Massachusetts Institute of Technology
Conceptual engineering design and optimization methodologies using geometric programming
Abstract
dc:description.abstractGeometric programs (GPs) and other forms of convex optimization have recently experienced a resurgence due to the advent of polynomial-time solution algorithms and improvements in computing. Observing the need for fast and stable methods for multidisciplinary design optimization (MDO), previous work has shown that geometric programming can be a powerful framework for MDO by leveraging the mathematical guarantees and speed of convex optimization. However, there are barriers to the implementation of optimization in design. In this work, we formalize how the formulation of non-linear design problems as GPs facilitates design process. Using the principles of pressure and boundedness, we demonstrate the intuitive transformation of physics- and data-based engineering relations into GP-compatible constraints by systematically formulating an aircraft design model. We motivate the difference-of-convex GP extension called signomial programs (SPs) in order to extend the scope and fidelity of the model. We detail the features specific to GPkit, an object-oriented GP formulation framework, which facilitate the modern engineering design process. Using both performance and mission modeling paradigms, we demonstrate the ability to model and design increasingly complex systems in GP, and extract maximal engineering intuition using sensitivities and tradespace exploration methods. Though the methods are applied to an aircraft design problem, they are general to models with continuous, explicit constraints, and lower the barriers to implementing optimization in design.
Degree
thesis:*- Department dc:contributor.department
- Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
- Grantor dc:publisher
- Massachusetts Institute of Technology
- Year dc:date.issued
- 2018
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Öztürk, Berk
- Advisor dc:contributor.advisor
-
- Mark Drela.
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- 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.
- Licence dc:rights.uri
- Language dc:language.iso
- eng
Identifiers
dc:identifier.*- Handle dc:identifier.uri
- http://hdl.handle.net/1721.1/115595
- OAI identifier oai:identifier
- oai:dspace.mit.edu:1721.1/115595