Author:
Seba Mohamed Rida,Kebdani Said
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.
Publisher
Taiwan Association of Engineering and Technology Innovation
Subject
Management of Technology and Innovation,General Engineering,Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment,Environmental Engineering,General Computer Science
Cited by
4 articles.
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