Optimizing Variable Stiffness Sandwich Structures with Tunable Second-Order Corrugated Cores

This paper presents an automated computational framework for optimizing a type of advanced sandwich panel with a corrugated core made from second-order variable-stiffness composites. This automates the entire process, from geometry creation to result analysis. An integrated genetic algorithm efficiently handles two optimization scenarios: finding the ideal fiber angles and mate-rial thicknesses. Homogenization approach is used to model a single unit-cell of the corrugated core as a representative volume element for the entire structure's behavior. Given the complexity of design variables in variable stiffness, conventional numerical and analytical methods prove inadequate. To overcome this problem, a tailored computational framework is developed that in-tegrates Python with the ABAQUS finite element solver. A closed-loop optimization system is provided that can efficiently ex-plore the design space without manual intervention. The presented method is also versatile, designed to incorporate other opti-mization algorithms and address additional mechanical criteria like natural frequencies and buckling resistance.