Master'sOpen Access

Investigation of mechanical behaviour of adhesively bonded joints via digital image correlation (DIC) technic

2018
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Advisor: Prof. Dr. Murat Demir Aydın

Abstract (EN)

Adhesively bonded joints are widely used as an alternative to traditional bonding methods because of the important advantages of adhesively bonded joints. However, using the bonded joints for structural purposes is possible with reliable and reproducible data of their mechanical behavior. In this study, mechanical behavior of structural adhesives were investigated by Digital Image Correlation technique. So, samples of bulk and joint form were produced from the selected two-part structural adhesive (DP410). First, these bulk (tensile, Iosipescu and Arcan) and joint (TAST) specimens were exposed to uniaxial tension and shear loads and the mechanical properties of the DP410 were determined by two different measurement methods (DIC and video extensometer). Then, the mechanical behaviors of the single lap joints (SLJ) exposed to uniaxial tension and four point bending loads, were investigated using the Digital Image Correlation technique and the nonlinear finite element method (SEY). When the results obtained from bulk specimens were compared, it was found that the DIC technique yielded reproducible results in the determination of the mechanical properties of adhesives. On the other hand, it has been determined that there is a sufficient degree of conformity, even though it is not very close when the strain distributions obtained by DIC technique are compared with the finite element method analyzes for single lap joints. In this study, considering that two dimensional analysis with DIC technique and three dimensional analysis with finite element method is performed, it can be said that three dimensional analysis with DIC technique will yield more compatible and more accurate results.

Author

Dr. Elanur Çelebi

How to Cite

Elanur Çelebi (Master Thesis). Investigation of mechanical behaviour of adhesively bonded joints via digital image correlation (DIC) technic, 2018, Erzurum Technical University.

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CC BY 4.0

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