Strength of Hybrid Steel-BFRP Reinforced Concrete Beams with Openings in the D-Region Strengthened Internally and Externally

Abstract

The opened beams always confused the designers due to the guidelines missing. In this research, six hybrid beams reinforced with mixed steel and basalt fiber-reinforced polymer (BFRP) bars and having constant cross-sections of 150 mm × 300 mm and a clear span of 1800 mm were cast and tested under a four-point loading setup. Generally, five beams had symmetrical rectangular openings with dimensions of 150 mm × 250 mm located at a distance of 250 mm (equivalent to the beam effective depth) from the beam support, while an additional solid beam served as a control. The studied parameters included the effect of using internal reinforcement (steel or BFRP bars) provided adjacent to the opening sides or by incorporating an external BFRP sheet around the opening corners. Also, double enhancement with internal steel reinforcement bars together with external strengthening BFRP sheet was investigated. The relevant results showed that the opened beam without enhancement lost 75% of the maximum load compared with the solid beam. Placing internal steel or BFRP bars around the openings increased the maximum load by 62% and 60%, respectively, compared to the non-enhanced opened beams. Using an external BFRP sheet to strengthen the opening corners of the beam enhanced the maximum load by 76% compared with the non-enhanced opened beam. Consequently, by combining both the internal steel reinforcement and external BFRP sheet around the openings, the maximum load increased by 137% compared with the non-enhanced opened beam. Ultimately, a numerical analysis of the three-dimensional finite element model was performed to confirm the experimental findings, and the relevant results showed compatibility correlations with the experimental ones. Also, the effect of various parameters such as BFRP reinforcement ratio and number of BFRP sheet layers around the openings was investigated by adapting the validated numerical model.