In contrast to most commercial air traffic today, vehicles serving the urban air mobility (UAM) market are anticipated to operate within communities and be close to the public at large. The approved model for assessing environmental impact of air traffic actions in the United States, the Federal Aviation Administration (FAA) Aviation Environmental Design Tool (AEDT), does not directly support analysis of such operations due to a combined lack of UAM aircraft flight performance model data and aircraft noise data. This paper addresses the latter by offering two prediction-based approaches for generation of noise-power-distance (NPD) data for use within AEDT. One utilizes AEDT’s fixed-wing aircraft modeling approach and the other utilizes the rotary-wing aircraft modeling approach.


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    Title :

    Prediction-Based Approaches for Generation of Noise-Power-Distance Data with Application to Urban Air Mobility Vehicles


    Contributors:

    Conference:

    28th AIAA/CEAS Aeroacoustics Conference ; 2022 ; Southampton, GB


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English







    Prediction-Based Approaches for Generation of Noise-Power-Distance Data with Application to Urban Air Mobility Vehicles

    Rizzi, Stephen A. / Letica, Stefan J. / Boyd, D. D. et al. | British Library Conference Proceedings | 2022


    Prediction of Noise-Power-Distance Data for Urban Air Mobility Vehicles

    Rizzi, Stephen A. / Letica, Stefan J. / Boyd, D. Douglas et al. | AIAA | 2023