Collaborative optimization with inverse reliability for multidisciplinary systems uncertainty analysis

Abstract

This article introduces a method which combines the collaborative optimization framework and the inverse reliability strategy to assess the uncertainty encountered in the multidisciplinary design process. This method conducts the sub-system analysis and optimization concurrently and then improves the process of searching for the most probable point (MPP). It reduces the load of the system-level optimizer significantly. This advantage is specifically more prominent for large-scale engineering system design. Meanwhile, because the disciplinary analyses are treated as the equality constraints in the disciplinary optimization, the computation load can be further reduced. Examples are used to illustrate the accuracy and efficiency of the proposed method.

Keywords:

• reliability analysis
• multidisciplinary design optimization (MDO)
• collaborative optimization
• uncertainty
• inverse reliability analysis

Acknowledgements

This research was partially supported by the National Natural Science Foundation of China under the contract number 50775026 and the National Basic Research Program of China under contract number 61382. The authors would like to acknowledge valuable suggestions and comments by Prof. Hae Chang Gea in the Department of Mechanical and Aerospace Engineering, Rutgers University, Piscataway, NJ 08854, USA.