Prediction of punching shear capacity of RC flat slabs using artificial neural network

Punching shear of flat slabs is a local, brittle failure that may occur before the more favourable ductile flexural failure. This study develops an artificial neural network (ANN) modelling for the prediction of punching shear strength of flat slabs using 281 test data available in the literature. T...

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Bibliographic Details
Main Authors: Safiee, Nor Azizi, Ashour, Ashraf
Format: Article
Published: Springer Cham 2017
Online Access:http://psasir.upm.edu.my/id/eprint/62800/
https://www.researchgate.net/publication/316634574_Prediction_of_punching_shear_capacity_of_RC_flat_slabs_using_artificial_neural_network
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Institution: Universiti Putra Malaysia
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Summary:Punching shear of flat slabs is a local, brittle failure that may occur before the more favourable ductile flexural failure. This study develops an artificial neural network (ANN) modelling for the prediction of punching shear strength of flat slabs using 281 test data available in the literature. The paper also evaluates the current design codes for the prediction of punching shear capacity of reinforced concrete flat slabs using the test results reported in the literature. Furthermore, a parametric study was conducted using the trained ANN to establish the trend of the main influencing variables on the punching shear capacity of flat slabs. The results were, then, employed to develop a simplified equation for the prediction of the characteristic/design punching shear strength of flat slabs based on the design assisted by testing approach proposed in Annex D of EN 1990.