Publication:
Multiobjective crashworthiness optimization of graphene type multi-cell tubes under various loading conditions

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Date

2021-05

Authors

Albak, Emre İsa
Solmaz, Erol
Yıldız, Ali Rıza
Öztürk, Ferruh

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Springer

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Abstract

Nature is an important source of inspiration for researchers to create better designs. In this study, graphene type multi-cell tubes is inspired by graphene due to its strong and lightweight mechanical properties. Peak crushing force (PCF), energy absorption (EA) and crushing force efficiency crashworthiness indicators have been taken into consideration under different loading angles, and the complex proportion assessment (COPRAS) which is a multicriteria decision-making method has been used to determine the best model. The best model is found to be GTMT5 (second-order and third-order hollow cylinders in the graphene type multi-cell tube) by the COPRAS selection method. The multiobjective optimization, whose objective is to minimize PCF and maximize EA, is applied on the GTMT5 using the multiobjective particle swarm optimization and non-dominated sorting genetic algorithm II methods, and the techniques are compared. The optimization study is carried out on the radial basis function metamodels. This study shows that circular structures placed in multi-cell tubes have a significant effect on the crashworthiness performance.

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Keywords

Multi-cell thin-walled tube, Oblique impact, Crashworthiness, Complex proportion assessment, Multiobjective optimization, Energy-absorption characteristics, Thin-walled structures, Crushing analysis, Theoretical prediction, Numerical-simulation, Square tubes, Design, Columns, Sections, Hollow, Biomechanics, Cells, Crushing, Cytology, Decision making, Genetic algorithms, Graphene, Particle swarm optimization (PSO), Screening, Circular structures, Crashworthiness optimization, Loading condition, Multi objective particle swarm optimization, Multi-criteria decision making methods, Non-dominated sorting genetic algorithm - ii, Optimization studies, Radial basis functions, Multiobjective optimization

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