Jules Colas

Étude numérique de la propagation du bruit des éoliennes et des parcs éoliens dans différentes conditions atmosphériques et topographiques: Le bruit généré par les éoliennes est fortement influencé par sa propagation dans l'atmosphère. Par conséquent, la prédiction précise de la propagation du son est essentielle pour déterminer les niveaux de bruit et résoudre les problèmes de nuisance sonore associés aux éoliennes. Dans cette thèse, des méthodes numériques pour prédire le bruit des éoliennes et des parcs éoliens dans l'atmosphère sont développées. L'effet de la topographie et de l'atmosphère sur la propagation du bruit provenant d'éoliennes isolées et de parcs éoliens est ensuite étudié. Des écoulements atmosphériques réalistes, prenant en compte les effets de sol et les interactions avec les éoliennes, sont calculés à l'aide de simulations aux grandes échelles (Large Eddy Simulations). Les résultats sont ensuite utilisés pour calculer les niveaux de bruit émis, via un modèle de source étendue basé sur la théorie d'Amiet, et les effets de propagation, en utilisant plusieurs modèles basés sur l'équation parabolique ou les équations d'Euler linéarisées. Cette méthode numérique est ensuite employée pour étudier l'effet de la topographie sur la propagation du son, en comparant différents cas en présence de topographie avec un cas plat. La topographie a un impact significatif sur la propagation du bruit, directement par des effets de barrière et de réflexion, et indirectement en modifiant l'écoulement et donc la réfraction des ondes. Ainsi, la prise en compte de la topographie est vitale pour une prédiction précise du bruit. L'étude examine ensuite comment les conditions atmosphériques et les interactions de sillage affectent les niveaux de bruit et la modulation d'amplitude pour des éoliennes fonctionnant à proximité.Une étude préliminaire sur deux éoliennes dans différent agencements montre que la position des éoliennes et la synchronisation ont un impact significatif sur les émissions acoustiques et la propagation.Enfin, un parc éolien de 16 éoliennes est analysé, en comparant les conditions atmosphériques stables et neutres, ainsi que les dispositions alignées et en quinconce. Pour les parcs éoliens, la stabilité atmosphérique a moins d'impact sur le cas aligné que pour une éolienne isolée, tandis que la disposition est critique. Le parc éolien décalé présente des niveaux de bruit en aval plus élevés que le parc aligné.

The influence of turbine–turbine interactions on sound propagation is investigated using numerical simulations. Three configurations are examined: turbines aligned downstream of each other, placed side by side, and arranged in a staggered pattern. The simulation framework combines large-eddy simulations for aerodynamic interactions, an aeroacoustic source model to simulate turbine sound emission, and parabolic equation methods for sound propagation. When a second turbine is positioned directly downstream, wake-induced flow focusing enhances sound pressure levels (SPLs) and amplitude modulation (AM) by several decibels downwind. In side-by-side and staggered configurations, SPL increases are limited (<2 dBA), and AM is generally reduced because of spatial averaging. Distinct AM patterns emerge in regions where acoustic contributions from both turbines are comparable. For identical rotor speeds, AM is strongly affected by the angular offset between rotors. When rotor speeds differ slightly, beating effects occur, resulting in intermittent AM. These findings highlight the sensitivity of AM to rotor dynamics, a key factor influencing sound perception, with implications for environmental impact and turbine siting.

This study demonstrates how wind farm flow physics influence noise generation and downstream propagation through numerical simulations. The flow field is modeled using large-eddy simulations (LES), and the time-averaged output serves as input to acoustic models that predict wind turbine noise. In the first turbine row, turbulence-induced noise (TIN) and trailing edge noise (TEN) contribute equally, with TIN dominating at low frequencies and TEN at higher frequencies. Downstream, TEN decreases due to lower wind speeds, while TIN mostly persists due to increased turbulence dissipation. These effects are more pronounced in aligned wind farms, where stronger wake interactions occur, than in staggered layouts. However, staggered farms produce more noise overall because turbines operate at higher wind speeds.Additionally, wind farm flow significantly affects sound propagation downwind. The wake superposition modifies sound focusing leading to different amplification area than for an isolated turbine. For a staggered layout it particularly shows enhanced sound focusing downwind due to the position of the turbine wakes. This leads to higher sound levels and higher amplitude modulation downwind for the wind farm compared to an aligned layout. These phenomena are not captured by models based on isolated turbines. These findings underscore the importance of integrating flow and acoustic models to more accurately assess the environmental impact of wind farms.

Wind turbine noise propagation in a hilly terrain is studied through numerical simulation in different scenarios. Linearized Euler equations are solved in a moving frame that follows the wavefront, and wind turbine noise is modeled with an extended moving source. We employ large-eddy simulations to simulate the flow around the hill and the wind turbine. The sound pressure levels (SPLs) obtained for a wind turbine in front of a 2D hill and a wind turbine on a hilltop are compared to a baseline flat case. First, the source height and wind speed strongly affect sound propagation downwind. We find that topography influences the wake shape, inducing changes in the sound propagation that drastically modify the SPL downwind. Placing the turbine on the hilltop increases the average sound pressure level and amplitude modulation downwind. For the wind turbine placed upstream of a hill, a strong shielding effect is observed. But, because of the refraction by the wind gradient, levels are comparable with the baseline flat case just after the hill. Thus, considering how terrain topography alters the flow and wind turbine wake is essential to accurately predict wind turbine noise propagation.

Parabolic equations are among the most popular numerical techniques in many fields of physics. This article considers extra-wide-angle parabolic equations, wide-angle parabolic equations, and narrow-angle parabolic equations (EWAPEs, WAPEs, and NAPEs, respectively) for sound propagation in moving inhomogeneous media with arbitrarily large variations in the sound speed and Mach number of the (subsonic) wind speed. Within their ranges of applicability, these parabolic equations exactly describe the phase of the sound waves and are, thus, termed the phase-preserving EWAPE, WAPE, and NAPE. Although variations in the sound speed and Mach number are often relatively small, omitting the second-order terms pertinent to these quantities can result in large cumulative phase errors for long propagation ranges. Therefore, the phase-preserving EWAPE, WAPE, and NAPE can be preferable in applications. Numerical implementation of the latter two equations can be performed with minimal modifications to existing codes and is computationally efficient. Numerical results demonstrate that the phase-preserving WAPE and NAPE provide more accurate results than the WAPE and NAPE based on the effective sound speed approximation.

Noise generated by wind turbines is significantly impacted by its propagation in the atmosphere. Hence, for annoyance issues, an accurate prediction of sound propagation is critical to determine noise levels around wind turbines. This study presents a method to predict wind turbine sound propagation based on linearized Euler equations. We compare this approach to the parabolic equation method, which is widely used since it captures the influence of atmospheric refraction, ground reflection, and sound scattering at a low computational cost. Using the linearized Euler equations is more computationally demanding but can reproduce more physical effects as fewer assumptions are made. An additional benefit of the linearized Euler equations is that they provide a time-domain solution. To compare both approaches, we simulate sound propagation in two distinct scenarios. In the first scenario, a wind turbine is situated on flat terrain; in the second, a turbine is situated on a hilltop. The results show that both methods provide similar noise predictions in the two scenarios. We find that while some differences in the propagation results are observed in the second case, the final predictions for a broadband extended source are similar between the two methods.