IOCAS-IR  > 海洋环境腐蚀与生物污损重点实验室
Global sensitivity analysis of influence parameters in pitting corrosion behavior of 304 stainless steel using adaptive neuro-fuzzy inference systems
Xu, Kaixin1; Sun, Wen1; Wang, Lida1; Yang, Zhengqing1; Wang, Jing2; Wang, Suilin3; Liu, Guichanng1
2020-11-23
Source PublicationMATERIALS AND CORROSION-WERKSTOFFE UND KORROSION
ISSN0947-5117
Pages11
Corresponding AuthorSun, Wen(sunw@dlut.edu.cn) ; Liu, Guichanng(gchliu@dlut.edu.cn)
AbstractPitting corrosion is simultaneously influenced by many parameters. However, conventional experimental methods do not offer information on the relative importance of each parameter to pitting corrosion. Herein, pitting corrosion of 304SS under multiple parameter influences was investigated by the global sensitivity analysis (GSA) based on adaptive neuro-fuzzy inference system (ANFIS). It was applied for the first time in quantitatively analyzing the relative importance of each parameter to pitting corrosion. It was developed in two different systems, based on the experimental data and the published data, respectively. Both results show that ANFIS exhibits a highly accurate prediction result. The GSA based on ANFIS quantitatively analyzes the relative importance of the initiation of pitting corrosion of 304SS for each parameter, and based on the results of GSA, it can also be determined whether the parameter inhibits or promotes pitting corrosion. We believe this method could provide guidance for corrosion research.
Keywordadaptive neuro‐ fuzzy inference system global sensitivity analysis pitting corrosion stainless steels
DOI10.1002/maco.202012120
Indexed BySCI
Language英语
Funding ProjectFundamental Research Funds for the Central Universities[DUT19RC(4)003] ; Beijing Scholars Program[022] ; China Postdoctoral Science Foundation[2017M610177] ; China Postdoctoral Science Foundation[2018T110222] ; Research Fund of Open Studio for Marine Corrosion and Protection, Pilot National Laboratory for Marine Science and Technology[HYFSKF-201804] ; National Natural Science Foundation of China[21703026] ; National Natural Science Foundation of China[21978036] ; National Natural Science Foundation of China[51671047] ; National Natural Science Foundation of China[U1808210]
WOS Research AreaMaterials Science ; Metallurgy & Metallurgical Engineering
WOS SubjectMaterials Science, Multidisciplinary ; Metallurgy & Metallurgical Engineering
WOS IDWOS:000591353600001
PublisherWILEY-V C H VERLAG GMBH
Citation statistics
Document Type期刊论文
Identifierhttp://ir.qdio.ac.cn/handle/337002/169193
Collection海洋环境腐蚀与生物污损重点实验室
Corresponding AuthorSun, Wen; Liu, Guichanng
Affiliation1.Dalian Univ Technol, Dept Chem Engn, Dalian 116024, Peoples R China
2.Chinese Acad Sci, Inst Oceanol, Key Lab Marine Environm Corros & Biofouling, Qingdao, Peoples R China
3.Beijing Univ Civil Engn & Architecture, Sch Environm & Energy Engn, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Xu, Kaixin,Sun, Wen,Wang, Lida,et al. Global sensitivity analysis of influence parameters in pitting corrosion behavior of 304 stainless steel using adaptive neuro-fuzzy inference systems[J]. MATERIALS AND CORROSION-WERKSTOFFE UND KORROSION,2020:11.
APA Xu, Kaixin.,Sun, Wen.,Wang, Lida.,Yang, Zhengqing.,Wang, Jing.,...&Liu, Guichanng.(2020).Global sensitivity analysis of influence parameters in pitting corrosion behavior of 304 stainless steel using adaptive neuro-fuzzy inference systems.MATERIALS AND CORROSION-WERKSTOFFE UND KORROSION,11.
MLA Xu, Kaixin,et al."Global sensitivity analysis of influence parameters in pitting corrosion behavior of 304 stainless steel using adaptive neuro-fuzzy inference systems".MATERIALS AND CORROSION-WERKSTOFFE UND KORROSION (2020):11.
Files in This Item:
File Name/Size DocType Version Access License
maco.202012120.pdf(2856KB)期刊论文出版稿延迟开放CC BY-NC-SAView 2023-7-1后可获取
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Xu, Kaixin]'s Articles
[Sun, Wen]'s Articles
[Wang, Lida]'s Articles
Baidu academic
Similar articles in Baidu academic
[Xu, Kaixin]'s Articles
[Sun, Wen]'s Articles
[Wang, Lida]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Xu, Kaixin]'s Articles
[Sun, Wen]'s Articles
[Wang, Lida]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: maco.202012120.pdf
Format: Adobe PDF
This file does not support browsing at this time
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.