期刊
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
卷 59, 期 6, 页码 1949-1968出版社
SPRINGER
DOI: 10.1007/s00158-018-2165-2
关键词
Multidisciplinary robust design optimization (MRDO); Improved collaboration pursuing method (ICPM); Mode pursuing sampling (MPS); Interval uncertainty
资金
- National Natural Science Foundation of China [51675196, 51721092]
- Program for HUST Academic Frontier Youth Team
The collaboration pursuing method (CPM) is a computationally efficient approach for deterministic multidisciplinary design optimization (MDO). However, it has not been employed to handle problems with uncertainty. Moreover, obtaining actual uncertainty probability distributions is challenging. Compared to probability distributions, the interval information of uncertainties can be more easily obtained. Thus, multidisciplinary robust design optimization (MRDO) under interval uncertainty has been widely investigated. To overcome the inefficiency of existing methods for solving MRDO, this paper proposes an improved collaboration pursuing method (ICPM). In this method, the collaboration model (CM) is utilized to filter the samples that satisfy the coupled state equations in system analysis (SA) or multidisciplinary analysis (MDA). Then, a robustness discrepancy model (RDM) is developed to efficiently select candidate samples that meet the robustness requirements. Next, the mode pursuing sampling (MPS) method is utilized as a global optimizer to drive the optimization process and identify the robust optimum. Finally, a mathematical example and two engineering examples are utilized to evaluate the feasibility and effectiveness of the proposed method.
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