Numerical Simulation and Preforming Parameters Optimization of Carbon-Kevlar Hybrid Woven Reinforcement Materials Based on Genetic Algorithm

Abstract

Carbon-Kevlar hybrid woven reinforcement materials have high specific strength and modulus, excellent fatigue resistance, which are widely used in aerospace applications. Due to its special mechanical properties by hybridization, the forming quality is affected by various factors such as reinforcement properties and process parameters. In order to improve the forming quality of Carbon-Kevlar hybrid woven reinforcement and reduce the forming defects, this paper proposes a new optimization method combined with genetic algorithm. Taking the maximum shear angle of the preform as the optimization objective, a genetic algorithm is used to optimize the load and size of the tetrahedral structure blank holder. The results indicate that the peak shear angle decreased from 52.14° to 43.90°, while the optimal forces on the five parts of the blank holder are RF₁ = 20 N, RF₂ = 26 N, RF₃ = 45 N, RF₄ = 14 N, RF₅ = 45 N, respectively, and the optimal gaps between the blank holder parts is BW₁ = 4 mm, BW₂ = 22 mm. Then, potential wrinkling areas were predicted by the in-plane negative strain. It was found that the minimum in-plane negative strain of the sample in the two main fiber directions was effectively controlled, and the negative strain distribution in the useful areas was more uniform, thereby reducing the potential wrinkling areas, indicating the effectiveness of the optimization method.