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Structural Engineering and Mechanics
  Volume 47, Number 5, September10 2013 , pages 679-700
DOI: https://doi.org/10.12989/sem.2013.47.5.679
 


Neuro-fuzzy optimisation to model the phenomenon of failure by punching of a slab-column connection without shear reinforcement
Mariam Hafidi, Fattoum Kharchi and Abdelouhab Lefkir

 
Abstract
    Two new predictive design methods are presented in this study. The first is a hybrid method, called neuro-fuzzy, based on neural networks with fuzzy learning. A total of 280 experimental datasets obtained from the literature concerning concentric punching shear tests of reinforced concrete slab-column connections without shear reinforcement were used to test the model (194 for experimentation and 86 for validation) and were endorsed by statistical validation criteria. The punching shear strength predicted by the neuro-fuzzy model was compared with those predicted by current models of punching shear, widely used in the design practice, such as ACI 318-08, SIA262 and CBA93. The neuro-fuzzy model showed high predictive accuracy of resistance to punching according to all of the relevant codes. A second, more userfriendly design method is presented based on a predictive linear regression model that supports all the geometric and material parameters involved in predicting punching shear. Despite its simplicity, this formulation showed accuracy equivalent to that of the neuro-fuzzy model.
 
Key Words
    punching shear strength; slab-column connection; neuro-fuzzy system; size effect; linear regression; meta-heuristics method
 
Address
Mariam Hafidi, Fattoum Kharchi : Houari Boumedienne University (USTHB), Civil Engineering Faculty, Laboratory of Built in Environment (LBE), Bp 32 Bab Ezzouar 16111 Alger, Algeria
Abdelouhab Lefkir : Polytechnic National School (ENP), laboratory of construction and environment (LCE), 10, Avenue Hassen Badi EL Harrach, 16182, Alger, Algeria
 

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