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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, Qiangfei1,3; Liu, Yuchen1; Zhang, Tao1,2; Geng, Shujiang3; Wang, Fuhui1,2
刊名JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
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
DOI10.1016/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
出版者JOURNAL MATER SCI TECHNOL
WOS记录号WOS:000449263900023
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
内容类型期刊论文
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.Northeastern Univ, Corros & Protect Div, Shenyang Natl Lab Mat Sci, Shenyang 110819, Liaoning, Peoples R China
2.Chinese Acad Sci, Inst Met Res, Lab Corros & Protect, Shenyang 110016, Liaoning, Peoples R China
3.Northeastern Univ, Sch Met, 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.
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