Neural networks modeling of shear strength of SFRC corbels without stirrups

Applied Soft Computing Journal

Volumn 10, Issue 1, 2010, Pages 135-148

  Kumar, Shailendra ^a,b   Barai, S V ^b  

^a NATIONAL INSTITUTE OF TECHNOLOGY   (India)

^b INDIAN INSTITUTE OF TECHNOLOGY   (India)

Author keywords

Artificial neural network; Fiber reinforced concrete; Reinforced concrete corbels; Shear strength; Stirrups

Indexed keywords

ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORK MODELS; BACKPROPAGATION NETWORK; CHARACTERISTIC EQUATION; FIBER REINFORCED CONCRETE; LAVENBERG-MARQUARDT ALGORITHM; PARAMETRIC STUDY; PROGRAMMING PACKAGES; SATISFACTORY PREDICTIONS; SEMI-EMPIRICAL; SHEAR REINFORCEMENT; STIRRUPS; TEST RESULTS; ULTIMATE SHEAR STRENGTH; VERTICAL LOADINGS;

BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; BUILDING MATERIALS; CONCRETE BUILDINGS; MATLAB; NEURAL NETWORKS; REINFORCED CONCRETE; REINFORCEMENT;

SHEAR STRENGTH;

EID: 70350097446     PISSN: 15684946     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.asoc.2009.06.012     Document Type: Article

References (50)

1. Abdul-Wahab H.M.S. Strength of reinforced concrete corbels with fibers. ACI Structural Journal 86 1 (1989) 60-66
2. ACI Committee 544, Design considerations for steel fiber reinforced concrete (ACI 544.4R-88), ACI Structural Journal 85(5) (1988) 563-580.
3. ACI Committee 318, Building code requirements for reinforced concrete (ACI 318-95), American Concrete Institute, Detroit, MI 48219, 1995.
4. Abdallaa J.A., Elsanosib A., and Abdelwahab A. Modeling and simulation of shear resistance of R/C beams using artificial neural network. Journal of the Franklin Institute 344 (2007) 741-756
5. Adhikary B.B., and Mutsuyoshi H. Artificial neural networks for the prediction of shear capacity of steel plate strengthened RC beams. Construction and Building Materials 18 (2004) 409-417
6. Bilim C., Atis C.D., Tanyildizi H., and Karahan O. Predicting the compressive strength of ground granulated blast furnace slag concrete using artificial neural network. Advances in Engineering Software 40 (2009) 334-340
7. El-Chabib H., Nehdi M., and Said A. Predicting shear capacity of NSC and HSC slender beams without stirrups using artificial intelligence. Computers and Concrete 2 1 (2005) 79-96
8. Chuang P.H., Goh A.T.C., and Wu X. Modeling the capacity of pin-ended slender reinforced concrete columns using neural network. Journal of Structural Engineering ASCE 124 7 (1998) 830-838
9. 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) 917-926
10. Cladera A., and Mari A.R. Shear design procedure for reinforced normal and high-strength concrete beams using artificial neural networks. Part II. Beams with stirrups. Engineering Structures 26 (2004) 927-936
11. Cladera A., and Mari A.R. Experimental study on high-strength concrete beams failing in shear. Engineering Structures 27 (2005) 1519-1527
12. Cox H.L. The elasticity and strength of paper and other fibrous materials. British Journal of Applied Physics 3 (1952) 72-79
13. Demir F. Prediction of elastic modulus of normal and high strength concrete by artificial neural networks. Construction and Building Materials 22 (2008) 1428-1435
14. Demuth H., and Beale M. Neural Network Toolbox User's Guide (1998), The Mathworks Inc.
15. Fattuhi N.I. Corbels with shear reinforcement in the form of stirrups or fibres. Proceedings third RILEM International Symposium on Development of Fibre Reinforced Cement and Concrete, vol. 2 (1986), University of Sheffield, July paper No. 8.8
16. Fattuhi N.I. Column-load effect on reinforced concrete corbels. Journal of Structural Engineering ASCE 116 1 (1990) 188-197
17. Fattuhi N.I. Strength of SFRC corbels subjected to vertical load. Journal of Structural Engineering ASCE 116 3 (1990) 701-718
18. Fattuhi N.I., and Hughes B.P. Reinforced steel fiber concrete corbel with various shear span-to-depth ratios. ACI Materials Journal 86 6 (1989) 590-596
19. Fattuhi N.I., and Hughes B.P. Ductility of reinforced concrete corbels containing either steel fibers or stirrups. ACI Structural Journal 86 6 (1989) 644-651
20. Flood I., Muszynski L., and Nandy S. Rapid analysis of externally reinforced concrete beams using neural networks. Computers and Structures 79 (2001) 1553-1559
21. Ghosh S., Bhattacharya C., and Ray S.P. Effective wire spacing in steel fibre reinforced concrete. Journal the Institution of Engineers (India) CI 69 (1989) 222-227
22. Goh A.T.C. Prediction of ultimate shear strength of deep beams using neural networks. ACI Structural Journal 92 1 (1995) 28-32
23. Guang N.H., and Zong W.J. Prediction of compressive strength of concrete by neural networks. Cement and Concrete Research 30 (2000) 1245-1250
24. Hadi M.N.S. Neural networks applications in concrete structures. Computers and Structures 81 (2003) 373-381
25. Hagberg T. Design of concrete brackets: on the application of the truss analogy. ACI Journal 80 1 (1983) 3-12
26. Haykin S. Neural Network: A Comprehensive Foundation. 2nd ed. (2004), Prentice-Hall of India Private Limited, New Delhi, India
27. Hughes B.P., and Fattuhi N.I. Reinforced steel and polypropylene fiber concrete corbel tests. The Structural Engineer London 67 4 (1989) 68-72
28. Ji-Zong W., Ni H.G., and Jin-Yun H. The application of automatic acquisition of knowledge to mix design of concrete. Cement and Concrete Research 29 (1999) 1875-1880
29. Jung S., and Kim K.S. Knowledge-based prediction of shear strength of concrete beams without shear reinforcement. Engineering Structures 30 (2008) 1515-1525
30. Kasperkiewicz J., Racz J., and Dubrawski A. HPC strength prediction using artificial neural network. Journal of Computing in Civil Engineering ASCE 9 4 (1995) 279-284
31. Kim J.I., Kim D.K., Feng M.Q., and Yazdani F. Application of neural networks for estimation of concrete strength. Journal of Materials in Civil Engineering ASCE 16 3 (2004) 257-264
32. Kumar S. Shear strength of reinforced fibrous concrete corbels without shear reinforcement. Journal the Institution of Engineers (India) 85 (2004) 202-212
33. Lee S.-C. Prediction of concrete strength using artificial neural networks. Engineering Structures 25 (2003) 849-857
34. Lee S.C., Park S.K., and Lee B.H. Development of the approximate model for the stub-girder system using neural network. Computers and Structures 79 (2001) 1013-1025
35. Mansour M.Y., Dicleli M., Lee J.Y., and Zhang J. Predicting the shear strength of reinforced concrete beams using artificial neural networks. Engineering Structures 26 (2004) 781-799
36. Mukherjee A., and Deshpande J.M. Application of artificial neural networks in structural design expert systems. Computers and Structures 54 3 (1995) 367-375
37. Oreta A.W.C., and Kawashima K. Neural network modeling of confined compressive strength and strain of circular concrete columns. Journal of Structural Engineering ASCE 129 4 (2003) 554-581
38. Oreta A.W.C. Simulating Size effect on shear strength of RC beams without stirrups using neural network. Engineering Structures 26 (2004) 681-691
39. Park P., and Paulay T. Reinforced Concrete Structures (1975), A Wiley-Interscience Publication, John Wiley & Sons, New York
40. Paswan K., Kumar S., and Ray S.P. Shear strength of reinforced fibrous concrete beams without web reinforcement. Journal of the Bridge and Structural Engineer, Indian National group of IABSE, New Delhi 30 3 (2000) 17-29
41. Raghu Prasad B.K., Eskandari H., and Reddy B.V.V. Prediction of compressive strength of SCC and HPC with high volume fly ash using ANN. Construction and Building Materials 23 (2009) 117-128
42. Rajasekaran S., and Amalraj R. Predictions of design parameters in civil engineering problems using SLNN with a single hidden RBF neuron. Computers and Structures 80 (2002) 2495-2505
43. Sanad A., and Saka M.P. Prediction of ultimate shear strength of reinforced concrete deep beams using neural networks. Journal of Structural Engineering ASCE 127 7 (2001) 818-828
44. Sari{dotless}demir M. Prediction of compressive strength of concretes containing metakaolin and silica fume by artificial neural networks. Advances in Engineering Software 40 (2009) 350-355
45. Soroushian P., and Lee C.D. Constitutive modeling of steel fibre reinforced concrete under direct tension and compression. Proceedings of the International Conference on Recent Development in Fibre Reinforced Cement and Concrete. Cardiff (1989) 363-377
46. Swamy R.N., and Al-Ta'an S.A. Deformation and ultimate strength in flexure of reinforced concrete beams made with steel fibres concrete. ACI Journal Title 78 36 (1981) 395-405
47. Trtnik G., Kavčič F., and Turk G. Prediction of concrete strength using ultrasonic pulse velocity and artificial neural networks. Ultrasonics 49 (2009) 53-60
48. Topçu I.B., and Sari{dotless}demir M. Prediction of properties of waste AAC aggregate concrete using artificial neural network. Computational Materials Science 41 (2007) 117-125
49. Waszczyszyn Z., and Ziemiański L. Neural networks in mechanics of structures and materials-new results and prospects of applications. Computers and Structures 79 (2001) 2261-2276
50. Yeh I.-C. Modeling concrete strength with augment-neuron networks. Journal of Materials in Civil Engineering ASCE 10 4 (1998) 263-268