基于条件生成对抗网络的双相奥氏体不锈钢焊缝裂纹萌生预测方法

IF 7.4 1区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Yule Wu, Jiamei Wang, Xianglong Guo, Lefu Zhang
{"title":"基于条件生成对抗网络的双相奥氏体不锈钢焊缝裂纹萌生预测方法","authors":"Yule Wu,&nbsp;Jiamei Wang,&nbsp;Xianglong Guo,&nbsp;Lefu Zhang","doi":"10.1016/j.corsci.2024.112494","DOIUrl":null,"url":null,"abstract":"<div><div>A novel integration approach of a conditional generative adversarial network (cGAN) with an improved electro-chemo-mechanical (E−C−M) model was developed to calculate the localised electrochemistry and evaluate the stress corrosion cracking (SCC) crack initiation properties in high-temperature water. The results demonstrate the superior accuracy, computational efficiency and robust generalisation capabilities of the hybrid method. High-temperature electrochemical tests were conducted to validate and optimize the E−C−M model for calculating the stress induced corrosion behavior of austenite stainless steel (ASS) in high-temperature water. The SCC initiation test results corroborate the predicted corrosion current distribution on ASS with a dual-phase structure.</div></div>","PeriodicalId":290,"journal":{"name":"Corrosion Science","volume":"240 ","pages":"Article 112494"},"PeriodicalIF":7.4000,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Conditional generative adversarial network-based predictive method for crack initiation in a dual-phase austenite stainless weld\",\"authors\":\"Yule Wu,&nbsp;Jiamei Wang,&nbsp;Xianglong Guo,&nbsp;Lefu Zhang\",\"doi\":\"10.1016/j.corsci.2024.112494\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>A novel integration approach of a conditional generative adversarial network (cGAN) with an improved electro-chemo-mechanical (E−C−M) model was developed to calculate the localised electrochemistry and evaluate the stress corrosion cracking (SCC) crack initiation properties in high-temperature water. The results demonstrate the superior accuracy, computational efficiency and robust generalisation capabilities of the hybrid method. High-temperature electrochemical tests were conducted to validate and optimize the E−C−M model for calculating the stress induced corrosion behavior of austenite stainless steel (ASS) in high-temperature water. The SCC initiation test results corroborate the predicted corrosion current distribution on ASS with a dual-phase structure.</div></div>\",\"PeriodicalId\":290,\"journal\":{\"name\":\"Corrosion Science\",\"volume\":\"240 \",\"pages\":\"Article 112494\"},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2024-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Corrosion Science\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0010938X24006899\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATERIALS SCIENCE, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Corrosion Science","FirstCategoryId":"88","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0010938X24006899","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

摘要

研究人员开发了一种新颖的条件生成对抗网络(cGAN)与改进的电化学-机械(E-C-M)模型的集成方法,用于计算高温水中的局部电化学并评估应力腐蚀开裂(SCC)的裂纹起始特性。结果表明混合方法具有卓越的准确性、计算效率和强大的概括能力。为了验证和优化用于计算高温水中奥氏体不锈钢(ASS)应力诱导腐蚀行为的 E-C-M 模型,进行了高温电化学测试。SCC 引发试验结果证实了具有双相结构的 ASS 上预测的腐蚀电流分布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Conditional generative adversarial network-based predictive method for crack initiation in a dual-phase austenite stainless weld
A novel integration approach of a conditional generative adversarial network (cGAN) with an improved electro-chemo-mechanical (E−C−M) model was developed to calculate the localised electrochemistry and evaluate the stress corrosion cracking (SCC) crack initiation properties in high-temperature water. The results demonstrate the superior accuracy, computational efficiency and robust generalisation capabilities of the hybrid method. High-temperature electrochemical tests were conducted to validate and optimize the E−C−M model for calculating the stress induced corrosion behavior of austenite stainless steel (ASS) in high-temperature water. The SCC initiation test results corroborate the predicted corrosion current distribution on ASS with a dual-phase structure.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Corrosion Science
Corrosion Science 工程技术-材料科学:综合
CiteScore
13.60
自引率
18.10%
发文量
763
审稿时长
46 days
期刊介绍: Corrosion occurrence and its practical control encompass a vast array of scientific knowledge. Corrosion Science endeavors to serve as the conduit for the exchange of ideas, developments, and research across all facets of this field, encompassing both metallic and non-metallic corrosion. The scope of this international journal is broad and inclusive. Published papers span from highly theoretical inquiries to essentially practical applications, covering diverse areas such as high-temperature oxidation, passivity, anodic oxidation, biochemical corrosion, stress corrosion cracking, and corrosion control mechanisms and methodologies. This journal publishes original papers and critical reviews across the spectrum of pure and applied corrosion, material degradation, and surface science and engineering. It serves as a crucial link connecting metallurgists, materials scientists, and researchers investigating corrosion and degradation phenomena. Join us in advancing knowledge and understanding in the vital field of corrosion science.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信