Crushing analysis and multiobjective crashworthiness optimization of combined shrinking circular tubes under impact loading

This paper proposes a new type of energy absorber with combined shrinking circular tubes for a high-speed train. An impact experiment is conducted to investigate the dynamic crushing performance of this energy absorber with combined shrinking circular tubes. The results show that the combined tubes experience steady dynamic shrinking deformation. Finite element (FE) models of the energy absorber are then developed, and the dynamic crushing forces are in good agreement with the impact test. A theoretical solution for the dynamic shrinking crushing load is derived. Based on the validated FE models, the effects of the friction coefficient, wall thickness and die radius on the dynamic crushing force and energy absorption are investigated. An increase in the wall thickness leads to a substantial growth in the maximum crushing force (F-max) and specific energy absorption (SEA), but the growth rate of F-max is much larger than that of the SEA as the wall thickness increases. In addition, comparing theoretical and FE results demonstrates that predictions of the dynamic steady-state forces for the combined shrinking circular tubes with different friction coefficients, wall thicknesses (t) and die radius (R-die) are satisfactory. Finally, to improve the crashworthiness of the expanding circular tubes, Sobol' sensitivity analysis is employed to analyze the effects of the design parameters (t and R-die) on the objective responses (SEA and F-max) using the Kriging model. A Pareto front of double optimization objective SEA and F-max was obtained after being optimized by multiobjective particle swarm optimization (MOPSO). The results show that SEA and F-max are positively correlated, and a balance between the SEA and F-max was obtained at optimal point C (SEA = 13.09 kJ/kg, F-max = 581.11 kN).

Automated summary

This paper proposes a new type of energy absorber with combined shrinking circular tubes for a high-speed train, investigates the dynamic crushing performance and effects of design parameters through experiments and modeling, and achieves the optimal balance of SEA and F-max through multiobjective particle swarm optimization.