Multidisciplinary Optimization of Naval Ship Design and Mission Effectiveness
Abstract
The Engineous Software STTR Team, including team members from Northrop Grumman, Naval Undersea Warfare Center (NUWC), Massachusetts Institute of Technology (MIT), and Elon University; proposed at the outset of the project that it could develop an integrated Multi-disciplinary Optimization (MDO) system of naval ship design and mission effectiveness. Specifically, the team intended to use a ship model of interest to the Navy in an effort to demonstrate that disparate ship analysis tools could be integrated under a single framework and automated. This integrated, automated system would allow its users to measure ship performance and effectiveness, as well as accounting for uncertainty in those measurements, through design exploration techniques, such as optimization, design of experiments (DOE), and quality engineering analysis (e.g. Monte Carlo analysis). The primary struggle on the project was acquiring analysis models to use in the MDO system. The time required to obtain the models, unfortunately, limited the amount of analysis the team was able to perform. However, once the models were obtained, the team was able to quickly integrate them and show the power and flexibility of the MDO system. The results showed that the system was able to quickly apply numerous exploration techniques, including the Multi-Objective Genetic Algorithm specifically developed for the STTR, to the integrated models. Hundreds of ship designs were evaluated in the pursuit of an optimum design; while taking into account uncertainty. A measured improvement of 6% in lifecycle cost was calculated for an optimization analysis. It was also found that while introducing uncertainty in the analysis that the lifecycle cost was perturbed by only a maximum variation of 1%.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 02, 2004
- Accession Number
- ADA421304
Entities
People
- Justin Vianese