A new software tool called AIRNOISEUAM is introduced that models the noise exposure of Urban Air Mobility (UAM) operations. Given relevant UAM aircraft performance models, mission profiles, and Noise-Power-Distance data, AIRNOISEUAM predicts the noise exposure footprint for receptors on the ground. The performance of AIRNOISEUAM using a Robinson R66 helicopter model and a six-passenger quadrotor model, and a diverse set of scenarios from NASA’s UAM human-in-the-loop simulations is compared to that of the industry-standard tool with the same inputs. The predicted noise exposure results from both tools are found to be nearly identical. AIRNOISEUAM offers a fast-time, flexible interface and modular design to facilitate the dynamic requirements of the aviation research community.


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    Titel :

    AIRNOISEUAM: An Urban Air Mobility Noise-Exposure Prediction Tool


    Beteiligte:
    Jinhua Li (Autor:in) / Yun Zheng (Autor:in) / Menachem Rafaelof (Autor:in) / Hok Ng (Autor:in) / Stephen A. Rizzi (Autor:in)

    Kongress:

    50th International Congress and Exposition on Noise Control Engineering ; 2021 ; Virtual, US


    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Keine Angabe


    Sprache :

    Englisch




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