Noise Emissions from Installed Propeller-Wing Configurations using Mid-Fidelity Unsteady Panel Method coupled to FW-H equation-based solver

Kurzfassung

The following work is carried out in the scope of L²INK project at DLR and presents an approach to determine noise emissions from small aircraft due to propeller installation effects, using a mid-fidelity numerical scheme. The small aircraft selected for this particular study is the DLR DO-228 research aircraft with a 5 bladed, wing mounted tractor propeller of 2.5m diameter. The mid-fidelity based unsteady panel method code is coupled with the acoustics prediction code based on the FW-H equations solver for the computation of aerodynamic loads and acoustic pressure signals in the far-field of the source (DLR APSIM code). The DLR unsteady panel code simulates the aerodynamic loads under the assumption of incompressible, inviscid, irrotational, and unsteady flow. The aerodynamic loading data, i.e., lift-drag coefficient, and the surface pressure, obtained from the propeller blade and wing are further used as an input to the FW-H equation-based solver code. Loading noise and the thickness noise generated from the lifting surfaces in the near-field are determined from the surface pressures provided via UPM aerodynamics simulations, and the spatial coordinates of the propeller blade and of the wing. The pressure signal in the near-field of the noise source is further propagated in a uniform flow to calculate the acoustic pressure in the far-field. An array of microphones is defined at distinctive polar and azimuthal angles, forming a hemispherical shape to capture the noise directivity in the far-field from the source. Further, the DLR noise assessment tool PANAM takes this hemisphere with acoustic pressures as input and propagates it to selected observer positions on the ground. The noise levels predicted by the coupling of UPM (DLR panel code) and APSIM (DLR time domain code for FW-H), on the ground using propagation in uniform flow is validated with the measured data from a flyover campaign. Furthermore, the noise levels from APSIM are compared to the noise levels computed at the observer position on ground using PANAM.