SUAVE is a multi-fidelity conceptual design environment. Its purpose is to credibly produce conceptual-level design conclusions for future aircraft incorporating advanced technologies.
License: LGPL-2.1
Guides and Forum available at suave.stanford.edu.
- Andrew Wendorff
- Anil Variyar
- Carlos Ilario
- Emilio Botero
- Francisco Capristan
- Jordan Smart
- Juan Alonso
- Luke Kulik
- Matthew Clarke
- Michael Colonno
- Michael Kruger
- Michael Vegh
- Pedro Goncalves
- Rick Fenrich
- Tarik Orra
- Theo St. Francis
- Tim MacDonald
- Tim Momose
- Tom Economon
- Trent Lukaczyk
- Walter Maier
- Stanford University Aerospace Design Lab (adl.stanford.edu)
- Embraer (www.embraer.com)
- NASA (www.nasa.gov)
git clone https://github.com/suavecode/SUAVE.git
cd SUAVE/trunk
python setup.py install
More information available at download.
numpy, scipy, matplotlib, pip, scikit-learn
See develop.