kang, Davy Joao Etienne Brouzet, and Sanjiva K., Lele

TL;DR
This study combines large-eddy simulations and wavelet transforms to identify and analyze the sources of airfoil trailing-edge noise, providing clearer insights into noise mechanisms at different flow structures.
Contribution
It introduces a wavelet-based denoising and decomposition method to distinguish and analyze various noise sources in airfoil flow simulations.
Findings
Wavelet denoising clarifies true noise sources.
Separates vortex shedding and LSB noise by frequency.
Decomposes pressure fields to reveal noise mechanisms.
Abstract
Airfoil noise is predicted and analyzed using wall-resolved large-eddy simulations and wavelet transforms for a NACA 0012 airfoil at a Mach number of 0.06 and a Reynolds number of 400,000 using a stair-strip forced transition and a natural transition. At a high angle of attack, vortex shedding and a laminar separation bubble (LSB) occur on the suction side. The LSB triggers the flow transition for both the forced and natural transition cases. The wavelet thresholding and denoising algorithm is used to decompose the pressure fields into the coherent or denoised pressure and the incoherent or background noise pressure. This denoising technique provides a clear picture of true noise generation and propagation. It also reveals the dominant noise source at specific frequencies when multiple noise sources are present. In another usage, the wavelet thresholding algorithm with down-sampling…
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Taxonomy
TopicsAerodynamics and Acoustics in Jet Flows · Fluid Dynamics and Turbulent Flows · Model Reduction and Neural Networks
