Finite Element and Neural Network Based Predictive Model to Determine Natural Frequency of Laminated Composite Plates with Eccentric Cutouts under Free Vibration

Mohamed Rida Seba; Said Kebdani

doi:10.46604/aiti.2022.8909

Authors

Mohamed Rida Seba Applied Mechanics Laboratory, Faculty of Mechanical Engineering, University of Science and Technology Oran Mohamed-Boudiaf, Oran, Algeria
Said Kebdani Applied Mechanics Laboratory, Faculty of Mechanical Engineering, University of Science and Technology Oran Mohamed-Boudiaf, Oran, Algeria

DOI:

https://doi.org/10.46604/aiti.2022.8909

Keywords:

artificial neural network, free vibration, finite element model, cutout, natural frequency

Abstract

This research proposes a predictive model to identify changes in the mechanical and geometrical properties of composite plates with eccentric cutouts based on natural frequency. Finite elements (FE) and neural networks are used to develop the model based on machine learning. First, the numerical analysis of free vibration is performed by the FE model on the laminated composite plates with a stacking sequence [0/90]_2s under a clamped-free (CFFF) boundary condition. The outputs of the FE model (520 configurations) are then utilized to train the artificial neural network (ANN) model through the Levenberg-Marquardt method, and the developed ANN model is then used to evaluate the influence of various parameters on the natural frequency. The results show that the changes in the mechanical and geometrical properties of composite plates have impacts on the natural frequency. Furthermore, the findings of the ANN model are substantially identical to those of the numerical model, with a small margin of error.

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