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- 저자 : Shuxing Yang (검색결과 1 건)
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A moment-matching robust collaborative optimization method
Fenfen Xiong,Gaorong Sun,Ying Xiong,Shuxing Yang 대한기계학회 2014 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.28 No.4
Robust collaborative optimization (RCO) is a widely used approach to design multidisciplinary system under uncertainty. In most ofthe existing RCO frameworks, the mean of the state variable is considered as auxiliary design variable and the implicit uncertainty propagationmethod is employed for estimating their uncertainties (interval or standard deviation), which are then used to calculate uncertaintiesin the ending performances. However, as repeated calculation of the global sensitivity equations (GSE) is demanded during the optimizationprocess of the existing approaches, it is typically very cumbersome or even impossible to obtain GSE for many practical engineeringproblems due to the non-smoothness and discontinuity of the black-box-type analysis models. To address this issue, a new RCOmethod is proposed in this paper, in which the standard deviation of the state variable is introduced as auxiliary design variable in additionto the mean. Accordingly, interdisciplinary compatibility constraint on the standard deviation of state variable is added to enhancethe design compatibility between various disciplines. The effectiveness of the proposed method is demonstrated through two mathematicalexamples. The results generated by the conventional robust all-in-one (RAIO) approach are used as benchmarks for comparison. Ourstudy shows that the optimal solutions produced by the proposed RCO method are highly close to those of RAIO while exhibiting goodinterdisciplinary compatibility.
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