Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/128167
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dc.contributor.authorZhang, C.en
dc.contributor.authorZecchin, A.en
dc.contributor.authorLambert, M.en
dc.contributor.authorGong, J.en
dc.contributor.authorSimpson, A.en
dc.date.issued2018en
dc.identifier.citationJournal of Hydroinformatics, 2018; 20(2):281-300en
dc.identifier.issn1464-7141en
dc.identifier.issn1465-1734en
dc.identifier.urihttp://hdl.handle.net/2440/128167-
dc.description.abstractFault detection in water distribution systems is of critical importance for water authorities to maintain pipeline assets effectively. This paper develops an improved inverse transient analysis (ITA) method for the condition assessment of water transmission pipelines. For long transmission pipelines ITA approaches involve models using hundreds of discretized pipe reaches (therefore hundreds of model parameters). As such, these methods struggle to accurately and uniquely determine the many parameter values, despite achieving a very good fit between the model predictions and measured pressure responses. In order to improve the parameter estimation accuracy of ITA applied to these high dimensional problems, a multi-stage parameter-constraining ITA approach for pipeline condition assessment is proposed. The proposed algorithm involves the staged constraining of the parameter search-space to focus the inverse analysis on pipeline sections that have a higher likelihood of being in an anomalous state. The proposed method is verified by numerical simulations, where the results confirm that the parameters estimated by the proposed method are more accurate than the conventional ITA. The proposed method is also verified by a field case study. Results show that anomalies detected by the proposed methods are generally consistent with anomalies detected by ultrasonic measurement of pipe wall thickness.en
dc.description.statementofresponsibilityChi Zhang, Aaron C. Zecchin, Martin F. Lambert, Jinzhe Gong and Angus R. Simpsonen
dc.language.isoenen
dc.publisherIWA Publishingen
dc.rights© IWA Publishing 2018en
dc.subjectCondition assessment; identifiability; inverse transient analysis; water pipelinesen
dc.titleMulti-stage parameter-constraining inverse transient analysis for pipeline condition assessmenten
dc.typeJournal articleen
dc.identifier.rmid0030085805en
dc.identifier.doi10.2166/hydro.2018.154en
dc.relation.granthttp://purl.org/au-research/grants/arc/DP140100994en
dc.relation.granthttp://purl.org/au-research/grants/arc/LP130100567en
dc.identifier.pubid405774-
pubs.library.collectionCivil and Environmental Engineering publicationsen
pubs.library.teamDS14en
pubs.verification-statusVerifieden
pubs.publication-statusPublisheden
dc.identifier.orcidZecchin, A. [0000-0001-8908-7023]en
dc.identifier.orcidLambert, M. [0000-0001-8272-6697]en
dc.identifier.orcidGong, J. [0000-0002-6344-5993]en
dc.identifier.orcidSimpson, A. [0000-0003-1633-0111]en
Appears in Collections:Civil and Environmental Engineering publications

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