Crashworthiness analysis and uncertainty optimization of novel multi-wall tube

Abstract

Multi-wall tube has excellent crashworthiness therefore is widely used in energy absorption. The crashworthiness of multi-wall tube is not only related to shape but also materials. However, the specific value of some material parameters cannot be determined, instead, only interval can be confirmed. In this work, a novel multi-wall tube (NMT) that is composed of octagon and nested quadrilateral was designed and an interval uncertainty optimization method was proposed to improve the crashworthiness. Firstly, the crashworthiness of the NMT, octagonal multi-wall tube (OMT) and square double-wall tube (SDT) under axial load was compared and analyzed by experimental and numerical simulation. It indicated that NMT has obvious energy absorption advantages and good progressive deformation mode. Moreover, the energy absorption of NMT structure is more sensitive to wall thickness than wall spacing ratio and inner wall length. Then, based on the theory of simplified super folding element (SSFE), the theoretical model of NMT was proposed. The theoretical analysis is consistent with the simulation results. Finally, according to the interval number theory, the uncertain interval optimization problem was transformed into deterministic optimization and reliability analysis. Non-dominated sorting genetic algorithm II (NSGA-II) was used to seek superior crashworthiness of NMT. When considering interval uncertainty in optimization, the reliability of crashworthiness of the NMT can be further improved. The research results provide a good guidance and theoretical support for crashworthiness optimization design.

Keywords:

• Multi-wall tube
• crashworthiness optimization
• interval uncertainty
• reliability analysis

Disclosure Statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this work.

Data Availability

The data used to support the findings of this study are available from the corresponding author upon request.

Additional information

Funding

This research was supported by National Nature Science Foundation of China (52271023), Research Project of Education Department of Liaoning Province (LJKZ0493) and Dalian Science and Technology Innovation Fund Application Basic Research Project (2022JJ12GX029).