Height-independent optimal gradients in honeycombs boost energy absorption through delocalized deformation mechanism

Abstract

Gradients, as ubiquitous features in nature, have served as a fundamental inspiration for the design and fabrication of high-performance synthetic materials and components with spatially varying properties. In our previous work, gradient strategy was implemented in honeycomb structures (HCSs) for enhanced impact resistance, where optimal gradient profiles were determined through a neural network-based machine learning approach. Following the established methodology, this study extends the optimization to graded HCSs of different characteristic heights (defined as H/d, where H is HCS height and d is indenter tip diameter). It was found that for both hexagonal and re-entrant HCSs, the optimal gradient parameters are independent of characteristic height, whereas their energy absorption capacity exhibits linear scaling with height. Through numerical analysis and 3D printing-based experimental validation, this scaling behavior was attributed to the delocalized deformation mechanism, which causes the energy dissipation zone to expand proportionally with increasing structural height. Results presented in this work would provide critical insights for implementing functionally graded HCSs in various energy-absorbing applications, significantly advancing their practical engineering utility.