Dynamic Behavior of Origami Structures: Computational and Experimental Study

TL;DR

This paper develops and validates a generalizable dynamic modeling approach for origami structures, combining computational and experimental methods to understand their vibrational behavior and improve design accuracy.

Contribution

It introduces a distributed mass modeling approach for origami structures, validated through experiments and finite element comparisons, enhancing dynamic analysis capabilities.

Findings

Triangle circumcenter mass distribution captures dynamics effectively.

The analytical model accurately predicts free vibration responses.

Experimental results align well with model predictions.

Abstract

Origami structures have been receiving a lot of attention from engineering and scientific researchers owing to their unique properties such as deployability, multi-stability, negative stiffness, etc. However, dynamic properties of origami structures have not been explored much due to a lack of validated analytical dynamic modeling approaches. Given the range of interesting properties and applications of origami structures, it is important to study the dynamic behavior of origami structures. In this study, a dynamic modeling approach for origami structures is presented considering distributed mass modeling, which has the potential to be a generalizable approach. In the proposed approach, stiffness is modeled using the bar and hinge modeling approach while the mass is modeled using the mass distribution approach. Various candidate mass distribution approaches were investigated by comparing their responses to the finite element method responses for various geometric conditions, loading and boundary conditions, and deformation modes. It was observed that a dynamic modeling approach with triangle circumcenter mass distribution was able to capture most of the dynamics satisfactorily consistently. Subsequently, a Miura-ori specimen was manufactured and its free vibration response was determined experimentally and then compared to the prediction of the analytical model. The comparison demonstrated that the analytical model was able to capture most of the dynamics in the longitudinal direction.