Predicting of nonlinear deflection of beams using Artificial Neural Networks
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Full Text |
Pdf
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Author |
Hanane Moulay Abdelali and Rhali Benamar
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e-ISSN |
1819-6608 |
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On Pages
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430-442
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Volume No. |
21
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Issue No. |
7
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Issue Date |
June 10, 2026
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DOI |
https://doi.org/10.59018/042651
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Keywords |
artificial intelligence, beam, deflection, statique, nonlinear, predictive modelling, ANN.
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Abstract
In this paper, artificial neural networks (ANNs) are used to predict the nonlinear deflection of beams subjected to concentrated loads at different sections and under various limit boundaries. The research focuses on developing ANN models capable of accurately predicting large deflections of beams. A comprehensive dataset, generated through semi-analytical methods, finite element simulations, and experimental results, was used to train and validate the models. The input variables included excitation force, contribution coefficient, and linear and nonlinear terms of rigidity. The performance of the ANN models was evaluated by comparing predicted deflections with known data available in the literature, showing high accuracy and reliability. The results demonstrate the potential of ANN-based approaches for efficient and accurate deflection prediction in structural engineering applications, offering a valuable tool for designing and analyzing beams in complex loading scenarios.
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