A heuristic for including black box analysis tools into a geometric programming formulation
Author(s)
Karcher, Cody Jacob
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Other Contributors
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
Advisor
Warren W. Hoburg.
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Recently, geometric programming has been proposed as a powerful tool for enhancing aircraft conceptual design. While geometric programming has shown promise in early studies, current formulations preclude the designer from using black box analysis codes which are prolific in the aircraft design community. Previous work has shown the ability to fit data from these black box codes prior to the optimization run, however, this is often a time consuming and computationally expensive process that does not scale well to higher dimensional black boxes. Based upon existing iterative optimization methods, we propose a heuristic for including black box analysis codes in a geometric programming framework by utilizing sequential geometric programming (SGP). We demonstrate a heuristic SGP method and apply it to a solar powered aircraft using a black boxed GP compatible profile drag function. Using this heuristic algorithm, we achieve less than a 1% difference in the objective function between a direct implementation of the constraint and a black box implementation of the constraint.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2017. Cataloged from PDF version of thesis. Includes bibliographical references (pages 79-82).
Date issued
2017Department
Massachusetts Institute of Technology. Department of Aeronautics and AstronauticsPublisher
Massachusetts Institute of Technology
Keywords
Aeronautics and Astronautics.