扩展空间子集模拟的马尔科夫链可靠性优化方法
DOI:
作者:
作者单位:

1.厦门大学;2.厦门大学航空航天学院;3.中国航发商用航空发动机有限责任公司

作者简介:

通讯作者:

中图分类号:

V215.7

基金项目:

国家自然科学基金(52475491, 51705440);福建省自然科学基金(2019J01044);航空科学基金(20170368001、20230003068002、20240003068001);国家科技重大专项(J2019-III-0008, J2019-VII-0013-0153);智能制造装备与技术全国重点实验室基金(IMETKF2024013);福建省中科院STS计划配套院省合作重大项目(2022T3071);厦门大学四川研究院开放课题(202401YB002);四川省省院省校科技合作项目(2025YFHZ0039);国家科技重大专项(编号:J2019-II-0022-0043和J2019-VII-0013-0153)


Markov chain reliability optimization method for augmented space subset simulation
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    针对复杂结构系统的可靠性优化设计问题,提出一种高效的基于扩展空间子集模拟及马尔科夫链模拟的优化方法。在扩展空间中将参数设计为基本随机变量分布参数的可靠性优化问题进行转化,优化目标失效概率函数,等价转化成参数后验密度函数,通过子集模拟方法获得覆盖全设计域的初始失效样本点,再结合近似序列优化框架,采用高效的马尔科夫链模拟方法在逐步缩小的设计域内进行模拟,逐次更新设计参数后验密度函数的估计,并解耦求解得到优化问题的最优解。与已有方法相比,所提方法仅需一次可靠性分析即可避免局部优化解,得到全局最优解。所给算例说明所提方法在分析计算精度和效率上的优越性及工程适用性。

    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.

    参考文献
    相似文献
    引证文献
引用本文
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2023-03-27
  • 最后修改日期:2025-03-31
  • 录用日期:2023-10-07
  • 在线发布日期: 2025-04-03
  • 出版日期:
文章二维码