| Type of Document |
Master's Thesis |
| Author |
Martz, Matthew
|
| Author's Email Address |
mmartz@vt.edu |
| URN |
etd-05272008-153619 |
| Title |
Preliminary Design of an Autonomous Underwater Vehicle Using a Multiple-Objective Genetic Optimizer |
| Degree |
Master of Science |
| Department |
Aerospace and Ocean Engineering |
| Advisory Committee |
| Advisor Name |
Title |
| Neu, Wayne L. |
Committee Chair |
| Brown, Alan J. |
Committee Member |
| Stilwell, Daniel J. |
Committee Member |
|
| Keywords |
- MDO
- Optimization
- Genetic
- Genetic Algorithm
- AUV
- Autonomous Underwater Vehicle
|
| Date of Defense |
2008-05-27 |
| Availability |
unrestricted |
Abstract
The process developed herein uses a Multiple Objective Genetic Optimization (MOGO) algorithm. The optimization is implemented in ModelCenter (MC) from Phoenix Integration. It uses a genetic algorithm that searches the design space for optimal, feasible designs by considering three Measures of Performance (MOPs): Cost, Effectiveness, and Risk. The complete synthesis model is comprised of an input module, the three primary AUV synthesis modules, a constraint module, three objective modules, and a genetic algorithm. The effectiveness rating determined by the synthesis model is based on nine attributes identified in the US Navy’s UUV Master Plan and four performance-based attributes calculated by the synthesis model. To solve multi-attribute decision problems the Analytical Hierarchy Process (AHP) is used. Once the MOGO has generated a final generation of optimal, feasible designs the decision-maker(s) can choose candidate designs for further analysis. A sample AUV Synthesis was performed and five candidate AUVs were analyzed.
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| Files |
| Filename |
Size |
Approximate Download Time
(Hours:Minutes:Seconds)
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56K Modem |
ISDN (64 Kb) |
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MartzThesisRev1.pdf |
8.46 Mb |
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