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A new framework for estimating noise impact of novel aircraft

A new framework for estimating noise impact of novel aircraft
A new framework for estimating noise impact of novel aircraft
Air traffic demand is forecast to significantly grow during the next few years. To compensate for the associated potential increase of aviation environmental impact, ambitious aircraft noise and emissions reduction goals have been set by several organisations worldwide. Accommodating these goals requires planning new mitigation strategies involving technological advances, optimised flight operations, and novel aircraft concepts. Methods for predicting the impact of potential mitigation strategies is vital to support effective planning.

This thesis presents a new framework for estimating the noise impact of mitigation strategies (i.e. involving each or both of technological and operational changes) aspiring to: a) bypass the dependance on empirical flyover data and hence enable impact assessment of novel aircraft and operations, b) be independent of specific noise prediction methods and confidential inputs that are normally required by many noise prediction tools, c) have low computational requirements and thus be efficient in parametric studies, and d) provide inputs to emissions prediction tools, facilitating a more holistic strategic mitigation that considers various environmental concerns.

The crux of the framework developed is that rather than seeking absolute noise values, it computationally estimates the noise impact of mitigation strategies, starting from a baseline scenario for which noise levels are known. This eliminates the need for measurements whilst minimising complexity and dependance on confidential inputs. Noise and emissions interdependencies are incorporated by expressing noise changes as a function of thrust, which is a common influencing parameter. In addition, the framework provides means for deriving purely computational NPD curves, enabling the construction of noise exposure contour maps for future aircraft and contemporary operations.

The framework’s applicability on innovative flight operations and its capability of including the interdependencies between noise and emissions is demonstrated by estimating the environmentally-optimum approach and takeoff angles for civil aircraft of different sizes. The applicability to novel aircraft is displayed through noise estimations (including noise exposure contours) for various electric aircraft featuring Distributed Electric Propulsion (DEP), as well as for a Blended-Wing-Body (BWB) aircraft.

The results obtained for future scenarios generally conform with the expected trends (deriving from e.g. higher-fidelity tools or historical trends) highlighting the framework’s great potential and usefulness in contributing in effective planning and decision-making.
University of Southampton
Synodinos, Athanasios
fc4f6dd2-7200-48b4-b0bf-67a2f62dda3b
Synodinos, Athanasios
fc4f6dd2-7200-48b4-b0bf-67a2f62dda3b
Self, Rodney
8b96166d-fc06-48e7-8c76-ebb3874b0ef7

Synodinos, Athanasios (2017) A new framework for estimating noise impact of novel aircraft. University of Southampton, Doctoral Thesis, 245pp.

Record type: Thesis (Doctoral)

Abstract

Air traffic demand is forecast to significantly grow during the next few years. To compensate for the associated potential increase of aviation environmental impact, ambitious aircraft noise and emissions reduction goals have been set by several organisations worldwide. Accommodating these goals requires planning new mitigation strategies involving technological advances, optimised flight operations, and novel aircraft concepts. Methods for predicting the impact of potential mitigation strategies is vital to support effective planning.

This thesis presents a new framework for estimating the noise impact of mitigation strategies (i.e. involving each or both of technological and operational changes) aspiring to: a) bypass the dependance on empirical flyover data and hence enable impact assessment of novel aircraft and operations, b) be independent of specific noise prediction methods and confidential inputs that are normally required by many noise prediction tools, c) have low computational requirements and thus be efficient in parametric studies, and d) provide inputs to emissions prediction tools, facilitating a more holistic strategic mitigation that considers various environmental concerns.

The crux of the framework developed is that rather than seeking absolute noise values, it computationally estimates the noise impact of mitigation strategies, starting from a baseline scenario for which noise levels are known. This eliminates the need for measurements whilst minimising complexity and dependance on confidential inputs. Noise and emissions interdependencies are incorporated by expressing noise changes as a function of thrust, which is a common influencing parameter. In addition, the framework provides means for deriving purely computational NPD curves, enabling the construction of noise exposure contour maps for future aircraft and contemporary operations.

The framework’s applicability on innovative flight operations and its capability of including the interdependencies between noise and emissions is demonstrated by estimating the environmentally-optimum approach and takeoff angles for civil aircraft of different sizes. The applicability to novel aircraft is displayed through noise estimations (including noise exposure contours) for various electric aircraft featuring Distributed Electric Propulsion (DEP), as well as for a Blended-Wing-Body (BWB) aircraft.

The results obtained for future scenarios generally conform with the expected trends (deriving from e.g. higher-fidelity tools or historical trends) highlighting the framework’s great potential and usefulness in contributing in effective planning and decision-making.

Text
Synodinos_Final Thesis - Accepted Manuscript
Available under License University of Southampton Thesis Licence.
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Published date: July 2017

Identifiers

Local EPrints ID: 416509
URI: http://eprints.soton.ac.uk/id/eprint/416509
PURE UUID: 53efd6d7-6835-40e5-a41f-49e817a828c7

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Date deposited: 20 Dec 2017 17:30
Last modified: 15 Mar 2024 17:18

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Contributors

Author: Athanasios Synodinos
Thesis advisor: Rodney Self

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