Wind turbine noise is one of the grand challenges in the public acceptance of onshore wind farm projects. The field of psychoacoustics identifies the auralisation of wind turbine noise as a link between technical design and annoyance estimation. There is currently limited work on the auralisation of wind turbine noise, and none targets an application in psychoacoustic research.

This work investigates the auralisation of the aeroacoustics output of DTU's HAWC2 for use in annoyance estimation. A Gaussian beam tracing approach propagates the frequency domain output to observer locations. The resulting spectrograms are converted into sound signals by applying random phase and the inverse short-time Fourier transform. This work includes a binaural rendering module to enable future VR applications. The methodology's implementation results in the Wind Turbine Auralisation tool, WinTAur.

The noise signal output of WinTAur is validated using the HAWC2 model of a stall-controlled NTK 500/41 wind turbine and corresponding acoustic field measurements. Psychoacoustic sound quality metrics show significant differences between the auralised and measured noise. In the overall psychoacoustic annoyance metric, these differences mainly depend on the observer's position around the turbine. All metrics show this directionality dependence, while the loudness, sharpness and tonality metrics also indicate a dependence on wind speed. Differences in fluctuation strength show a minor dependence on the simulation case but are difficult to relate to a specific simulation parameter.
Spectral analysis of the simulation output samples reflects the limitations of HAWC2, demonstrating that it is the primary source of discrepancy. The analysis especially highlights the inaccurate prediction of the directionality and stall noise of the HAWC2 code. The choice of ground type is another probable source of discrepancy, as it does not accurately represent the measurement setup.
A subjective listening experiment demonstrates the significance of these discrepancies in human perception with generally high difference ratings between the simulated and recorded noise. The results illustrate a dependence on wind speed and the position around the turbine. These dependencies match well with the findings from the numerical validation.\\

Future work should focus on a sensitivity analysis of WinTAur since the case-independent parameters may be additional sources of discrepancy. Another recommendation is to investigate the unveiled errors in the underlying methodology. Lastly, better propagation modelling concerning the wind turbine wake and turbulence should be part of future wind turbine noise modelling.

Overall, using modelled wind turbine noise for the auralisation in psychoacoustic research has shown promising results. Validation with sound quality metrics provides good insights into the discrepancies found in subjective listening experiments. Eliminating the existing discrepancies through modelling improvements will allow this work to be applied in a fully modelled approach to estimate wind turbine noise annoyance.

Trailing-edge noise can be the dominant noise source of diverse industrial applications, including wind turbines. Noise regulations may limit the power production and installation of new wind farms. There is a need to reduce it. In order to achieve so, we first need to predict it, and to do so we need experimental data to support and validate the new methodologies. A new experimental campaign has been carried out to provide a benchmark of trailing-edge noise applicable to wind turbine noise. It involves a broad range of Reynolds numbers and angles of attack, and covers the noise reduction effect of serrations. This Thesis studies the aforementioned novel data set. The trends of the far-field noise with the forcing of the boundary layer, angle
of attack, and Reynolds number have been studied. Furthermore, scaling laws have been applied to compare different test conditions. The collapse quality has been studied, and the differences have been linked to the aerodynamics and possible post-processing effects. The effect of the serrations has also been studied. Additionally, the noise reduction dependence on the aerodynamic loading is discussed. The influence of the microphone locations on the far-field spectra uncertainty is also studied. The Monte-Carlo method has been applied using the Delay-and-Sum and Clean-SC beamformers. The effect of the input uncertainty correlation, wind tunnel velocity, facility, and algorithm are examined.

In this master thesis project the initial steps for the design of a new wind tunnel
for aeroacoustic measurements are made. Well-documented sizing methods for
different wind tunnel parts were found in a literature study and were used
together with 2D CFD simulations to create a new wind tunnel design. Thick
corner vanes were used in this design with the purpose of using them as baffle
mufflers to create a better environment for aeroacoustic measurements inside the test section. The performance of the wind tunnel was evaluated thereafter by 3D CFD simulations. The 3D simulations provide an idea of the flow velocities, the flow uniformity, turbulence intensities, pressure losses and noise sources inside the wind tunnel. Since an existing wind tunnel fan and 42 kW motor was to be reused, noise measurements were done to find the noise characteristics of the fan-motor combination and to have an idea of how noise would propogate in
the environment were the new wind tunnel would be placed. After the noise
measurements, predictions of the transmission loss through the corner vanes
were made by using finite element analyses.