基于人工神经网络的饮用水钢管点蚀影响因素分析

IF 1.6 3区环境科学与生态学 Q3 WATER RESOURCES

Urban Water Journal Pub Date : 2023-04-03 DOI:10.1080/1573062X.2023.2198996

Kibum Kim, Heechang Kang, Taehyeon Kim, D. T. Iseley, Jaeho Choi, J. Koo

{"title":"基于人工神经网络的饮用水钢管点蚀影响因素分析","authors":"Kibum Kim, Heechang Kang, Taehyeon Kim, D. T. Iseley, Jaeho Choi, J. Koo","doi":"10.1080/1573062X.2023.2198996","DOIUrl":null,"url":null,"abstract":"ABSTRACT Steel is a metal, and thus, it undergoes corrosion over time. The comprehensive analysis of the factors influencing corrosion can aid in developing strategies, such as new ways to avoid corrosive environments. This study explored the factors influencing pitting corrosion in steel water pipes in South Korea between 1988–2020, using artificial neural networks. Partial dependence plots and variable importance are used to identify the degree of influence of the 12 corrosion-influencing factors. Pipe age had the highest importance and strongest influence on corrosion among the corrosion-influencing factors. Soil resistivity strongly influenced external corrosion, especially at values less than 5,000 Ω-cm, and the influence of sulfide concentration on external corrosion was also relatively strong. Water alkalinity exhibited the strongest influence on internal corrosion. This study will serve as reference data for developing corrosion depth prediction models and will contribute to understanding corrosive environments when laying new pipelines and improving existing ones.","PeriodicalId":49392,"journal":{"name":"Urban Water Journal","volume":"20 1","pages":"550 - 563"},"PeriodicalIF":1.6000,"publicationDate":"2023-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Influencing factors analysis for drinking water steel pipe pitting corrosion using artificial neural network\",\"authors\":\"Kibum Kim, Heechang Kang, Taehyeon Kim, D. T. Iseley, Jaeho Choi, J. Koo\",\"doi\":\"10.1080/1573062X.2023.2198996\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Steel is a metal, and thus, it undergoes corrosion over time. The comprehensive analysis of the factors influencing corrosion can aid in developing strategies, such as new ways to avoid corrosive environments. This study explored the factors influencing pitting corrosion in steel water pipes in South Korea between 1988–2020, using artificial neural networks. Partial dependence plots and variable importance are used to identify the degree of influence of the 12 corrosion-influencing factors. Pipe age had the highest importance and strongest influence on corrosion among the corrosion-influencing factors. Soil resistivity strongly influenced external corrosion, especially at values less than 5,000 Ω-cm, and the influence of sulfide concentration on external corrosion was also relatively strong. Water alkalinity exhibited the strongest influence on internal corrosion. This study will serve as reference data for developing corrosion depth prediction models and will contribute to understanding corrosive environments when laying new pipelines and improving existing ones.\",\"PeriodicalId\":49392,\"journal\":{\"name\":\"Urban Water Journal\",\"volume\":\"20 1\",\"pages\":\"550 - 563\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Urban Water Journal\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1080/1573062X.2023.2198996\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"WATER RESOURCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Urban Water Journal","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1080/1573062X.2023.2198996","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"WATER RESOURCES","Score":null,"Total":0}

引用次数: 0

摘要

摘要：钢是一种金属，因此，它会随着时间的推移而发生腐蚀。全面分析影响腐蚀的因素有助于制定策略，例如避免腐蚀环境的新方法。本研究利用人工神经网络探讨了1988年至2020年间韩国钢管点蚀的影响因素。使用部分依赖图和变量重要性来确定12个腐蚀影响因素的影响程度。在腐蚀影响因素中，管龄的重要性最高，对腐蚀的影响最强。土壤电阻率对外部腐蚀有很大影响，尤其是在小于5000Ω-cm的情况下，硫化物浓度对外部腐蚀的影响也相对较强。水的碱度对内腐蚀的影响最大。这项研究将作为开发腐蚀深度预测模型的参考数据，并有助于在铺设新管道和改进现有管道时了解腐蚀环境。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Influencing factors analysis for drinking water steel pipe pitting corrosion using artificial neural network

ABSTRACT Steel is a metal, and thus, it undergoes corrosion over time. The comprehensive analysis of the factors influencing corrosion can aid in developing strategies, such as new ways to avoid corrosive environments. This study explored the factors influencing pitting corrosion in steel water pipes in South Korea between 1988–2020, using artificial neural networks. Partial dependence plots and variable importance are used to identify the degree of influence of the 12 corrosion-influencing factors. Pipe age had the highest importance and strongest influence on corrosion among the corrosion-influencing factors. Soil resistivity strongly influenced external corrosion, especially at values less than 5,000 Ω-cm, and the influence of sulfide concentration on external corrosion was also relatively strong. Water alkalinity exhibited the strongest influence on internal corrosion. This study will serve as reference data for developing corrosion depth prediction models and will contribute to understanding corrosive environments when laying new pipelines and improving existing ones.

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

Urban Water Journal WATER RESOURCES-

CiteScore

4.40

自引率

11.10%

发文量

101

审稿时长

3 months

期刊介绍： Urban Water Journal provides a forum for the research and professional communities dealing with water systems in the urban environment, directly contributing to the furtherance of sustainable development. Particular emphasis is placed on the analysis of interrelationships and interactions between the individual water systems, urban water bodies and the wider environment. The Journal encourages the adoption of an integrated approach, and system''s thinking to solve the numerous problems associated with sustainable urban water management. Urban Water Journal focuses on the water-related infrastructure in the city: namely potable water supply, treatment and distribution; wastewater collection, treatment and management, and environmental return; storm drainage and urban flood management. Specific topics of interest include: network design, optimisation, management, operation and rehabilitation; novel treatment processes for water and wastewater, resource recovery, treatment plant design and optimisation as well as treatment plants as part of the integrated urban water system; demand management and water efficiency, water recycling and source control; stormwater management, urban flood risk quantification and management; monitoring, utilisation and management of urban water bodies including groundwater; water-sensitive planning and design (including analysis of interactions of the urban water cycle with city planning and green infrastructure); resilience of the urban water system, long term scenarios to manage uncertainty, system stress testing; data needs, smart metering and sensors, advanced data analytics for knowledge discovery, quantification and management of uncertainty, smart technologies for urban water systems; decision-support and informatic tools;...