Browse > Article
http://dx.doi.org/10.12989/cac.2018.22.2.197

GMDH-based prediction of shear strength of FRP-RC beams with and without stirrups  

Kaveh, Ali (Centre of Excellence for Fundamental Studies in Structural Engineering, Iran University of Science and Technology)
Bakhshpoori, Taha (Faculty of Technology and Engineering, Department of Civil Engineering, East of Guilan, University of Guilan)
Hamze-Ziabari, Seyed Mahmood (Centre of Excellence for Fundamental Studies in Structural Engineering, Iran University of Science and Technology)
Publication Information
Computers and Concrete / v.22, no.2, 2018 , pp. 197-207 More about this Journal
Abstract
In the present study, group method of data handling networks (GMDH) are adopted and evaluated for shear strength prediction of both FRP-reinforced concrete members with and without stirrups. Input parameters considered for the GMDH are altogether 12 influential geometrical and mechanical parameters. Two available and very recently collected comprehensive datasets containing 112 and 175 data samples are used to develop new models for two cases with and without shear reinforcement, respectively. The proposed GMDH models are compared with several codes of practice. An artificial neural network (ANN) model and an ANFIS based model are also developed using the same databases to further assessment of GMDH. The accuracy of the developed models is evaluated by statistical error parameters. The results show that the GMDH outperforms other models and successfully can be used as a practical and effective tool for shear strength prediction of members without stirrups ($R^2=0.94$) and with stirrups ($R^2=0.95$). Furthermore, the relative importance and influence of input parameters in the prediction of shear capacity of reinforced concrete members are evaluated through parametric and sensitivity analyses.
Keywords
shear strength prediction; FRP-RC beams; stirrup; GMDH; ANN; ANFIS;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 440, A.C. (2007), Guide for the Design and Construction of Structural Concrete Reinforced with FRP Bars.
2 Amanifard, N., Nariman-Zadeh, N., Farahani, M. and Khalkhali, A. (2008), "Modelling of multiple short-length-scale stall cells in an axial compressor using evolved GMDH neural networks", Energy Convers. Manage., 49(10), 2588-2594.   DOI
3 Bashir, R. and Ashour, A. (2012), "Neural network modelling for shear strength of concrete members reinforced with FRP bars", Compos. Part B: Eng., 43(8), 3198-3207.   DOI
4 Bulut, N., Anil, O. and Belgin, C.M. (2011), "Nonlinear finite element analysis of RC beams strengthened with CFRP strip against shear", Comput. Concrete, 8(6), 717-733.   DOI
5 C.S.A. (2006), Canadian Highway Bridge Design Code, Canadian Standards Association (CSA), Toronto.
6 C.S.A. (2012), Design and Construction of Buildings Components with Fiber-Reinforced Polymers, Toronto.
7 Campana, S., Fernandez Ruiz, M., Anastasi, A. and Muttoni, A. (2013), "Analysis of shear-transfer actions on one-way RC members based on measured cracking pattern and failure kinematics", Mag. Concrete Res., 1-19.
8 Chowdhury, M.A. and Islam, M.M. (2015), "Shear strength prediction of FRP-reinforced concrete beams: A state-of the-art review of available models", J. Civil Environ. Eng., 5(5), 186.
9 Council, I.R. (2007), Guide for the Design and Construction of Concrete Structures Reinforced with Fiber-Reinforced Polymer Bars, Rome.
10 Deitz, D.H., Harik, I.E. and Gesund, H. (1999), "One-way slabs reinforced with glass fiber reinforced polymer reinforcing bars, fiber reinforced polymer reinforcement for reinforced concrete structures", Eds. Dolan, C.W., et al., Proceedings of the 4-th International Conference, SP-188, Farmington Hills, Mich, American Concrete Institute.
11 El-Chabib, H., Nehdi, M. and Said, A. (2005), "Predicting shear capacity of NSC and HSC slender beams without stirrups using artificial intelligence", Comput. Concrete, 2(1), 79-96.   DOI
12 GangaRao, H.V., Taly, N. and Vijay, P. (2006), Reinforced Concrete Design with FRP Composites, CRC Press.
13 Golafshani, E.M. and Ashour, A. (2016), "A feasibility study of BBP for predicting shear capacity of FRP reinforced concrete beams without stirrups", Adv. Eng. Softw., 97, 29-39.   DOI
14 Golafshani, E.M., Rahai, A. and Sebt, M.H. (2015), "Artificial neural network and genetic programming for predicting the bond strength of GFRP bars in concrete", Mater. Struct., 48(5), 1581-1602.   DOI
15 Golafshani, E.M., Rahai, A., Sebt, M.H. and Akbarpour, H. (2012), "Prediction of bond strength of spliced steel bars in concrete using artificial neural network and fuzzy logic", Constr. Build. Mater., 36, 411-418.   DOI
16 Hoque, M.M. (2006), "3D nonlinear mixed finite-element analysis of RC beams and plates with and without FRP reinforcement", University of Manitoba
17 Hoult, N., Sherwood, E., Bentz, E.C. and Collins, M.P. (2008), "Does the use of FRP reinforcement change the one-way shear behavior of reinforced concrete slabs?", J. Compos. Constr., 12(2), 125-133.   DOI
18 Ivakhnenko, A. (1971), "Polynomial theory of complex systems", IEEE Tran. Syst. Man Cyber., 4, 364-378.
19 J.S.o.C.E. (1997), Recommendation for Design and Construction of Concrete Structures using Continuous Fiber Reinforcing Materials, Tokyo.
20 Ivakhnenko, A.G. and Ivakhnenko, G.A. (2000), "Problems of further development of the group method of data handling algorithms. Part I", Pattern Recognition and Image Analysis C/C Of Raspoznavaniye Obrazov I Analiz Izobrazhenii, 10(2), 187-194.
21 Jnaid, F. and Aboutaha, R. (2013), "Review of design parameters for FRP-RC members detailed according to ACI 440.1 R-06", Comput. Concrete, 11(2), 105-121.   DOI
22 Kara, I.F. (2011), "Prediction of shear strength of FRP-reinforced concrete beams without stirrups based on genetic programming", Adv. Eng. Softw., 42(6), 295-304.   DOI
23 Kaveh, A., Bakhshpoori, T. and Hamze-Ziabari, S. (2016), "Derivation of new equations for prediction of principal groundmotion parameters using M5' algorithm", J. Earthq. Eng., 20(6), 910-930.   DOI
24 Kaveh, A., Bakhshpoori, T. and Hamze-Ziabari, S. (2017), "New model derivation for the bond behavior of NSM FRP systems in concrete", Iran. J. Sci. Technol., Tran. A, 41(3), 249-262.
25 Kaveh, A., Hamze-Ziabari, S. and Bakhshpoori, T. (2016), "Patient rule-induction method for liquefaction potential assessment based on CPT data", Bull. Eng. Geol. Environ., 77(2), 849-865.
26 Kaveh, A., Hamze-Ziabari, S.M. and Bakhshpoori, T. (2017), "M5' algorithm for shear strength prediction of HSC slender beams without web reinforcement", Int. J. Model. Optim., 7(1), 48-53.
27 Lee, S. and Lee, C. (2014), "Prediction of shear strength of FRPreinforced concrete flexural members without stirrups using artificial neural networks", Eng. Struct., 61 99-112.   DOI
28 Madandoust, R., Bungey, J.H. and Ghavidel, R. (2012), "Prediction of the concrete compressive strength by means of core testing using GMDH-type neural network and ANFIS models", Comput. Mater. Sci., 51(1), 261-272.   DOI
29 Liang, J., Deng, Y., Hu, M. and Tang, D. (2017), "Cyclic performance of concrete beams reinforced with CFRP prestressed prisms", Comput. Concrete, 19(3), 227-232.   DOI
30 Machial, R., Alam, M.S. and Rteil, A. (2012), "Revisiting the shear design equations for concrete beams reinforced with FRP rebar and stirrup", Mater. Struct., 45(11), 1593-1612.   DOI
31 Najafzadeh, M., Barani, G.A. and Hessami-Kermani, M.R. (2015), "Evaluation of GMDH networks for prediction of local scour depth at bridge abutments in coarse sediments with thinly armored beds", Ocean Eng., 104, 387-396.   DOI
32 Nasrollahzadeh, K. and Basiri, M.M. (2014), "Prediction of shear strength of FRP reinforced concrete beams using fuzzy inference system", Expert Syst. Appl., 41(4), 1006-1020.   DOI
33 Nehdi, M., El Chabib, H. and Said, A.A. (2007), "Proposed shear design equations for FRP-reinforced concrete beams based on genetic algorithms approach", J. Mater. Civil Eng., 19(12), 1033-1042.   DOI
34 Oller, E., Mari, A., Bairan, J.M. and Cladera, A. (2015), "Shear design of reinforced concrete beams with FRP longitudinal and transverse reinforcement", Compos. Part B: Eng., 74 104-122.   DOI
35 Ramirez, J.A., French, C., Adebar, P., Bonacci, J. and Collins, M. (1998), "Recent approaches to shear design of structural concrete", J. Struct. Eng., 124(12), 1374.
36 Razaqpur, A.G. and Spadea, S. (2014), "Shear strength of FRP reinforced concrete members with stirrups", J. Compos. Constr., 19(1), 04014025.   DOI
37 Shahnewaz, M., Machial, R., Alam, M.S. and Rteil, A. (2016), "Optimized shear design equation for slender concrete beams reinforced with FRP bars and stirrups using genetic algorithm and reliability analysis", Eng. Struct., 107, 151-165.   DOI
38 Sahay, R.R. and Dutta, S. (2009), "Prediction of longitudinal dispersion coefficients in natural rivers using genetic algorithm", Hydrol. Res., 40(6), 544-552.   DOI
39 Sas, G., Taljsten, B., Barros, J., Lima, J. and Carolin, A. (2009), "Are available models reliable for predicting the FRP contribution to the shear resistance of RC beams?", J. Compos. Constr., 13(6), 514-534.   DOI
40 See, L. and Openshaw, S. (1999), "Applying soft computing approaches to river level forecasting", Hydrol. Sci. J., 44(5), 763-778.   DOI
41 Smith, G.N. (1986), Probability and Statistics in Civil Engineering, Collins London
42 Smith, S.T. and Teng, J.G. (2002), "FRP-strengthened RC beams. I: review of debonding strength models", Eng. Struct., 24(4), 385-395.   DOI
43 Srinivasan, D. (2008), "Energy demand prediction using GMDH networks", Neurocomput., 72(1), 625-629.   DOI
44 Tureyen, A. and Frosch, R.J. (2003), "Concrete shear strength: another perspective", ACI Struct. J., 100(5), 609-615.
45 Zhang, T., Oehlers, D.J. and Visintin, P. (2014), "Shear strength of FRP RC beams and one-way slabs without stirrups", J. Compos. Constr., 18(5), 04014007.   DOI