Investigation of the compressive behavior and failure modes of unconfined and FRP-confined concrete using digital image correlation
Date
2020
Authors
Fallah Pour, A.
Nguyen, G.D.
Vincent, T.
Ozbakkaloglu, T.
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Composite Structures, 2020; 252:1-16
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Ali Fallah Pour, Giang D. Nguyen, Thomas Vincent, Togay Ozbakkaloglu
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Abstract
This paper presents a detailed study on the development of axial, lateral and Von Mises strains measured by contact and non-contact methods under axial compression fiber reinforced polymer (FRP) confined and unconfined concrete specimens. The focus of the study was on the correlation between macro responses and localized deformations and the effects of FRP confinement on the localization of deformations. A total of 10 specimens were experimentally tested with a range of instrumentation to measure different types of strain. Digital image correlation (DIC) was used to obtain full-field strain evolution during compressive loading of concrete specimens confined with various fiber reinforced polymers. The effect of confinement material on the compressive behavior and strain distribution of FRP-confined concrete was investigated. The evolution of axial, lateral and Von Mises strains were recorded and examined during axial loading, including post-peak strain softening behavior. Data recorded by the typical contact method of linear variable displacement transformers (LVDTs) and strain gauges were used to validate the non-contact DIC method. The results obtained from DIC data in this study showed that expansion of shear zone for unconfined concrete is more localized than FRP-confined specimens. The results also show that specimens confined with CFRP induced homogenous compressive behavior, whereas GFRP and BFRP specimens with lower lateral stiffness displayed local strain concentration and less homogenous response. It was also observed that DIC provides a more accurate estimation of the ultimate condition compared to the contact methods due to the ability of DIC to capture the evolution of full-field strains.
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© 2020 Published by Elsevier Ltd.