Aircraft sound emissions are often associated with health risks for humans. Consequently, reducing the noise levels has been a research goal for many years. However, a simple level reduction does not consider the impact that specific characteristics of aircraft sound might have on noise annoyance. This issue is addressed by the auralization of aircraft noise as it investigates the causes of noise annoyance based on human perception of aircraft sound emissions through studies conducted in virtual environments. In this thesis, a MATLAB-based aircraft sound emission synthesizer is developed, using semi-empirical prediction models for airframe, jet, fan, and high-pressure compressor noise sources. The synthesizer independently generates noise from each component. The received sound can then be obtained at any spacial point assuming free-field conditions. To improve user-convenience, a graphical user interface is developed, providing the flexibility to choose and synthesize specific noise sources. The synthesized spectra of broadband noise components closely match the predicted levels within ±2dB in the dominant frequency bands. The synthesized overall sound pressure levels of the tonal sources precisely align with the predicted values. However, specific sound pressure levels in the spectrum differ from the desired ones by a maximum of ±4dB. Additionally, the source power and power spectral density of each noise source are calculated. It is observed that combination tone noise and jet shock noise dominate and that the source power is distributed fundamentally differently across the frequency domain for fan, airframe, and jet noise. The input parameters for the prediction models are determined based on a typical aircraft cruising scenario. Given the complexity of the input parameters, only plausible values could be determined. Hence, the synthesis and sound power results provide a useful impression but may not fully represent the actual conditions.

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