Flight Performance, Prediction, and Optimizations

Research on aircraft performance, particularly using open models and open data, is integral to advancing the aviation sector. My research focuses on developing and improving OpenAP and associated open tools that supports the study of trajectory optimization and predictions.

Highlights

OpenAP: Open Aircraft Performance Model

This project focuses on the development of OpenAP, a comprehensive Open Aircraft Performance and Emission Model. OpenAP aims to provide a fully open-source platform for modeling critical aircraft performance metrics, including kinematic properties, thrust, drag, and fuel flow rates. Built on the principle of transparency and accessibility, OpenAP is founded on open data and designed to advance air transport research. The repository houses a rich collection of OpenAP databases, along with a Python implementation that streamlines data access and facilitates complex aircraft performance computations. Overall, OpenAP serves as a transparent and accessible tool for fostering rigorous and collaborative research in air transport.

OpenAP.top: Open Flight Trajectory Optimizer

Presenting a fully open-source trajectory optimizer, providing researchers with seamless access to the sophisticated yet efficient direct collocation optimization approach. The optimizer is capable of adjusting to meteorological conditions and can be utilized for distinct flight phases independently or in combination. It encompasses conventional fuel and cost index objectives, as well as climate metrics-based objectives utilizing global warming or temperature potential.

Related publications

OpenAP. top: Open Flight Trajectory Optimization for Air Transport and Sustainability Research

Journal 2022
DOI: 10.3390/aerospace9070383

Sun, Junzi
Aerospace

Copy Sun, J. (2022). OpenAP. top: Open Flight Trajectory Optimization for Air Transport and Sustainability Research. Aerospace, 9(7), 383. https://doi.org/10.3390/aerospace9070383

Copy

@article{sun2022top,
  title = {OpenAP. top: Open Flight Trajectory Optimization for Air Transport and Sustainability Research},
  author = {Sun, Junzi},
  journal = {Aerospace},
  volume = {9},
  number = {7},
  pages = {383},
  year = {2022},
  month = jul,
  publisher = {Multidisciplinary Digital Publishing Institute},
  link = {https://doi.org/10.3390/aerospace9070383},
  doi = {10.3390/aerospace9070383},
  tag = {perf, sus}
}

Aircraft Trajectory Prediction using ADS-B Data
Conference 2022

YANG, X ; Sun, Junzi ; and Rajan, RT
In 42nd WIC Symposium on Information Theory and Signal Processing in the Benelux (SITB 2022)
Copy YANG, X., Sun, J., & Rajan, R. T. (2022, May). Aircraft Trajectory Prediction using ADS-B Data. 42nd WIC Symposium on Information Theory and Signal Processing in the Benelux (SITB 2022).
Copy
@inproceedings{yang2022aircraft, title = {Aircraft Trajectory Prediction using ADS-B Data}, author = {YANG, X and Sun, Junzi and Rajan, RT}, booktitle = {42nd WIC Symposium on Information Theory and Signal Processing in the Benelux (SITB 2022)}, year = {2022}, month = may, link = {https://research.tudelft.nl/en/publications/aircraft-trajectory-prediction-using-ads-b-data}, tag = {perf} }
OpenAP: An open-source aircraft performance model for air transportation studies and simulations
Journal 2020
DOI: 10.3390/aerospace7080104
Sun, Junzi ; Hoekstra, Jacco ; and Ellerbroek, Joost
Aerospace
Copy Sun, J., Hoekstra, J., & Ellerbroek, J. (2020). OpenAP: An open-source aircraft performance model for air transportation studies and simulations. Aerospace, 7(8), 104. https://doi.org/10.3390/aerospace7080104
Copy
@article{sun2020openap, title = {OpenAP: An open-source aircraft performance model for air transportation studies and simulations}, author = {Sun, Junzi and Hoekstra, Jacco and Ellerbroek, Joost}, journal = {Aerospace}, volume = {7}, number = {8}, pages = {104}, year = {2020}, month = jul, publisher = {Multidisciplinary Digital Publishing Institute}, link = {https://doi.org/10.3390/aerospace7080104}, doi = {10.3390/aerospace7080104}, tag = {perf} }
Estimating aircraft drag polar using open flight surveillance data and a stochastic total energy model
Journal 2020
DOI: 10.1016/j.trc.2020.01.026
Sun, Junzi ; Hoekstra, Jacco ; and Ellerbroek, Joost
Transportation Research Part C: Emerging Technologies
Copy Sun, J., Hoekstra, J., & Ellerbroek, J. (2020). Estimating aircraft drag polar using open flight surveillance data and a stochastic total energy model. Transportation Research Part C: Emerging Technologies, 114, 391–404. https://doi.org/10.1016/j.trc.2020.01.026
Copy
@article{sun2020estimating, title = {Estimating aircraft drag polar using open flight surveillance data and a stochastic total energy model}, author = {Sun, Junzi and Hoekstra, Jacco and Ellerbroek, Joost}, journal = {Transportation Research Part C: Emerging Technologies}, volume = {114}, pages = {391--404}, year = {2020}, month = may, publisher = {Elsevier}, link = {https://research.tudelft.nl/files/71038050/published_OpenAP_drag_polar.pdf}, doi = {10.1016/j.trc.2020.01.026}, tag = {ai, perf} }
Reconstructing Aircraft Turn Manoeuvres for Trajectory Analyses Using ADS-B Data
Conference 2019

Sun, Junzi ; Ellerbroek, Joost ; and Hoekstra, Jacco
In Proceedings of the 9th SESAR Innovation Days, Athens, Greece
Copy Sun, J., Ellerbroek, J., & Hoekstra, J. (2019). Reconstructing Aircraft Turn Manoeuvres for Trajectory Analyses Using ADS-B Data. Proceedings of the 9th SESAR Innovation Days, Athens, Greece, 2–5.
Copy
@inproceedings{sun2019reconstructing, title = {Reconstructing Aircraft Turn Manoeuvres for Trajectory Analyses Using ADS-B Data}, author = {Sun, Junzi and Ellerbroek, Joost and Hoekstra, Jacco}, booktitle = {Proceedings of the 9th SESAR Innovation Days, Athens, Greece}, pages = {2--5}, year = {2019}, month = dec, link = {https://www.sesarju.eu/sites/default/files/documents/sid/2019/papers/SIDs_2019_paper_57.pdf}, tag = {perf} }
Particle filter for aircraft mass estimation and uncertainty modeling
Journal 2019
DOI: 10.1016/j.trc.2019.05.030
Sun, Junzi ; Blom, Henk AP ; Ellerbroek, Joost ; and Hoekstra, Jacco
Transportation Research Part C: Emerging Technologies
Copy Sun, J., Blom, H. A. P., Ellerbroek, J., & Hoekstra, J. (2019). Particle filter for aircraft mass estimation and uncertainty modeling. Transportation Research Part C: Emerging Technologies, 105, 145–162. https://doi.org/10.1016/j.trc.2019.05.030
Copy
@article{sun2019particle, title = {Particle filter for aircraft mass estimation and uncertainty modeling}, author = {Sun, Junzi and Blom, Henk AP and Ellerbroek, Joost and Hoekstra, Jacco}, journal = {Transportation Research Part C: Emerging Technologies}, volume = {105}, pages = {145--162}, year = {2019}, month = aug, publisher = {Elsevier}, doi = {10.1016/j.trc.2019.05.030}, link = {https://research.tudelft.nl/files/54440038/1_s2.0_S0968090X18313524_main.pdf}, tag = {perf} }
WRAP: An open-source kinematic aircraft performance model
Journal 2019
DOI: 10.1016/j.trc.2018.11.009
Sun, Junzi ; Ellerbroek, Joost ; and Hoekstra, Jacco
Transportation Research Part C: Emerging Technologies
Copy Sun, J., Ellerbroek, J., & Hoekstra, J. (2019). WRAP: An open-source kinematic aircraft performance model. Transportation Research Part C: Emerging Technologies, 98, 118–138. https://doi.org/10.1016/j.trc.2018.11.009
Copy
@article{sun2019wrap, title = {WRAP: An open-source kinematic aircraft performance model}, author = {Sun, Junzi and Ellerbroek, Joost and Hoekstra, Jacco}, journal = {Transportation Research Part C: Emerging Technologies}, volume = {98}, pages = {118--138}, year = {2019}, month = jan, publisher = {Elsevier}, doi = {10.1016/j.trc.2018.11.009}, link = {https://research.tudelft.nl/files/52638054/1_s2.0_S0968090X18306089_main.pdf}, tag = {perf} }
Aircraft Drag Polar Estimation Based on a Stochastic Hierarchical Model
Conference 2018

Sun, Junzi ; Hoekstra, Jacco ; and Ellerbroek, Joost
In 8th International Conference on Research in Air Transportation
Copy Sun, J., Hoekstra, J., & Ellerbroek, J. (2018, June). Aircraft Drag Polar Estimation Based on a Stochastic Hierarchical Model. 8th International Conference on Research in Air Transportation.
Copy
@inproceedings{sun2018drag, title = {Aircraft Drag Polar Estimation Based on a Stochastic Hierarchical Model}, author = {Sun, Junzi and Hoekstra, Jacco and Ellerbroek, Joost}, booktitle = {8th International Conference on Research in Air Transportation}, year = {2018}, month = jun, link = {https://www.sesarju.eu/sites/default/files/documents/sid/2018/papers/SIDs_2018_paper_75.pdf}, tag = {perf} }
Aircraft Mass and Thrust Estimation Using Recursive Bayesian Method
Conference 2018

Sun, Junzi ; Blom, Henk A P ; Ellerbroek, Joost ; and Hoekstra, Jacco
In 8th International Conference on Research in Air Transportation
Copy Sun, J., Blom, H. A. P., Ellerbroek, J., & Hoekstra, J. (2018, June). Aircraft Mass and Thrust Estimation Using Recursive Bayesian Method. 8th International Conference on Research in Air Transportation.
Copy
@inproceedings{sun2018smc, title = {Aircraft Mass and Thrust Estimation Using Recursive Bayesian Method}, author = {Sun, Junzi and Blom, Henk A P and Ellerbroek, Joost and Hoekstra, Jacco}, booktitle = {8th International Conference on Research in Air Transportation}, year = {2018}, month = jun, link = {https://research.tudelft.nl/files/103003225/ICRAT_2018_paper_19_1_.pdf}, tag = {perf} }
Modeling Aircraft Performance Parameters with Open ADS-B Data
Conference 2017

Sun, Junzi ; Ellerbroek, Joost ; and Hoekstra, Jacco
In 12th USA/Europe Air Traffic Management Research and Development Seminar
Copy Sun, J., Ellerbroek, J., & Hoekstra, J. (2017, June). Modeling Aircraft Performance Parameters with Open ADS-B Data. 12th USA/Europe Air Traffic Management Research and Development Seminar.
Copy
@inproceedings{sun2017modeling, title = {Modeling Aircraft Performance Parameters with Open ADS-B Data}, author = {Sun, Junzi and Ellerbroek, Joost and Hoekstra, Jacco}, booktitle = {12th USA/Europe Air Traffic Management Research and Development Seminar}, year = {2017}, month = jun, link = {https://research.tudelft.nl/files/31444997/12th_ATM_RD_Seminar_paper_66.pdf}, tag = {perf} }