Leading-Edge Noise Mitigation on a Rod–Airfoil Configuration Using Regular and Irregular Leading-Edge Serrations
Source abstract
Abstract
Rod–airfoil configurations are commonly used to study turbulence–structure interaction noise, which is a major contributor to aerodynamic noise in various engineering applications. In this work, noise mitigation by regular and irregular leading-edge serrations is investigated for a rod–NACA0012–airfoil configuration using a direct hybrid CFD/CAA method. Large eddy simulations (LESs) are performed for the turbulent flow, and the acoustic perturbation equations (APEs) are solved to determine the acoustic field. The numerical results are validated by experimental data. The NACA0012 airfoil has different serrated leading edges, i.e., serrations with constant (regular) and varying (irregular) spanwise distributions of the amplitudes. Irregular spanwise amplitude distributions are generated by increasing or decreasing the amplitude of every second serration. The findings show an overall noise reduction for all configurations with regular and irregular serrations. The highest noise reductions are achieved by the irregular leading-edge serration configurations A3W2 and A6W2, with reductions of up to 11 dB in the Strouhal number range of St = 0.25–0.75. Regular serration designs with greater amplitudes (A1W1 and A1W2) outperform other regular serration designs, reducing noise levels by up to 10 dB. For irregular configurations, the level of mitigation is found to be correlated with the base amplitude of their regular serrated counterparts.
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Research context
OpenAlex topics: Aerodynamics and Acoustics in Jet Flows · Acoustic Wave Phenomena Research · Computational Fluid Dynamics and Aerodynamics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Institute of Aerodynamics, RWTH Aachen University, 52062 Aachen, Germany
Department of Mechanical Engineering, Necmettin Erbakan University, Konya 42140, Türkiye
JARA Center for Simulation and Data Science, RWTH Aachen University, 52062 Aachen, Germany
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