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Identification of crashworthiness indicators of column energy absorbers with triggers in the form of cylindrical embossing on the lateral edges using artificial neural networks

Ferdynus Mirosław, Gajewski Jakub

Eksploatacja i Niezawodność

2022

Vol. 24, no. 4

805--821

The paper presents the possibility of neural network application in order to identify the most advantageous design variants of column energy absorbers in terms of the achieved energy absorption indicators. Design variants of the column energy absorber made of standard thin-walled square aluminium profile with triggers in the form of four identical cylindrical embossments on the lateral edges were considered. These variants differ in the diameter of the trigger, its depth and position. The geometrical parameters of the trigger are crucial for the energy absorption performance of the energy absorber. The following indicators are studied: PCF (Peak Crushing Force), MCF (Mean Crushing Force), CLE (Crash Load Efficiency), SE (Stroke Efficiency) and TE (Total Efficiency). On the basis of numerical studies validated by experimentation, a neural network has been created with the aim of predicting the above-mentioned indices with an acceptable error for an energy absorber with the trigger of specified geometrical parameters and position. The paper demonstrates that the use of an effective multilayer perceptron can successfully speed up the design process, saving time on multivariate time-consuming analyses.

Numerical Crush Analysis of Thin-Walled Aluminium Columns with Square Cross-Section and a Partial Foam Filling

Ferdynus Mirosław, Rogala Michał

Advances in Science and Technology. Research Journal

2019

Vol. 13, no 3

144--151

The article presents the results of numerical crush simulations of thin-walled structures with a square cross-section and partial filling with foamed material. The influence of the length of the filling on the values of the energy efficiency index was analysed. Four types of foamed material were subjected to numerical analysis. The research was conducted using FEM in Abaqus 6.14 program. The obtained results were presented in the following forms: load-shortening characteristics, tables and diagrams. The best energy absorbing properties are shown by models filled with aluminium and polyethylene terephthalate foam.