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dc.contributor.authorWilhelmsen, Nils Christian Aars
dc.contributor.authorAamo, Ole Morten
dc.date.accessioned2024-06-07T11:50:59Z
dc.date.available2024-06-07T11:50:59Z
dc.date.created2024-01-15T16:36:31Z
dc.date.issued2023
dc.identifier.citationIEEE Conference on Decision and Control. Proceedings. 2023, 5208-5215.en_US
dc.identifier.issn0743-1546
dc.identifier.urihttps://hdl.handle.net/11250/3133106
dc.description.abstractA recursive procedure to obtain explicit expressions to a set of observer backstepping kernel equations for an interconnection (cascade) of N+1 systems of 2×2 linear hyperbolic PDEs, N>0 an integer, for use in leak detection in pipe flow networks containing loops is developed. The kernel equations, consisting of two sets each of N+1 pairs of Goursat PDEs defined over a triangular domain, and N(N+1)2 pairs of Goursat PDEs defined over a square domain, interconnected to each other in an overarching triangular structure, is separated into 2(N+1) systems consisting of k+1 pairs of PDEs over a triangular domain interconnected with (N−k2)(k+1) pairs of PDEs over a square domain, k∈{0,1,…,N} . Under the assumption that the mean friction factor of the network may be used in place of individual friction factors for each pipe, it is shown that the solution to each of the simplified kernel equation systems is expressed explicitly in terms of modified Bessel functions of the first kind, and may be constructed recursively. A numerical example is provided to illustrate the results.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleExplicit Backstepping Kernel Solutions for Leak Detection in Pipe Flow Networks Containing Loopsen_US
dc.title.alternativeExplicit Backstepping Kernel Solutions for Leak Detection in Pipe Flow Networks Containing Loopsen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© Copyright 2023 IEEE - All rights reserved.en_US
dc.source.pagenumber5208-5215en_US
dc.source.journalIEEE Conference on Decision and Control. Proceedingsen_US
dc.identifier.doi10.1109/CDC49753.2023.10383406
dc.identifier.cristin2227065
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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