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Uncertainty theory based reliability modeling for fatigue
Engineering Failure Analysis ( IF 4.4 ) Pub Date : 2020-09-25 , DOI: 10.1016/j.engfailanal.2020.104931
Xiao-Yang Li , Zhao Tao , Ji-Peng Wu , Wei Zhang

The study of the fatigue crack growth law is usually carried out by the fatigue crack growth experiments (FCGE), and is expressed by the fatigue crack growth model. Epistemic uncertainties exist in FCGE with small samples. Generally, Bayesian method, interval probability method, and fuzzy probability method are presented to quantify the epistemic uncertainty in the case of small samples. However, the expression of the epistemic uncertainty in most studies is greatly influenced by subjective information, and there are interval expansion problems in the calculation. Therefore, the problem of how to quantify the epistemic uncertainties in FCGE with small samples has not been well solved. Under such circumstance, a novel uncertain measure is used to quantify such epistemic uncertainty in this paper, which is belong to uncertainty theory proposed by Prof. Baoding Liu. Firstly, the fatigue crack growth model proposed by Zhang is introduced as the foundation of modeling. Then, the sources of uncertainties in FCGE are analyzed and the uncertainties are quantified based on the uncertainty theory. Finally, a belief reliability model of fatigue crack growth is proposed, in which the associated reliability function is derived, and the uncertain statistics for the parameter estimations is presented. The case study illustrates the proposed methodology and the corresponding discussions show that the uncertainty theory contributes to more stable reliability evaluation than probability theory when quantifying the epistemic uncertainty, and the influence of the material scatter on fatigue reliability should be emphasized.



中文翻译:

基于不确定性理论的疲劳可靠性建模

疲劳裂纹扩展规律的研究通常由疲劳裂纹扩展实验(FCGE)进行,并通过疲劳裂纹扩展模型来表示。具有少量样本的FCGE存在认知不确定性。通常,提出了贝叶斯方法,区间概率方法和模糊概率方法来量化小样本情况下的认知不确定性。但是,大多数研究中的不确定性表达受主观信息的影响很大,计算中存在区间扩展问题。因此,如何用小样本量化FCGE中的认知不确定性的问题尚未得到很好的解决。在这种情况下,本文采用一种新颖的不确定性度量来量化这种认知不确定性,这属于刘保定教授提出的不确定性理论。首先,介绍了张建中提出的疲劳裂纹扩展模型。然后,分析了FCGE中的不确定性来源,并根据不确定性理论对不确定性进行了量化。最后,提出了疲劳裂纹扩展的置信可靠性模型,推导了相关的可靠性函数,并给出了参数估计的不确定统计量。案例研究说明了所提出的方法,并进行了相应的讨论,结果表明,在量化认知不确定性时,不确定性理论比概率论更有助于可靠性评估,并且应强调材料散布对疲劳可靠性的影响。介绍了张建中提出的疲劳裂纹扩展模型作为建模基础。然后,分析了FCGE中的不确定性来源,并根据不确定性理论对不确定性进行了量化。最后,提出了疲劳裂纹扩展的置信可靠性模型,推导了相关的可靠性函数,并给出了参数估计的不确定统计量。案例研究说明了所提出的方法,并进行了相应的讨论,结果表明,在量化认知不确定性时,不确定性理论比概率论更有助于可靠性评估,并且应强调材料散布对疲劳可靠性的影响。介绍了张建中提出的疲劳裂纹扩展模型作为建模基础。然后,分析了FCGE中的不确定性来源,并根据不确定性理论对不确定性进行了量化。最后,提出了疲劳裂纹扩展的置信可靠性模型,推导了相关的可靠性函数,并给出了参数估计的不确定统计量。案例研究说明了所提出的方法,并进行了相应的讨论,结果表明,在量化认知不确定性时,不确定性理论比概率论更有助于可靠性评估,并且应强调材料散布对疲劳可靠性的影响。分析了FCGE中不确定性的来源,并根据不确定性理论对不确定性进行了量化。最后,提出了疲劳裂纹扩展的置信可靠性模型,推导了相关的可靠性函数,并给出了参数估计的不确定统计量。案例研究说明了所提出的方法,并进行了相应的讨论,结果表明,在量化认知不确定性时,不确定性理论比概率论更有助于可靠性评估,并且应强调材料散布对疲劳可靠性的影响。分析了FCGE中不确定性的来源,并根据不确定性理论对不确定性进行了量化。最后,提出了疲劳裂纹扩展的置信可靠性模型,推导了相关的可靠性函数,并给出了参数估计的不确定统计量。案例研究说明了所提出的方法,并进行了相应的讨论,结果表明,在量化认知不确定性时,不确定性理论比概率论更有助于可靠性评估,并且应强调材料散布对疲劳可靠性的影响。其中推导了相关的可靠性函数,并给出了参数估计的不确定统计量。案例研究说明了所提出的方法,并进行了相应的讨论,结果表明,在量化认知不确定性时,不确定性理论比概率论更有助于可靠性评估,并且应强调材料散布对疲劳可靠性的影响。其中推导了相关的可靠性函数,并给出了参数估计的不确定统计量。案例研究说明了所提出的方法,并进行了相应的讨论,结果表明,在量化认知不确定性时,不确定性理论比概率论更有助于可靠性评估,并且应强调材料散布对疲劳可靠性的影响。

更新日期:2020-10-16
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