MIT Libraries logoDSpace@MIT

MIT
View Item 
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
  • DSpace@MIT Home
  • MIT Libraries
  • MIT Theses
  • Graduate Theses
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

A heuristic for including black box analysis tools into a geometric programming formulation

Author(s)
Karcher, Cody Jacob
Thumbnail
DownloadFull printable version (7.579Mb)
Other Contributors
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
Advisor
Warren W. Hoburg.
Terms of use
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission. http://dspace.mit.edu/handle/1721.1/7582
Metadata
Show full item record
Abstract
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
2017
URI
http://hdl.handle.net/1721.1/112465
Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Publisher
Massachusetts Institute of Technology
Keywords
Aeronautics and Astronautics.

Collections
  • Graduate Theses

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

Login

Statistics

OA StatisticsStatistics by CountryStatistics by Department
MIT Libraries
PrivacyPermissionsAccessibilityContact us
MIT
Content created by the MIT Libraries, CC BY-NC unless otherwise noted. Notify us about copyright concerns.