Maintenance Cost Estimation in PSCI Girder Bridges Using Updating Probabilistic Deterioration Model
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Jin Hyuk | - |
dc.contributor.author | Choi, Yangrok | - |
dc.contributor.author | Ann, Hojune | - |
dc.contributor.author | Jin, Sung Yeol | - |
dc.contributor.author | Lee, Seung-Jung | - |
dc.contributor.author | Kong, Jung Sik | - |
dc.date.accessioned | 2021-08-31T22:48:04Z | - |
dc.date.available | 2021-08-31T22:48:04Z | - |
dc.date.created | 2021-06-18 | - |
dc.date.issued | 2019-12 | - |
dc.identifier.issn | 2071-1050 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/61429 | - |
dc.description.abstract | A deterioration model plays an important role to predict the valid total maintenance cost for sustainable maintenance of bridges. In the current state-of-the-art, the deterioration model has regression parameters as a probabilistic process by an initially determined mean and standard deviation, called an existing model. However, the existing model has difficulty to predict maintenance costs accurately, because it cannot reflect an information based on structural damage at an operational stage. In this research, updating the probabilistic deterioration model is presented for the prediction of pre-stressed concrete I-type (PSCI) girder bridges using a particle filtering technique which is an advanced Bayesian updating method based on big data analysis. The method enables predicting maintenance cost fitted in the current structural status, which includes the recent information by inspection with bridge-monitoring. The method is adapted in the Mokdo Bridge which is currently being used for evaluating the efficiency of maintenance cost by effects on updated probabilistic values with two different scenarios. As the result, it is shown that the proposed method is effective in predicting maintenance costs. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.subject | PREDICTION | - |
dc.title | Maintenance Cost Estimation in PSCI Girder Bridges Using Updating Probabilistic Deterioration Model | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kong, Jung Sik | - |
dc.identifier.doi | 10.3390/su11236593 | - |
dc.identifier.scopusid | 2-s2.0-85076571646 | - |
dc.identifier.wosid | 000508186400065 | - |
dc.identifier.bibliographicCitation | SUSTAINABILITY, v.11, no.23 | - |
dc.relation.isPartOf | SUSTAINABILITY | - |
dc.citation.title | SUSTAINABILITY | - |
dc.citation.volume | 11 | - |
dc.citation.number | 23 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
dc.relation.journalWebOfScienceCategory | Green & Sustainable Science & Technology | - |
dc.relation.journalWebOfScienceCategory | Environmental Sciences | - |
dc.relation.journalWebOfScienceCategory | Environmental Studies | - |
dc.subject.keywordPlus | PREDICTION | - |
dc.subject.keywordAuthor | deterioration model | - |
dc.subject.keywordAuthor | maintenance cost | - |
dc.subject.keywordAuthor | sustainable maintenance | - |
dc.subject.keywordAuthor | particle filtering | - |
dc.subject.keywordAuthor | bridge-monitoring | - |
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.