1. Mechanics of re-entrant anti-trichiral honeycombs with nature-inspired gradient distributions.
- Author
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Zhang, Ee Teng, Liu, Hu, and Ng, Bing Feng
- Subjects
- *
POISSON'S ratio , *STRAINS & stresses (Mechanics) , *HONEYCOMB structures , *SPECIFIC gravity , *UNIT cell - Abstract
• Novel REAT honeycomb structure derived from bio-inspired gradient-based distribution. • Extensive experiments were conducted to decipher different stages of compression and mechanical properties. • Discovery of a new driver for deformation based on the difference in negative poisson's ratio between layers. • Uncovered 80% higher elastic stiffness and 20% larger densification strain for Chiral-based gradient distribution than its conventional counterpart. • Early-stage compression demonstrated 60% more plateau stress and constant 25% higher energy absorption efficiency. This study focuses on the nature-inspired gradient-based approach to re-designing re-entrant anti-trichiral (REAT) honeycombs through extensive experimental quasi-static compression. Novel perspectives on REAT honeycomb are offered through the introduction of gradient distributions on two critical geometrical parameters, the cylindrical diameter (chiral) and height of the unit cell, rather than the traditional thickness-based gradient approach. Chiral-based gradient approach demonstrated clear advantages in elastic stiffness, specific energy absorption (SEA) and densification strain over uniform REAT structures of constant geometrical parameters. These advantages are exhibited in their extended and constantly increasing quasi-plateau stage, consistent specific energy absorption (SEA) especially during early stages of compression, and most importantly, the ability to maintain a relatively constant energy absorption efficiency that is 25% more than that of the Base uniform REAT structure. Height gradient-based REAT structures, on the other hand, were able to leverage on associations between the negative Poisson's ratio (NPR) effect and height of unit cell to demonstrate notable deformation patterns across various portions of the structure. The present work reveals the performance enhancements through alternative gradient-based approaches over thickness-based gradient approaches and highlighted the differences in NPR between layers as the main driver of compressive collapse apart from the commonly concluded difference in relative density. [Display omitted] [ABSTRACT FROM AUTHOR]
- Published
- 2023
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