An explainable machine learning model for superalloys creep life prediction coupling with physical metallurgy models and CALPHAD

doi:10.1016/j.commatsci.2023.112283

IMR OpenIR

	An explainable machine learning model for superalloys creep life prediction coupling with physical metallurgy models and CALPHAD
	Huang, Yuyu 1,2; Liu, Jide 1,2; Zhu, Chongwei 1,2; Wang, Xinguang 1; Zhou, Yizhou 1; Sun, Xiaofeng 1; Li, Jinguo 1
通讯作者	Liu, Jide(jdliu@imr.ac.cn)
	2023-08-01
发表期刊	COMPUTATIONAL MATERIALS SCIENCE
ISSN	0927-0256
卷号	227 页码:11
摘要	Data-driven research mode plays an increasingly important role in scientific research. In this study, a dimen-sionality reduction strategy coupling with physical metallurgy models and CALPHAD method was proposed to established a machine learning model for Ni-based single crystal creep life prediction. SHAP analysis was applied to explain the internal mechanisms and the final results of the model. The results showed that the model was of good prediction accuracy and its prediction results could be reasonably explained. Thus, the model can be applied to predict the creep lives of engineering-applied superalloys and to search for the relationship between microstructures and creep lives of superalloys, which is expected to be applied to the design of new alloy.
关键词	Creep life prediction Explainable machine learning Physical metallurgy models CALPHAD
资助者	National Science and Technology Major Project ; National Natural Science Foundation of China ; National Key R amp; D Program of China
DOI	10.1016/j.commatsci.2023.112283
收录类别	SCI
语种	英语
资助项目	National Science and Technology Major Project[J2019 -VI -0023-0139] ; National Science and Technology Major Project[J2019 -VII -0004- 0144] ; National Natural Science Foundation of China[51871221] ; National Key R amp; D Program of China[2020YFA0714900]
WOS研究方向	Materials Science
WOS类目	Materials Science, Multidisciplinary
WOS记录号	WOS:001011948100001
出版者	ELSEVIER
引用统计	被引频次：6[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/178367
专题	中国科学院金属研究所
通讯作者	Liu, Jide
作者单位	1.Chinese Acad Sci, Inst Met Res, Shi Changxu Innovat Ctr Adv Mat, Shenyang 110016, Peoples R China 2.Univ Sci & Technol China, Sch Mat Sci & Engn, Shenyang 110016, Peoples R China
推荐引用方式 GB/T 7714	Huang, Yuyu,Liu, Jide,Zhu, Chongwei,et al. An explainable machine learning model for superalloys creep life prediction coupling with physical metallurgy models and CALPHAD[J]. COMPUTATIONAL MATERIALS SCIENCE,2023,227:11.
APA	Huang, Yuyu.,Liu, Jide.,Zhu, Chongwei.,Wang, Xinguang.,Zhou, Yizhou.,...&Li, Jinguo.(2023).An explainable machine learning model for superalloys creep life prediction coupling with physical metallurgy models and CALPHAD.COMPUTATIONAL MATERIALS SCIENCE,227,11.
MLA	Huang, Yuyu,et al."An explainable machine learning model for superalloys creep life prediction coupling with physical metallurgy models and CALPHAD".COMPUTATIONAL MATERIALS SCIENCE 227(2023):11.