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Article: Framework development of performance prediction models for concrete bridges

TitleFramework development of performance prediction models for concrete bridges
Authors
KeywordsBest management practice
Bridge maintenance
Bridges, concrete
Markov process
Predictions
Issue Date2009
PublisherAmerican Society of Civil Engineers. The Journal's web site is located at http://www.pubs.asce.org/journals/te.html
Citation
Journal Of Transportation Engineering, 2009, v. 135 n. 8, p. 545-554 How to Cite?
AbstractSound performance prediction models are essential for maintenance decision making in bridge management systems (BMSs). Markov chain models have been extensively used for performance prediction in BMSs. However, these models have some limitations, for example, being previously based on constant inspection time intervals and/or on the Markov property assumption. Furthermore, these models do not make reference to the region-specific nature of the available condition data that may affect their effectiveness and applicability. This paper identifies some limitations of the Markov performance prediction models used in many state-of-the-art BMSs and proposes a framework that can address these limitations. The developed framework incorporates the semi-Markov approach in addition to the widely used Markov chain modeling. This combined approach is expected to improve the effectiveness and applicability of performance prediction models. © 2009 ASCE.
Persistent Identifierhttp://hdl.handle.net/10722/71129
ISSN
2015 Impact Factor: 0.801
2015 SCImago Journal Rankings: 0.627
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYang, YNen_HK
dc.contributor.authorPam, HJen_HK
dc.contributor.authorKumaraswamy, MMen_HK
dc.date.accessioned2010-09-06T06:29:10Z-
dc.date.available2010-09-06T06:29:10Z-
dc.date.issued2009en_HK
dc.identifier.citationJournal Of Transportation Engineering, 2009, v. 135 n. 8, p. 545-554en_HK
dc.identifier.issn0733-947Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/71129-
dc.description.abstractSound performance prediction models are essential for maintenance decision making in bridge management systems (BMSs). Markov chain models have been extensively used for performance prediction in BMSs. However, these models have some limitations, for example, being previously based on constant inspection time intervals and/or on the Markov property assumption. Furthermore, these models do not make reference to the region-specific nature of the available condition data that may affect their effectiveness and applicability. This paper identifies some limitations of the Markov performance prediction models used in many state-of-the-art BMSs and proposes a framework that can address these limitations. The developed framework incorporates the semi-Markov approach in addition to the widely used Markov chain modeling. This combined approach is expected to improve the effectiveness and applicability of performance prediction models. © 2009 ASCE.en_HK
dc.languageengen_HK
dc.publisherAmerican Society of Civil Engineers. The Journal's web site is located at http://www.pubs.asce.org/journals/te.htmlen_HK
dc.relation.ispartofJournal of Transportation Engineeringen_HK
dc.rightsJournal of Transportation Engineering. Copyright © American Society of Civil Engineers.en_HK
dc.subjectBest management practiceen_HK
dc.subjectBridge maintenanceen_HK
dc.subjectBridges, concreteen_HK
dc.subjectMarkov processen_HK
dc.subjectPredictionsen_HK
dc.titleFramework development of performance prediction models for concrete bridgesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0733-947X&volume=135 No 8&spage=545&epage=554&date=2009&atitle=Framework+Development+of+Performance+Prediction+Models+for+Concrete+Bridgesen_HK
dc.identifier.emailPam, HJ:pamhoatjoen@hku.hken_HK
dc.identifier.emailKumaraswamy, MM:mohan@hkucc.hku.hken_HK
dc.identifier.authorityPam, HJ=rp00071en_HK
dc.identifier.authorityKumaraswamy, MM=rp00126en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1061/(ASCE)TE.1943-5436.0000018en_HK
dc.identifier.scopuseid_2-s2.0-68049084706en_HK
dc.identifier.hkuros164571en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-68049084706&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume135en_HK
dc.identifier.issue8en_HK
dc.identifier.spage545en_HK
dc.identifier.epage554en_HK
dc.identifier.isiWOS:000268067100006-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridYang, YN=35217441200en_HK
dc.identifier.scopusauthoridPam, HJ=6602976141en_HK
dc.identifier.scopusauthoridKumaraswamy, MM=35566270600en_HK
dc.identifier.citeulike5174923-

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