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Structural Engineering and Mechanics Volume 87, Number 6, September25 2023 , pages 517-527 DOI: https://doi.org/10.12989/sem.2023.87.6.517 |
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Predicting and analysis of interfacial stress distribution in RC beams strengthened with composite sheet using artificial neural network |
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Bensattalah Aissa, Benferhat Rabia and Hassaine Daouadji Tahar
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| Abstract | ||
| The severe deterioration of structures has led to extensive research on the development of structural repair techniques using composite materials. Consequently, previous researchers have devised various analytical methods to predict the interface performance of bonded repairs. However, these analytical solutions are highly complex mathematically and necessitate numerous calculations with a large number of iterations to obtain the output parameters. In this paper, an artificial neural network prediction models is used to calculate the interfacial stress distribution in RC beams strengthened with FRP sheet. The R2value for the training data is evaluated as 0.99, and for the testing data, it is 0.92. Closed-form solutions are derived for RC beams strengthened with composite sheets simply supported at both ends and verified through direct comparisons with existing results. A comparative study of peak interfacial shear and normal stresses with the literature gives the usefulness and effectiveness of ANN proposed. A parametrical study is carried out to show the effects of some design variables, e.g., thickness of adhesive layer and FRP sheet. | ||
| Key Words | ||
| artificial neural network; FRP sheet; interfacial stresses; RC beam; strengthening | ||
| Address | ||
| Bensattalah Aissa: Faculty of Applied Sciences, Department of Civil Engineering, University of Tiaret, Algeria; Laboratoire des Méthodes de Conception des Systèmes (LMCS),16000 Oued-Smar, Algiers, Algeria Benferhat Rabia. Hassaine Daouadji Tahar: Faculty of Applied Sciences, Department of Civil Engineering, University of Tiaret, Algeria; Civil Engineering Department, University of Tiaret, Algeria; Laboratory of Geomatics and Sustainable Development, University of Tiaret, Algeria | ||