Collision performance and multi-objective robust optimization of a combined multi-cell thin-walled structure for high speed train

Abstract

Based on the Simplified Super Folding Element (SSFE) theory, the theoretical prediction of average crushing force (Favg) for multi-cell thin-walled structures is inferred and a combined five-cell thin-walled structure used in high speed train is proposed and investigated in this paper. The finite element model of the proposed structure and the theoretical prediction are validated by a full scaled impact experiment. Then, parametric studies are performed to evaluate the effects of design variables, including the thickness (t) and the side length (a) of the orthohexagonal cell, on collision responses based on the validated FE model and theoretical prediction. It is found that both specific energy absorption (SEA) and the maximum initial force (Fmax) are obviously affected by the design parameters. Particularly, the effect of parameter t on crushing performance is greater than that of parameter a. In further, to minimize the Fmax and maximum SEA under the constraint of Favg, a multi-objective robust optimization methodology is adopted. The Optimal Latin Hypercube Design (OLHD) and orthogonal design are combined to perform Design of Experiment (DoE) and dual response surface models (DRSM) are constructed for the optimization. The optimal results of deterministic optimization indicate that the Fmax decreases by 11.07% compared with the original design while the robust optimization optimal result of Fmax decreases by 10.01%. However, the robust optimization optimal design is more acceptable considering the robustness, which means the robust optimization is more attractive than deterministic optimization in practical engineering application.