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 引用本文: 郝鹏, 杨浩, 冯少军, 王博. 高置信水平结构逆可靠度分析与优化方法研究进展. 力学学报, 2024, 56(2): 310-326.
Hao Peng, Yang Hao, Feng Shaojun, Wang Bo. Research advances on the high-confidence structural inverse reliability analysis and optimization methods. Chinese Journal of Theoretical and Applied Mechanics, 2024, 56(2): 310-326.
 Citation: Hao Peng, Yang Hao, Feng Shaojun, Wang Bo. Research advances on the high-confidence structural inverse reliability analysis and optimization methods. Chinese Journal of Theoretical and Applied Mechanics, 2024, 56(2): 310-326.

## RESEARCH ADVANCES ON THE HIGH-CONFIDENCE STRUCTURAL INVERSE RELIABILITY ANALYSIS AND OPTIMIZATION METHODS

• 摘要: 不确定性客观存在于工程结构生产制造以及服役等各环节之中并对结构的承载性能影响显著. 特别是对于服役条件苛刻的航空航天承载装备, 在设计阶段考虑多源不确定性的影响对于结构安全至关重要. 在众多不确定性分析方法中, 逆可靠度分析方法在效率和稳健性方面具有一定优势. 为此, 国内外学者在高置信水平结构逆可靠度分析与优化方法方面开展了大量研究并取得了长足进步, 包括自适应迭代控制算法、先进可靠度优化策略与非充分样本下的高置信水平设计方法等. 本文首先对国内外逆可靠度分析与优化方法取得的进展进行了系统梳理与总结, 特别是逆可靠度分析方法的发展历程以及面临的挑战问题, 主要包括强非线性功能函数、多设计点以及低失效概率问题. 进一步, 针对长期困扰可靠度方法实际应用的小样本问题, 重点从结构高置信水平可靠度分析与优化理论角度开展系统介绍, 详细论述了小样本诱发的认知不确定性到可靠度置信水平的传播链条. 最后, 基于现有成果和国家重大前沿需求, 重点围绕航天装备可重复使用需求对结构可靠度未来研究方向进行了思考与展望, 期望相关研究成果能够进一步助力我国航空航天结构实现高可靠性与极致轻量化设计.

Abstract: Uncertainty is an inherent characteristic that objectively exists throughout various stages of engineering structures, such as manufacturing and service, which significantly affects the load-bearing performance of the structures. This impact is particularly pronounced in the case of aerospace and aircraft equipment with high load-bearing demands and harsh service conditions. Therefore, it is crucial to account for the influence of multiple sources of uncertainties during the design stage to ensure structural safety. Among the numerous methods available for uncertainty analysis, inverse reliability analysis methods have shown certain advantages in terms of efficiency and robustness. Consequently, numerous domestic and foreign scholars have conducted extensive research in the field of high-confidence structural inverse reliability analysis and optimization methods, resulting in notable advancements such as adaptive iterative control algorithms, advanced reliability-based optimization strategies, and high-confidence design methods under insufficient samples. This paper provides a systematic summary of the progress made in domestic and foreign research on the inverse reliability analysis and optimization methods, with a particular focus on the development process and challenges faced by structural inverse reliability analysis methods, including strongly nonlinear performance functions, multiple design points, and low failure probability problems. Further, to address the small-sample problem that has long plagued the practical application of reliability methods, a systematic introduction is made focusing on the high-confidence structural reliability analysis and optimization theory. Therein, the chain of propagation from epistemic uncertainty induced by small samples to the confidence level of reliability is also discussed in details. Finally, by drawing upon the existing accomplishments and major national demands, this paper reflects upon and outlines the future research directions of structural reliability methods on the reusable needs of the aerospace equipment, with the expectation that relevant research outcomes will further facilitate the achievement of high reliability and ultimate lightweight design for aerospace and aircraft structures.

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