Multi-objective optimization of composite sandwich panels using lamination parameters and spectral Chebyshev method

Composite materials are widely used in various industries because of their distinct properties. Hybridization is an efficient way of designing composite panels to decrease the cost and/or weight while maintaining stiffness properties. In this study, an accurate and efficient framework is developed to optimize laminated sandwich panels composed of high-stiffness face sheets and low-stiffness core. The stiffness properties of face sheets and core are represented using lamination parameters. The governing equations are derived following first-order shear deformation theory and solved using the spectral Chebyshev approach. In multi-objective optimization problems, genetic algorithm is used to determine Pareto-optimal solutions for fundamental frequency, frequency gap, buckling load, and cost metrics. In these analyses, optimal lamination parameters and thickness are found for face-sheets and core of sandwich panels, and the results are presented as 2D and 3D Pareto-optimal design points. When the individual performance metrics lead to different optimum points, a scattering behavior is observed in the 3D Pareto sets whose boundaries are defined by the 2-objective Pareto fronts. The results provide insights into the design requirements for improving the dynamic and load-carrying behavior of sandwich laminates while minimizing the cost that presents the usability of the presented approach in the multi-objective optimization.

Automated summary

In this study, an accurate and efficient framework is developed to optimize the design of laminated sandwich panels. Genetic algorithm is used to determine Pareto-optimal solutions for various performance metrics. The results provide insights into the design requirements for improving the dynamic and load-carrying behavior of sandwich laminates.