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Fitting fatigue test data with a novel S-N curve using frequentist and Bayesian inference

机译:使用频数和贝叶斯推断将疲劳测试数据与新的S-N曲线拟合

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摘要

In design against fatigue, a lower bound stress range vs. endurance curve (S-N curve) is employed to characterize fatigue resistance of plain material and structural details. With respect to the inherent variability of the fatigue life, the S-N curve is related to a certain probability of exceedance, a percentile of the fatigue life. This paper is concerned with modelling and estimating uncertainties in fatigue resistance of welded joints under constant amplitude loading. A new S-N curve format is proposed and fitted to fatigue test data by using the Maximum Likelihood Method. The results have been compared with the Random Fatigue Limit Model and the Bilinear Random Fatigue Limit Model. The proposed S-N curve appears to be more accurate in describing the S-N relation in high-cycle fatigue: it presents a smooth transition from finite to infinite-life regions and, differently from previous non-linear S-N relations with fatigue limit, this transition is controlled by an independent model parameter. Thereby it provides more flexibility for statistical fitting. In addition, a Bayesian framework is defined to fit the proposed relation including informative and non-informative prior distributions.
机译:在抗疲劳设计中,采用了较低的应力范围与耐力曲线(S-N曲线)来表征普通材料的疲劳强度和结构细节。关于疲劳寿命的固有可变性,S-N曲线与某个超出概率(疲劳寿命的百分数)有关。本文涉及在恒定振幅载荷下对焊接接头的疲劳强度进行建模和估计的不确定性。提出了一种新的S-N曲线格式,并使用最大似然法将其拟合到疲劳测试数据中。将结果与随机疲劳极限模型和双线性随机疲劳极限模型进行了比较。拟议的SN曲线似乎在描述高周疲劳中的SN关系时更为准确:它呈现了从有限寿命区域到无限寿命区域的平滑过渡,并且不同于先前具有疲劳极限的非线性SN关系,这种过渡是受控的通过一个独立的模型参数。因此,它为统计拟合提供了更大的灵活性。另外,贝叶斯框架被定义为适合所提议的关系,包括信息性和非信息性先验分布。

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