Neural network modelling of RC deep beam shear strength

A 9 × 18 × 1 feed-forward neural network (NN) model trained using a resilient back-propagation algorithm and early stopping technique is constructed to predict the shear strength of deep reinforced concrete beams. The input layer covering geometrical and material properties of deep beams has nine neurons, and the corresponding output is the shear strength. Training, validation and testing of the developed neural network have been achieved using a comprehensive database compiled from 362 simple and 71 continuous deep beam specimens. The shear strength predictions of deep beams obtained from the developed NN are in better agreement with test results than those determined from strut-and-tie models. The mean and standard deviation of the ratio between predicted capacities using the NN and measured shear capacities are 1·028 and 0·154, respectively, for simple deep beams, and 1·0 and 0·122, respectively, for continuous deep beams. In addition, the trends ascertained from parametric study using the developed NN...

[1]  Jonathan Jingsheng Shi.  Clustering Technique for Evaluating and Validating Neural Network Performance , 2002 .

[2]  An Experimental Study on the Shear Behavior of Reinforced Concrete Deep Beams Subject to Concentrated Loads , 1999 .

[3]  Martin T. Hagan,et al.  Neural network design , 1995 .

[4]  Ashraf F. Ashour,et al.  Shear Capacity of Reinforced Concrete Deep Beams , 2000 .

[5]  W. M. Jenkins.  Neural network weight training by mutation , 2006 .

[6]  M. Asin.  The Behaviour of Reinforced Concrete Continuous Deep Beams , 2000 .

[7]  K. Tan,et al.  High-strength concrete deep beams with effective span and shear span variations , 1995 .

[8]  C. P. Siess,et al.  Strength and Behavior of Deep Beams in Shear , 1965 .

[9]  Ashraf F. Ashour,et al.  Effectiveness Factor of Concrete in Continuous Deep Beams , 1996 .

[10]  G. N. J. Kani,et al.  HOW SAFE ARE OUR LARGE REINFORCED CONCRETE BEAMS , 1967 .

[11]  Sung-Woo Shin,et al.  Shear Strength of Reinforced High-Strength Concrete Deep Beams , 2001 .

[12]  Ashraf Ashour,et al.  Concrete breakout strength of single anchors in tension using neural networks , 2005, Adv. Eng. Softw..

[13]  Kang Hai Tan,et al.  Direct Strut-and-Tie Model for Prestressed Deep Beams , 2001 .

[14]  Keun-Hyeok Yang,et al.  Influence of Shear Reinforcement on Reinforced Concrete Continuous Deep Beams , 2007 .

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

[16]  Joost Walravena,et al.  Size effects in short beams loaded in shear , 1994 .

[17]  R. Manuel,et al.  DEEP BEAM BEHAVIOR AFFECTED BY LENGTH AND SHEAR SPAN VARIATIONS , 1971 .

[18]  Kang Hai Tan,et al.  HIGH STRENGTH CONCRETE DEEP BEAMS SUBJECTED TO COMBINED TOP- AND BOTTOM-LOADING , 1997 .

[19]  Wei Wang,et al.  Shear Strength of Reinforced Concrete Deep Beams , 1993 .

[20]  WenN Bin Siao,et al.  Strut-and-Tie Model for Shear Behavior in Deep Beams and Pile Caps Failing in Diagonal Splitting , 1993 .

[21]  David M. Rogowsky,et al.  Tests of Reinforced Concrete Deep Beams , 1986 .

[22]  Peter Marti,et al.  BASIC TOOLS OF REINFORCED CONCRETE BEAM DESIGN , 1985 .

[23]  K. H. Tan,et al.  Shear Behavior of Large Reinforced Concrete Deep Beams and Code Comparisons , 1999 .

[24]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[25]  Shear Reinforcement in Reinforced Concrete Deep Beams , 1989 .

[26]  Geoffrey E. Hinton,et al.  Learning representations by back-propagation errors, nature , 1986 .

[27]  I. Babuska,et al.  Finite Element Analysis , 2021 .

[28]  Ashraf F. Ashour,et al.  Influence of section depth on the structural behaviour of reinforced concrete continuous deep beams , 2007 .

[29]  Ashraf F. Ashour,et al.  Tests of Reinforced Concrete Continuous Deep Beams , 1997 .

[30]  K. N. Smith,et al.  Shear Strength of Deep Beams , 1982 .

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

[32]  Kang Hai Tan,et al.  Main Tension Steel in High Strength Concrete Deep andShort Beams , 1997 .

[33]  Alternative design for the non-slender beam (deep beam) , 2002 .

[34]  Kang Hai Tan,et al.  Effect of Web reinforcement on high-strength concrete deep beams , 1997 .

[35]  Keun-Hyeok Yang,et al.  Shear characteristics of high-strength concrete deep beams without shear reinforcements , 2003 .

[36]  Kang Hai Tan,et al.  Size Effect on Shear Strength of Deep Beams: Investigating with Strut-and-Tie Model , 2006 .

[37]  F. Kong,et al.  WEB REINFORCEMENT EFFECTS ON DEEP BEAMS , 1970 .

[38]  W. M. Jenkins.  A truss analogy and neural network for reinforced concrete deep beam analysis , 2002 .

[39]  D. Griffin,et al.  Finite-Element Analysis , 1975 .

[40]  V. Ramakrishnan,et al.  Ultimate Strength of Deep Beams in Shear , 1968 .