Research on hot deformation behavior of Cu-Ti alloy based on machine learning algorithms and microalloying

doi:10.1016/j.mtcomm.2024.108783

IMR OpenIR

	Research on hot deformation behavior of Cu-Ti alloy based on machine learning algorithms and microalloying
	Zhang, Mengxiao 1,2; Chen, Dayong 1; Liu, Huan 3; Zhang, Yanyan 1; Song, Hongwu 1; Xu, Yong 1; Zhang, Shihong 1
通讯作者	Song, Hongwu(hwsong@imr.ac.cn)
	2024-06-01
发表期刊	MATERIALS TODAY COMMUNICATIONS
卷号	39 页码:9
摘要	High strength and high elasticity copper alloys have good application prospects due to their excellent mechanical properties. The deformation and heat treatment in its preparation process are important steps to ensure the service performance. In this work, Cu -Ti based alloys were employed and hot compression experiments were conducted at 500 - 800 degree celsius under four different strain rates. Their constitutive equations and thermal processing maps were constructed. The influence of microalloying elements on activation energy was also analyzed. The microstructure evolution and recrystallization behavior under hot deformation conditions were studied based on the results of TEM. At the same time, Arrhenius, back propagation neural network (BPNN) and support vector machine (SVM) algorithms were used to predict the flow stress of the alloy. The results indicate that the relationship between flow stress and the input factors (strain rate, temperature and deformation) can be well predicted using the support vector machine algorithm. Microalloying can increase the activation energy of copper alloys, and the sensitivity of activation energy to temperature changes is related to the interaction between precipitates and dislocations.
关键词	Cu-Ti alloy Constitutive equations Thermal processing maps Machine learning algorithms
资助者	National Nature Science Foundation of China (NSCF) ; Science and Tech- nology Research Projects of Sichuan Province
DOI	10.1016/j.mtcomm.2024.108783
收录类别	SCI
语种	英语
资助项目	National Nature Science Foundation of China (NSCF)[52201148] ; Science and Tech- nology Research Projects of Sichuan Province[2023ZYD0135] ; Science and Tech- nology Research Projects of Sichuan Province[2022NSFSC1979]
WOS研究方向	Materials Science
WOS类目	Materials Science, Multidisciplinary
WOS记录号	WOS:001224610000001
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/321006/186266
专题	中国科学院金属研究所
通讯作者	Song, Hongwu
作者单位	1.Chinese Acad Sci, Shi Changxu Innovat Ctr Adv Mat, Inst Met Res, Shenyang 110016, Peoples R China 2.Univ Sci & Technol China, Sch Mat Sci & Engn, Shenyang 110016, Peoples R China 3.Shenyang Ligong Univ, Sch Mech Engn, Shenyang 110159, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Mengxiao,Chen, Dayong,Liu, Huan,et al. Research on hot deformation behavior of Cu-Ti alloy based on machine learning algorithms and microalloying[J]. MATERIALS TODAY COMMUNICATIONS,2024,39:9.
APA	Zhang, Mengxiao.,Chen, Dayong.,Liu, Huan.,Zhang, Yanyan.,Song, Hongwu.,...&Zhang, Shihong.(2024).Research on hot deformation behavior of Cu-Ti alloy based on machine learning algorithms and microalloying.MATERIALS TODAY COMMUNICATIONS,39,9.
MLA	Zhang, Mengxiao,et al."Research on hot deformation behavior of Cu-Ti alloy based on machine learning algorithms and microalloying".MATERIALS TODAY COMMUNICATIONS 39(2024):9.