Browse > Article
http://dx.doi.org/10.12989/sss.2014.14.5.785

An evolutionary fuzzy modelling approach and comparison of different methods for shear strength prediction of high-strength concrete beams without stirrups  

Mohammadhassani, Mohammad (Department of Structural Engineering, University of Malaya)
Nezamabadi-pour, Hossein (Department of Electrical Engineering, Shahid Bahonar University of Kerman)
Suhatril, Meldi (Department of Civil Engineering, University of Malaya)
shariati, Mahdi (Department of Structural Engineering, University of Malaya)
Publication Information
Smart Structures and Systems / v.14, no.5, 2014 , pp. 785-809 More about this Journal
Abstract
In this paper, an Adaptive nerou-based inference system (ANFIS) is being used for the prediction of shear strength of high strength concrete (HSC) beams without stirrups. The input parameters comprise of tensile reinforcement ratio, concrete compressive strength and shear span to depth ratio. Additionally, 122 experimental datasets were extracted from the literature review on the HSC beams with some comparable cross sectional dimensions and loading conditions. A comparative analysis has been carried out on the predicted shear strength of HSC beams without stirrups via the ANFIS method with those from the CEB-FIP Model Code (1990), AASHTO LRFD 1994 and CSA A23.3 - 94 codes of design. The shear strength prediction with ANFIS is discovered to be superior to CEB-FIP Model Code (1990), AASHTO LRFD 1994 and CSA A23.3 - 94. The predictions obtained from the ANFIS are harmonious with the test results not accounting for the shear span to depth ratio, tensile reinforcement ratio and concrete compressive strength; the data of the average, variance, correlation coefficient and coefficient of variation (CV) of the ratio between the shear strength predicted using the ANFIS method and the real shear strength are 0.995, 0.014, 0.969 and 11.97%, respectively. Taking a look at the CV index, the shear strength prediction shows better in nonlinear iterations such as the ANFIS for shear strength prediction of HSC beams without stirrups.
Keywords
ANFIS; shear strength; HSC beams; tensile reinforcement ratio; shear span to depth ratio; concrete compressive strength;
Citations & Related Records
Times Cited By KSCI : 5  (Citation Analysis)
연도 인용수 순위
1 Ahmed, S.H and Lue, D.M. (1987), "Flexure-shear interaction of reinforced high-strength concrete beams", ACI Struct. J., 330-341.
2 Abraham, A. (2005), Rule-based expert systems, Sydenham PH, Thorn R Handbook of measuring system design, Wiley, New York.
3 ACI. (2008), American Concrete Institute, Detroit, Vol. ACI Committee 318.
4 Ahmad, S.H., Khaloo, A.R. and Poveda, A. (1986), "Shear capacity of reinforced concrete beams", ACI J., 82, 297-305.
5 Ali, S. (2001), Flexural and shear behavior of high-strength concrete beams, MSc Thesis, Taxila University.
6 Berg F.J. (1962), "Shear strength of reinforced concrete beams without web reinforcement", ACI J., 59, 1587-1599.
7 Bukhari, I.A. and Ahmad, S. (2007), "Evaluation of shear strength of high-strength concrete beams without Stirrups", Arabian J. Sci. Eng., 33, 321-336.
8 Choi, K.K., Sherif, A.G., Reda Taha, M.M. and Chung, L. (2009), "Shear strength of slender reinforced concrete beams without web reinforcement: A model using fuzzy set theory", Eng Struct., 31, 768-777.   DOI   ScienceOn
9 Clair, A. and Sinha, S. (2011), "Development and the comparison of a weighted factor and fuzzy inference model for performance prediction of metallic water pipelines", Proceedings of the Pipelines, 24-32. doi: 10.1061/41187(420)3   DOI
10 Elahi, A. (2003), Effect of reinforcement ratio and shear span on shear strength of high-strength concrete beams, MSc Thesis, Taxila University.
11 Herrera, F. and Lozano, M. (2003), "Fuzzy adaptive genetic algorithm: design, taxonomy, and future directions", Soft Comput., 7, 545-562.   DOI   ScienceOn
12 Jang, J.S.R. (1993), "ANFIS: Adaptive network based fuzzy inference system", IEEE T. Syst. Man Cy., 23(3), 665-685.   DOI   ScienceOn
13 Gopalakrishnan, K. and Ceylan, H. (2009), "Adaptive neuro-fuzzy inference system-based backcalculation approach to airport pavement structural analysis", Proceedings of the Material Design, Construction, Maintenance, and Testing of Pavements, 9-16.doi: 10.1061/41045(352)2   DOI
14 Hakim, S.J.S., Noorzaei, J., Jaafar, M.S., Jameel, M. and Mohammadhassani, M. (2011), "Application of artificial neural networks to predict compressive strength of high strength concrete", Int. J. Phys. Sci., 6(5), 975-981.
15 Kani, G.N.J. (1964), "The riddle of shear failure and its solution", ACI J., 61, 441-467.
16 Khan, M., Rossow, E. and Shah, S. (2000), "Shear design of high strength concrete beams", Adv. Technol. Struct. Eng., 1-9. doi: 10.1061/40492(2000)167 .
17 Li, L., Song, G. and Ou, J. (2013), "A nonlinear structural experiment platform with adjustable plastic hinges: analysis and vibration control", Smart Struct. Syst., 11(3), 315-329.   DOI   ScienceOn
18 Lee, J.Y. and Kim, U.Y. (2008), "Effect of longitudinal tensile reinforcement ratio and shear span-depth ratio on minimum shear reinforcement in beams", ACI Struct. J., 105(2), 134-144.
19 Mamdani, E. and Assilian, S. (1975), "An experiment in linguistic synthesis with a fuzzy logic controller", Int. J. Man Mach. Stud., 7(1), 1-13.   DOI   ScienceOn
20 Mashrei Mohammed, A , Nabeel, A., Y, A.T. and M.S, R. (2010), "Neural networks model and adaptive neuro-fuzzy inference system for predicting the moment capacity of ferrocement members", Eng. Struct., 32(6), 1723-1724.   DOI   ScienceOn
21 Mohammadhassani, M., Jumaat, M.Z., Chemrouk, M., Maghsoudi, A.A., Jameel, M. and Akib, S. (2011), "An experimental investigation on bending stiffness and neutral axis depth variation of over-reinforced high strength concrete beams", Nucl. Eng. Des., 241(6), 2060-2067..   DOI   ScienceOn
22 Mohammadhassani, M., Nezamabadi-pour, H. Jumaat, M.Z., Jameel, M. and Arumugam, A.M.S. (2013c), "Application of artificial neural networks (ANNs) and linear regressions (LR) to predict the deflection of concrete deep beams", Comput. Concrete, 11(3), 237-252.   DOI   ScienceOn
23 Mohammadhassani, M., Nezamabadi-Pour, H., Jumaat, M.Z., Jameel, M., Hakim, S.J.S. and Zargar, M. (2013), "Application of the ANFIS model in deflection prediction of concrete deep beams", Struct. Eng. Mech., 45(3), 323-336.   DOI   ScienceOn
24 Mohammadhassani, M., Nezamabadi-pour, H., Suhatril, M. and Shariati, M. (2013a), "Identification of a suitable ANN architecture in predicting strain in tie section of concrete deep beams", Struct. Eng. Mech., 46(6), 853-868. DOI: http://dx.doi.org/10.12989/sem.2013.46.6.853   과학기술학회마을   DOI   ScienceOn
25 Mohammadhassani, M., Nezamabadi-pour, H., Jameel, M. and Karim, G. (2013b), "Applications of the ANFIS and LR in the prediction of strain in tie section of concrete deep beams", Comput. Concrete, 12(3), 243-259. DOI: http://dx.doi.org/10.12989/cac.2013.12.3.243   과학기술학회마을   DOI   ScienceOn
26 Sun, B. and Qiu, Y. (2010), "Fuzzy expert system for flexible pavements crack performance prediction", ICLEM 2010, 2415-2421. doi: 10.1061/41139(387)337   DOI
27 Ren, L., Xiang, X. and Ni, J. (2011). "Forecast modeling of monthly runoff with adaptive neural fuzzy inference system and wavelet analysis", J. Hydrol. Eng., 10.1061/(ASCE)HE.1943-5584.0000514 (Sep. 28, 2011).   DOI
28 Shiri, J., Makarynskyy, O., Kisi, O., Dierickx, W. and Fard, A. (2011). "Prediction of short-term operational water levels using an adaptive neuro-fuzzy inference system", J. Waterw. Port. C. Ocean Eng., 137(6), 344-354. Technical notes.   DOI
29 Reddy, L.S., Ramana Rao, .N.V and Gunneswara Rao, T.D. (2010), "Shear resistance of high strength concrete beams without shear reinforcement", Int J. Civil. Struct. Eng., 1, 101-113.
30 Takagi, T. and Sugeno, M. (1985), "Fuzzy identification of systems and its applications to modeling and control", IEEE T. Syst. Man. Cy., 35(1), 116-132.
31 Yang, K.H., Chung, H.S. and Ashour, A.F. (2007), "Influence of section depth on the structural behaviour of reinforced concrete continuous deep beams", Mag. Concrete Res., 59(8), 575-586.   DOI   ScienceOn
32 Voo, Y., Poon, W. and Foster, S. (2010), "Shear strength of steel fiber-reinforced ultrahigh- performance concrete beams without stirrups", J. Struct. Eng. - ASCE, 136(11), 1393-1400.   DOI   ScienceOn
33 Wafa Faisal, F. and AShour Samir, A. (1994), "Shear behavior of reinforced high-strength concrete beams without shear reinforcement", Eng. J. Qatar Univ., 7, 91-113.
34 Yaqub, M. (2002), Shear behavior of high-strength concrete beams without shear reinforcement, MSc Thesis, Taxila University.
35 Zeidan, M., Barakat, M., Mahmoud, Z. and Khalifa, A. (2011), "Evaluation of concrete shear strength for FRP reinforced beams", Proceedings of the Structures Congress, 1816-1826. doi: 10.1061/41171(401)158   DOI
36 Zadeh, L.A. (1965), "Fuzzy sets", Inform. Control, 8(3), 338-353.   DOI