Methodologies and algorithms for sound propagation in complex environments with application to urban air mobility

Abstract

The demand for transportation has increased significantly in recent decades, resulting in rising community noise pollution, with aircraft identified as one of the major contributors. The emergence of urban air mobility (UAM) vehicles as a new transportation mode has further intensified noise concerns because these vehicles operate differently from conventional aircraft and are expected to fly within densely populated urban environments. Accurately evaluating their noise footprint while accounting for design, operational, and environmental factors is therefore essential for developing effective noise mitigation strategies. However, existing aircraft community noise (ACN) prediction methods often simplify or neglect these factors. This thesis proposes new methodologies and algorithms to improve ACN predictions by incorporating these influences.

The study first examines the relationship between aircraft design and operational parameters and their acoustic footprint in a homogeneous propagation environment. A computational framework combining a low-fidelity noise source prediction approach with a straight-ray propagation model is used. The effects of advance ratio and blade count during steady forward flight are analysed. Results show that higher advance ratios can change source directivity and increase the acoustic footprint by up to 30 dBA. Increasing the blade count from five to seven leads to a variation of 16 dBA due to directivity changes. While additional blades reduce loading noise, total noise levels remain largely unchanged due to increased thickness noise and higher tip Mach numbers. Overall, ground noise levels are more sensitive to changes in advance ratio than to blade count.

The influence of atmospheric conditions on long-distance noise propagation is then investigated using a newly developed 3D curved-ray tracing algorithm. Simulations for steady level flight under typical summer weather conditions reveal that upwind flight can generate a refractive shadow zone, particularly when the vehicle is far from receivers. This effect diminishes as the vehicle approaches. In contrast, downwind flight shows limited impact on the acoustic footprint. These findings highlight the role of atmospheric conditions in shaping long-range sound propagation.

To capture more realistic urban environments, the study introduces an advanced ray-acoustics model based on Gaussian beam tracing. This model accounts for three-dimensional variations in temperature, wind velocity, and multiple reflections from irregular terrain and buildings. A semi-empirical formulation is proposed to reduce truncation errors in beam summation, improving accuracy compared to conventional implementations. Validation against finite element simulations demonstrates that the method provides reliable and computationally efficient predictions for high-frequency noise propagation in urban areas.

The framework is further extended to include complex source directivity and moving atmospheric media to assess noise impacts of eVTOL vehicles in vertiport environments. Results show that buildings can increase ground noise levels by about 5 dB due to reflections, while simultaneously creating shadow zones behind structures. Wind flow also modifies acoustic patterns and can intensify noise levels, particularly at higher frequencies.

Finally, broadband noise calculations are enabled by coupling the Gaussian beam tracer with a high-fidelity noise source model. Simulations of helicopter noise over mountainous terrain show that terrain and atmospheric flow can significantly alter acoustic propagation, producing variations of up to 35 dB. These findings provide insights that can support the design and operation of future UAM vehicles to minimize noise impacts on surrounding communities