This is Xoptfoil-JX, a fork of Xoptfoil - the amazing airfoil optimizer by Daniel Prosser

The project was started to handle some off the difficulties when it comes to optimize an airfoil having more advanced requirements on the quality of the generated airfoil.

Main changes and improvements made up to now based on the original Xoptfoil

• Aerodynamic target values for an operating point to ease the final tweaking of an optimization - or to reverse engineer an airfoil from an existing polar.
• Geometric target values to replace optimization based on geometric constraints
• Instead of Hicks Henne shape functions the geometric airfoil parameters thickness, camber and leading edge radius can be used to perform a lightweight and fast optimization
• Support for polar type 1 (fixed speed) and polar type 2 (fixed lift) optimization
• Generation of a complete polar set of the final airfoil to import into xflr5 or flow5 (part of the sub project 'The Strak Machine')
• Utility tool Xfoil_worker to perform a little jobs like airfoil normalization or smoothing of an airfoil
• Minor other modifications in Xoptfoil and visualizer

The additional options of Xoptfoil-JX compared to the original Xoptfoil are described in Xoptfoil-JX Reference

The development of a high end F3F airfoil using Xoptfoil-JX is described in the arctivle Entwicklung eines F3F-Profils - sorry, it's in German.

Various ready to run examples can be found in the ./examples folder including a brief description of the features used.

The actual compiled Windows version of Xoptfoil-JX can be found in Code-Releases tab on this side. Download the zip file and copy the files either in an existing Xoptfoil directory or into a new directory of your choice. In the latter case add the bin folder of Xoptfoil-JX to your path environment (or just copy the exe files into your project folder)

Xoptfoil newbies will have to install a python environment like Anaconda.

• The optimizer Xopfoil-JX is started from a windows command prompt (shell).
• The visualizer Xoptfoil_visualizer-JX.py is started from a 'Python/Anaconda prompt'.

Developers and linux users should download the complete repository. The build script (build_windows.bat and build_linux.sh) will start the compilation.

Windows developers will have to install the MinGW toolchain for compilation.

• Initial fork and first modifications by Jochen Guenzel
• Camber & Tickness based optimization by Matthias Boese and Jochen Guenzel

Feel free to contact us - and of course we are happy for any contributions and suggestions!

Jochen Guenzel, November 2020