Water Distribution System Design to Minimize Costs and Maximize Topological and Hydraulic Reliability
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jung, Donghwi | - |
dc.contributor.author | Kim, Joong Hoon | - |
dc.date.accessioned | 2021-09-02T07:23:39Z | - |
dc.date.available | 2021-09-02T07:23:39Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2018-09 | - |
dc.identifier.issn | 0733-9496 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/73628 | - |
dc.description.abstract | Many surrogate measures for water distribution system (WDS) reliability have been introduced in the last three decades. This study investigated the differences between designs based on topological and hydraulic reliabilities. The former considers network structural redundancy and connectivity, whereas the latter considers system performance under uncertain future conditions. Two topological reliabilities are proposed based on the network theory: the average node degree ratio (ANDr) and meshedness coefficient ratio (MCr). The capacity reliability and robustness are classified as hydraulic reliability. The Pareto optimal pipe sizes and configuration were found for a real medium-size grid-type network to minimize the total cost and maximize ANDr, MCr, capacity reliability, and robustness individually. The nondominated sorting genetic algorithm II was used for the optimization, and the uncertainty of the nodal pressures was quantified using the first-order second-moment approximation method. The results were compared in terms of the configuration, pipe sizes, and four reliability values to develop guidelines on selecting a reliability metric for WDS design. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ASCE-AMER SOC CIVIL ENGINEERS | - |
dc.subject | DISTRIBUTION NETWORKS | - |
dc.subject | GENETIC ALGORITHM | - |
dc.subject | OPTIMIZATION | - |
dc.subject | UNCERTAINTY | - |
dc.subject | ENTROPY | - |
dc.subject | MODELS | - |
dc.title | Water Distribution System Design to Minimize Costs and Maximize Topological and Hydraulic Reliability | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Jung, Donghwi | - |
dc.contributor.affiliatedAuthor | Kim, Joong Hoon | - |
dc.identifier.doi | 10.1061/(ASCE)WR.1943-5452.0000975 | - |
dc.identifier.scopusid | 2-s2.0-85048854621 | - |
dc.identifier.wosid | 000438018100010 | - |
dc.identifier.bibliographicCitation | JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, v.144, no.9 | - |
dc.relation.isPartOf | JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT | - |
dc.citation.title | JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT | - |
dc.citation.volume | 144 | - |
dc.citation.number | 9 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Water Resources | - |
dc.relation.journalWebOfScienceCategory | Engineering, Civil | - |
dc.relation.journalWebOfScienceCategory | Water Resources | - |
dc.subject.keywordPlus | DISTRIBUTION NETWORKS | - |
dc.subject.keywordPlus | GENETIC ALGORITHM | - |
dc.subject.keywordPlus | OPTIMIZATION | - |
dc.subject.keywordPlus | UNCERTAINTY | - |
dc.subject.keywordPlus | ENTROPY | - |
dc.subject.keywordPlus | MODELS | - |
dc.subject.keywordAuthor | Reliability | - |
dc.subject.keywordAuthor | Robustness | - |
dc.subject.keywordAuthor | Average node degree | - |
dc.subject.keywordAuthor | Meshedness coefficient | - |
dc.subject.keywordAuthor | Multiobjective optimization | - |
dc.subject.keywordAuthor | Pipe sizing and layout optimization | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.