Research on hot deformation behavior of Cu-Ti alloy based on machine learning algorithms and microalloying
文献类型：期刊论文
| 作者 | Zhang, Mengxiao1,2; Chen, Dayong1; Liu, Huan3; Zhang, Yanyan1; Song, Hongwu1; Xu, Yong1; Zhang, Shihong1 |
| 刊名 | MATERIALS TODAY COMMUNICATIONS
 |
| 出版日期 | 2024-06-01 |
| 卷号 | 39页码:9 |
| 关键词 | Cu-Ti alloy Constitutive equations Thermal processing maps Machine learning algorithms |
| DOI | 10.1016/j.mtcomm.2024.108783 |
| 通讯作者 | Song, Hongwu(hwsong@imr.ac.cn) |
| 英文摘要 | 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. |
| 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 |
| 语种 | 英语 |
| WOS记录号 | WOS:001224610000001 |
| 出版者 | ELSEVIER |
| 资助机构 | National Nature Science Foundation of China (NSCF) ; Science and Tech- nology Research Projects of Sichuan Province |
| 源URL |  |
| 专题 | 金属研究所_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. |
入库方式： OAI收割
来源：金属研究所
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