Investigating Static and Dynamic Behaviors in 3D Chiral Mechanical Metamaterials by Disentangled Generative Models

Abstract

Chiral mechanical metamaterials with engineered asymmetric structures have garnered significant interest owing to their potential for manipulating mechanical waves and unconventional mechanical properties. Although several design methodologies have made significant strides in the design and discovery of chiral mechanical metamaterials, 3D designs that incorporate multiple mechanical characteristics remain largely unexplored and the static and dynamic properties of these structures have not received sufficient attention. Here, an innovative approach is introduced for the inverse design of 3D chiral mechanical metamaterials with desired static and dynamic properties, leveraging streamlined shapes to enable a versatile design. By employing conditional generative adversarial networks (c-GANs), the desired mechanical properties are targeted by focusing on both wave attenuation and stress distribution under compression and shear loading. 3D chiral mechanical metamaterials with additive manufacturing are fabricated to demonstrate the performance of the proposed c-GAN. Experimental investigations show that the generated structures exhibited a wide range of wave attenuation properties, low stress concentrations, and a variety of stress-strain curve profiles including nonlinear stiffness, demonstrating their effectiveness in achieving the desired mechanical characteristics. This research offers significant advancements in the on-demand design capabilities of metamaterials and their applications.