Abstract
An experimental investigation was conducted to evaluate the flexural-shear behavior of deteriorated reinforced concrete (RC) beams strengthened with carbon fiber fabric-reinforced cementitious matrix (C-FRCM) composites, focusing on their failure modes, ultimate bearing capacity, ductility, and stiffness. The strengthening efficiencies of a carbon fiber woven mesh and a carbon fiber cloth were comparatively analyzed. The results indicated that the C-FRCM effectively restrained the crack propagation process: the RC beams strengthened with the C-FRCM (carbon fiber woven mesh) exhibited relatively uniform crack development trends, whereas those strengthened with carbon fiber-reinforced polymer (CFRP) exhibited delayed crack growth prior to steel bar yielding. Future studies will add strengthening tests with different numbers of layers to further verify the generality of this law. Under two-layer strengthening conditions, smaller mesh sizes produced more significant performance improvements. Conversely, for mesh sheets with constant distribution ratios, increasing the number of layers further improved the effectiveness of strengthening. The C-FRCM also enhanced the ductility and flexural stiffness of deteriorated RC beams to a certain extent, providing improvement trends that were consistent with those observed in the ultimate bearing capacity. However, the ductility enhancement varied among the samples, with differentiation arising from the stiffness improvement characteristics and plastic deformation capacities associated with different strengthening configurations. A calculation method for determining the flexural bearing capacities of C-FRCM-strengthened degraded RC beams was proposed, accounting for concrete strength degradations, cross-sectional damage characteristics, the steel corrosion rate, reinforcement configuration parameters, the effective utilization rates of composite materials, and fiber strength exploitation efficiency. The validity of the proposed methodology was established through an experimental validation by incorporating statistical performance metrics such as the mean error and coefficient of variation, while a comparative analysis against the existing code-based formulations demonstrated its technical advantages.
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