Reliability-based Design Optimization of Laminated Composite Structures under Delamination and Material Property Uncertainties

被引:47
|
作者
An, Haichao [1 ]
Youn, Byeng D. [1 ,2 ,3 ]
Kim, Heung Soo [4 ]
机构
[1] Seoul Natl Univ, Dept Mech Engn, Seoul 08826, South Korea
[2] Seoul Natl Univ, Inst Adv Machines & Design, Seoul 08826, South Korea
[3] OnePredict Inc, Seoul 06160, South Korea
[4] Dongguk Univ Seoul, Dept Mech Robot & Energy Engn, Seoul 04620, South Korea
关键词
Composite delamination; Uncertainty analysis; Reliability-based design optimization (RBDO); Composite laminate; Gaussian process regression; STACKING-SEQUENCE OPTIMIZATION; GENETIC ALGORITHM; VIBRATION; FAILURE; BEAMS; PERFORMANCE; PREDICTION; FREQUENCY; STRENGTH; PLATES;
D O I
10.1016/j.ijmecsci.2021.106561
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Delamination is a major type of defects from manufacturing process in laminated composite structures, exhibiting uncertain characteristics which are represented by mixed random variables of continuous in-plane position and delamination size, as well as discrete through-the-thickness position, which should be considered in the design phase of composite structures. Thus, this paper presents a reliability-based design framework for optimal design of composite stacking sequence, for the first time to consider both delamination and material property uncer-tainties from manufacturing process. Mixed continuous-discrete random variables are involved, and a reliability analysis method is newly proposed to tackle this mixed-variable problem, maintaining high levels of both accu-racy and efficiency. The formula of total probability is first employed to formulate the reliability constraint so that discrete and continuous random variables are decoupled; Monte Carlo simulation is then used for reliability analysis with respect to continuous random variables, and a surrogate modelling approach based on Gaussian process regression model is adopted to reduce computation costs. As design variables of ply angles are limited to a discrete set, a genetic algorithm with some proposed improvements is used to handle discrete design vari-ables. Consequently, an optimization framework is devised for composite laminate design under uncertainties from manufacturing process, which is verified via case studies of a cantilever composite plate and can also be extended as a general solution for other composite laminates. With integrated consideration of manufacturing limitations and imperfections as well as structural performances, the presented framework provides a valuable tool in composite structure design.
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页数:14
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