国防科技大学学报2025，Vol.47Issue(3)：203-212,10.DOI:10.11887/j.cn.202503021
扩展空间子集模拟的马尔可夫链可靠性优化方法
Markov chain reliability optimization method for augmented space subset simulation
摘要
Abstract
Aiming at the reliability-based design optimization problem of complex structural systems,an efficient optimization method based on subset simulation and Markov chain simulation in augmented space was proposed.Considering the reliability-based design optimization problem in which the design parameters were distributed parameters of basic random variables,the target failure probability was transformed into a posterior density function of the design parameters in the augmented space,obtained a set of initial failure samples in the whole design domain through subset simulation,and then adopted the efficient Markov chain simulation to generate more failure samples in the gradually smaller design domain under the sequential approximate optimization framework.The target posterior density function was estimated and updated,and the decoupling approach was used to solve the transformed optimization problem to finally obtain the optimum.Compared with the existing methods,the proposed method requires only one reliability analysis and can avoid local optimal solution,resulting in the global optimal solution.Examples were given to illustrate the applicability of the proposed method in engineering and its superiority in the accuracy and efficiency of analysis and calculation.关键词
可靠性优化设计/子集模拟/马尔可夫链模拟/扩展空间/贝叶斯定理Key words
reliability-based design optimization/subset simulation/Markov chain simulation/augmented space/Bayes' theorem分类
航空航天引用本文复制引用
袁修开,陈敬强,张景豫,谭智勇,董一巍..扩展空间子集模拟的马尔可夫链可靠性优化方法[J].国防科技大学学报,2025,47(3):203-212,10.基金项目
国家自然科学基金资助项目(52475491) （52475491）
国家科技重大专项基金资助项目(J2019-Ⅱ-0022-0043,J2019-Ⅶ-0013-0153) （J2019-Ⅱ-0022-0043,J2019-Ⅶ-0013-0153）
航空科学基金资助项目(20230003068002,20240003068001) （20230003068002,20240003068001）
四川省省院省校科技合作资助项目(2025YFHZ0039) （2025YFHZ0039）
