Optimal metaheuristic design of CFRP wrapping for enhancing the shear capacity of reinforced concrete columns

Abstract

Reinforced concrete (RC) columns are prone to brittle shear failure under lateral loads like earthquakes, especially in older structures. Carbon fiber reinforced polymer (CFRP) wrapping effectively enhances shear capacity, ductility, and energy dissipation. This study optimizes CFRP jacket design to increase shear strength while minimizing material volume per meter of column. The objective function includes the number of layers (n), strip width (W_f), spacing (S_f), and thickness (t_f), following ACI 440.2R-2017 and ACI 318-05 constraints on strain, shear contribution, and capacity. Three metaheuristic algorithms—JAYA, Teaching-Learning-Based Optimization (TLBO), and Flower Pollination Algorithm (FPA)—were used to solve the nonlinear problem in MATLAB with randomized populations, 100–500 iterations, and 30 independent runs. Analyses for 100–500 kN shear demands (20%–100% increases) yield valid designs. Low shear demands typically require minimal CFRP, often a single layer with moderate strip width and large spacing. Higher demands required more intensive reinforcement through increased layer count and reduced spacing, with width adjustments as needed to satisfy code constraints. FPA achieved the lowest CFRP volumes due to its Lévy-flight global search, TLBO produced the most stable results with low variability, and JAYA offered the fastest computation. Increasing iteration count and population size improved convergence in all algorithms, yielding solutions closer to the optimum. Results confirm that metaheuristics enable economical, reliable CFRP retrofitting, promoting sustainability. Future work could include multi-objective optimization for cost and constructability.