A Study of the Compressive Behavior of Concrete Columns Confined with SRP Jackets using Digital Image Analysis
Abstract
This paper describes the results of an experimental study carried out to understand the behavior of short plain concrete prisms with a square cross-section confined by steel reinforced polymer (SRP) jackets subjected to a monotonic concentric compressive load. The effectiveness of the confinement is studied in terms of load-bearing capacity and ultimate strain with respect to unconfined prisms. Test parameters considered in this study are the density of steel fibers, concrete corner condition, concrete surface treatment, SRP jacket height, and number of confinement layers. Digital image correlation (DIC) is used to qualitatively and quantitatively study the displacement and strain fields on the composite surface. SRP confinement is shown to improve the compressive strength and the ultimate strain of concrete prisms relative to the unconfined condition. Increases in fiber density and number of confinement layers are not proportional to increases in confined compressive strength.
Recommended Citation
L. Sneed et al., "A Study of the Compressive Behavior of Concrete Columns Confined with SRP Jackets using Digital Image Analysis," Composite Structures, vol. 179, pp. 195 - 207, Elsevier, Nov 2017.
The definitive version is available at https://doi.org/10.1016/j.compstruct.2017.07.047
Department(s)
Civil, Architectural and Environmental Engineering
Keywords and Phrases
Concrete beams and girders; Concretes; Image analysis; Plasma confinement; Prisms; Steel fibers; Strain measurement; Surface treatment; Confined compressive strengths; D. digital image correlation (DIC); Digital image analysis; Digital image correlations; Load-bearing capacity; SRP jacket; Steel reinforced polymer; Unconfined conditions; Compressive strength; Confinement; Digital image correlation
International Standard Serial Number (ISSN)
0263-8223
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2017 Elsevier, All rights reserved.
Publication Date
01 Nov 2017