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dc.contributor.authorOlufsen, Sindre Nordmark
dc.contributor.authorAndersen, Marius Endre
dc.contributor.authorFagerholt, Egil
dc.date.accessioned2020-06-12T08:36:00Z
dc.date.available2020-06-12T08:36:00Z
dc.date.created2020-01-01T12:09:19Z
dc.date.issued2020
dc.identifier.issn2352-7110
dc.identifier.urihttps://hdl.handle.net/11250/2657842
dc.description.abstractWe here present a Digital Image Correlation toolkit, formulated as a Python package. This package aims at providing a complete toolkit for performing DIC analysis on experimental data, performing virtual experiments, as well as a framework for further development. A suite of tools for generating synthetic speckle images, modelling of sensor artefacts and deformation of images by displacement fields, are included. The virtual experiments are used as a part of the accuracy assessment of the toolkit as well as for testing during development. B-spline elements are employed for the discretisation of the displacement fields and allow the polynomial order and degree of continuity to be controlled by the user.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.subjectDigital Image Correlationen_US
dc.subjectB-splinesen_US
dc.subjectSpeckle image generationen_US
dc.subjectVirtual experimentsen_US
dc.subjectPythonen_US
dc.titleμDIC: An open-source toolkit for digital image correlationen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersionen_US
dc.rights.holder© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.source.volume11en_US
dc.source.journalSoftwareXen_US
dc.identifier.doi10.1016/j.softx.2019.100391
dc.identifier.cristin1764664
dc.relation.projectNorges forskningsråd: 237885en_US
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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