A probability of improvement-based multi-fidelity robust optimization approach for aerospace products design

Quan Lin; Lintao Gong; Yunlong ZhangMeng KouQi Zhou

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A probability of improvement-based multi-fidelity robust optimization approach for aerospace products design

机译：A probability of improvement-based multi-fidelity robust optimization approach for aerospace products design

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Uncertainty is inevitable in aerospace products design optimization, which may lead to the undesired performance of aerospace products and even infeasible designs. Robust design optimization (RDO) aims to obtain a solution with a desirable performance mean and is insensitive to uncertainty. However, it is computationally intensive during the RDO process, which is unaffordable for aerospace product design optimization. Multi-fidelity (MF) surrogate modeling is a widely used strategy to alleviate the heavy computational burden in RDO problems. The existing MF surrogate modeling-based RDO approaches, however, generate the samples in a one-shot way, which requires sufficient samples distributed in the entire design space. In this work, a probability of improvement-based adaptive sampling approach is proposed for multi-fidelity robust design optimization. The multi-level hierarchical Kriging (MHK) model is used for multi-fidelity modeling, which allows the proposed approach to deal with data of multiple fidelities. Both design variable uncertainty and interpolation uncertainty are considered within the approach. An extended PI (EPI) function is developed to simultaneously select the design location and fidelity level of the updated sample. To deal with RDO problems with constraints, the proposed EPI function is extended by combining with the probability of feasibility functions. The proposed approach is demonstrated using four numerical examples and an engineering example of robust design optimization for a micro-aerial vehicle fuselage.

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来源
《Aerospace science and technology》 |2022年第9期|107764.1-107764.12|共12页
作者
Quan Lin; Lintao Gong; Yunlong ZhangMeng KouQi Zhou;
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作者单位

School of Aerospace Engineering, Huazhong University of Science and Technology. Wuhan 430074, China;

School of Aerospace Engineering, Huazhong University of Science and Technology. Wuhan 430074, China, Beijing Institute of Space System Engineering, Beijing 100076, China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
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关键词
Robust design optimization; Multi-fidelity surrogate; Adaptive sampling; Probability of improvement;

A probability of improvement-based multi-fidelity robust optimization approach for aerospace products design

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