Time-variant reliability analysis using phase-type distribution-based methods

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software Pub Date : 2024-10-18 DOI:10.1016/j.advengsoft.2024.103792

Junxiang Li , Xiwei Guo , Longchao Cao , Xinxin Zhang

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引用次数: 0

Abstract

The performance of engineering structures often varies over time due to the randomness and time variability of material properties, environmental conditions and load effects. This paper proposes phase-type (PH) distribution-based methods for efficient time-variant reliability analysis. The core of the proposed methods is to approximate the extreme value of a stochastic process as a PH distributed random variable, and treat the time parameter as a uniformly distributed variable. Consequently, the time-variant reliability problem is transformed into a time-invariant one. Three representative time-invariant reliability methods, first-order reliability method (FORM), importance sampling (IS) and adaptive Kriging (AK) surrogate model-based IS method (AK-IS), are integrated with the PH distribution-based approximation strategy to form the proposed methods, namely PH-FORM, PH-IS and PH-AKIS. The efficiency and accuracy of these methods are demonstrated through three examples. All codes in the study are implemented in MATLAB and provided as supplementary materials.

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利用基于相位分布的方法进行时变可靠性分析

由于材料特性、环境条件和荷载效应的随机性和时变性，工程结构的性能往往随时间而变化。本文提出了基于相位型（PH）分布的高效时变可靠性分析方法。所提方法的核心是将随机过程的极值近似为 PH 分布随机变量，并将时间参数视为均匀分布变量。因此，时变可靠性问题被转化为时不变可靠性问题。将三种具有代表性的时变可靠性方法，即一阶可靠性方法（FORM）、重要度抽样（IS）和基于自适应克里金（AK）代理模型的 IS 方法（AK-IS），与基于 PH 分布的近似策略相结合，形成了所提出的方法，即 PH-FORM、PH-IS 和 PH-AKIS。通过三个实例展示了这些方法的效率和准确性。研究中的所有代码均在 MATLAB 中实现，并作为补充材料提供。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Advances in Engineering Software 工程技术-计算机：跨学科应用

CiteScore

7.70

自引率

4.20%

发文量

169

审稿时长

37 days

期刊介绍： The objective of this journal is to communicate recent and projected advances in computer-based engineering techniques. The fields covered include mechanical, aerospace, civil and environmental engineering, with an emphasis on research and development leading to practical problem-solving. The scope of the journal includes: • Innovative computational strategies and numerical algorithms for large-scale engineering problems • Analysis and simulation techniques and systems • Model and mesh generation • Control of the accuracy, stability and efficiency of computational process • Exploitation of new computing environments (eg distributed hetergeneous and collaborative computing) • Advanced visualization techniques, virtual environments and prototyping • Applications of AI, knowledge-based systems, computational intelligence, including fuzzy logic, neural networks and evolutionary computations • Application of object-oriented technology to engineering problems • Intelligent human computer interfaces • Design automation, multidisciplinary design and optimization • CAD, CAE and integrated process and product development systems • Quality and reliability.