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Noise assessment of aircraft with distributed electric propulsion using a new noise estimation framework

Noise assessment of aircraft with distributed electric propulsion using a new noise estimation framework
Noise assessment of aircraft with distributed electric propulsion using a new noise estimation framework
Future aircraft are envisioned to have significantly smaller noise footprint and emissions impact in order to satisfy the ambitious long-term aircraft noise and emissions goals set by several organisations worldwide, for example ACARE and NASA. Distributed electric propulsion (DEP) is anticipated as one of the most suitable and efficient options for powering these aircraft. DEP is the dispersion of thrust among multiple propulsors that are driven electrically rather than mechanically. This paper presents preliminary noise estimations for a civil aircraft that uses various DEP architectures (e.g. different number of electric propulsors, powered by either batteries or gas turbine engines), obtained through a new noise estimation framework that estimates noise variations arising from technological and/or operational changes with respect to a baseline scenario, where the noise levels are known. The aim of the paper is therefore twofold; investigate the possible noise benefits of DEP aircraft, whilst on the other hand demonstrate the core methodology and capabilities of our framework for estimating the noise impact of future aircraft concepts. This preliminary study indicates the framework’s potential in correctly capturing trends.
Synodinos, Athanasios
fc4f6dd2-7200-48b4-b0bf-67a2f62dda3b
Self, Rodney
8b96166d-fc06-48e7-8c76-ebb3874b0ef7
Torija Martinez, Antonio
6dd0d982-fcd6-42b6-9148-211175fd3287
Synodinos, Athanasios
fc4f6dd2-7200-48b4-b0bf-67a2f62dda3b
Self, Rodney
8b96166d-fc06-48e7-8c76-ebb3874b0ef7
Torija Martinez, Antonio
6dd0d982-fcd6-42b6-9148-211175fd3287

Synodinos, Athanasios, Self, Rodney and Torija Martinez, Antonio (2017) Noise assessment of aircraft with distributed electric propulsion using a new noise estimation framework. 24th International Congress on Sound and Vibration, Park Plaza Westminster Bridge Hotel, London, United Kingdom. 23 - 27 Jul 2017.

Record type: Conference or Workshop Item (Paper)

Abstract

Future aircraft are envisioned to have significantly smaller noise footprint and emissions impact in order to satisfy the ambitious long-term aircraft noise and emissions goals set by several organisations worldwide, for example ACARE and NASA. Distributed electric propulsion (DEP) is anticipated as one of the most suitable and efficient options for powering these aircraft. DEP is the dispersion of thrust among multiple propulsors that are driven electrically rather than mechanically. This paper presents preliminary noise estimations for a civil aircraft that uses various DEP architectures (e.g. different number of electric propulsors, powered by either batteries or gas turbine engines), obtained through a new noise estimation framework that estimates noise variations arising from technological and/or operational changes with respect to a baseline scenario, where the noise levels are known. The aim of the paper is therefore twofold; investigate the possible noise benefits of DEP aircraft, whilst on the other hand demonstrate the core methodology and capabilities of our framework for estimating the noise impact of future aircraft concepts. This preliminary study indicates the framework’s potential in correctly capturing trends.

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More information

Published date: 25 July 2017
Venue - Dates: 24th International Congress on Sound and Vibration, Park Plaza Westminster Bridge Hotel, London, United Kingdom, 2017-07-23 - 2017-07-27

Identifiers

Local EPrints ID: 416340
URI: http://eprints.soton.ac.uk/id/eprint/416340
PURE UUID: 1dc6c6c4-15dc-47fc-a31a-1f98f5ad5c05
ORCID for Antonio Torija Martinez: ORCID iD orcid.org/0000-0002-5915-3736

Catalogue record

Date deposited: 13 Dec 2017 17:30
Last modified: 15 Mar 2024 17:19

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Contributors

Author: Athanasios Synodinos
Author: Rodney Self
Author: Antonio Torija Martinez ORCID iD

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