Dr Carlos Ramos Romero C.A.RamosRomero@salford.ac.uk
Postdoctoral Research Fellow Acoustics
Towards a Taxonomy for the Assessment of the Unmanned Aerial Systems Noise Emissions
Ramos Romero, Carlos; Green, Nathan; Asensio, César; Martinez, Antonio
Authors
Nathan Green
César Asensio
Prof Antonio Torija Martinez A.J.TorijaMartinez@salford.ac.uk
Professor
Abstract
Despite the many advantages of unconventional aerial systems, mainly for logistics and transportation applications, noise has emerged as one of the main public acceptance factors that can delay the start of commercial operations of Advanced Air Mobility (AAM) platforms. As a result, many teams of researchers, policymakers, airspace regulators, and manufacturers have started with the acoustic characterisation of AAM aircraft; consequently, sound databases have been generated. In general, these databases share a set of basic indicators and metadata, including source description, averaged acoustic en ergy metrics, sensor configuration, and flight operation. This document proposes a minimum set of factors related to the acoustics of AAM platforms that should be reported alongside the measurement results. This taxonomy will enable for more harmonious communication of results between research groups. Furthermore, it is expected that this list will be periodically reviewed to adjust to the requirements identified during measurement campaigns. Under standing the acoustic characteristics of unmanned aerial systems (UAS) harmoniously and coherently among research groups aims to contribute to their incorporation into our skies.
Citation
Ramos Romero, C., Green, N., Asensio, C., & Martinez, A. (2024). Towards a Taxonomy for the Assessment of the Unmanned Aerial Systems Noise Emissions. . https://doi.org/10.17866/rd.salford.27886254.v1
Start Date | Sep 8, 2024 |
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End Date | Sep 11, 2024 |
Acceptance Date | Sep 8, 2024 |
Online Publication Date | Nov 26, 2024 |
Publication Date | Nov 26, 2024 |
Deposit Date | Nov 26, 2024 |
DOI | https://doi.org/10.17866/rd.salford.27886254.v1 |
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