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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, Qiangfei; Liu, Yuchen; Zhang, Tao; Geng, Shujiang; Wang, Fuhui | |
2019 | |
Source Publication | JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
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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 |
Indexed By | SCI |
Language | 英语 |
WOS ID | WOS:000449263900023 |
Publisher | JOURNAL MATER SCI TECHNOL |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.imr.ac.cn/handle/321006/81529 |
Collection | 中国科学院金属研究所 |
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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