Fan noise is one of the major sources of aircraft noise. This can be modelled by means of frequency and time domain CAA methods. Frequency domain methods based on the convected Helmholtz equation are widely used for noise propagation and radiation from turbofan intakes. However, these methods are unsuited to deal easily with turbofan exhaust noise and presently unable to solve large 3D (three-dimensional) problems at high frequencies. In this thesis the application of time-domain Discontinuous Galerkin Methods (DGM) for solving linearized Euler equations is investigated. The research is focused on large 3D problems with arbitrary mean flows. A commercially available DGM code, Actran DGM, is used. An automatic procedure has been developed to perform the DGM simulations for axisymmetric and 3D intake problems by providing simple control of all the parameters (flow, geometry, liners). Moreover, a new method for integrating source predictions obtained from CFD calculations for the fan stage of a turbofan engine with the DGM code to predict tonal noise radiation in the far field has been proposed, implemented and validated. The DGM is validated and benchmarked for intake and exhaust problems against analytical solutions and other numerical methods. The principal properties of the DGM are assessed, best practice is defined, and important issues which relate to the accuracy and stability of the liner model are identified. The accuracy and efficiency of the CFD/CAA coupling are investigated and results obtained are compared to rig test data. The influence of the 3D intake shapes and the mean flow distortion on the sound field is investigated for static rig and flight conditions by using the DGM approach. Moreover, it is shown that the mean flow distortion can have a significant effect on the sound attenuation by a liner.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:632606 |
| Date | January 2014 |
| Creators | Rarata, Zbigniew |
| Contributors | Gabard, Gwenael |
| Publisher | University of Southampton |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | https://eprints.soton.ac.uk/371795/ |
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