Study on the key features of dynamic compressive fracture strain of Ti-Zr-Nb solid solution alloys through random forest regressor

Bojian Fan, Xingwei Liu*, Shengping Si, Shuang Liu, Ruyue Xie, Jinxu Liu

*此作品的通讯作者

科研成果: 期刊稿件会议文章同行评审

摘要

In some specific application fields, dynamic fracture strain regarding as evaluating dynamic properties of Ti-Zr-Nb solid solution alloy have attracted extensive attention. However, the main influence factors of the dynamic strain of alloys were unclear. For the purpose of regulating Ti-Zr-Nb alloys' dynamic plasticity and clarify main influence factors of the dynamic plasticity of the materials, powder metallurgy, dynamic properties test combined with machine learning were performed. 56 Ti-Zr-Nb alloys were prepared through powder metallurgy and their dynamic compressive fracture strain was tested. Furthermore, optimization of machine learning model and selection of key features for the prediction of dynamic compressive fracture strain were carried out. The prediction accuracy of optimized model was more than 80%, and three key features that significantly influence the dynamic fracture strain were selected and ordered as: VEC>λ>ΔG.

源语言英语
文章编号012078
期刊Journal of Physics: Conference Series
2355
1
DOI
出版状态已出版 - 2022
活动2022 5th International Conference on Mechanical, Electrical and Material Application, MEMA 2022 - Chengdu, 中国
期限: 17 6月 202219 6月 2022

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