This study presents a hybrid experimental–numerical methodology for the preliminary design and optimization of a CFRP crash box intended for high-performance automotive applications. An initial experimental campaign was conducted on frustum-shaped crash boxes manufactured by Pagani Automobili S.p.A., comparing constant and variable thickness configurations through drop tower impact tests to evaluate energy absorption, crushing stability, and failure mechanisms. A lightweight finite element model was developed in Abaqus/Explicit using shell elements and Hashin-based damage criteria, achieving calibration errors below 10% for most parameters and under 15% for peak forces. Geometric enhancements, including continuous flanges, removal of the top surface, and an internal cruciform reinforcement, significantly improved energy absorption (up to 110%) but introduced trade-offs in stroke efficiency and mean force levels. To mitigate these effects, a genetic algorithm was employed to optimize laminate layup by varying ply orientations, resulting in improved stroke efficiency and reduced peak and average forces while maintaining crushing stability. The proposed approach demonstrates that integrating experimental validation with efficient numerical modeling and optimization accelerates the development of lightweight, high-performance crash absorbers, offering a robust framework for motorsport and automotive applications that balances safety, efficiency, and manufacturability.
Caporale et al. (2026) studied this question.