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Simulating Fleet Noise for Notional UAM Vehicles and Operations in New York  (2019)
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This paper presents the results of systems-level simulations using Metrosim that were conducted for notional Urban Air Mobility (UAM)-style vehicles analyzed for two different scenarios for New York (NY). UAM is an aviation industry term for passenger or cargo-carrying air transportation services, which are often automated, operating in an urban/city environment. UAM-style vehicles are expected to use vertical takeoff and landing with fixed wing cruise flight. Metrosim is a metroplex-wide route and airport planning tool that can also be used in standalone mode as a simulation tool. The scenarios described and reported in this paper were used to evaluate a fleet noise prediction capability for this tool. The work was a collaborative effort between the National Aeronautics and Space Administration (NASA), Intelligent Automation, Inc (IAI), and the Port Authority of New York and New Jersey (PANYNJ). One scenario was designed to represent an expanded air-taxi operation from existing helipads around Manhattan to the major New York airports. The other case represented a farther term vision case with commuters using personal air vehicles to hub locations just outside New York, with an air-taxi service running frequent connector trips to a few key locations inside Manhattan. For both scenarios, the trajectories created for the entire fleet were passed to the Aircraft Environmental Design Tool (AEDT) to generate Day-Night Level (DNL) noise contours for inspection. Without data for actual UAM vehicles available, surrogate AEDT empirical Noise-Power-Distance (NPD) tables used a similar sized current day helicopter as the Baseline, and a version of that same data linearly scaled as a first guess at possible UAM noise data. Details are provided for each of the two scenario configurations, and the output noise contours are presented for the Baseline and reduced noise DNL cases.
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Fleet, New, Noise, Operations, Simulating, UAM, Vehicles, York
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38th Digital Avionics Systems Conference, San Diego, CA
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Adobe PDF Icon  DASC_2019_GlaabEtA.pdf (Download Acrobat Reader Click to download Adobe Acrabat Reader)
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Curator: Phil So
NASA Official: Joey Mercer
Last Updated: August 15, 2019