Aircraft classification for efficient modelling of environmental noise impact of aviation

Torija Martinez, AJ; Self, RH

Abstract

With the environmental externalities of civil aviation under unprecedented scrutiny, and with the projected
significant increase in air traffic demand over the next few decades, fleet-level studies are required to assess the
potential benefit of novel aircraft technologies and operational procedures for minimizing environmental impact
of aviation. Using a statistical classification process, the UK commercial aircraft fleet is reduced to four representative-
in-class aircraft on the basis of aircraft physical characteristics, and aircraft noise and engine exhaust
emissions. These four representative aircraft, that appropriately capture the noise and emissions characteristics
for each category within the UK commercial fleet, are also selected to be used as baseline cases for the
high-level assessment of the environmental benefit of novel aircraft technologies. For the particular case of
aviation noise, the modelling tools are highly sensitive to the number of aircraft types in the flight schedule. A
reduction of about 80% in computational time with relatively minor decrease in accuracy (between −4% and
+5%) is observed when the whole aircraft fleet is replaced with the four representative-in-class aircraft for
computing noise contours. Therefore, the statistical classification and selection of representative-in-class aircraft
presented in this paper is a valid approach for the rapid and accurate computation of a large number of exploratory
cases to assess aviation noise reduction strategies.

• Journal Article Type: Article
• Acceptance Date: Dec 22, 2017
• Online Publication Date: Jan 3, 2018
• Publication Date: Mar 1, 2018
• Deposit Date: Dec 2, 2019
• Publicly Available Date: Dec 2, 2019
• Journal: Journal of Air Transport Management
• Print ISSN: 0969-6997
• Publisher: Elsevier
• Volume: 67
• Pages: 157-168
• DOI: https://doi.org/10.1016/j.jairtraman.2017.12.007
• Publisher URL: https://doi.org/10.1016/j.jairtraman.2017.12.007
• Related Public URLs: https://www.sciencedirect.com/journal/journal-of-air-transport-management
• Additional Information: Funders : Engineering and Physical Sciences Research Council (EPSRC);Innovate UK; Projects : AIRPORT CAPACITY CONSEQUENCES LEVERAGING AVIATION INTEGRATED MODELLING (ACCLAIM);SYSTEMS ASPECTS OF ELECTRIC COMMERCIAL AIRCRAFT (SAECA); Grant Number: EP/M026868/1; Grant Number: TSB/113086