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
- Racheal Erhard
- 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, plotly
See develop.
This respository may be cited via BibTex as:
@software{SUAVEGit,
author = {
Wendorff, A. and
Variyar, A. and
Ilario, C. and
Botero, E. and
Capristan, F. and
Smart, J. and
Alonso, J. and
Kulik, L. and
Clarke, M. and
Colonno, M. and
Kruger, M. and
Vegh, J. M. and
Goncalves, P. and
Erhard, R. and
Fenrich, R. and
Orra, T. and
St. Francis, T. and
MacDonald, T. and
Momose, T. and
Economon, T. and
Lukaczyk, T. and
Maier, W.
},
title = {SUAVE: An Aerospace Vehicle Environment for Designing Future Aircraft},
url = {https://github.com/suavecode/SUAVE},
version = {2.1},
year = {2020},
}
The most recent publication covering the general capabilities of SUAVE was presented at the 18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference and may be cited via BibTex as:
@inbook{SUAVE2017,
author = {Timothy MacDonald and Matthew Clarke and Emilio M. Botero and Julius M. Vegh and Juan J. Alonso},
title = {SUAVE: An Open-Source Environment Enabling Multi-Fidelity Vehicle Optimization},
booktitle = {18th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference},
chapter = {},
pages = {},
doi = {10.2514/6.2017-4437},
URL = {https://arc.aiaa.org/doi/abs/10.2514/6.2017-4437},
eprint = {https://arc.aiaa.org/doi/pdf/10.2514/6.2017-4437}
}
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