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Comparison of RECAT-EU and ICAO wake turbulence category on the Point Merge System

Published online by Cambridge University Press:  10 March 2023

S. Demirel Open the ORCID record for S. Demirel [Opens in a new window]
S. Demirel*
Affiliation:
Erzincan Binali Yildirim University, Erzincan, Turkey
*
Email: sdemirel@erzincan.edu.tr
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Abstract

This study presents a mathematical model that schedules arrival aircraft regarding RECAT-EU that is new categorisation for applying separation minima and analyses its effect on the performance of the Point Merge System (PMS) at Sabiha Gökcen International Airport (LTFJ). There are two main scenarios: one of them uses RECAT-EU and the other employs the ICAO wake turbulence category. Both scenarios have ten different test problems to examine the mathematical model. The model applies RECAT-EU wake turbulence categories and compares the outcome with the ICAO wake turbulence categories. The model aims to minimise flight duration on the sequencing leg and ground delay in the departure queue using the RECAT-EU and ICAO wake turbulence categories individually. The results were analysed to reveal the PMS performance using the two different approaches to turbulence categories. Statistical analysis was also carried out to compare the means of the two groups in the model.

Keywords

RECAT-EUaircraft sequencingpoint mergedelaywake turbulence category
Type
Research Article
Information
The Aeronautical Journal , Volume 127 , Issue 1315 , September 2023 , pp. 1623 - 1637
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Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of Royal Aeronautical Society

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References

EUROCONTROL. Five-year forecast 2020-2024 European flight movements and service units: three scenarios for recovery from covid-19, 2020.Google Scholar
EUROCONTROL. European aviation in 2040-challenges of growth, 2018.Google Scholar
Adler, N., Liebert, V. and Yazhemsky, E. Benchmarking airports from a managerial perspective, Omega, 2013, 41, (2), pp 442–458, https://doi.org/10.1016/j.omega.2012.02.004 CrossRefGoogle Scholar
Bennell, J.A., Mesgarpour, M. and Potts, C.N. Airport runway scheduling, Ann. Oper. Res., 2013, 204, (1), pp 249–270, https://doi.org/10.1007/s10479-012-1268-1 CrossRefGoogle Scholar
Sama, M., D’Ariano, A., D’Ariano, P. and Pacciarelli, D. Scheduling models for optimal aircraft traffic control at busy airports: tardiness, priorities, equity and violations considerations, Omega, 2017, 67, pp 81–98.10.1016/j.omega.2016.04.003CrossRefGoogle Scholar
Beasley, J.E., Krishnamoorthy, M., Sharaiha, Y.M. and Abramson, D. Scheduling aircraft landings - the static case, Transp. Sci., 2000, 34, (2), pp 180–197, https://doi.org/10.1287/trsc.34.2.180.12302 CrossRefGoogle Scholar
Beasley, J.E., Sonander, J. and Havelock, P. Scheduling aircraft landings at London Heathrow using a population heuristic, J. Oper. Res. Soc., 2001, 52, (5), pp 483–493.10.1057/palgrave.jors.2601129CrossRefGoogle Scholar
Chen, S. and Xia, X. Researches on optimal scheduling model for aircraft landing problem, 2009 WASE International Conference on Information Engineering, ICIE 2009, vol. 1, pp 418–421, https://doi.org/10.1109/ICIE.2009.248 CrossRefGoogle Scholar
Dalmau, R., Alenka, J. and Prats, X. Combining the assignment of pre-defined routes and RTAs to sequence and merge arrival traffic, 17th AIAA Aviation Technology, Integration, and Operations Conference, 2017, pp 1–12.10.2514/6.2017-4260CrossRefGoogle Scholar
Sáez, R., Dalmau, R. and Prats, X. Optimal assignment of 4D close-loop instructions to enable CDOs in dense TMAs, AIAA/IEEE Digital Avionics Systems Conference - Proceedings, 2018, https://doi.org/10.1109/DASC.2018.8569597 CrossRefGoogle Scholar
Sáez, R., Prats, X., Polishchuk, T. and Polishchuk, V. Traffic synchronization in terminal airspace to enable continuous descent operations in trombone sequencing and merging procedures: an implementation study for Frankfurt airport, Transp. Res. Part C, 2020, 121, https://doi.org/10.1016/j.trc.2020.102875 CrossRefGoogle Scholar
Boursier, L., Favennec, B., Hoffman, E., Trzmiel, A., Vergne, F. and Zeghal, K. Merging arrival flows without heading instructions, Proceedings of the 7th USA/Europe Air Traffic Management Research and Development Seminar, ATM, 2007, pp 414–421.Google Scholar
Liang, M., Delahaye, D. and Maréchal, P. Integrated sequencing and merging aircraft to parallel runways with automated conflict resolution and advanced avionics capabilities, Transp. Res. Part C, 2017, 85, pp 268–291, https://doi.org/10.1016/j.trc.2017.09.012 CrossRefGoogle Scholar
Liang, M., Delahaye, D. and Marechal, P. Conflict-free arrival and departure trajectory planning for parallel runway with advanced point-merge system, Transp. Res. Part C, 2018, 95, pp 207–227. https://doi.org/10.1016/j.trc.2018.07.006 CrossRefGoogle Scholar
Sahin, O., Usanmaz, O. and Turgut, E.T. An assessment of flight efficiency based on the point merge system at metroplex airports, Aircraft Eng. Aerospace Technol., 2018, 90, (1), pp 1–10. https://doi.org/10.1108/AEAT-06-2016-0097 CrossRefGoogle Scholar
Cecen, R.K. Multi-objective TMA management optimization using the point merge system, Aircraft Eng. Aerospace Technol., 2021, 93, (1), pp 15–24, https://doi.org/10.1108/AEAT-09-2019-0181 CrossRefGoogle Scholar
Cecen, R.K. The fuel consumption impact of the turning point location for the point merge system, Int. J. Sustainable Aviat., 2022, 8, (1), https://doi.org/10.1504/IJSA.2022.120612 Google Scholar
Cecen, R.K., Saraç, T. and Çetek, C. Emission and flight time optimization model for aircraft landing problem, Transp. Res. Record J. Transp. Res. Board, 2022, https://doi.org/10.1177/03611981221108398 Google Scholar
Cecen, R.K. A path stretching model for effective terminal airspace management, Int. J. Aeronaut. Space Sci., 2022, pp 1–10. https://doi.org/10.1007/s42405-022-00486-z Google Scholar
ICAO. MIDANPIRG air traffic management sub-group, third meeting (ATM SG/3), 2017, Cairo, Egypt.Google Scholar
Liang, M., Delahaye, D. and Xu, X.H. A novel approach to automated merge 4D arrival trajectories for multi-parallel runways, EIWAC 2015, 4th ENRI International Workshop on ATM/CNS, 2015.Google Scholar
Lang, S., Tittsworth, J., Bryant, W.H., Wilson, P., Lepadatu, C., Delisi, D.P., Lai, D.Y. and Greene, G.C. Progress on an ICAO wake turbulence re-categorization effort, AIAA Atmospheric and Space Environments Conference, 2010, Toronto, Canada.10.2514/6.2010-7682CrossRefGoogle Scholar
EUROCONTROL. European wake turbulence categorisation and separation minima on approach and departure RECAT-EU, EUROCONTROL, 2015, Brussels.Google Scholar
Rooseleer, F., Treve, V. Visscher, I.D. and Graham, R. Wake turbulence re-categorisation on approach and departure for safe and more efficient air traffic management, 30th Congress of the International Council of the Aeronautical Sciences, 2016, Dajeon, Korea.Google Scholar
Cheng, J., Tittsworth, J., Gallo, W. and Awwad, A. The development of wake turbulence recategorization in the United States, AIAA Atmospheric and Space Environments Conference, 2016, Toronto, Canada.10.2514/6.2016-3434CrossRefGoogle Scholar
Aybek Çetek, F. and Aydoğan, E. Air traffic flow impact analysis of RECAT for Istanbul new airport using discrete-event simulation, Düzce Üniversitesi Bilim ve Teknoloji Dergisi , 2019, 7, (1), pp 434–444, https://doi.org/10.29130/dubited.457442 CrossRefGoogle Scholar
Itoh, E. and Mitici, M. Evaluating the impact of new aircraft separation minima on available airspace capacity and arrival time delay, Aeronaut. J., 2020, 124, (1274), pp 447–471, doi: 10.1017/aer.2019.160 CrossRefGoogle Scholar
Sekine, K., Kato, F., Kageyama, K. and Itoh, E. Data-driven simulation for evaluating the impact of lower arrival aircraft separation on available airspace and runway capacity at Tokyo International Airport, Aerospace, 2021, 8, (6), pp 165. https://doi.org/10.3390/aerospace8060165 CrossRefGoogle Scholar
EUROCONTROL. ATFCM Users Manual-Network Manager, 2018.Google Scholar
Büyüköztürk, S. Sosyal Bilimler için Veri Analizi El Kitab (En: Data Analysis Handbook for Social Science), Pegem Akademi Yaynclk (En: Pegem Akademi Publishing), 2007, Ankara.Google Scholar