dc.contributor.author | Olufsen, Sindre Nordmark | |
dc.contributor.author | Andersen, Marius Endre | |
dc.contributor.author | Fagerholt, Egil | |
dc.date.accessioned | 2020-09-14T13:44:20Z | |
dc.date.available | 2020-09-14T13:44:20Z | |
dc.date.created | 2020-01-01T12:09:19Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 2352-7110 | |
dc.identifier.uri | https://hdl.handle.net/11250/2677753 | |
dc.description.abstract | We 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.iso | eng | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | μDIC: An open-source toolkit for digital image correlation | en_US |
dc.type | Peer reviewed | en_US |
dc.type | Journal article | en_US |
dc.description.version | publishedVersion | en_US |
dc.source.volume | 11 | en_US |
dc.source.journal | SoftwareX | en_US |
dc.identifier.doi | 10.1016/j.softx.2019.100391 | |
dc.identifier.cristin | 1764664 | |
dc.relation.project | Norges forskningsråd: 237885 | en_US |
dc.description.localcode | © 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 |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 1 | |