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WRAP : An open-source kinematic aircraft performance model. / Sun, Junzi; Ellerbroek, Joost; Hoekstra, Jacco M.

In: Transportation Research Part C: Emerging Technologies, Vol. 98, 01.01.2019, p. 118-138.

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Sun, Junzi ; Ellerbroek, Joost ; Hoekstra, Jacco M. / WRAP : An open-source kinematic aircraft performance model. In: Transportation Research Part C: Emerging Technologies. 2019 ; Vol. 98. pp. 118-138.

BibTeX

@article{84afd7743c4f49a5a52e6eb0532f322e,
title = "WRAP: An open-source kinematic aircraft performance model",
abstract = "Open access to flight data from Automatic Dependent Surveillance-Broadcast (ADS-B) has provided researchers with more insights for air traffic management than aircraft tracking alone. With large quantities of trajectory data collected from a wide range of different aircraft types, it is possible to extract accurate aircraft performance parameters. In this paper, a set of more than thirty parameters from seven distinct flight phases are extracted for common commercial aircraft types. It uses various data mining methods, as well as a maximum likelihood estimation approach to generate parametric models for these performance parameters. All parametric models combined can be used to describe a complete flight that includes takeoff, initial climb, climb, cruise, descent, final approach, and landing. Both analytical results and summaries are shown. When available, optimal parameters from these models are also compared with the Base of Aircraft Data and the Eurocontrol aircraft performance database. This research presents a comprehensive set of methods for extracting different aircraft performance parameters. It also provides the first set of open parametric performance data for common aircraft types. All model data are published as open data under a flexible open-source license.",
keywords = "ADS-B, Aircraft performance, Data analytics, Data mining, Kinematic model",
author = "Junzi Sun and Joost Ellerbroek and Hoekstra, {Jacco M.}",
note = "Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.",
year = "2019",
month = "1",
day = "1",
doi = "10.1016/j.trc.2018.11.009",
language = "English",
volume = "98",
pages = "118--138",
journal = "Transportation Research. Part C: Emerging Technologies",
issn = "0968-090X",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - WRAP

T2 - Transportation Research. Part C: Emerging Technologies

AU - Sun, Junzi

AU - Ellerbroek, Joost

AU - Hoekstra, Jacco M.

N1 - Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Open access to flight data from Automatic Dependent Surveillance-Broadcast (ADS-B) has provided researchers with more insights for air traffic management than aircraft tracking alone. With large quantities of trajectory data collected from a wide range of different aircraft types, it is possible to extract accurate aircraft performance parameters. In this paper, a set of more than thirty parameters from seven distinct flight phases are extracted for common commercial aircraft types. It uses various data mining methods, as well as a maximum likelihood estimation approach to generate parametric models for these performance parameters. All parametric models combined can be used to describe a complete flight that includes takeoff, initial climb, climb, cruise, descent, final approach, and landing. Both analytical results and summaries are shown. When available, optimal parameters from these models are also compared with the Base of Aircraft Data and the Eurocontrol aircraft performance database. This research presents a comprehensive set of methods for extracting different aircraft performance parameters. It also provides the first set of open parametric performance data for common aircraft types. All model data are published as open data under a flexible open-source license.

AB - Open access to flight data from Automatic Dependent Surveillance-Broadcast (ADS-B) has provided researchers with more insights for air traffic management than aircraft tracking alone. With large quantities of trajectory data collected from a wide range of different aircraft types, it is possible to extract accurate aircraft performance parameters. In this paper, a set of more than thirty parameters from seven distinct flight phases are extracted for common commercial aircraft types. It uses various data mining methods, as well as a maximum likelihood estimation approach to generate parametric models for these performance parameters. All parametric models combined can be used to describe a complete flight that includes takeoff, initial climb, climb, cruise, descent, final approach, and landing. Both analytical results and summaries are shown. When available, optimal parameters from these models are also compared with the Base of Aircraft Data and the Eurocontrol aircraft performance database. This research presents a comprehensive set of methods for extracting different aircraft performance parameters. It also provides the first set of open parametric performance data for common aircraft types. All model data are published as open data under a flexible open-source license.

KW - ADS-B

KW - Aircraft performance

KW - Data analytics

KW - Data mining

KW - Kinematic model

UR - http://www.scopus.com/inward/record.url?scp=85057500698&partnerID=8YFLogxK

U2 - 10.1016/j.trc.2018.11.009

DO - 10.1016/j.trc.2018.11.009

M3 - Article

VL - 98

SP - 118

EP - 138

JO - Transportation Research. Part C: Emerging Technologies

JF - Transportation Research. Part C: Emerging Technologies

SN - 0968-090X

ER -

ID: 47735207