Computational Design of Finite Strain Auxetic Metamaterials via Topology Optimization and Nonlinear Homogenization

TL;DR

This paper introduces a computational framework combining topology optimization and nonlinear homogenization to design auxetic metamaterials with negative Poisson's ratio over large strains, validated through simulations and stability analysis.

Contribution

It presents a novel integrated approach for designing finite strain auxetic metamaterials, including multimaterial and stability considerations, advancing the field of metamaterial engineering.

Findings

New auxetic designs with negative Poisson's ratio achieved.

Validated designs through multiscale stability analysis.

Identified potential instabilities affecting performance.

Abstract

A novel computational framework for designing metamaterials with negative Poisson's ratio over a large strain range is presented in this work by combining the density-based topology optimization together with a mixed stress/deformation driven nonlinear homogenization method. A measure of Poisson's ratio based on the macro deformations is proposed, which is further validated through direct numerical simulations. With the consistent optimization formulations based on nonlinear homogenization, auxetic metamaterial designs with respect to different loading orientations and with different unit cell domains are systematically explored. In addition, the extension to multimaterial auxetic metamaterial designs is also considered, and stable optimization formulations are presented to obtain discrete metamaterial topologies under finite strains. Various new auxetic designs are obtained based on the proposed framework. To validate the performance of optimized designs, a multiscale stability analysis is carried out using the Bloch wave method and rank-one convexity check. As demonstrated, short and/or long wavelength instabilities can occur during the loading process, leading to a change of periodicity of the microstructure, which can affect the performance of an optimized design.