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Tracking the shape deformation of voids from tensile loading by the use of computed tomography
Örebro University, School of Science and Technology.ORCID iD: 0000-0003-1286-3420
Örebro University, School of Science and Technology.ORCID iD: 0000-0003-1408-2249
Örebro University, School of Science and Technology.ORCID iD: 0000-0003-1655-0392
2015 (English)In: Digital Industrial Radiology and Computed Tomography (DIR 2015), 2015, 18034Conference paper, Published paper (Refereed)
Abstract [en]

The understanding of interaction between voids such as pores or holes in additive manufactured open structures is of importance in understanding the strength of components. Behavior in three dimensions is of particular interest. X-ray tomography is one of the few techniques that has the possibility to nondestructively aid in analyzing issues such as shape deformation. In this work, X-ray computed tomography was applied as a nondestructive tool for tracking the shape deformation of voids.

A simplified model representing three dimensional voids is used to investigate the effect of influential parameters like void size, their distance from each other and orientation of voids in respect to the uniaxial tensile load. A set of ex-situ X-ray micro tomography tensile test is performed on flat aluminum (6082-T6) tensile bars with drilled through holes representing different configuration of voids. Digital image correlation was used to measure the strain localization in the adjacent area of the holes. Corresponding Finite Element (FE) analysis is performed to predict the shape deformation and by this validate the model. This modelling may give a better insight of pores interaction under more complex loading scenarios and leads to better controllability of internal structure design of additive manufactured (AM) parts.

Place, publisher, year, edition, pages
2015. 18034
Keyword [en]
Defect, X-Ray computed tomography, Digital image correlation, shape deformation
National Category
Other Mechanical Engineering
Research subject
Mechanical Engineering
Identifiers
URN: urn:nbn:se:oru:diva-55204OAI: oai:DiVA.org:oru-55204DiVA: diva2:1070718
Conference
Digital Industrial Radiology and Computed Tomography (DIR 2015), Ghent, Belgium, June 22-25, 2015
Available from: 2017-02-02 Created: 2017-02-02 Last updated: 2017-10-18Bibliographically approved

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Zekavat, Amir RezaPejryd, LarsEkengren, Jens
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CiteExportLink to record
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