Improved Low-Velocity Impact Response of Functionally Graded Graphene-Reinforced Composite Plate

Functionally graded (FG) graphene-reinforced composites have emerged as promising materials for advanced engineering applications due to their superior mechanical properties with tunable characteristics. However, there is limited work on the low-velocity response of such FG composite structures. This study presents a multiscale analysis on the low-velocity impact response of a multi-layer functionally graded graphene nanoplatelet-reinforced composite (FG-GNPRC) plate. The Halpin–Tsai model and rule of mixtures are employed for obtaining material property, while ABAQUS, together with a modified Hertz contact model, is used for the impact responses of the structures. The effects of graphene distribution patterns, the number of FG layers, and characteristics of the impactor on the macroscopic impact responses are comprehensively investigated. Representative volume element (RVE) at the microscale is used to explore the influence of the geometry and orientation of the graphene filler and porosity on the impact responses. The results indicate that increasing the graphene concentration significantly enhances the impact resistance of the FG-GNPRC plates, with optimal performance at [Formula: see text] orientation of the GNP reinforcements. The FG-GNPRC plates with distribution profile X demonstrate superior impact performance. Increasing the number of FG layers up to eight significantly improves the impact resistance, but a further increase in the number of layers shows limited benefits. A critical porosity threshold is unexpectedly identified, beyond which rapid impact resistance variation occurs. Additionally, the characteristics of the impactor, including velocity, size, and geometry, substantially affect the impact dynamics. This multiscale analysis provides valuable insights for optimizing FG-GRCs, potentially leading to the development of more resilient structures for impact-resistant applications across various industries.