疲劳极限试验两相优化设计

IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Probabilistic Engineering Mechanics Pub Date : 2023-11-17 DOI:10.1016/j.probengmech.2023.103551
Lujie Shi , Leila Khalij , Christophe Gautrelet , Chen Shi , Denis Benasciutti
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引用次数: 0

摘要

为了克服阶梯法估计疲劳极限分布的固有缺陷,提出了一种基于Langlie法和d -最优准则的两阶段法。本文确定了当前的挑战,并提供了现有解决方案的概述,设定了开发高效数据收集协议的目标。进一步解释了d -最优性准则的应用,描述了两阶段协议,并给出了相关实例。这种方法最显著的优点是它对测试前信息的需求最小。通过仿真分析了输入参数的敏感性,并与传统的阶梯优化方法和贝叶斯优化方法的有效性进行了比较。数值模拟结果表明,该方法在预试信息最少的情况下,对疲劳极限分布均值和标准差的估计性能有较好的提高。
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Two-phase optimized experimental design for fatigue limit testing

This study proposes an innovative Two-phase method, based on the Langlie method and the D-optimality criterion, to overcome the intrinsic shortcomings of the staircase method used in estimating the fatigue limit distribution. This paper identifies the current challenges and provides an overview of existing solutions, setting the goal of developing an efficient data collection protocol. It further explains the application of D-optimality criterion and describes the Two-phase protocol, accompanied by a relevant example. The most significant advantage of this approach is its minimal requirement for pre-test information. A simulation-based study was executed to analyze the sensitivity of the input parameters and compare the effectiveness of the proposed method with the traditional staircase and Bayesian optimized method. The numerical simulations reveal that the proposed method offers improved estimation performance for the mean and standard deviation of the fatigue limit distribution, even with minimal pre-test information.

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来源期刊
Probabilistic Engineering Mechanics
Probabilistic Engineering Mechanics 工程技术-工程:机械
CiteScore
3.80
自引率
15.40%
发文量
98
审稿时长
13.5 months
期刊介绍: This journal provides a forum for scholarly work dealing primarily with probabilistic and statistical approaches to contemporary solid/structural and fluid mechanics problems encountered in diverse technical disciplines such as aerospace, civil, marine, mechanical, and nuclear engineering. The journal aims to maintain a healthy balance between general solution techniques and problem-specific results, encouraging a fruitful exchange of ideas among disparate engineering specialities.
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