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赵维涛,王建业,祁武超.结构可靠性优化的三阶段解耦方法[J].计算力学学报,2018,35(1):7~13
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结构可靠性优化的三阶段解耦方法
Three-stage decoupling method of reliability-based design optimization
投稿时间:2016-10-09  修订日期:2016-12-07
DOI:10.7511/jslx20161009002
中文关键词:  基于可靠性的结构优化  解耦法  安全因子  灵敏度  重量因子
英文关键词:reliability-based design optimization  decoupling  safety factor  sensitivity  weight factor
基金项目:国家自然科学基金(11502149);国防基础科研计划基金(JCKY2013601B);辽宁省自然科学基金(201602579);辽宁省教育厅项目(L2014072)资助项目.
作者单位E-mail
赵维涛 沈阳航空航天大学 辽宁省飞行器复合材料结构分析与仿真重点实验室, 沈阳 110136 zhwt201@163.com 
王建业 沈阳航空航天大学 辽宁省飞行器复合材料结构分析与仿真重点实验室, 沈阳 110136  
祁武超 沈阳航空航天大学 辽宁省飞行器复合材料结构分析与仿真重点实验室, 沈阳 110136  
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中文摘要:
      为提高基于可靠性的结构优化效率,提出一种三阶段解耦分析方法。第一阶段利用可靠性安全因子进行确定性优化,并将确定性优化结果作为初始样本点;第二阶段利用可靠性灵敏度和重量因子对样本点进行调整,获取目标函数与失效概率的数据集合;第三阶段利用目标函数与失效概率的关系,曲线获取可接受失效概率对应的目标函数,并求解最终优化设计变量。本文方法只需一次确定性优化,且现有结构可靠性求解算法均可使用,适应性强。算例分析结果表明,本文方法可以明显减少失效概率评估次数,且计算结果对可靠性安全因子与重量因子不敏感。
英文摘要:
      In order to improve the efficiency of reliability-based design optimization (RBDO),a three-stage decoupling method is proposed in this paper.In the first stage,the deterministic optimization based on the reliability safety factor is used to find an optimal design,and the optimal design is chosen as an initial sample point.In the second stage,sample points are adjusted by using reliability sensitivities and a weight factor,and a data set between the objective function and the failure probability is obtained.In the third stage,the objective function corresponding to the acceptable failure probability is extracted by using a relationship curve between the objective function and the failure probability,and final optimization design variables are obtained.The deterministic optimization is used only one time in the proposed method,and all classical algorithms of structural reliability can be used for the proposed method.The adaptability of the proposed method is strong.The numerical results show that the proposed method can obviously reduce the number of evaluation of failure probability,and results are not sensitive to the reliability safety factor and weight factor.
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