Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical features

doi:10.1016/j.jmrt.2022.06.011

IMR OpenIR

	Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical features
	Xu, Jinghui 1; Li, Longfei 1; Liu, Xingang 2; Li, Hui 2; Feng, Qiang 1
通讯作者	Li, Longfei(lilf@skl.ustb.edu.cn)
	2022-07-01
发表期刊	JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T
ISSN	2238-7854
卷号	19 页码:2301-2313
摘要	The microstructural evolution prediction and operating condition evaluation of nickel-based single crystal (SX) superalloys during creep are of great significance for damage assessment in service. In this paper, quantitative models of crept microstructural evolution of a nickel-based SX superalloy containing Re and Ru were constructed by using the machine learning method with physical and statistical features of microstructure. Firstly, a sequence of high temperature creep tests was conducted on high-throughput specimens with multiple conditions. The physical microstructural features, i.e., volume fraction (Vf), rafting degree (Omega), and rafts thickness (D) of gamma' precipitates of 8 different specimens were quantitated continuously. Secondly, the statistic features were introduced as supplementary to improve the specificity of microstructural features, using the two statistical methods of two-point correlation and principal component analysis (PCA). Then, two machine learning models were constructed through a neural network algorithm, to predict the microstructure under a certain creep condition and evaluate the creep condition with a certain microstructural feature. The validation creep test showed that these two models have good performance. The quantitative models constructed in this study have great significance in the alloy optimization and damage assessment of nickel-based SX superalloys, which can be extended to other SX superalloys. (C) 2022 The Author(s). Published by Elsevier B.V.
关键词	Nickel-based SX superalloy High-throughput creep tests Statistical microstructural features Microstructure-property correlation Artificial neural networks
资助者	National Science and Technology Major Project ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; 111 Project
DOI	10.1016/j.jmrt.2022.06.011
收录类别	SCI
语种	英语
资助项目	National Science and Technology Major Project[:2017-VI-0002-0072] ; National Key Research and Development Program of China[:2016YFB0701403] ; National Natural Science Foundation of China[51631008] ; National Natural Science Foundation of China[91860201] ; 111 Project[B170003]
WOS研究方向	Materials Science ; Metallurgy & Metallurgical Engineering
WOS类目	Materials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering
WOS记录号	WOS:000861359200004
出版者	ELSEVIER
引用统计	被引频次：7[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/321006/175778
专题	中国科学院金属研究所
通讯作者	Li, Longfei
作者单位	1.Univ Sci & Technol Beijing, Beijing Adv Innovat Ctr Mat Genome Engn, State Key Lab Adv Met & Mat, Beijing 100083, Peoples R China 2.Chinese Acad Sci, Inst Met Res, Superalloys Div, Shenyang 110016, Peoples R China
推荐引用方式 GB/T 7714	Xu, Jinghui,Li, Longfei,Liu, Xingang,et al. Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical features[J]. JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T,2022,19:2301-2313.
APA	Xu, Jinghui,Li, Longfei,Liu, Xingang,Li, Hui,&Feng, Qiang.(2022).Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical features.JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T,19,2301-2313.
MLA	Xu, Jinghui,et al."Quantitative models of high temperature creep microstructure-property correlation of a nickel-based single crystal superalloy with physical and statistical features".JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T 19(2022):2301-2313.