Integrating computer vision techniques with finite element phase field damage analysis

dc.contributorAalto-yliopistofi
dc.contributorAalto Universityen
dc.contributor.authorZhang, Youqi
dc.contributor.authorNiiranen, Jarkko
dc.contributor.departmentDepartment of Civil Engineeringen
dc.contributor.groupauthorPerformance in Building Design and Constructionen
dc.contributor.groupauthorStructures – Structural Engineering, Mechanics and Computationen
dc.date.accessioned2025-05-14T08:41:11Z
dc.date.available2025-05-14T08:41:11Z
dc.date.issued2025-08
dc.descriptionPublisher Copyright: © 2025 The Author(s)
dc.description.abstractRealistic and accurate finite element (FE) models are crucial for understanding and predicting the health, performance, and safety of deteriorated structures. Accordingly, this paper presents a novel approach that integrates computer vision techniques and a phase field method to enhance FE damage analyses. Computer vision techniques are employed to analyze the visual inspection or monitoring data and to extract the geometric features of a structure and its damage, while the phase field method provides a robust numerical solution for representing the damage and simulating its progression. The integration of these methods allows for automated and precise updates of damage information in the FE model, improving model accuracy and reducing manual intervention. Case studies on a paper board and a steel cross beam of a bridge demonstrate the applicability and effectiveness of the proposed approach, highlighting its feasibility for monitoring and assessment in real-world engineering applications.en
dc.description.versionPeer revieweden
dc.format.extent12
dc.format.mimetypeapplication/pdf
dc.identifier.citationZhang, Y & Niiranen, J 2025, 'Integrating computer vision techniques with finite element phase field damage analysis', Computers & Structures, vol. 315, 107793. https://doi.org/10.1016/j.compstruc.2025.107793en
dc.identifier.doi10.1016/j.compstruc.2025.107793
dc.identifier.issn0045-7949
dc.identifier.issn1879-2243
dc.identifier.otherPURE UUID: cff2de49-d016-491f-8571-1f60652d1486
dc.identifier.otherPURE ITEMURL: https://research.aalto.fi/en/publications/cff2de49-d016-491f-8571-1f60652d1486
dc.identifier.otherPURE FILEURL: https://research.aalto.fi/files/181348385/1-s2.0-S0045794925001518-main.pdf
dc.identifier.urihttps://aaltodoc.aalto.fi/handle/123456789/135393
dc.identifier.urnURN:NBN:fi:aalto-202505143667
dc.language.isoenen
dc.publisherElsevier
dc.relation.ispartofseriesComputers & Structuresen
dc.relation.ispartofseriesVolume 315en
dc.rightsopenAccessen
dc.rightsCC BY
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.keywordComputer vision
dc.subject.keywordDamage update
dc.subject.keywordDigital twin
dc.subject.keywordFinite element analysis
dc.subject.keywordPhase field method
dc.titleIntegrating computer vision techniques with finite element phase field damage analysisen
dc.typeA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessäfi
dc.type.versionpublishedVersion

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
1-s2.0-S0045794925001518-main.pdf
Size:
6.76 MB
Format:
Adobe Portable Document Format