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兵工学报 ›› 2020, Vol. 41 ›› Issue (2): 398-405.doi: 10.3969/j.issn.1000-1093.2020.02.023

• 论文 • 上一篇    下一篇

结构可靠性优化的通用生成函数-序列优化与可靠性评估方法

朱达伟1, 周金宇2, 庄百亮3   

  1. (1.江苏理工学院 机械工程学院, 江苏 常州 213001;2.金陵科技学院 机电工程学院, 江苏 南京 211169;3.机械科学研究总院江苏分院有限公司, 江苏 常州 213001)
  • 收稿日期:2019-07-10 修回日期:2019-07-10 上线日期:2020-04-04
  • 作者简介:朱达伟(1996—),男,硕士研究生。E-mail:286281649@qq.com
  • 基金资助:
    国家科技重大专项项目(2018ZX04026001-008);江苏省高校自然科学研究重大项目(16KJA460002);金陵科技学院科研课题项目(jit-rcyj-201901)

UGF-SORA Method for Reliability Optimization of Structure

ZHU Dawei1, ZHOU Jinyu2, ZHUANG Bailiang3   

  1. (1.School of Mechanical Engineering, Jiangsu University of Technology, Changzhou 213001, Jiangsu, China;2.College of Mechanical and Electrical Engineering, Jinling Institute of Technology, Nanjing 211169, Jiangsu, China;3.Jiangsu Institute, China Academy of Machinery Science & Technology Co., Ltd., Changzhou 213001, Jiangsu, China)
  • Received:2019-07-10 Revised:2019-07-10 Online:2020-04-04

摘要: 通用生成函数(UGF)法在处理随机变量为非正态、功能函数为高度非线性的概率分析问题时具有较大优势。为提高结构可靠性优化求解的精度,提出了一种基于通用生成函数的序列优化与可靠性评估方法。该算法引入高精度可靠性分析方法和偏移向量求解策略完成优化,将迭代过程分为3个环节完成:第1环节利用最小二乘法拟合偏移函数的响应面回归模型,根据模型和许可可靠指标求解偏移向量;第2环节根据所求偏移向量完成确定性优化,得到当前设计点;第3环 节利用UGF法进行可靠性分析和评估,并根据相关约束重新构建偏移函数。算例分析表明,所提方法在保证求解效率的同时提高了优化精度,并很好地解决功能函数为高度非线性时优化结果无法收敛的问题。

关键词: 结构可靠性优化, 通用生成函数, 序列优化, 最小二乘法

Abstract: Universal generating function (UGF) method has great advantages in dealing with probabilistic analysis problems with non-normal random variables and highly non-linear performance functions.A method of sequential optimization and reliability assessment based on universal generating function (UGF-SORA) is proposed to improve the optimization accuracy of structural reliability. In the porposed method, the high precision reliability analysis method and the offset vector solving strategy are introduced for optimization, and the iteration process is divided into three parts. In the first step, the least square method is used to fit the response surface regression model of migration function, and the offset vectors are solved according to the model and the permissible reliability index. In the second step, according to the offset vector, the deterministic optimization is completed and the current design points are obtained. In the third step, the reliability analysis and evaluation are carried out by UGF method. Furthermore, the migration function is reconstructed according to the relevant constraints. It is shown through the example analysis that the proposed method is used to ensure the efficiency of solution, but also improve the accuracy of optimization. It also solves the problem that the optimization results can't converge when the performance function is highly non-linear. Key

Key words: structuralreliabilityoptimization, universalgenerationfunction, sequentialoptimization, leastsquaremethod

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