Analysis of a Reduced-Order Model for the Simulation of Elastic Geometric Zigzag-Spring Meta-Materials

TL;DR

This paper presents a reduced-order simulation approach for elastic zigzag-spring meta-materials, enabling efficient modeling of complex cellular structures by simplifying their representation and learning their deformation behavior.

Contribution

It introduces a simplified model for zigzag-spring meta-materials and analyzes how sampling and model expressiveness affect simulation accuracy.

Findings

Reduced models can effectively approximate full simulations.

Sampling strategies significantly impact model accuracy.

Simplified models enable faster simulations of complex structures.

Abstract

We analyze the performance of a reduced-order simulation of geometric meta-materials based on zigzag patterns using a simplified representation. As geometric meta-materials we denote planar cellular structures which can be fabricated in 2d and bent elastically such that they approximate doubly-curved 2-manifold surfaces in 3d space. They obtain their elasticity attributes mainly from the geometry of their cellular elements and their connections. In this paper we focus on cells build from so-called zigzag springs. The physical properties of the base material (i.e., the physical substance) influence the behavior as well, but we essentially factor them out by keeping them constant. The simulation of such complex geometric structures comes with a high computational cost, thus we propose an approach to reduce it by abstracting the zigzag cells by a simpler model and by learning the properties of their elastic deformation behavior. In particular, we analyze the influence of the sampling of the full parameter space and the expressiveness of the reduced model compared to the full model. Based on these observations, we draw conclusions on how to simulate such complex meso-structures with simpler models.