PERFORMABILITY DESIGN OF DYNAMIC SYSTEMS

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 single-value-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.