Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011. / Cataloged from PDF version of thesis. / Includes bibliographical references (p. 178-183). / Ship design is a large-scale, multi-level, complex problem that requires decision-making at every stage of the design process. As such, it requires a great deal of time and resources. The evolution of the process of ship design has been relatively slow and is still based to a large extent on traditional methods that have been used for many decades. Evans' design spiral, which dates back to 1959, is the most characteristic example. These methods are reflected on the structure of various modem ship design software. However, these methods include inherent inefficiencies that need to be addressed. Some of them are the increased number of iterations, as well as the speed of execution of every iteration. The methods proposed in this dissertation try to alleviate such inefficiencies by introducing novel and easy-to-use approaches, including the formulation of new algorithms. Furthermore, concrete models are introduced in cases where there is no systematic approach to a problem. These approaches include both optimization and heuristic techniques. Neural networks belong to the first category, and although they have been used for small-scale marine problems, they haven't been extensively tested in a more general framework. Heuristics include methods such as the Mapping Model and the QuickEst algorithm, which are not found in marine applications. Heuristic methods are divided into quantitative and qualitative techniques. This research focuses on Air Cushion Vehicles since they are the newest type of advanced marine vehicles and their study is considered both tedious and challenging. However, the research also expands to other types of marine vehicles. Both design and operational aspects are examined as case studies. The results from these methods are cross-validated with other well-established and widely-used methods such as Multiple Linear Regression, proving the usefulness and validity of the considered methods. / by Georgios Gougoulidis. / Ph.D.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/67582 |
| Date | January 2011 |
| Creators | Gougoulidis, Georgios |
| Contributors | Henry S. Marcus., Massachusetts Institute of Technology. Dept. of Mechanical Engineering., Massachusetts Institute of Technology. Dept. of Mechanical Engineering. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 239 p., application/pdf |
| Rights | 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., http://dspace.mit.edu/handle/1721.1/7582 |
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