SUAVE is a conceptual level aircraft design environment built with the ability to analyze and optimize both conventional and unconventional designs. This capability is achieved in part by allowing analysis information for aircraft to be drawn from multiple sources. Many other software tools for aircraft conceptual design rely on fixed empirical correlations and other handbook approximation. SUAVE instead provides a framework that can be used to design aircraft featuring advanced technologies by augmenting relevant correlations with physics-based methods.
While SUAVE is quite capable as built today, its most important strength is in the ease of creating and adding new vehicles, mission types, analyses, and optimizers. This flexibility is aided by SUAVE's status as an open-source Python code. Development is currently led by the Aerospace Design Lab at Stanford University. If you're interested in joining us, please visit our develop page for general instructions or reach out to us though our forum or email.
We've recently presented papers on the technical background of SUAVE as applied to the analysis and optimization of aerospace vehicles. The first paper describes the initial models available and the motivations for the programming structures used in the package. The second paper details the schematics of setting up optimization problems and sample results. The third paper shows how higher fidelity models can be incorporated into the code. Finally, the fourth paper shows how optimization can be performed with multiple levels of fidelity.
T. Lukaczyk, A. Wendorff, E. Botero, T. MacDonald, T. Momose, A. Variyar, J. M. Vegh, M. Colonno, T. Economon, J. J. Alonso, T. Orra, C. Ilario, "SUAVE: An Open-Source Environment for Multi-Fidelity Conceptual Vehicle Design", 16th AIAA Multidisciplinary Analysis and Optimization Conference, Dallas, TX, June 2015.
E. Botero, A. Wendorff, T. MacDonald, A. Variyar, J. M. Vegh, T. Lukaczyk, J. J. Alonso, T. Orra, C. Ilario da Silva. "SUAVE: An Open-Source Environment for Conceptual Vehicle Design and Optimization", 54th AIAA Aerospace Sciences Meeting, San Diego, CA, January 2016.
T. MacDonald, E. Botero, J. M. Vegh, A. Variyar, J. J. Alonso, T. Orra, C. Ilario da Silva. "SUAVE: An Open-Source Environment Enabling Unconventional Designs through Higher Fidelity", 55th AIAA Aerospace Sciences Meeting, Grapevine, TX, January 2017.
T. MacDonald, M. Clarke, E. Botero, J. M. Vegh, J. J. Alonso. "SUAVE: An Open-Source Environment Enabling Multi-fidelity Vehicle Optimization", 16th AIAA Multidisciplinary Analysis and Optimization Conference, Denver, CO, June 2017.