Abstract
The design of dynamic systems in terms of dependability and sustainability is a computationally intensive task - especially since probabilities are required. This paper presents a methodology that greatly reduces the design time with a controlled loss of accuracy. The proposed approach combines design of computer experiments, a judicious application of linear metamodels and an explicit evaluation of probabilities. This approach is much faster than traditional Monte Carlo simulation. A further reduction in time can be accomplished through the application of singlevalue- decomposition. The application of the methodology for two popular forms of metamodels (i.e. response surface methods via Least-squares fit and Kriging) is presented. Parameter design is provided by combining robust design principles with constrained optimization. A detailed case study of a system with multiple performance measures and multiple design variables shows the efficacy and practicality of the methodology.
Original language | English (US) |
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Title of host publication | Proceedings - 15th ISSAT International Conference on Reliability and Quality in Design |
Pages | 59-63 |
Number of pages | 5 |
State | Published - Dec 1 2009 |
Event | 15th ISSAT International Conference on Reliability and Quality in Design - San Francisco, CA, United States Duration: Aug 6 2009 → Aug 8 2009 |
Other
Other | 15th ISSAT International Conference on Reliability and Quality in Design |
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Country/Territory | United States |
City | San Francisco, CA |
Period | 8/6/09 → 8/8/09 |
Keywords
- Dynamic Systems
- FORM
- Limit-state functions
- Metamodels
- Robust design
- Singular value decomposition