Optimization via Genetic Algorithm of the Sandwich Composite Structure for the Racing Car Monocoque

The aim of the study was to carry out optimization via genetic algorithm in order to select the best configuration of the sandwich composite structure from which the racing car monocoque is built. The tools used were the static structural analysis by means of the finite element method and multi-objective genetic algorithm implemented in the Ansys Workbench 2024 R1 software. The optimization was carried out to determine the optimal number of layers and orientation of fibers in the sandwich structure. To evaluate the efficiency of the composite structure proposed for the racing car monocoque, two key indicators were employed: Inverse Reserve Factor (IRF) and Total Deformation Load Multiplier (TDLM). The objective function was designed to minimize the overall weight while maintaining the required strength and stiffness of the structure. The results of the conducted analyses demonstrate that the applied optimization via the genetic algorithm method delivers the desired outcomes, meeting the specified design criteria and enhancing the mechanical performance of the monocoque.