The aim of the present study is to investigate the effect of cyclic loading on FRP-confined slender circular RC columns. For this purpose, a total of 6 circular slender RC columns of height 1200 mm and diameter 150 mm were cast; 3 of which were tested under monotonic whereas remaining three were tested under cyclic compressive loads. Out of the six specimens, two were the control specimens and other four were strengthened using two different CFRP-strengthening schemes. In the first strengthening scheme, the two columns were strengthened using a single layer of CFRP sheets with the fibers orientation in the hoop direction. In the second strengthening scheme, other two columns were strengthened using two layers of CFRP with fibers in longitudinal direction and one layer of CFRP fibers in the hoop direction. The hoop CFRP sheet was bonded over the longitudinal sheets to improve the anchorage of longitudinal fibers and reduce the likelihood of flexural debonding failures. The monotonic and cyclic compression tests were performed using Amsler compression testing machine under pinned end conditions and an axial load eccentricity of 25 mm. To apply cyclic loading, the specimens were first loaded from 0 to 80% of the monotonic peak load and then unloaded to zero. This loading-unloading cycle (0 to 80%) was then repeated 3 times, and then finally load was increased monotonically until failure. The load-deflection response of control and strengthened slender RC columns were plotted to study the success of FRP-strengthening on improving the strength and deformation capacity of slender RC columns. In slender columns, the effect of longitudinal FRP fibers in carrying the load in post-yielding stage was more significant than hoop FRP fibers. The test results also showed that FRP-strengthening of slender columns is equally effective in cyclic compression as in monotonic compression.
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Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong 999077, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong 999077, Hong Kong, Peoples R China
Gao, W. Y.
Dai, Jian-Guo
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Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong 999077, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong 999077, Hong Kong, Peoples R China
Dai, Jian-Guo
Teng, J. G.
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Hong Kong Polytech Univ, Dept Civil & Environm Engn, Struct Engn, Hong Kong 999077, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong 999077, Hong Kong, Peoples R China
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Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong, Hong Kong, Peoples R China
Gao, Wan-Yang
Dai, Jian-Guo
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Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong, Hong Kong, Peoples R China
Dai, Jian-Guo
Teng, J. G.
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Hong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Civil & Environm Engn, Hong Kong, Hong Kong, Peoples R China
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Sejong Univ, Deep Learning Architecture Res Ctr, Dept Architectural Engn, 209 Neungdong Ro, Seoul 05006, South KoreaSejong Univ, Deep Learning Architecture Res Ctr, Dept Architectural Engn, 209 Neungdong Ro, Seoul 05006, South Korea
To, Quoc Bao
Shin, Jiuk
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Gyeongsang Natl Univ, Dept Architectural Engn, Jinju 52828, South KoreaSejong Univ, Deep Learning Architecture Res Ctr, Dept Architectural Engn, 209 Neungdong Ro, Seoul 05006, South Korea