可持续城市供水系统管道风险指数的三维建模

T. Dawood, E. Elwakil, H. Novoa, J. Delgado
{"title":"可持续城市供水系统管道风险指数的三维建模","authors":"T. Dawood, E. Elwakil, H. Novoa, J. Delgado","doi":"10.1109/SusTech51236.2021.9467435","DOIUrl":null,"url":null,"abstract":"The risk assessment and modeling of watermains are complicated tasks, which are proportional to the intricacy of underground water networks. These networks are known to be nonlinear, dynamic, and involve a multitude of influential factors that cannot be measured accurately in any conventional metrics. In general, deterioration factors obtained from field inspections reports or from experts’ survey have certain degrees of ambiguity and subjectivity. One of the potent methods that have emerged in the last four decades to solve civil infrastructure problems, is the fuzzy inference system (FIS). This method can encode the deterioration factors into risk indices while coping with the inaccuracy, ambiguity, and fuzziness of data. The objective of this paper is to develop a risk index model for water transmission pipes based on simulation and FIS. First, the input and output datasets of the proposed model are defined based on inspection reports and experts’ questionnaire; both the input and output datasets are fed into the FIS engine. Second, the fuzzy logic control engine is designed by defining the membership functions and the rules in the fuzzy operator. The third step includes","PeriodicalId":127126,"journal":{"name":"2021 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"3D Modeling of Pipe Risk Index for a Sustainable Urban Water System\",\"authors\":\"T. Dawood, E. Elwakil, H. Novoa, J. Delgado\",\"doi\":\"10.1109/SusTech51236.2021.9467435\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The risk assessment and modeling of watermains are complicated tasks, which are proportional to the intricacy of underground water networks. These networks are known to be nonlinear, dynamic, and involve a multitude of influential factors that cannot be measured accurately in any conventional metrics. In general, deterioration factors obtained from field inspections reports or from experts’ survey have certain degrees of ambiguity and subjectivity. One of the potent methods that have emerged in the last four decades to solve civil infrastructure problems, is the fuzzy inference system (FIS). This method can encode the deterioration factors into risk indices while coping with the inaccuracy, ambiguity, and fuzziness of data. The objective of this paper is to develop a risk index model for water transmission pipes based on simulation and FIS. First, the input and output datasets of the proposed model are defined based on inspection reports and experts’ questionnaire; both the input and output datasets are fed into the FIS engine. Second, the fuzzy logic control engine is designed by defining the membership functions and the rules in the fuzzy operator. The third step includes\",\"PeriodicalId\":127126,\"journal\":{\"name\":\"2021 IEEE Conference on Technologies for Sustainability (SusTech)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE Conference on Technologies for Sustainability (SusTech)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SusTech51236.2021.9467435\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Conference on Technologies for Sustainability (SusTech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SusTech51236.2021.9467435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

管网风险评估与建模是一项复杂的任务,与地下水网的复杂性成正比。众所周知,这些网络是非线性的、动态的,并且涉及许多无法用任何常规指标精确测量的影响因素。一般来说,从实地考察报告或专家调查中获得的劣化因素具有一定程度的模糊性和主观性。模糊推理系统(FIS)是近四十年来出现的解决民用基础设施问题的有效方法之一。该方法在处理数据的不准确性、模糊性和模糊性的同时,可以将恶化因素编码为风险指标。本文的目的是建立一个基于仿真和FIS的输水管道风险指数模型。首先,根据检测报告和专家问卷定义模型的输入和输出数据集;输入和输出数据集都被输入到FIS引擎中。其次,通过定义模糊算子中的隶属函数和规则,设计了模糊逻辑控制引擎;第三步包括
本文章由计算机程序翻译,如有差异,请以英文原文为准。
3D Modeling of Pipe Risk Index for a Sustainable Urban Water System
The risk assessment and modeling of watermains are complicated tasks, which are proportional to the intricacy of underground water networks. These networks are known to be nonlinear, dynamic, and involve a multitude of influential factors that cannot be measured accurately in any conventional metrics. In general, deterioration factors obtained from field inspections reports or from experts’ survey have certain degrees of ambiguity and subjectivity. One of the potent methods that have emerged in the last four decades to solve civil infrastructure problems, is the fuzzy inference system (FIS). This method can encode the deterioration factors into risk indices while coping with the inaccuracy, ambiguity, and fuzziness of data. The objective of this paper is to develop a risk index model for water transmission pipes based on simulation and FIS. First, the input and output datasets of the proposed model are defined based on inspection reports and experts’ questionnaire; both the input and output datasets are fed into the FIS engine. Second, the fuzzy logic control engine is designed by defining the membership functions and the rules in the fuzzy operator. The third step includes
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
自引率
0.00%
发文量
0
×
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