A method to reduce the sampling variability of time-domain fatigue life by optimizing parameters in Monte Carlo simulations

IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Probabilistic Engineering Mechanics Pub Date : 2024-01-01 DOI:10.1016/j.probengmech.2024.103591
Hong Sun , Yuanying Qiu , Jing Li , Jin Bai , Ming Peng
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Abstract

Monte Carlo numerical simulations for generating stationary Gaussian random time-domain signal samples fulfil an important role in random fatigue life prediction. Control parameters such as the random seed, the sampling frequency and the number of sampling points in the numerical simulations have significant effects on the time-domain random fatigue life. In this paper, the effects are investigated systematically by utilizing commonly used power spectrum samples and engineering materials, and so a new method for optimizing the control parameter values is proposed. The proposed method solves the critical problem found in many papers that the relative error between the frequency-domain fatigue life and the time-domain fatigue life increases with the slope K of the S–N curve. Furthermore, it observably reduces the sampling variability of time-domain fatigue life for the large slope K, which will help the related researchers to establish better frequency-domain models for fatigue life prediction by using the time-domain fatigue life values as standard data.

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通过优化蒙特卡洛模拟参数减少时域疲劳寿命采样变异性的方法
用于生成静态高斯随机时域信号样本的蒙特卡罗数值模拟在随机疲劳寿命预测中发挥着重要作用。数值模拟中的随机种子、采样频率和采样点数等控制参数对时域随机疲劳寿命有显著影响。本文利用常用的功率谱样本和工程材料系统地研究了这些影响,并提出了优化控制参数值的新方法。本文提出的方法解决了许多论文中发现的关键问题,即频域疲劳寿命和时域疲劳寿命之间的相对误差会随着曲线斜率的增加而增大。此外,它还明显降低了大斜率时域疲劳寿命的采样变异性,这将有助于相关研究人员利用时域疲劳寿命值作为标准数据,建立更好的频域疲劳寿命预测模型。
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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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