Neural networks modeling of shear strength of SFRC corbels without stirrups

Based on developed semi-empirical characteristic equations an artificial neural network (ANN) model is presented to measure the ultimate shear strength of steel fibrous reinforced concrete (SFRC) corbels without shear reinforcement and tested under vertical loading. Backpropagation networks with Lavenberg-Marquardt algorithm is chosen for the proposed network, which is implemented using the programming package MATLAB. The model gives satisfactory predictions of the ultimate shear strength when compared with available test results and some existing models. Using the proposed networks results, a parametric study is also carried out to determine the influence of each parameter affecting the failure shear strength of SFRC corbels with wide range of variables. This shows the versatility of ANNs in constructing relationship among multiple variables of complex physical relationship.

[1]  Okan Karahan,et al.  Predicting the compressive strength of ground granulated blast furnace slag concrete using artificial neural network , 2009, Adv. Eng. Softw..

[2]  Hong-Guang Ni,et al.  Prediction of compressive strength of concrete by neural networks , 2000 .

[3]  H. L. Cox.  The elasticity and strength of paper and other fibrous materials , 1952 .

[4]  Moncef L. Nehdi,et al.  Predicting shear capacity of NSC and HSC slender beams without stirrups using artificial intelligence , 2005 .

[5]  R. Swamy,et al.  DEFORMATION AND ULTIMATE STRENGTH IN FLEXURE OF REINFORCED CONCRETE BEAMS MADE WITH STEEL FIBER CONCRETE , 1981 .

[6]  B. P. Hughes,et al.  Ductility of Reinforced Concrete Corbels Containing Either Steel Fibers or Stirrups , 1989 .

[7]  Anthony T. C. Goh,et al.  Modeling the Capacity of Pin-Ended Slender Reinforced Concrete Columns Using Neural Networks , 1998 .

[8]  Muhammad N. S Hadi.  Neural networks applications in concrete structures , 2003 .

[9]  Kazuhiko Kawashima,et al.  Neural Network Modeling of Confined Compressive Strength and Strain of Circular Concrete Columns , 2003 .

[10]  B. P. Hughes,et al.  REINFORCED STEEL FIBER CONCRETE CORBELS WITH VARIOUS SHEAR SPAN-TO-DEPTH RATIOS , 1989 .

[11]  Wang Ji-Zong,et al.  The application of automatic acquisition of knowledge to mix design of concrete , 1999 .

[12]  Aly Marei Said,et al.  Predicting Shear Capacity of NSC and HSC Slender Beams Using Artificial Intelligence , 2005 .

[13]  F. Demir.  Prediction of elastic modulus of normal and high strength concrete by artificial neural networks , 2008 .

[14]  Maria Q. Feng,et al.  Application of neural networks for estimation of concrete strength , 2002 .

[15]  Seung Chang Lee,et al.  Development of the approximate analytical model for the stub-girder system using neural networks , 2001 .

[16]  Antoni Cladera,et al.  Experimental study on high-strength concrete beams failing in shear , 2005 .

[17]  Abhijit Mukherjee,et al.  Application of artificial neural networks in structural design expert systems , 1995 .

[18]  İlker Bekir Topçu,et al.  Prediction of properties of waste AAC aggregate concrete using artificial neural network , 2007 .

[19]  Seung-Chang Lee,et al.  Prediction of concrete strength using artificial neural networks , 2003 .

[20]  P HughesB,et al.  Reinforced steel and polypropylene fibre concrete corbel tests. , 1989 .

[21]  Anthony T. C. Goh,et al.  Prediction of Ultimate Shear Strength of Deep Beams Using Neural Networks , 1995 .

[22]  I. Yeh.  Modeling Concrete Strength with Augment-Neuron Networks , 1998 .

[23]  Thore Hagberg,et al.  Design of Concrete Brackets: On the Application of the Truss Analogy , 1983 .

[24]  Mustafa Saridemir,et al.  Prediction of compressive strength of concretes containing metakaolin and silica fume by artificial neural networks , 2009, Adv. Eng. Softw..

[25]  N. I. Fattuhi.  Column‐Load Effect on Reinforced Concrete Corbels , 1990 .

[26]  Antoni Cladera,et al.  Shear design procedure for reinforced normal and high-strength concrete beams using artificial neural networks. Part II: beams with stirrups , 2004 .

[27]  Jamal A. Abdalla,et al.  Modeling and simulation of shear resistance of R/C beams using artificial neural network , 2007, J. Frankl. Inst..

[28]  T. Paulay,et al.  Reinforced Concrete Structures , 1975 .

[29]  B. V. Venkatarama Reddy,et al.  Prediction of compressive strength of SCC and HPC with high volume fly ash using ANN , 2009 .

[30]  Saurabh Ghosh,et al.  Effective wire spacing in steel fibre reinforced concrete , 1987 .

[31]  Janette B. Bradley,et al.  Neural networks: A comprehensive foundation: S. HAYKIN. New York: Macmillan College (IEEE Press Book) (1994). v + 696 pp. ISBN 0-02-352761-7 , 1995 .

[32]  Hiroshi Mutsuyoshi,et al.  Artificial neural networks for the prediction of shear capacity of steel plate strengthened RC beams , 2004 .

[33]  Hashim M. S. Abdul-Wahab,et al.  Strength of Reinforced Concrete Corbels With Fibers , 1989 .

[34]  Leonard Ziemiański,et al.  Neural networks in mechanics of structures and materials – new results and prospects of applications , 2001 .

[35]  Sundaramoorthy Rajasekaran,et al.  Predictions of design parameters in civil engineering problems using SLNN with a single hidden RBF neuron , 2002 .

[36]  Murat Dicleli,et al.  Predicting the shear strength of reinforced concrete beams using artificial neural networks , 2004 .

[37]  Shailendra Kumar,et al.  Shear strength of reinforced steel fibrous concrete corbels without shear reinforcement , 2004 .

[38]  Ian Flood,et al.  Rapid analysis of externally reinforced concrete beams using neural networks , 2001 .

[39]  Artur Dubrawski,et al.  HPC Strength Prediction Using Artificial Neural Network , 1995 .

[40]  G. Trtnik,et al.  Prediction of concrete strength using ultrasonic pulse velocity and artificial neural networks. , 2009, Ultrasonics.

[41]  Kang Su Kim,et al.  Knowledge-based prediction of shear strength of concrete beams without shear reinforcement , 2008 .

[42]  Mehmet Polat Saka,et al.  PREDICTION OF ULTIMATE SHEAR STRENGTH OF REINFORCED-CONCRETE DEEP BEAMS USING NEURAL NETWORKS , 2001 .

[43]  N. I. Fattuhi,et al.  Strength of SFRC Corbels Subjected to Vertical Load , 1990 .

[44]  Andres Winston C. Oreta,et al.  Simulating size effect on shear strength of RC beams without stirrups using neural networks , 2004 .