Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 30172
Prediction of Compressive Strength of Self- Compacting Concrete with Fuzzy Logic

Authors: Paratibha Aggarwal, Yogesh Aggarwal

Abstract:

The paper presents the potential of fuzzy logic (FL-I) and neural network techniques (ANN-I) for predicting the compressive strength, for SCC mixtures. Six input parameters that is contents of cement, sand, coarse aggregate, fly ash, superplasticizer percentage and water-to-binder ratio and an output parameter i.e. 28- day compressive strength for ANN-I and FL-I are used for modeling. The fuzzy logic model showed better performance than neural network model.

Keywords: Self compacting concrete, compressive strength, prediction, neural network, Fuzzy logic.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1330501

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1910

References:


[1] M. Pala, E. Ozbay, A. Oztas, and M.I. Yuce, "Appraisal of long-term effects of fly ash and silica fume on compressive strength of concrete by neural networks", Construction and Building Materials, 2007, vol. 21(2), pp. 384-394.
[2] A. Shigdi, and L.A. Gracia, "Parameter estimation in ground-water hydrology using artificial neural networks",. J Comput Civ Eng, 2003, vol.17(4), pp. 281-289.
[3] J.L. Rogers, "Simulating structural analysis with neural network", J Comput Civ Eng, 1994, vol. 8(2), pp.252-265.
[4] J. Kasperkiewicz, J. Rach, and A. Dubrawski, "HPC strength prediction using Artificial neural network", J Compu Civ Eng, 1995, vol. 9(4), pp. 279-284.
[5] J.W. Oh, J.T. Kim, and G.W. Lee, "Application of neural networks for proportioning of concrete mixes", ACI Mater J, 1999, vol. 96(1), pp. 61- 67.
[6] S. Lai, and M. Serra, "Concrete strength prediction by means of neural network", Const Build Mater, 1997, vol. 11(2), pp. 93-98.
[7] I.C. Yeh, "Modeling Concrete strength Using Augment-Neuron Network", J Mater Civ Eng, Nov. 1998a, vol.10 (4).
[8] I.C. Yeh, "Modeling of Strength of High-Performance Concrete Using Artificial Neural Networks", Cem Concr Res, 1998b, vol. 28(12), pp.1797-1808.
[9] I.C. Yeh, "Design of High-Performance Concrete Mixture Using Neural Networks And Nonlinear Programming", J Comp Civ Eng, Jan. 1999, vol.13(1).
[10] M. Sebastia, I.F. Olmo, and A. Irabien, "Neural network prediction of unconfined compressive strength of coal fly ash-cement mixtures", Cem Concr Res, 2003, vol. 33, pp. 1137-1146.
[11] J.I. Kim, D.K. Kim, M.Q. Feng, and F. Yazdani, "Application of Neural Networks for Estimation of Concrete Strength", J. Mater Civ Eng, 2004, vol.16 (3), pp. 257-264.
[12] W.P.S. Dias, and S.P. Pooliyadda, "Neural networks for predicting properties of concretes with Admixtures", Const Build Mater, 2001, vol.15, pp. 371-379.
[13] N. Hong-Guang, and W. Ji-Zong, "Prediction of compressive strength of concrete by neural networks", Cem Concr Res, 2000, vol. 3(8), pp.1245- 1250.
[14] L.Q. Ren, and Z.Y. Zhao, "An Optimal Neural Network and Concrete Strength modeling", J Adv Eng Software, 2002, vol. 33, pp. 117-130.
[15] S. Lee, "Prediction of concrete strength using artificial neural networks", Engg Struct, 2003, vol.25 (7), pp. 849-857.
[16] M. Nehdi, H.E. Chabib, and M.H.E. Naggar, "Predicting performance of self-compacting concrete mixtures using artificial neural networks", ACI Mater J, 2001, vol. 98(5), pp. 394-401.
[17] M. Sonebi, "Application of Statistical models in proportioning medium strength self-consolidating concrete", ACI Mater J, 2004, vol. 101(5), pp. 339-346.
[18] M. Sonebi, "Medium strength self-compacting concrete containing fly ash: Modelling using factorial experimental plans", Cem Concr Res, 2004, vol. 34(7), pp. 1199-1208.
[19] L.A. Zadeh, "Fuzzy Sets", Information and Control, 1965, vol. 8, pp. 338-353.
[20] F. Demir, "Prediction of compressive strength of concrete using ANN and Fuzzy logic", Cement and Concrete Research, 2005, vol. 35, pp. 1531-1538.
[21] Z. S_en, "Combining Back propagations and Genetic Algorithms to train to train neural networks for Ambient Temperature Modelling", Solar Energy, 1998 vol. 63 (1), pp. 39-49.
[22] E.H. Mamdani, "Fuzzy Logic control of aggregate production planning", S. Assilian, International Journal of Man-Machine Studies, 1975, vol. 7, pp. 1-13.
[23] K.M. Passino, "Stable Fuzzy Logic design of point to point control for mechanical systems", S. Yurkovich, Fuzzy Control, Addison-Wesley, 1998.
[24] D.W.C. Ho, and P.A. Zhang, "Design of Fuzzy Wavelet Neural Networks using the GA approach for function approximation and system identification", J. Xu, IEEE Transactions on Fuzzy Systems, 2001, vol. 9, pp. 200-211.
[25] F.M. McNeill, "Application of Fuzzy Logic in Interior Daylight Estimation", E. Thro, Fuzzy Logic: A Practical Approach, AP Professional, Boston, MA, 1994.
[26] G. Inan, and A.B. Goktepe, "Prediction of sulfate expancion of PC mortar using adaptive neuro-fuzzy methodology", K. Ramyar, A. Sezer, Building and Environment, 2007 vol. 42 (3), pp. 1264-1269.
[27] M. Sugeno, and G.T. Kang, "Fuzzy Sets Systems Man and Cybernetics", 1993, vol. 23 (3), pp. 665-685.
[28] T. Takagi, and M. Sugeno, "IEEE Transactions on Systems Man and Cybernetics", 1985, vol. 15, pp. 116-132.
[29] J.S.R. Jang, and C.T. Sun, Proceedings of the IEEE 83 (1995) 378-405.
[30] S. Akbulut, A.S. Hasilog¢lu, and S. Pamukcu, Soil Dynamics and Earthquake Engineering, 24 (2004) 805-814.
[31] N. Bouzoubaa, and M. Lachemi, "Self-Compacting concrete incorporating high volumes of class F fly ash Preliminary results", Cem Concr Res, 2001, vol. 31, pp. 413-420.
[32] V.K. Bui, Y. Akkaya, and S.P. Shah, "Rheological Model for selfconsolidating concrete", ACI Mater J, 2002, vol. 99(6), pp. 549-559.
[33] R. Patel, K.M.A. Hossain, S. Shehata, N. Bouzoubaa, and M. Lachemi, "Development of statistical models for mixture design of high-volume fly ash self-consolidation concrete", ACI Mater J, 2004, vol. 101(4), pp. 294-302.