American Journal of Civil Engineering and Architecture
ISSN (Print): 2328-398X ISSN (Online): 2328-3998 Website: Editor-in-chief: Dr. Mohammad Arif Kamal
Open Access
Journal Browser
American Journal of Civil Engineering and Architecture. 2013, 1(4), 75-81
DOI: 10.12691/ajcea-1-4-2
Open AccessArticle

Prediction of Ultimate Shear Capacity of Reinforced Normal and High Strength Concrete Beams Without Stirrups Using Fuzzy Logic

Abdulkhaliq Abdulyimah Jaafer1,

1Civil Engineering Department, College of Engineering, Misan University, Misan, Iraq

Pub. Date: May 26, 2013

Cite this paper:
Abdulkhaliq Abdulyimah Jaafer. Prediction of Ultimate Shear Capacity of Reinforced Normal and High Strength Concrete Beams Without Stirrups Using Fuzzy Logic. American Journal of Civil Engineering and Architecture. 2013; 1(4):75-81. doi: 10.12691/ajcea-1-4-2


The main objective of the present study is to predict the ultimate shear capacity of reinforced concrete beams no contains web reinforcement. Fuzzy inference system (FIS) was developed to predict the shear strength of these beams using Mamadani method. Fuzzy inference system (FIS) model has been proved to be very effective in predicting the ultimate shear strength of concrete beams without stirrups. The regression analysis between the output of the FIS model and the corresponding target, R2 = 0.9969 and 0.9509 for training and testing data, respectively. Based on FIS results, a parametric analysis was carried out to study the influence of each parameter affecting the shear strength of beams without stirrups and these results are compared with the provisions of ACI-code.

high strength concrete fuzzy inference system shear strength

Creative CommonsThis work is licensed under a Creative Commons Attribution 4.0 International License. To view a copy of this license, visit


Figure of 16


[1]  Cladera, A., and Mari, A. R., "Shear design procedure for reinforced normal and high-strength concrete beams using artificial neural networks. Part I: beams without stirrups", Engineering Structures, 26, 2004, pp. 917-926.
[2]  Collins M.P., and Kuchma, D.,"How safe are our large, lightly reinforced concrete beams, slabs and footings", ACI Struct J, 96 (4), 1999, pp. 482-490.
[3]  Fujita M, Sato R, Matsumoto K, Takaki Y. ,"Size effect on shear capacity of RC Beams using HSC without shear reinforcement", Proc. 6th Int Sympon Utilization of HS/HP Concrete. 2002, pp. 235-45.
[4]  Paratibha, A. and Yogesh, A., "Prediction of compressive strength of self compacting concrete with fuzzy logic", World Academic Science, Engineering and Technology, 77, 2011, pp. 847-854.
[5]  Fa-Liang, G., "A new way of predicting cement strength - fuzzy logic", Cement and Concrete Research, 27, 6, 1997, pp. 883-888.
[6]  Akkurt, S., Tayfurb, G., and Can, S., "Fuzzy logic model for the prediction of cement compressive strength", Cement and Concrete Research, 34, 2004, pp. 1429-1433.
[7]  Demir, F., "A new way of prediction elastic modulus of normal and high strength concrete-fuzzy logic", Cement and Concrete Research, 35, 2005, pp. 1531-1538.
[8]  Nataraja, M.C., Jayaram, M.A., and Ravikumar, C.N., "Prediction of early strength of concrete: a fuzzy inference system model", International Journal of Physical Sciences, Vol. 1, 2, 2006, pp. 047-056.
[9]  Unala, O., Demir, F., and Uygunoglua, T., "Fuzzy logic approach to predict stress–strain curves of steel fiber-reinforced concretes in compression", Building and Environment, 42, 2007, pp. 3589-3595.
[10]  Topcu,I.B., and Saridemir, M., "Prediction of rubberized concrete properties using artificial neural network and fuzzy logic", Construction and Building Materials, 22, 2008, pp. 532-540.
[11]  Ozcan, F., Atis, C.D., Karahan, O., Uncuoglu, U., and Tanyildizi, H., "Comparison of artificial neural network and fuzzy logic models for prediction of long-term compressive strength of silica fume concrete", Advances in Engineering Software, 40, 2009, pp. 856-863.
[12]  American Concrete Institute (ACI), "Building code requirements for structural concrete" ACI 318-08, American Concrete Institute, Detroit, 2008.
[13]  Zadeh, L.A., "From circuit to system theory", Roc. of Institute of Ratio Eng., Vol. 50, 1962, pp. 856-865.
[14]  Zadeh, L.A., "Fuzzy sets", Journal of Information and Control, 8, 1965, pp. 338-353.
[15]  Kirschfink, H., and Lieven, K., "Basic tools for fuzzy modeling", Liebigstrasse 20, D-52070, Aachen, Germany, 2000.
[16]  Fuzzy Logic Toolbox User's Guide: for Use with MATLAB, 2012.
[17]  Karl, H. R., Daniel, A. K., Kang, S. K., and Sina, M., "Shear database for reinforced concrete members without shear reinforcement," ACI Structural Journal, V.100, No.2, 2003, pp.240-249.