Signomial programming for aircraft design
Name
962735101-MIT.pdf
Description
Full printable version
Size
1.3 MB
Format
Adobe PDF
Checksum (MD5)
cc1c626d1d468947dcf46603a8104418
Author(s)
Kirschen, Philippe G. (Philippe Gilbert)
Advisor(s)
Warren W. Hoburg.
Date Issued
2016
Publisher
Massachusetts Institute of Technology
Abstract
Due to the coupled nature of aircraft system design, it is important to consider all major subsystems when optimizing a configuration. This, however, is easier said than done, particularly because each individual subsystem model can be arbitrarily complex. By restricting an optimization problem to have a certain mathematical structure, significantly more effective and tractable solution techniques can be used. Geometric programming, an example of one such technique, guarantees finding a globally optimal solution. Although it has been shown that geometric programming can be used to solve some conceptual aircraft design problems, the required formulation can prove too restrictive for certain relationships. Signomial programming is a closely related relaxation of geometric programming that offers enhanced expressiveness, but without the guarantee of global optimality. Despite this, solution methods for signomial programs are disciplined and effective. In the present work, signomial programming models are proposed for optimal preliminary sizing of the vertical tail, horizontal tail, fuselage, landing gear, and wing of a commercial aircraft with a tube-and- wing configuration. These models are then combined together to produce a full aircraft optimization model. Signomial programming's relaxed formulation allows it to handle some of the key constraints in tail, fuselage, landing gear, and wing design, and therefore an improvement in fidelity over geometric programming models is achieved. The models are readily extensible and easily combined with other models, making them effective building blocks for future work. A primary contribution of this work is to demonstrate signomial programming as a viable tool for multidisciplinary aircraft design optimization.
Description
Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2016.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 125-127).
Subjects
Aeronautics and Astronautics.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
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