吞吐量
威布尔分布
事件(粒子物理)
样品(材料)
罕见事件
计算机科学
材料科学
可靠性工程
统计
数学
物理
电信
量子力学
热力学
无线
作者
Yifan Zhou,Xuhui Zhang,Meng Yang,Yudong Pan,Zhenjiang Du,Jose Blanchet,Zhigang Suo,Tongqing Lu
出处
期刊:Matter
[Elsevier]
日期:2022-01-01
标识
DOI:10.1016/j.matt.2021.12.017
摘要
Summary
The conditions for rupture of a material commonly vary from sample to sample. Of great importance to applications are the conditions for rare-event rupture, but their measurements require many samples and consume much time. Here, the conditions for rare-event rupture are measured by developing a high-throughput experiment. For each run of the experiment, 1,000 samples are printed under the same nominal conditions and pulled simultaneously to the same stretch. Identifying the rupture of individual samples is automated by processing the video of the experiment. Under monotonic load, the rupture stretch for each sample is recorded. Under cyclic load, the number of cycles to rupture for each sample is also recorded. Rare-event rupture is studied by using the Weibull distribution and the peak-over-threshold method. This work reaffirms that predicting rare events requires large datasets. The high-throughput experiments enable the prediction of rare events with high accuracy and confidence.
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