Numerical investigation the influence of layers number and their orientation in a CFRP using improved ANN

issue 14(1)2024
Published Feb 5, 2024
https://doi.org/10.46223/HCMCOUJS.acs.en.14.1.46.2024
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Received: 2023-10-17
Accepted: 2024-01-22
Published: 2024-02-05
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14(1)2024

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Abdeldjebar Zara
University M’hamed Bougara Boumerdes, Boumerdes, Algeria
Idir Belaidi
University M’hamed Bougara Boumerdes, Boumerdes, Algeria
Noureddine Fahem
University M’hamed Bougara Boumerdes, Boumerdes, Algeria
Chouaib Aribi
University M’hamed Bougara Boumerdes, Boumerdes, Algeria
Abdelmoumin Oulad Brahim - moumindoc@gmail.com
Polytechnic University of Marche, Ancona, Italy
https://orcid.org/0000-0003-4729-298X
Erica Magagnini
Polytechnic University of Marche, Ancona, Italy
Abdelwahhab Khatir
Polytechnic University of Marche, Ancona, Italy

Abstract

Technological advancements in the field of artificial intelligence have enabled significant progress in various areas, particularly in optimizing the structural configuration of multi-layer composites. The main objective of this study is to investigate how geometric parameters, such as fiber orientation and number of layers, influence the mechanical properties of these materials. To predict the mechanical properties based on the number and orientation of layers during bending tests, we used a hybrid E-Jaya-ANN optimization technique and compared it with the hybrid Jaya-ANN to evaluate the accuracy of the approach. Additionally, using ABAQUS software, a numerical model has been created based on Hashin’s damage criterion to predict the behavior of composite specimens (CFRP) under bending loads and to collect a number of databases starting with the validation model. Subsequently, we generated a series of numerical results representing various practical scenarios to serve as a basis for training an Improved Artificial Neural Network (IANN). Our ability to obtain a better architecture for the laminated layers was made possible by the influence and variation of these materials’ mechanical properties.

Keywords

composite laminate, E-Jaya-ANN, fiber orientations, Jaya-ANN, number of layers

License
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite
Zara, A., Belaidi, I., Fahem, N., Aribi, C., Oulad Brahim, A., Magagnini, E., & Khatir, A. (2024). Numerical investigation the influence of layers number and their orientation in a CFRP using improved ANN. HCMCOU Journal of Science – Advances in Computational Structures, 14(1), 20–32. https://doi.org/10.46223/HCMCOUJS.acs.en.14.1.46.2024
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