Skip to main navigationSkip to main content
The University of Southampton
We're launching a new website soon and would love your feedback. See the new design
Airbus Noise Technology CentreResearch projects

Numerical Investigation of Landing Gear Noise

Aerodynamic noise from a generic two-wheel landing gear model is predicted by using a CFD/FW-H hybrid method. The unsteady flow field is computed by using a compressible Navier-Stokes solver based on high-order finite difference schemes. The calculated time history of the surface data is used in an FW-H solver to predict the far field noise levels. Both aerodynamic and aeroacoustic results are compared with wind tunnel measurements and show good agreement. Individual contributions from three components, i.e. wheels, axle and strut of the landing gear model, are also investigated to identify the major noise source component. It is found that strong flow-body interaction noise is generated by the flow separated from the tire rim impinging on the axle.

Because of the multi-element geometry of aircraft landing gears, the flows around these aircraft components are rather complex and have complicated contributions to the airframe noise. As a result, the prediction of noise from such flows has been difficult and currently relies on empirical tools. These tools require heavy calibrations with existing test data; therefore have a limited reliability on predicting noise from unconventional gear architectures at the design stage. Computational simulation for landing gear noise prediction would be a general method in principle, which could then be applied to any novel landing gear architecture because they do not need to be calibrated against existing test results.

A high-order computation of a landing gear noise with a fully structured grid is presented. Both aerodynamic and acoustic results compare very well with the existing wind tunnel measurement data. Narrowband acoustic PSD spectra are well predicted in a frequency range up to 4 kHz for this particular landing gear model. Far field OASPL prediction is generally in good agreement with the measurement, within a  deviation of 2 dB.

Privacy Settings