Propeller and rotor based propulsion systems are the dominating choice of power delivery system in the upcoming Urban Air Mobility market. Fully electric air-taxis (car sized vehicles with Vertical Take-off and Landing, VTOL, capabilities) concepts are using the benefits of the scalable
properties of electric motors to distribute propulsor units all over the airframe. The large variety of concepts and configurations of these vehicles poses a serious issue in predicting noise generated on the ground. The need for a high-level model to aid in acoustic decision making is evident.
Through the demonstrated methodology of computationally deriving Noise - Power - Distance curves for conventional turbo fan aircraft, this paper delivers the capability of dealing with propeller propulsion systems and the associated propeller tonal noise sources to generate the NPDs and therefore
noise exposure maps. The aims can be broken down into two objectives: a) demonstrate the capabilities of the proposed propeller harmonics noise scaling laws to calculate noise variation from a baseline scenario and b) incorporate the scaling components into the larger capability of producing
noise exposure contours, by the means of computationally deriving NPD curves for propeller powered aircraft. Preliminary NPD curves for General Aviation sized propeller power aircraft are generated and discussed.
It is predicted that urban air mobility, including the use of small to medium sized unmanned aerial vehicle (UAV) delivery systems, will be introduced into cities across the globe within the next 15 years. It is known, however, that noise is one of the main limiting factors for the
wider adoption of these vehicles. Neither the metrics nor the methods used for conventional aircraft seem to be optimal for this novel source of noise. This research will aid in developing suitable psychoacoustic methodologies and metrics, specifically designed to quantify community noise
impact of these vehicles. This paper describes a psychoacoustic experiment used to gather participant responses to UAV sound recordings, both isolated and with typical background noise in a diversity of soundscapes. Results from this psychoacoustic experiment will be used to correlate perceptions
of UAV noise with objective sound quality metrics, and build new regression relationships that could describe the impact of a given UAV on the perception of soundscape environments. Future extension to the research may include evaluating the differences in psychoacoustic responses when introducing
more accurate reproduction methods, such as virtual reality systems, and how these could be incorporated into a standardised human response measurement procedure.
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