Computational investigation of the post-yielding behavior of 3D-printed polymer lattice structures

Abstract Sandwich structures are widely used due to their light weight, high specific strength, and high specific energy absorption. Three-dimensional (3D) printing has recently been explored for creating the lattice cores of these sandwich structures. Experimental evaluation of the mechanical response of lattice cell structures (LCSs) is expensive in time and materials. As such, the finite element analysis (FEA) can be used to predict the mechanical behavior of LCSs with many different design variations more economically. Though there have been several reports on the use of FEA to develop models for predicting the post-yielding stages of 3D-printed LCSs, they are still insufficient to be a more general purpose due to the limitations associated with the lattice prediction behavior of specific features, certain geometries, and common materials along with showing sometimes poor prediction due to the computationally cheap elements out of which these models have been composed in most cases. This study focuses on the response of different LCSs at post-yielding stages based on the hexahedral elements to capture accurately the behaviors of 3D-printed polymeric lattices made of the Acrylonitrile Butadiene Styrene material. For this reason, three types of lattices such as body centered cubic, tetrahedron with horizontal struts, and pyramidal are considered. The FEA models are developed to capture the post-yielding compressive behavior of these different LCSs. These models are used to understand and provide detailed information of the failure mechanisms and relation between post-yielding deformations and the topologies of the lattice. All of these configurations were tested before experimentally during compression in the z-direction under quasi-static conditions and are compared here with the FEA results. The post-yielding behavior obtained from FEA matches reasonably well with the experimental observations, providing the validity of the FEA models.