Efficient optimization of reliability-constrained structural design problems including interval uncertainty

被引:31
作者
Liu, Yan [1 ]
Jeong, Han Koo [2 ]
Collette, Matthew [1 ]
机构
[1] Univ Michigan, Dept Naval Architecture & Marine Engn, Ann Arbor, MI 48109 USA
[2] Kunsan Natl Univ, Dept Naval Architecture, Gunsan Si, Jeollabuk Do, South Korea
关键词
Surrogate model; Optimization; Interval uncertainty; Reliability; Composite structures; TOPOLOGY OPTIMIZATION; ALGORITHM;
D O I
10.1016/j.compstruc.2016.08.004
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A novel interval uncertainty formulation for exploring the impact of epistemic uncertainty on reliability constrained design performance is proposed. An adaptive surrogate modeling framework is developed to locate the lowest reliability value within a multi-dimensional interval. This framework is combined with a multi-objective optimizer, where the interval width is considered as an objective. The resulting Pareto front examines how uncertainty reduces performance while maintaining a specified reliability threshold. Two case studies are presented: a cantilever tube under multiple loads and a composite stiffened panel. The proposed framework demonstrates its ability to resolve the Pareto front in an efficient manner. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1 / 11
页数:11
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