journal article·2025-10-21Open access

Theoretical Assessment of Runway Capacity for Training and Transport Airport Considering Wake Vortex Encounter Safety: A Case Study of Luoyang Beijiao Airport

Chen Zhang, Weijun Pan, Yingwei Zhu, Yanqiang Jiang, Xuan Wang

Applied Sciences· Volume 15· Issue 20

Abstract

Wake vortex is a critical factor affecting aircraft safety and airport runway capacity. To assess the runway capacity of mixed operations for training and transport airports, this study first simulated the wake vortex dissipation process of the commonly used A321 aircraft at Luoyang Beijiao Airport using a wake vortex prediction model. The SR20 training aircraft was selected as the subject for wake vortex encounters, with the rolling moment coefficient used as an indicator to assess the risk of wake encounters, and the wake vortex safety separation was calculated. Finally, a runway capacity model based on runway average service time for mixed training and transport operations was developed, calculating both runway landing capacity and the total runway capacity in the continuous landing and interleaved takeoff mode. The simulation results indicate that under different atmospheric BV frequencies, the safe wake vortex separations for the A321–SR20 combination are 6375 m, 6188 m, and 5700 m, respectively, representing reductions of 31.5%, 33.2%, and 38.4% shorter than the current CCAR-93TM-R6 regulatory separations, and compared to the RECAT 1.5 and RECAT-EU standards. Under reduced separation conditions, runway capacity demonstrated improvement across various atmospheric conditions and operational modes.
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Research context

OpenAlex topics: Air Traffic Management and Optimization · Aerodynamics and Fluid Dynamics Research · Aerospace and Aviation Technology

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, China

Flight Technology and Flight Safety Research Base of the Civil Aviation Administration of China, Civil Aviation Flight University of China, Guanghan 618307, China

Mianyang Flight College, Civil Aviation Flight University of China, Guanghan 618307, China

School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 611756, China

Funding

National Natural Science Foundation of China · Fundamental Research Funds for the Central Universities · Civil Aviation Flight University of China Science Innovation Fund for Graduate Students · Sichuan Provincial Civil Aviation Flight Technology and Flight Safety Engineering Technology Research Center · Funds for CAAC the Key Laboratory of Flight Techniques and Flight Safety

References (33)

Show source-provided references
1. A Review of Recent Wake Vortex Research for Increasing Airport Capacity10.1016/j.paerosci.2018.03.003 ↗
2. Pan, W., Wang, Y., Deng, L., Jiang, Y., and Leng, Y. (2025). Aircraft Wake Vortex Recognition Method Based on Improved Inception-VGG16 Hybrid Network. Sensors, 25.10.3390/s25092909 ↗
3. Deep Learning for Aircraft Wake Vortex Identification10.1088/1757-899X/685/1/012015 ↗
4. Simulation of Runway Operations with Application of Dynamic Wake Separations to Study Runway Limitations10.1177/0361198120953152 ↗
5. Stability Theory for a Pair of Trailing Vortices10.2514/3.6083 ↗
6. An Approximate Model of Vortex Decay in the Atmosphere10.2514/3.45345 ↗
7. Wake-Vortex Eddy-Dissipation Model Predictions Compared with Observations10.2514/2.2820 ↗
8. Probabilistic Two-Phase Wake Vortex Decay and Transport Model10.2514/2.3096 ↗
9. On an Analytical Model of Wake Vortex Separation of Aircraft10.1017/aer.2016.89 ↗
10. Luo, H., Pan, W., Wang, Y., and Luo, Y. (2024). A330-300 Wake Encounter by ARJ21 Aircraft. Aerospace, 11.10.3390/aerospace11020144 ↗
11. Pan, W., Jiang, Y., and Zhang, Y. (2023). Simulation Study of the Effect of Atmospheric Stratification on Aircraft Wake Vortex Encounter. Sustainability, 15.10.3390/su15086391 ↗
12. Deng, L., Pan, W., Zhao, P., Chen, K., and Wang, X. (2025). TransCNN: A Hybrid Framework for Aircraft Wake Vortex Detection and Safety Interval Assessment. IEEE Trans. Aerosp. Electron. Syst., 1–15.10.1109/TAES.2025.3578555 ↗
13. Deng, L., Pan, W., Wang, Y., Luan, T., and Leng, Y. (2024). Aircraft Wake Evolution Prediction Based on Parallel Hybrid Neural Network Model. Aerospace, 11.10.20944/preprints202405.0814.v1 ↗
14. De Visscher, I., Stempfel, G., Rooseleer, F., and Treve, V. (2018, January 23–27). Data Mining and Machine Learning Techniques Supporting Time-Based Separation Concept Deployment. Proceedings of the 2018 IEEE/AIAA 37th Digital Avionics Systems Conference (DASC), London, UK.10.1109/DASC.2018.8569325 ↗
15. Modelling and Simulation Studies of the Runway Capacity of Changi Airport10.1017/aer.2018.48 ↗
16. Hu, J., Mirmohammadsadeghi, N., and Trani, A. (2019, January 17–21). Runway Occupancy Time Constraint and Runway Throughput Estimation under Reduced Arrival Wake Separation Rules. Proceedings of the AIAA Aviation 2019 Forum, Dallas, TX, USA.10.2514/6.2019-3046 ↗
17. Chen, Z., Xiang, H., Han, B., Shen, Y., Zhou, T., and Zhang, F. (2024). Research on Runway Capacity Evaluation of General Aviation Airport Based on Runway Expansion System. Symmetry, 16.10.3390/sym16111555 ↗
18. Maltinti, F., Flore, M., Pigozzi, F., and Coni, M. (2024). Optimizing Airport Runway Capacity and Sustainability through the Introduction of Rapid Exit Taxiways: A Case Study. Sustainability, 16.10.3390/su16135359 ↗
19. Air Traffic Forecast and Its Impact on Runway Capacity. A System Dynamics Approach10.1016/j.jairtraman.2020.101946 ↗
20. Sekine, K., Kato, F., Kageyama, K., and Itoh, E. (2021). Data-Driven Simulation for Evaluating the Impact of Lower Arrival Aircraft Separation on Available Airspace and Runway Capacity at Tokyo International Airport. Aerospace, 8.10.3390/aerospace8060165 ↗
21. Simulation Modelling of Runway Capacity for Flight Training Airports10.1017/S0001924000009039 ↗
22. Evaluating the Impact of New Aircraft Separation Minima on Available Airspace Capacity and Arrival Time Delay10.1017/aer.2019.160 ↗
23. Understanding the Capacity of Airport Runway Systems10.1016/j.trc.2025.104998 ↗
24. Mascio, P.D., Rappoli, G., and Moretti, L. (2020). Analytical Method for Calculating Sustainable Airport Capacity. Sustainability, 12.10.3390/su12219239 ↗
25. Ahmad, N.N., and Proctor, F. (2014, January 13–17). Review of Idealized Aircraft Wake Vortex Models. Proceedings of the 52nd Aerospace Sciences Meeting, National Harbor, MD, USA.10.2514/6.2014-0927 ↗
26. Decay of Wake Vortices of Large Aircraft10.2514/2.570 ↗
27. Analytical Solutions of the Internal Gravity Wave Equation for a Semi-Infinite Stratified Layer of Variable Buoyancy10.1134/S0965542519050051 ↗
28. Aircraft Vortices in Stably Stratified and Weakly Turbulent Atmospheres: Simulation and Modeling10.2514/1.J051742 ↗
29. Van Baren, G., Treve, V., Rooseleer, F., Van Der Geest, P., and Heesbeen, B. (2017, January 9–13). Assessing the Severity of Wake Encounters in Various Aircraft Types in Piloted Flight Simulations. Proceedings of the AIAA Modeling and Simulation Technologies Conference, Grapevine, TX, USA.10.2514/6.2017-1084 ↗
30. Lang, S., Tittsworth, J., Bryant, W., Wilson, P., Lepadatu, C., Delisi, D., Lai, D., and Greene, G. (2010, January 2–5). Progress on an ICAO Wake Turbulence Re-Categorization Effort. Proceedings of the AIAA Atmospheric and Space Environments Conference, Toronto, ON, Canada.10.2514/6.2010-7682 ↗
31. (2016). Wake Turbulence Recategorization (Standard No. JO7110.659C).
32. (2024). RECAT-EU: European Wake Turbulence Categorisation and Separation Minima on Approach and DepartureAvailable online: https://www.eurocontrol.int/publication/european-wake-turbulence-categorisation-and-separation-minima-approach-and-departure.
33. (2023). Civil Aviation Air Traffic Management Rules (Standard No. CCAR-93TM-R6).