Optimization of the octagonal origami tube energy absorption using the artificial neural network and heuristic method

Abstract

This article presents a hybrid optimization approach for improving the crashworthiness characteristics of thin-walled metallic tubes using a unique multilayered origami pattern. In the quasi-static axial loading condition, a total of 120 thin-walled tube samples were simulated using the full factorial design method to assess the impact of geometric parameters on their crashworthiness behavior, including the dihedral angle, module number, and outer layer height. Additionally, based on the input parameters, an artificial neural network was implemented to estimate the mechanical response of the tubes. Then, to determine the ideal design parameters, a hybrid multi-objective optimization approach was used. The Technique for Order of Preference by Similarity to Ideal Solution technique was utilized to extract the optimal design to balance the objectives of energy absorption and initial peak force. The specific energy absorption of the optimal tube was discovered to be 68% higher than that of the base tube. The simulation results demonstrate that the proposed multilayered origami pattern provides a unique structure that improves the crashworthiness properties of the thin-walled metallic tubes.