火焰喷涂自支撑构件的力学失效统计

IF 2.7 Q1 MATERIALS SCIENCE, CERAMICS
Florian Kerber, Magda Hollenbach, M. Neumann, T. Wetzig, T. Schemmel, H. Jansen, C. Aneziris
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引用次数: 2

摘要

本研究的目的是研究火焰喷涂陶瓷构件抗弯强度的变异性,并确定哪一个双参数分布函数最适合代表实验数据。此外,还讨论了试样数量的影响。火焰喷射过程的随机性会导致潜在组分的特性发生显著变化,因此表征断裂统计数据至关重要。为了实现这一点,本研究使用了两个大型数据集,每个数据集由1000个火焰喷射样本组成。除了标准威布尔方法外,该研究还检查了使用其他双参数分布函数(正态、对数正态和伽玛)表示实验数据的质量。为了评估分布函数及其特征参数的准确性,对实验数据进行重采样,生成随机子样本,并根据采样大小对结果进行评估。研究发现,Weibull分布和Gamma分布都能很好地代表实验数据,拟合质量与正、负离群值的数量相关。威布尔拟合对正异常值更敏感,而伽马拟合对负异常值更敏感。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Statistics of Mechanical Failure in Flame-Sprayed Self-Supporting Components
The objective of this study was to investigate the variability of flexural strength for flame-sprayed ceramic components and to determine which two-parametric distribution function was best suited to represent the experimental data. Moreover, the influence of the number of tested specimens was addressed. The stochastic nature of the flame-spraying process causes a pronounced variation in the properties of potential components, making it crucial to characterise the fracture statistics. To achieve this, this study used two large data sets consisting of 1000 flame-sprayed specimens each. In addition to the standard Weibull approach, the study examined the quality of representing the experimental data using other two-parametric distribution functions (Normal, Log-Normal, and Gamma). To evaluate the accuracy of the distribution functions and their characteristic parameters, random subsamples were generated by resampling of the experimental data, and the results were assessed based on the sampling size. It was found that the experimental data were best represented by either the Weibull or Gamma distribution, and the quality of the fit was correlated with the number of positive and negative outliers. The Weibull fit was more sensitive to positive outliers, whereas the Gamma fit was more sensitive to negative outliers.
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来源期刊
CiteScore
3.00
自引率
7.10%
发文量
66
审稿时长
10 weeks
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