Project Details
Projekt
Numerical optimization of porous surfaces to reduce trailing-edge noise
Subject Area
Fluid Mechanics
Term
from 2012 to 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 209951091
At landing approach, airframe noise is one of the major contributors to the overall noise level. Since trailing-edge noise defines an essential part of airframe noise, it is necessary to lower it, to reduce the environmental impact of aircraft noise emissions on the population near airports. In this project, a passive noise reduction technology for trailing-edge noise, i.e., porous surfaces applied to generic trailing edges, is investigated by a hybrid large-eddy simulation/computational aeroacoustics (LES/CAA) approach.In the first phase, the impact of porous surfaces to reduce tonal trailing-edge noise has been analyzed. The computations for various trailing-edge shapes and porous structures have shown to reduce the correlation of the turbulent eddies and to lower the overall sound pressure level by 11dB. The tonal noise has been lowered by an additional 4dB for a porosity having been optimized by a newly developed adjoint formulation of the LES/CAA aproach.In the second phase, the investigation will be extended to broadband noise reduction. The novelty of this analysis is defined by a spanwise variation of the shape of the porous surface, i.e., a sawtooth shape is considered, and an alteration of the porous structure in the streamwise and spanwise direction. Based on a high-fidelity surrogate optimization model, the shape and the structure of the porous surface are optimized. Furthermore, the impact of the angle-of-attack on the noise reduction gain is taken into account and the influence of higher Mach numbers on the acoustic gain at the trailing edge, i.e., on the acoustic perturbations and their effect on the overall aerodynamics, is investigated.In brief, it is the overall objective of this project to analyze the impact of porosity on broadband trailing-edge noise and to reduce it.
DFG Programme
Research Grants
Co-Investigators
Dr.-Ing. Matthias Meinke; Dr. Emre Özkaya
