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

doi:10.1016/j.jmst.2018.06.017

IMR OpenIR

	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 1,2; Liu, Yuchen 2; Zhang, Tao 2,3; Geng, Shujiang 1; Wang, Fuhui 2,3
通讯作者	Zhang, Tao(zhangtao@mail.neu.edu.co)
	2019
发表期刊	JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY
ISSN	1005-0302
卷号	35 期号:1 页码:168-175
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.
关键词	Ni-Cr-Mo-V steel Deep sea corrosion Design of experiment Artificial neural network
资助者	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
收录类别	SCI
语种	英语
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
WOS类目	Materials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering
WOS记录号	WOS:000449263900023
出版者	JOURNAL MATER SCI TECHNOL
引用统计	被引频次：45[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.imr.ac.cn/handle/321006/130456
专题	中国科学院金属研究所
通讯作者	Zhang, Tao
作者单位	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
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.