by Peter Sharpe (<pds [at] mit [dot] edu>)

AeroSandbox is a Python package for design optimization of engineered systems such as aircraft.

At its heart, AeroSandbox is an optimization suite that combines the ease-of-use of familiar NumPy syntax with the power of modern automatic differentiation.

This automatic differentiation dramatically improves optimization performance on large problems: design problems with tens of thousands of decision variables solve in seconds on a laptop.

AeroSandbox also comes with dozens of end-to-end-differentiable aerospace physics models, allowing you to simultaneously optimize an aircraft's aerodynamics, structures, propulsion, mission trajectory, stability, and more.

VLM simulation of a glider, aileron deflections of +-30°. Runtime of 0.35 sec on a typical laptop (i7-8750H).

Panel simulation of a wing (extruded NACA2412, α=15°, AR=4). Note the strong three-dimensionality of the flow near the tip.

In short:

• pip install aerosandbox[full] for a complete install.

• pip install aerosandbox for a lightweight (headless) installation with minimal dependencies. All optimization, numerics, and physics models are included, but optional visualization dependencies are skipped.

For more installation details (e.g., if you're new to Python), see here.

To get started, check out the tutorials folder here! All tutorials are viewable in-browser, or you can open them as Jupyter notebooks by cloning this repository.

For a more detailed and theory-heavy introduction to AeroSandbox, please see this thesis.

For a yet-more-detailed developer-level description of AeroSandbox modules, please see the developer README.

You can print documentation and examples for any AeroSandbox object by using the built-in help() function (e.g., help(asb.Airplane)). AeroSandbox code is also documented extensively in the source and contains hundreds of unit test examples, so examining the source code can also be useful.

One final point to note: as we're all sensible and civilized here, all inputs and outputs to AeroSandbox are expressed in base SI units, or derived units thereof (e.g, m, N, kg, m/s, J, Pa).

The only exception to this rule is when units are explicitly noted via variable name suffix. For example:

• battery_capacity -> Joules
• battery_capacity_watt_hours -> Watt-hours.

All angles are in radians, except for α and β which are in degrees due to long-standing aerospace convention. (In any case, units are marked on all function docstrings.)

If you wish to use other units, consider using aerosandbox.tools.units to convert easily.

Please feel free to join the development of AeroSandbox - contributions are always so welcome! If you have a change you'd like to make, the easiest way to do that is by submitting a pull request.

The text file CONTRIBUTING.md has more details for developers and power users.

If you've already made several additions and would like to be involved in a more long-term capacity, please message me! Contact information can be found next to my name near the top of this README.

If you like this software, please consider donating to support development via PayPal or GitHub Sponsors! I'm a grad student, so every dollar that you donate helps wean me off my diet of instant coffee and microwaved ramen noodles.

Please, please report all bugs by creating a new issue at https://github.com/peterdsharpe/AeroSandbox/issues!

AeroSandbox loosely uses semantic versioning, which should give you an idea of whether or not you can probably expect backward-compatibility and/or new features from any given update. However, the code is a work in progress and things change rapidly - for the time being, please freeze your version of AeroSandbox for any serious deployments. Commercial users: I'm more than happy to discuss consulting work for active AeroSandbox support if this package proves helpful!

If you find AeroSandbox useful in a research publication, please cite it using the following BibTeX snippet:

@mastersthesis{aerosandbox,
    title = {AeroSandbox: A Differentiable Framework for Aircraft Design Optimization},
    author = {Sharpe, Peter D.},
    school = {Massachusetts Institute of Technology},
    year = {2021}
}

MIT License, full terms here.