Modeling the corrosion behavior of Ni-Cr-Mo-V high strength steel in the simulated deep sea environments using design of experiment and artificial neural network
文献类型：期刊论文
| 作者 | Hu, Qiangfei2,3; Liu, Yuchen3; Zhang, Tao1,3; Geng, Shujiang2; Wang, Fuhui1,3 |
| 刊名 | JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
 |
| 出版日期 | 2019 |
| 卷号 | 35期号:1页码:168-175 |
| 关键词 | Ni-Cr-Mo-V steel Deep sea corrosion Design of experiment Artificial neural network |
| ISSN号 | 1005-0302 |
| DOI | 10.1016/j.jmst.2018.06.017 |
| 通讯作者 | Zhang, Tao(zhangtao@mail.neu.edu.co) |
| 英文摘要 | Corrosion in complex coupling environments is an important issue in corrosion field, because it is difficult to take into account a large number of environment factors and their interactions. Design of Experiment (DOE) can present a methodology to deal with this difficulty, although DOE is not commonly spread in corrosion field. Thus, modeling corrosion of Ni-Cr-Mo-V steel in deep sea environment was performed in order to provide example demonstrating the advantage of DOE. In addition, an artificial neural network mapping using back-propagation method was developed for Ni-Cr-Mo-V steel such that the ANN model can be used to predict polarization curves under different complex sea environments without experimentation. Furthermore, roles of environment factors on corrosion of Ni-Cr-Mo-V steel in deep sea environment were discussed. (C) 2018 Published by Elsevier Ltd on behalf of The editorial office of Journal of Materials Science & Technology. |
| 资助项目 | National Natural Science Foundation of China[51371182] ; National Program for the Young Top-notch Professionals ; Fundamental Research Funds for the Central Universities[N170205002] |
| WOS研究方向 | Materials Science ; Metallurgy & Metallurgical Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000449263900023 |
| 出版者 | JOURNAL MATER SCI TECHNOL |
| 资助机构 | National Natural Science Foundation of China ; National Program for the Young Top-notch Professionals ; Fundamental Research Funds for the Central Universities |
| 源URL | [http://ir.imr.ac.cn/handle/321006/130452]  |
| 专题 | 金属研究所_中国科学院金属研究所 |
| 通讯作者 | Zhang, Tao |
| 作者单位 | 1.Chinese Acad Sci, Inst Met Res, Lab Corros & Protect, Shenyang 110016, Liaoning, Peoples R China 2.Northeastern Univ, Sch Met, Shenyang 110819, Liaoning, Peoples R China 3.Northeastern Univ, Corros & Protect Div, Shenyang Natl Lab Mat Sci, Shenyang 110819, Liaoning, Peoples R China |
| 推荐引用方式 GB/T 7714 | Hu, Qiangfei,Liu, Yuchen,Zhang, Tao,et al. Modeling the corrosion behavior of Ni-Cr-Mo-V high strength steel in the simulated deep sea environments using design of experiment and artificial neural network[J]. JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY,2019,35(1):168-175. |
| APA | Hu, Qiangfei,Liu, Yuchen,Zhang, Tao,Geng, Shujiang,&Wang, Fuhui.(2019).Modeling the corrosion behavior of Ni-Cr-Mo-V high strength steel in the simulated deep sea environments using design of experiment and artificial neural network.JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY,35(1),168-175. |
| MLA | Hu, Qiangfei,et al."Modeling the corrosion behavior of Ni-Cr-Mo-V high strength steel in the simulated deep sea environments using design of experiment and artificial neural network".JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY 35.1(2019):168-175. |
入库方式： OAI收割
来源：金属研究所
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