A new strength prediction model for rectangular RC columns strengthened with FRP wraps and anchors

What is it about?

In recent years, experimental tests on the effects of aspect ratio and size of cross-sections on the effectiveness of fibre-reinforced polymer (FRP) confinement for rectangular RC columns have revealed significant enhancements in their peak and ultimate strengths, particularly for well-confined columns of less than 300 mm in cross-sectional depth. On contrary, the confinement effectiveness for columns having a cross-sectional depth of larger than 300 mm and an aspect ratio equal to or larger than 3.0 is mostly limited. One of the key solutions to significantly increase the confinement effectiveness provided to such large-sized columns is by the use of a combination of FRP anchors and FRP wraps. For a save analysis and design of the FRP-confined rectangular RC columns, it is necessary to have a good model to assess their axial strength capacities. The axial compression models available for rectangular columns have concentrated on unreinforced concrete columns of small cross-sections confined with FRP. Therefore, this paper provides a new strength prediction model with a wider scope than those in the existing literature. Forty-four specimens with their test results provided by two independent researchers were used as a basis for the model expressions. The database of this paper included columns with aspect ratios ranging from 1.5 to 4.0. Furthermore, the depth of the section varied from 100 mm to 600 mm. The key parameters that influence the confined strength included the aspect ratio, number of FRP layers, hoop steel reinforcement, and cross-sectional area and configuration of FRP anchors were all accounted for. For a sufficient amount of FRP-confinement, the threshold values of the lightly and heavily FRP confined columns were proposed to be 0.125 and 0.25, respectively. Finally, the accuracy of the proposed model was verified by comparing its predictions with the database, together with the predictions of other existing models.

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