In this study, the analysis of reinforced concrete (RC) beams strengthened with Fiber Reinforced Polymer (FRP) composites against bending and shear loads was carried out with the finite element technique, using ABAQUS software, which is widely used in simulating experimental circumstances in numerical studies. It has been reported that buildings in areas damaged by earthquakes are generally constructed using low-strength concrete and inadequate reinforcement. Additionally, construction errors also contribute to reducing the load-bearing capacity of structural elements. For this purpose, nine rectangular cross-section RC beams were experimentally constructed using low-strength concrete and inadequate bending and shear reinforcement. These beams were strengthened by wrapping them in different configurations with Carbon and Glass FRP (CFRP and GFRP) composites to resist shear and bending forces in both transverse and longitudinal directions, and their load-displacement curves were obtained. Subsequently, a three-dimensional Finite Element Model (FEM) was created to validate the experimental results. The FEM validation demonstrated high accuracy in replicating experimental outcomes, emphasizing the influence of mesh size, dilation angle, and concrete constitutive models on simulation fidelity. Parametric studies revealed that increasing longitudinal reinforcement diameters had minimal effect on load capacity but highlighted the critical role of transverse reinforcement, as reducing stirrup spacing significantly improved load-bearing capacity. GFRP-reinforced beams exhibited superior ductility and a 15% higher strength compared to CFRP, suggesting their suitability for applications demanding enhanced displacement capacity. Furthermore, the findings underline the need for refined FEM models to better capture inclined fiber orientations and optimize structural reinforcement strategies.
Primary Language | English |
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Subjects | Reinforced Concrete Buildings, Numerical Modelization in Civil Engineering |
Journal Section | Research Articles |
Authors | |
Early Pub Date | December 28, 2024 |
Publication Date | December 31, 2024 |
Submission Date | April 18, 2024 |
Acceptance Date | December 17, 2024 |
Published in Issue | Year 2024 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.