Paper Information

Journal:   ASIAN JOURNAL OF CIVIL ENGINEERING (BUILDING AND HOUSING)   2017 , Volume 18 , Number 2; Page(s) 285 To 309.
 
Paper:  PREDICTION OF PUNCHING SHEAR CAPACITY OF RC FLAT SLABS USING ARTIFICIAL NEURAL NETWORK
 
Author(s):  SAFIEE N.A.*, ASHOUR A.
 
* DEPARTMENT OF CIVIL ENGINEERING, UNIVERSITY PUTRA MALAYSIA, 43400 SERDANG, SELANGOR
 
Abstract: 

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.

 
Keyword(s): PUNCHING SHEAR, FLAT SLABS, SLAB-COLUMN CONNECTIONS, NEURAL NETWORK