Crashworthy optimization of skeleton-filled FRP tubes based on back propagation neural network

Abstract

Lightweight composite tubes have been widely used in vehicle safety systems as energy absorbers. To improve the crashworthiness of tubes, composite skeletons with a variety of cross-sectional profiles were ingeniously designed as internal reinforcements. Herein, a novel composite skeleton comprising cross-ribs and an inner circle (OS-skeleton) was proposed and integrally fabricated through the special assembling molds. The novel OS-skeleton presented a steady progressive failure mode under dynamic impact loads, leading to remarkable material utilization and energy absorption characteristics. Subsequently, finite element analysis (FEA) models were developed. The predicted response curves and deformation modes were consistent with the experimental results. Finally, a multi-objective optimization utilizing the back propagation neural network (BPNN) was then conducted to further enhance the mean crushing force (MCF) and specific energy absorption (SEA) by adjusting several structural parameters. The results showed that MCF and SEA increased with the increasing thickness of the skeletons and the number of circumferential ribs. By comparison, the diameter of inner tube and the number of circumferential ribs showed a non-linear relationship with the energy absorption characteristics due to their combined effects. In sum, the proposed composite tubes filled with OS-skeletons could maximize certain aspects of crashworthiness performance through proper structural design, demonstrating great potential for lightweight energy absorbers.

Keywords

• Thin-walled structures
• Fiber-reinforced plastic
• Crashworthiness
• Multi-objective optimization