Bulletin of the American Physical Society
77th Annual Meeting of the Division of Fluid Dynamics
Sunday–Tuesday, November 24–26, 2024; Salt Lake City, Utah
Session A34: Aeroacoustics
8:00 AM–9:57 AM,
Sunday, November 24, 2024
Room: 255 F
Chair: Benshuai Lyu, Peking University
Abstract: A34.00009 : A Mathematical Model for the Interaction of Anisotropic Turbulence with Porous Surfaces*
9:44 AM–9:57 AM
Presenter:
Alistair Hales
(University of Cambridge)
Authors:
Alistair Hales
(University of Cambridge)
Lorna J Ayton
(University of Cambridge)
Angus Wills
(University of New South Wales)
Chaoyang Jiang
(University of New South Wales)
Charitha M De Silva
(University of New South Wales)
Danielle Moreau
(University of New South Wales)
Con Doolan
(University of New South Wales)
This presentation explores how existing theoretical leading-edge noise models can account for porosity at the leading edge and for anisotropic flow.
The model has two key components. First, we adjust the velocity spectrum to account for the possibility of complex anisotropy ratios in the flow. Second, we adapt the fully analytical acoustic transfer function to account for different boundaries by implementing convective impedance boundary conditions when formulating the gust diffraction problem. We apply the Wiener–Hopf technique to solve the gust-diffraction problem along the semi-infinite boundary.
Each modification is inspired by leading-edge noise experimental data obtained using a series of different porous leading edges. Experimental data demonstrates the interplay between anisotropy and leading-edge modifications while achieving the characteristic
mid-frequency noise reduction expected from porous leading edges. Our model is adapted to best fit the trends of the data via a tailored impedance function, leading to good agreement with all data sets across an extended frequency range.
*A. D. G. Hales acknowledges support from EPSRC studentship EP/T517847/1. L. J. Ayton acknowledges support from EPSRC Early Career Fellowship EP/P015980/1.This research was supported partially by the Australian Government through the Australian Research Council’s Discovery Projects funding scheme (project DP210102288)
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