Bayesian Inverse Transient Analysis for Pipeline Condition Assessment: Parameter Estimation and Uncertainty Quantification
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posted on 2024-09-06, 05:33 authored by C Zhang, MF Lambert, James GongJames Gong, AC Zecchin, AR Simpson, ML StephensBayesian Inverse Transient Analysis for Pipeline Condition Assessment: Parameter Estimation and Uncertainty Quantification
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Dordrecht, The NetherlandsOpen access
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This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://dx.doi.org/10.1007/s11269-020-02582-9Language
EnglishPublication classification
C1 Refereed article in a scholarly journalJournal
Water Resources ManagementVolume
34Pagination
2807-2820ISSN
0920-4741eISSN
1573-1650Issue
9Publisher
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CALIBRATIONDIFFERENTIAL EVOLUTIONEngineeringEngineering, CivilEXPERIMENTAL-VERIFICATIONHydraulic transientInverse transient analysisLEAK DETECTIONMarkov chain Monte CarloMONTE-CARLO-SIMULATIONPhysical SciencesPipeline condition assessmentScience & TechnologyTechnologyUncertainty assessmentWATERWater ResourcesMD Multidisciplinary4005 Civil engineering4015 Maritime engineering
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