Adaptive Kriging-based method with learning function allocation scheme and hybrid convergence criterion for efficient structural reliability analysis

IF 8.7 2区 工程技术 Q1 Mathematics
Jiaguo Zhou, Guoji Xu, Zexing Jiang, Yongle Li, Jinsheng Wang
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引用次数: 0

Abstract

Structural reliability analysis poses significant challenges in engineering practices, leading to the development of various state-of-the-art approximation methods. Active learning methods, known for their superior performance, have been extensively investigated to estimate the failure probability. This paper aims to develop an efficient and accurate adaptive Kriging-based method for structural reliability analysis by proposing a novel learning function allocation scheme and a hybrid convergence criterion. Specifically, the novel learning function allocation scheme is introduced to address the challenge of no single learning function universally outperforms others across various engineering contexts. Six learning functions, including EFF, H, REIF, LIF, FNEIF, and KO, constitute a portfolio of alternatives in the learning function allocation scheme. The hybrid convergence criterion, combining the error-based stopping criterion with a stabilization convergence criterion, is proposed to terminate the active learning process at an appropriate stage. Moreover, an importance sampling algorithm is leveraged to enable the proposed method with the capability to deal with rare failure events. The efficiency and accuracy of the proposed method are demonstrated through four numerical examples and one engineering case.

Abstract Image

基于学习函数分配方案和混合收敛标准的自适应克里金方法,用于高效结构可靠性分析
结构可靠性分析是工程实践中的重大挑战,因此开发了各种最先进的近似方法。主动学习方法以其卓越的性能而著称,已被广泛用于失效概率的估算。本文旨在通过提出一种新颖的学习函数分配方案和混合收敛准则,为结构可靠性分析开发一种高效、精确的基于克里金的自适应方法。具体来说,新颖的学习函数分配方案是为了解决在各种工程背景下没有一种学习函数能普遍优于其他学习函数的难题。六种学习函数,包括 EFF、H、REIF、LIF、FNEIF 和 KO,构成了学习函数分配方案中的备选方案组合。混合收敛准则结合了基于误差的停止准则和稳定收敛准则,可在适当阶段终止主动学习过程。此外,还利用重要度采样算法,使所提出的方法具有处理罕见故障事件的能力。通过四个数值示例和一个工程案例,证明了所提方法的效率和准确性。
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
Engineering with Computers
Engineering with Computers 工程技术-工程:机械
CiteScore
16.50
自引率
2.30%
发文量
203
审稿时长
9 months
期刊介绍: Engineering with Computers is an international journal dedicated to simulation-based engineering. It features original papers and comprehensive reviews on technologies supporting simulation-based engineering, along with demonstrations of operational simulation-based engineering systems. The journal covers various technical areas such as adaptive simulation techniques, engineering databases, CAD geometry integration, mesh generation, parallel simulation methods, simulation frameworks, user interface technologies, and visualization techniques. It also encompasses a wide range of application areas where engineering technologies are applied, spanning from automotive industry applications to medical device design.
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