A Surface-Pressure-Based Noise Source Localization Method for Moving Surfaces

AIAA/CEAS Aeroacoustics Conference

Abstract

This work extends a surface-pressure-based noise-source localization method from fixed to moving surfaces to identify aerodynamic noise sources on rotating propeller blades. Building on the fixed-surface formulation of Delfs and Ruck, the pure-reflection mirror principle is generalized to moving surfaces and a new rotating-observer retarded-time formulation is introduced. High-resolution surface-pressure data from large-eddy simulations are used in two validation cases: an isolated NACA0012 airfoil at a mild angle of attack and phase-synchronized co-rotating propellers with aerodynamic interactions. For the airfoil case, the extracted acoustic surface pressure is much lower than the hydrodynamic pressure in the near field, yet it correctly localizes the dominant trailing-edge noise source and agrees with analytical and beamforming solutions. For the propeller case, the method captures steady and unsteady loading noise sources on the rotating blades and shows that aerodynamic interaction mainly affects the low-frequency acoustic source distribution in the leading-edge region, whereas the high-frequency source becomes increasingly concentrated near the trailing edge of the blade tip. Wavenumber-frequency analysis and far-field noise predictions consistently show that the filter suppresses convected hydrodynamic pressure fluctuations while retaining the radiating component of the surface-pressure signal. The method provides an observer-independent and computationally efficient framework for high-resolution noise-source localization on both stationary and rotating aerodynamic surfaces.

Authors 5

1. Zhe Yang Aachen

   RWTH Aachen University

   Affiliation as printed

   Rheinisch-Westfalische Technische Hochschule Aachen Fakultat fur Maschinenwesen

2. Ramina Karimova Aachen

   RWTH Aachen University

   Affiliation as printed

   Rheinisch-Westfalische Technische Hochschule Aachen Fakultat fur Maschinenwesen

3. Matthias H. Meinke Aachen

   RWTH Aachen University

   Affiliation as printed

   Rheinisch-Westfalische Technische Hochschule Aachen Fakultat fur Maschinenwesen

4. Dominik J. Krug Aachen

   RWTH Aachen University

   Affiliation as printed

   Rheinisch-Westfalische Technische Hochschule Aachen Fakultat fur Maschinenwesen

5. Wolfgang Schröeder Aachen

   RWTH Aachen University

   Affiliation as printed

   Rheinisch-Westfalische Technische Hochschule Aachen Fakultat fur Maschinenwesen