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dc.contributor.authorYe, Cong
dc.contributor.authorAcikgoz, M
dc.contributor.authorPendrigh, Stephen
dc.contributor.authorRiley, Ewan
dc.contributor.authorDe Jong, Matthew
dc.date.accessioned2018-11-26T13:58:35Z
dc.date.available2018-11-26T13:58:35Z
dc.date.issued2018-10-15
dc.identifier.issn0141-0296
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/285978
dc.description.abstractMany historic masonry arch bridges experience damage due to support movements during their lifetime. This damage may influence the performance of the bridge and reduce its load carrying capacity. This paper proposes a new method to quantify past support movements by investigating distortions in bridge geometry. In this method, the bridge geometry is recorded in point cloud format and segmented into different structural components (e.g. 3D piers and barrels or 2D pier and barrel cross-sections). The geometry of each component is investigated further withby fitting primitive shapes (e.g. 3D planes and cylinders or 2D lines and arcs) which represent the design intent. The discrepancy between these fitted shapes and the point clouds reveals a characteristic distortion signature. This signature is compared with theoretical distortion traces, which are obtained from kinematical analyses of the arch subjected to a range of support movements. The most likely support movement scenarios identified from these comparisons are then validated with visual indications of damage, such as crack location and size, and other geometric quantities, such as the change of the bedding joint elevations along the bridge. The proposed technique is applied to two masonry rail viaducts in the UK, which demonstrate different evidence of damage. Using the proposed method, past support movements of both bridges, which led to the observed damage, are inferred.
dc.languageeng
dc.publisherElsevier
dc.rightsAttribution 4.0 International
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectMasonry arch bridge
dc.subjectSupport movement
dc.subjectPoint clouds
dc.subjectPrimitive fitting
dc.titleMapping deformations and inferring movements of masonry arch bridges using point cloud data
dc.typeArticle
prism.endingPage545
prism.publicationDate2018
prism.publicationNameEngineering Structures
prism.startingPage530
prism.volume173
dc.identifier.doi10.17863/CAM.33303
dcterms.dateAccepted2018-06-25
rioxxterms.versionofrecord10.1016/j.engstruct.2018.06.094
rioxxterms.versionVoR
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/
rioxxterms.licenseref.startdate2018-10-15
dc.contributor.orcidYe, Cong [0000-0001-9106-1578]
dc.contributor.orcidDe Jong, Matthew [0000-0002-6195-839X]
dc.identifier.eissn1873-7323
dc.publisher.urlhttps://www.sciencedirect.com/science/article/pii/S0141029617338439?via=ihub#!
rioxxterms.typeJournal Article/Review
pubs.funder-project-idEngineering and Physical Sciences Research Council (EP/N021614/1)
pubs.funder-project-idTechnology Strategy Board (920035)
cam.issuedOnline2018-07-11
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S0141029617338439?via=ihub#!


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International