Replication Data for: Shape Optimization of auxetic unit cells under dynamic loading in macroscopic components

This study introduces an optimization methodology that enables independent shape adjustments of auxetic mesostructures within different regions of a macroscopic component. Using a Bayesian optimization algorithm, the unit cell geometry is optimized to maximize energy dissipation, enhance dynamic stiffness, and minimize mass, ensuring a well-balanced trade-off between these competing objectives. A macroscopic cantilever beam composed of reentrant auxetic unit cells serves as a real-world-inspired case study and is analyzed under dynamic loading conditions, demonstrating the effectiveness of the optimized mesostructure in improving structural performance.

Beyond the optimized structure itself, this study provides an in-depth analysis of the optimization process, offering valuable insights into the application of auxetic metamaterials in real life components and therefore in engineering practice. Additionally, a mesh convergence study is conducted to validate numerical accuracy. The results underscore the potential of auxetic metamaterials for aerospace applications, highlighting their performance-driven optimization and real-world applicability.