Design and optimization of the laminated composite structures used in aerospace industry

Composite materials, which have a wide range of applications in the aerospace industry, provide great advantages in terms of lightness, durability and fuel efficiency. In this context, optimization methods have been frequently used in recent years to improve the performance of composite materials. In this thesis, it is aimed to minimize the structural deformation of a continuous fiber-reinforced laminated composite structure by performing optimization processes with Genetic Algorithm (GA). In addition, with this study, it is aimed to consider artificial intelligence-based optimization processes in the design of laminated composite structures which are widely used in the aerospace industry and to guide the integration of such new technologies into enterprises. At the beginning of the study, codes specific to this study were developed in Python language, and the integration of the genetic algorithm with the finite element solver was achieved through these codes. In the code, the basic functions required for optimization operations with the genetic algorithm were developed and the basic optimization parameters, especially the objective function and constraint function, were defined. In the second part of the study, composite shells with different layer arrangements were designed and FEM analyses were performed for each of them in order to compare with the optimization results. In the last part of the study, optimization processes were performed for the designed composite shells. In this section, the critical parameters that may affect the optimization process were determined and operations were performed with different parameter values in each optimization process. When the obtained results are examined, the deflection amounts of the composite shells calculated by FEM analysis were reduced up to 60% as a result of the optimizations made with the genetic algorithm and optimum fiber orientation angles were obtained.