Performance Study of Origami Crash Tubes Based on Energy Dissipation History

• Main Authors: Sun, Z. (Author), Wang, H. (Author), Xiang, X. (Author), Zhang, P. (Author)
• Format: Article
• Language: English
• Published: MDPI 2022
• Subjects: 3D modeling; ABAQUS; automatic model modeling; Automatic model modeling; Automatic modeling; Automotive industry; Crushing; Data set; Energy absorption; Energy dissipation; energy dissipation history; Energy dissipation history; Energy utilization; Energy-consumption; Finite element method; Image resolution; Learning algorithms; machine learning; Machine learning; Morphology; Multi morphologies; multi-morphology origami; Multi-morphology origami; Numerical methods; Origami tube; origami tubes; Performance study; Thin walled structures; Thin walled tubes
• Online Access: View Fulltext in Publisher

 Thin-walled tubes are widely used as energy-absorbing components in traffic vehicles, which can absorb part of the energy in time by using the plastic deformation of the components during collision so as to reduce the damage of the vehicle body and improve the overall safety and reliability of traffic vehicles. The prefolded design of thin-walled tube components can guide it to achieve the ideal energy dissipation performance according to the preset damage path, so the related research based on origami tubes has attracted a lot of attention. Since the geometry of the origami tubes is controlled by many parameters and stress and deformation is a complex nonlinear damage process, most of the previous studies adopted the method of case analysis to carry out numerical simulation and experimental verification of the relevant influence parameters. This paper makes a new exploration of this kind of problem and focuses on solving the related technical problems in three aspects: 1. The automatic model modeling and 3D display based on parameters are proposed; 2. System integration using Python programming to automatically generate the data files of ABAQUS for finite element simulation was realized, and we sorted the finite element analysis results into an artificial intelligence analysis data set; 3. Clustering analysis of the energy consumption history of the data set is carried out using a machine learning algorithm, and the key design parameters that affect the energy consumption history are studied in depth. The sensitivity of the energy absorption performance of the origami tubes with multi-morphology patterns to the crease spacing is studied, and it is shown that the concave–convex crease spacing distribution with a distance larger than 18 mm could be used to activate specific crushing modes. In the optimal case, its initial peak force is reduced by 66.6% compared to uniformly spaced creases, while the average crushing force is essentially the same. Furthermore, this paper finds a new path to optimizing the design of parameters for origami tubes including a multi-morphology origami pattern from the perspective of energy dissipation. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.