Neuro-fuzzy optimisation to model the phenomenon of failure by punching of a slab-column connection without shear reinforcement

被引：4

作者：

Hafidi, Mariam ^{[1
]}

Kharchi, Fattoum ^{[1
]}

Lefkir, Abdelouhab ^{[2
]}

机构：

[1] Houari Boumedienne Univ USTHB, Fac Civil Engn, Lab Built Environm, Bab Ezzouar 16111, Alger, Algeria

[2] Polytech Natl Sch ENP, Lab Construct & Environm LCE, Badi El Harrach 16182, Alger, Algeria

来源：

STRUCTURAL ENGINEERING AND MECHANICS | 2013年 / 47卷 / 05期

关键词：

punching shear strength; slab-column connection; neuro-fuzzy system; size effect; linear regression; meta-heuristics method; CONCRETE SLABS; STRENGTH; BEAMS; NETWORKS; CAPACITY; PREDICTION;

D O I：

10.12989/sem.2013.47.5.679

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

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 user-friendly 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.

引用

页码：679 / 700

页数：22

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