Faster inverse transient analysis with a head-based method of characteristics and a flexible computational grid for pipeline condition assessment Zhang, Chi, Gong, Jinzhe, Zecchin, Aaron, Lambert, Martin and Simpson, Angus 2018, Faster inverse transient analysis with a head-based method of characteristics and a flexible computational grid for pipeline condition assessment, Journal of hydraulic engineering, vol. 144, no. 4, pp. 1-12, doi: 10.1061/(ASCE)HY.1943-7900.0001438. Attached Files Name Description MIMEType Size Downloads Title Faster inverse transient analysis with a head-based method of characteristics and a flexible computational grid for pipeline condition assessment Author(s) Zhang, Chi Gong, Jinzhe orcid.org/0000-0002-6344-5993 Zecchin, Aaron Lambert, Martin Simpson, Angus Journal name Journal of hydraulic engineering Volume number 144 Issue number 4 Article ID 04018007 Start page 1 End page 12 Total pages 12 Publisher American Society of Civil Engineers Place of publication Reston, Va. Publication date 2018-04 ISSN 0733-9429 1943-7900 Keyword(s) Pipelines Fluid transient Inverse transient analysis Deterioration Transient modeling Flexible grid Science & Technology Technology Physical Sciences Engineering, Civil Engineering, Mechanical Water Resources Engineering Language eng DOI 10.1061/(ASCE)HY.1943-7900.0001438 Indigenous content off Field of Research 0905 Civil Engineering HERDC Research category C1.1 Refereed article in a scholarly journal ERA Research output type C Journal article Copyright notice ©2018, American Society of Civil Engineers Persistent URL http://hdl.handle.net/10536/DRO/DU:30123828 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment School of Engineering Related Links Link Description Connect to published version Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Thu, 27 Jun 2019, 15:52:22 EST Fri, 28 Jun 2019, 05:00:50 EST Fri, 28 Jun 2019, 08:08:24 EST Mon, 12 Aug 2019, 15:26:04 EST Tue, 13 Aug 2019, 06:02:01 EST Thu, 15 Aug 2019, 16:05:24 EST Thu, 15 Aug 2019, 16:07:23 EST Wed, 02 Sep 2020, 11:39:48 EST Wed, 02 Sep 2020, 11:40:39 EST Filtered Full Citation counts:   Cited 10 times in TR Web of Science Cited 11 times in Scopus Search Google Scholar Access Statistics: 161 Abstract Views, 2 File Downloads  -  Detailed Statistics Created: Mon, 12 Aug 2019, 15:26:04 EST

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