Uncertainty-Based Reliability Modeling and Analysis Method of Flight Vehicle Separation

被引：0
作者：
Zhang H.-R. [1 ]
Wang H. [1 ]
Wang Y. [1 ]
Hong D.-P. [1 ]
机构：
[1] China Academy of Launch Vehicle Technology, Beijing
来源：
Yuhang Xuebao/Journal of Astronautics | 2019年 / 40卷 / 04期
关键词：
Active learning Kriging; Reliability analysis; Reliability modeling; Uncertainty; Vehicle separation;
D O I：
10.3873/j.issn.1000-1328.2019.04.002
中图分类号：
学科分类号：
摘要：
In order to evaluate the hypersonic vehicle separation reliability efficiently, the influence of the separation process uncertainties on the hypersonic vehicle separation reliability is studied and a new uncertainty-based reliability modeling and analysis method for the hypersonic vehicle separation is proposed. In this method, the kinetic model is constructed based on the hypersonic vehicle separation task requirements. The significant uncertainty parameters are identified through the sensitivity analysis method for the construction of the separation reliability model. To improve the efficiency of the separation reliability evaluation, an improved active Kriging (IAK) method is proposed in which the point that has a higher potential failure probability by a new sampling strategy is regarded as the next training point. It is shown that the influence of the uncertainties can be described exactly, and the accuracy and efficiency of the separation reliability analysis are improved, which can further support the detailed design of the vehicle separation. © 2019, Editorial Dept. of JA. All right reserved.
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页码：378 / 385
页数：7
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