Artificially smart optimization of crash cushion device sustained by experimental and numerical study of re-entrant auxetic honeycomb

Abstract

Honeycomb structures are widely used in energy absorption, and more recently auxetic honeycombs have been studied in order to improve absorption capabilities of such structures. The hexagonal re-entrant (HR) honeycomb is foreseen to be a promising structure under impact velocities. An experimental analysis of the re-entrant honeycomb under impact velocity has led to a finite elements model validation at scale one, i.e. scale of current car crash cushions. A new objective function based on the European Standard has been developed in order to improve crash cushions capabilities while avoiding peak deceleration by using a meta-heuristic optimization algorithm. The global optimization process has been performed using Inverse-PageRank-PSO algorithm. The algorithm has led to an optimal geometrical configuration of HR honeycomb improving the performance of current road safety devices. The optimal structure presents a quasi-linear absorption curve, as recommended by European standards.

Keywords:

• Optimization
• energy absorption
• hexagonal re-entrant honeycomb
• road safety

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Called” velocity” in the literature, V is actually a displacement imposed to particles.

Additional information

Funding

The authors acknowledge the ‘Délégation à la Sécurité Routière’ (Road safety Delegation) of French government for their financial support (Convention 21 02 59 88 39).