摘要
自适应混沌控制方法是一种高效、稳健的逆可靠度分析方法,但在求解强非线性凹功能函数时,计算效率仍然有待提高,且可能会陷入局部最优.通过对混沌控制因子更新策略进行改进,提出了基于改进自适应混沌控制的逆可靠度分析方法.数值算例分析表明:该方法能够有效地改善混沌控制因子自适应选取时的合理性,具有更好的收敛性和更高的计算效率,为结构可靠度分析和可靠度优化问题提供了更加高效、稳健的求解途径.
The adaptive chaos control（ACC） method was an efficient and robust method for inverse reliability analysis. However,for strongly nonlinear concave performance functions,the computational efficiency of ACC still needs to be enhanced. Moreover,it might be trapped in the local optimum.Through revision of the update strategy for the chaos control factors,an improved adaptive chaos control method was presented for the inverse reliability analysis. Numerical results show that the proposed method effectively improves the rationality of adaptive selection of chaos control factors,so as to get better convergence and higher efficiency in computation. Furthermore,it makes a more efficient and robust approach for the reliability analysis and reliability-based design optimization.
作者
李彬
郝鹏
孟增
李刚
LI Bin HAO Peng MENG Zeng LI Gang(State Key Laboratory of Structural Analysis for Industrial Equipment （ Dalian University of Technology Department of Engineering Mechanics, Dalian University of Technology, Dalian , Liaoning 115024, P.R. China 2. School of Civil Engineering, Hefei University of Technology, Hefei 230009, P.R. China)
出处
《应用数学和力学》
CSCD
北大核心
2017年第9期979-987,共9页
Applied Mathematics and Mechanics
基金
国家重点基础研究发展计划(973计划)(2014CB046506
2014CB046803)
国家自然科学基金(11372061
11402049
11602076)~~
关键词
逆可靠度分析
混沌控制
强非线性
局部最优
高效稳健
inverse reliability analysis
chaos control
strong nonlinearity
local optimum
efficient and robust
