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Landing gear ground manoeuvre statistics from automatic dependent surveillance-broadcast transponder data

Published online by Cambridge University Press:  03 June 2021

J. Hoole Open the ORCID record for J. Hoole [Opens in a new window] ,
P. Sartor Open the ORCID record for P. Sartor [Opens in a new window] ,
J.D. Booker Open the ORCID record for J.D. Booker [Opens in a new window] ,
J.E. Cooper Open the ORCID record for J.E. Cooper [Opens in a new window] ,
X.V. Gogouvitis  and
R.K. Schmidt
J. Hoole*
Affiliation:
Faculty of Engineering University of BristolBristolUK
P. Sartor
Affiliation:
Faculty of Engineering University of BristolBristolUK
J.D. Booker
Affiliation:
Faculty of Engineering University of BristolBristolUK
J.E. Cooper
Affiliation:
Faculty of Engineering University of BristolBristolUK
X.V. Gogouvitis
Affiliation:
Safran Landing SystemsGloucesterUK
R.K. Schmidt
Affiliation:
Safran Landing SystemsAjax, OntarioCanada
*
jh12317@bristol.ac.uk
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Abstract

Landing gear are exposed to cyclic loads from the ground manoeuvres that aircraft perform in-service. Variability is observed in the loading magnitude associated with ground manoeuvres, along with the per-flight variability in ground manoeuvre occurrence and sequencing. Whilst loading magnitude variability has been widely characterised, significant assumptions are required regarding manoeuvre occurrence and sequencing when constructing landing gear load spectra for fatigue design. These assumptions are required due to the limited availability of data concerning ground manoeuvre occurrence and sequencing relating to aircraft in-service and require validation to facilitate the design of more efficient components. ‘Big-Data’ approaches, employing Automatic Dependent Surveillance-Broadcast (ADS-B) transponder data, enable aircraft ground tracks to be identified. This paper presents a methodology to characterise the variability in ground manoeuvre occurrence and sequencing using ADS-B data sourced from Flightradar24® for a wide-body aircraft fleet. Using statistics generated for the fleet, it was identified that significant variability exists in the occurrence and sequencing of turning and braking manoeuvres. The statistics also validate existing assumptions, including that the proportional share of left and right turning manoeuvres is equal. Finally, this paper discusses the utility of ADS-B datasets for constructing landing gear load spectra and monitoring of landing gear in-service.

Keywords

ADS-BLanding GearFatigueLoading SpectraManoeuvre StatisticsBig-DataData Analytics
Type
Research Article
Information
The Aeronautical Journal , Volume 125 , Issue 1293 , November 2021 , pp. 1942 - 1976
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Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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