🦸 Trajectory Optimizer

Previously, the majority of flight optimizers mentioned in the literature remained closed-source, which posed a significant drawback in terms of reproducible research.

The trajectory optimizer (TOP) addresses this lack of open-source flight trajectory optimizer by providing everyone with open access to trajectory optimization based on a non-linear optimal control direct collocation approach.

The TOP library can consider 3D or 4D wind fields. It can be utilized in various flight phases, either individually or in combination. It provides traditional fuel and cost index objectives alongside climate metrics-based objectives that incorporate global warming or temperature potential.

Furthermore, There is a mechanism to include a 3D or 4D cost grid in trajectory optimization. This implementation allows easy generation of, for example, contrail-optimal trajectories, or generate trajectoies that avoids areas with convective weathers.

Use cases

The following chapters demonstrate various optimization scenarios and practical applications:

  • Chapter 7: explains how you can easily generate fuel and other simple cost-optimal trajectories.
  • Chapter 8: provides two approaches to obtaining wind fields and using them in your optimization.
  • Chapter 9: dives deeper into optimization with more complex 3D or 4D grids.
  • Chapter 10: provides a concrete example of flight optimization considering contrails.

Install

The opeanp.top library is designed to be a module inside the openap scope. You can install the most recent release thorugh pip:

pip install --upgrade openap-top

This will install openap.top and related dependencies.

Alternatively, if you want to install the most recent development version (usually it is also recommended to update openap to the latest dev version):

pip install --upgrade git+https://github.com/junzis/openap
pip install --upgrade git+https://github.com/junzis/openap-top

Paper

The optimization framework was first published in the following paper: Sun (2022)

To cite the paper:

@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},
}
Caution

While the fundamental principle of trajectory optimization (based on non-linear optimal control) remains unchanged, the software has evolved significantly since the paper’s publication.

Key improvements include:

  • Enhanced performance models
  • More robust trajectory generation logic, and better convergence
  • Optimized computational performance, much faster πŸš€