Safety-based multi-objective life-cycle management system for steel box girder bridges
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Kyung-Hoon | - |
dc.contributor.author | Lee, Sang-Yoon | - |
dc.contributor.author | Park, Cheolwoo | - |
dc.contributor.author | Cho, Hyo-Nam | - |
dc.contributor.author | Kong, Jung Sik | - |
dc.date.accessioned | 2021-09-06T10:52:02Z | - |
dc.date.available | 2021-09-06T10:52:02Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2012 | - |
dc.identifier.issn | 1573-2479 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/106270 | - |
dc.description.abstract | In many countries including Korea, a number of studies have been carried out to propose methods for managing the deterioration of bridges in order to obtain the optimum maintenance strategy associated with higher performance and lower cost. A number of computer-aided bridge management systems have been developed based on these methods. Bridge condition based on visual inspection was monitored and used as a threshold. Because of the limitation of visual inspection as a safety index, other safety related indexes such as a damage index or reliability index have been adopted while the bridge management system has evolved as a decision making tool equipped with the capability of generating the optimal maintenance scenario. However, most bridge management systems still have some restrictions in producing feasible solutions. Some important restrictions are related to the multi-objectives, cost-maintenance interaction and subordinate relation between bridge members. In this study, a new bridge management method is proposed and computer software based on this method has been developed to obtain the life-cycle optimum maintenance strategy for deteriorating steel box girder bridges. A multi-objective optimisation problem is formulated and the Genetic Algorithm is applied to obtain optimal tradeoff maintenance scenarios. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | TAYLOR & FRANCIS LTD | - |
dc.subject | DETERIORATING BRIDGES | - |
dc.subject | MAINTENANCE | - |
dc.subject | OPTIMIZATION | - |
dc.subject | RELIABILITY | - |
dc.title | Safety-based multi-objective life-cycle management system for steel box girder bridges | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kong, Jung Sik | - |
dc.identifier.doi | 10.1080/15732470903517983 | - |
dc.identifier.scopusid | 2-s2.0-84862972795 | - |
dc.identifier.wosid | 000302542000001 | - |
dc.identifier.bibliographicCitation | STRUCTURE AND INFRASTRUCTURE ENGINEERING, v.8, no.3, pp.211 - 225 | - |
dc.relation.isPartOf | STRUCTURE AND INFRASTRUCTURE ENGINEERING | - |
dc.citation.title | STRUCTURE AND INFRASTRUCTURE ENGINEERING | - |
dc.citation.volume | 8 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 211 | - |
dc.citation.endPage | 225 | - |
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.journalWebOfScienceCategory | Engineering, Civil | - |
dc.relation.journalWebOfScienceCategory | Engineering, Mechanical | - |
dc.subject.keywordPlus | DETERIORATING BRIDGES | - |
dc.subject.keywordPlus | MAINTENANCE | - |
dc.subject.keywordPlus | OPTIMIZATION | - |
dc.subject.keywordPlus | RELIABILITY | - |
dc.subject.keywordAuthor | bridge maintenance system | - |
dc.subject.keywordAuthor | life-cycle cost | - |
dc.subject.keywordAuthor | life-cycle performance | - |
dc.subject.keywordAuthor | multi-objective optimum maintenance problem | - |
dc.subject.keywordAuthor | deterioration | - |
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.