Numerical Investigation of Noise Emissions from a Cargo eVTOL UAV

Urban air mobility (UAM) applications such as cargo electric vertical take-off and landing (eVTOL) unmanned aerial vehicles (UAVs) promise additional transportation capacities for congested urban areas. A major drawback facing UAM operations in future is that the new aerial vehicle movements are bound to lead to additional traffic noise emissions affecting urban areas. Minimum noise designs are therefore essential for UAM aircraft. This paper presents a numerically based computational fluid dynamics (CFD)/Ffowcs Williams-Hawkings (FW-H) model of the noise emissions generated by a cargo eVTOL UAV with separate hover and cruise propellers and focuses on the cruise flight. Installation effects play a predominant role in the noise generation of this highly integrated aerial vehicle configuration. The numerical results of the vehicle’s base configuration are validated by inflight noise measurement data. The noise results are split into propeller and airframe components. Alternative tail and propeller configurations are simulated to identify noise reduction potentials that stem from the effects of decreased aerodynamic interaction. It is envisaged that these investigations should form the groundwork for future numerical noise optimizations of the before mentioned base configuration, which explicitly consider the effects of aerodynamic interaction on noise emissions. The noise reduction potentials identified in this study support the idea of parallel rotor and airframe optimization.     «

Urban air mobility (UAM) applications such as cargo electric vertical take-off and landing (eVTOL) unmanned aerial vehicles (UAVs) promise additional transportation capacities for congested urban areas. A major drawback facing UAM operations in future is that the new aerial vehicle movements are bound to lead to additional traffic noise emissions affecting urban areas. Minimum noise designs are therefore essential for UAM aircraft. This paper presents a numerically based computational fluid dyna...     »