MATEC Web Conf.
Volume 252, 2019III International Conference of Computational Methods in Engineering Science (CMES’18)
|Number of page(s)||5|
|Section||Computational Artificial Intelligence|
|Published online||14 January 2019|
Estimation of critical force of the buckling composite structures using modelling methods
Lublin University of Technology, Mechanical Engineering Faculty, Nadbystrzycka 36, 20-618 Lublin, Poland
2 University of Defence in Brno, Faculty of Military Technologies, Kounicova 65, 662 10 Brno, Czech Republic
* Corresponding author: firstname.lastname@example.org
The study reported in this paper employed Artificial Neural Networks (ANN) to predict the critical force of the buckling composite structures. The critical force depends upon various factors such as thickness, stacking sequence, etc. These factors have been identified in earlier studies by means of the Finite Elements Method (FEM). The critical force is affected by the above-mentioned factors. Various approaches have been applied in the course of the presented study. Apart from our FEM simulation, the ANN approach has been applied and the results were compared. The main contribution of these two approaches is the estimation of the critical force. The ANN model is trained to predict the critical force for different configurations of input variables.
© The Authors, published by EDP Sciences, 2019
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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