Optimization of Fiber-Reinforced Polymer Patches for Repairing Fatigue Cracks in Steel Plates Using a Genetic Algorithm

Abstract

A practical design optimization of fiber-reinforced polymer (FRP) patches for repairing fatigue cracks in metallic structures is presented. The design procedure combines finite-element (FE), genetic programming (GP), and genetic algorithm (GA) approaches. An optimum patch design is defined as the combination of design parameters that simultaneously minimizes the patch volume and reduces the stress intensity factor (SIF) range below the fatigue threshold range. A patching correction factor, which accounts for the positive effects of material and geometric properties of the patch and adhesive layer on the SIF solution, is proposed. The correction factor is developed by performing symbolic regression via GP analyses on the SIF values obtained from the three-dimensional FE models. The closed-form SIF solution facilitates the visualization of the effects of design parameters, simplifies the calculation of fatigue life, and reduces the computation effort for design optimization. An example of the center-cracked steel plate subjected to constant amplitude fatigue loading and then repaired with double-sided adhesive-bonded FRP patches is used to illustrate the optimization procedure.