| 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 | |
| Hu, Qiangfei1,2; Liu, Yuchen2; Zhang, Tao2,3; Geng, Shujiang1; Wang, Fuhui2,3 | |
| Corresponding Author | Zhang, Tao(zhangtao@mail.neu.edu.co) |
| 2019 | |
| Source Publication | JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
 |
| ISSN | 1005-0302 |
| Volume | 35Issue:1Pages:168-175 |
| Abstract | 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. |
| Keyword | Ni-Cr-Mo-V steel Deep sea corrosion Design of experiment Artificial neural network |
| Funding Organization | National Natural Science Foundation of China ; National Program for the Young Top-notch Professionals ; Fundamental Research Funds for the Central Universities |
| DOI | 10.1016/j.jmst.2018.06.017 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[51371182] ; National Program for the Young Top-notch Professionals ; Fundamental Research Funds for the Central Universities[N170205002] |
| WOS Research Area | Materials Science ; Metallurgy & Metallurgical Engineering |
| WOS Subject | Materials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering |
| WOS ID | WOS:000449263900023 |
| Publisher | JOURNAL MATER SCI TECHNOL |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.imr.ac.cn/handle/321006/130451 |
| Collection | 中国科学院金属研究所 |
| Corresponding Author | Zhang, Tao |
| Affiliation | 1.Northeastern Univ, Sch Met, Shenyang 110819, Liaoning, Peoples R China 2.Northeastern Univ, Corros & Protect Div, Shenyang Natl Lab Mat Sci, Shenyang 110819, Liaoning, Peoples R China 3.Chinese Acad Sci, Inst Met Res, Lab Corros & Protect, Shenyang 110016, Liaoning, Peoples R China |
| Recommended Citation 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. |
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