Predictive model to the bond strength of FRP-to-concrete under direct pullout using gene expression programming
Abstract
Gene expression programming (GEP) is used in this research to develop an empirical model that predicts the bond strength between the concrete surface and carbon fiber reinforced polymer (CFRP) sheets under direct pull out. Therefore, a large and reliable database containing 770 test specimens is collected from the literature. The gene expression programming model is developed using eight parameters that predominantly control the bond strength. These parameters are concrete compressive strength, maximum aggregate size, fiber reinforced polymer (FRP) tensile strength, FRP thickness, FRP modulus of elasticity, adhesive tensile strength, FRP length, and FRP width. The model is validated using the experimental results and a statistical assessment is implemented to evaluate the performance of the proposed GEP model. Furthermore, the predicted bond results, obtained using the GEP model, are compared to the results obtained from several analytical models available in the literature and a parametric study is conducted to further ensure the consistency of the model by checking the trends between the input parameters and the predicted bond strength. The proposed model can reasonably predict the bond strength that is most fitting to the experimental database compared to the analytical models and the trends of the GEP model are in agreement with the overall trends of the analytical models and experimental tests.
First published online 30 August 2019
Keyword : bond strength, gene expression programming, FRP, concrete, large data base
How to Cite
Murad, Y., Ashteyat, A., & Hunaifat, R. (2019). Predictive model to the bond strength of FRP-to-concrete under direct pullout using gene expression programming. Journal of Civil Engineering and Management, 25(8), 773-784. https://doi.org/10.3846/jcem.2019.10798
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Antoniou, M. A., Georgopoulos, E. F., Theofilatos, K. A., Vassilopoulos, A. P., & Likothanassis, S. D. (2010). A Gene Expression Programming environment for fatigue modeling of composite materials (pp. 297-302). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-12842-4_33
Aval, S. B. B., Ketabdari, H., & Gharebaghi, A. S. (2017). Estimating shear strength of short rectangular reinforced concrete columns using nonlinear regression and Gene Expression Programming. Structures, 12, 13-23. https://doi.org/10.1016/j.istruc.2017.07.002
Adhikary, B. B., & Mutsuyoshi, H. (2001). Study on the bond between concrete and externally bonded CFRP sheet. In FRPRCS-5: Fibre-reinforced plastics for reinforced concrete structures, 1. https://doi.org/10.1680/frprcsv1.30299
Biolzi, L., Ghittoni, C., Fedele, R., & Rosati, G. (2013). Experimental and theoretical issues in FRP-concrete bonding. Construction and Building Materials, 41, 182-190. https://doi.org/10.1016/j.conbuildmat.2012.11.082
Cevik, A., & Sonebi, M. (2008). Modelling the performance of self-compacting SIFCON of cement slurries using genetic programming technique. Computers and Concrete, 5(5), 475-490. https://doi.org/10.12989/cac.2008.5.5.475
Czaderski, C., Soudki, K., & Motavalli, M. (2010). Front and side view image correlation measurements on FRP to concrete pull-off bond tests. Journal of Composites for Construction, 14(4), 451-463. https://doi.org/10.1061/(ASCE)CC.1943-5614.0000106
Ferreira, C. (2002). Gene Expression Programming in problem solving. In Soft Computing and Industry (pp. 635–653). London: Springer. https://doi.org/10.1007/978-1-4471-0123-9_54
Gandomi, A. H., Alavi, A. H., Kazemi, S., & Gandomi, M. (2014). Formulation of shear strength of slender RC beams using gene expression programming, part I: Without shear reinforcement. Automation in Construction, 42, 112-121. https://doi.org/10.1016/j.autcon.2014.02.007
Gandomi, A. H., Alavi, A. H., Ting, T. O., & Yang, X.-S. (2013). Intelligent modeling and prediction of elastic modulus of concrete strength via Gene Expression Programming (pp. 564–571). Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-38703-6_66
Gepsoft. (2014). GeneXproTools. Data modeling & Analysis software. Retrieved from: https://www.gepsoft.com/
Gholampour, A., Gandomi, A. H., & Ozbakkaloglu, T. (2017). New formulations for mechanical properties of recycled aggregate concrete using gene expression programming. Construction and Building Materials, 130, 122-145. https://doi.org/10.1016/j.conbuildmat.2016.10.114
Ghorbani, M., Mostofinejad, D., & Hosseini, A. (2017). Experimental investigation into bond behavior of FRP-to-concrete under mixed-mode I/II loading. Construction and Building Materials, 132, 303-312. https://doi.org/10.1016/j.conbuildmat.2016.11.057
González-Taboada, I., González-Fonteboa, B., Martínez-Abella, F., & Pérez-Ordóñez, J. L. (2016). Prediction of the mechanical properties of structural recycled concrete using multivariable regression and genetic programming. Construction and Building Materials, 106, 480-499. https://doi.org/10.1016/j.conbuildmaT.2015.12.136
Haddad, R., Al-Rousan, R., & Almasry, A. (2013). Bond-slip behavior between carbon fiber reinforced polymer sheets and heat-damaged concrete. Composites Part B: Engineering, 45(1), 1049-1060. https://doi.org/10.1016/j.compositesb.2012.09.010
Haddad, R., Al-Rousan, R., Ghanma, L., & Nimri, Z. (2015). Modifying CFRP-concrete bond characteristics from pullout testing. Magazine of Concrete Research, 67(13), 707-717. https://doi.org/10.1680/macr.14.00271
Haddad, R. H., & Al Dalou, A. A. (2018). Experimental study on bond behavior between corrosion-cracked reinforced concrete and CFRP sheets. Journal of Adhesion Science and Technology, 32(6), 590-608. https://doi.org/10.1080/01694243.2017.1371912
Hadigheh, S. A., Gravina, R. J., & Setunge, S. (2015). Identification of the interfacial fracture mechanism in the FRP laminated substrates using a modified single lap shear test set-up. Engineering Fracture Mechanics, 134, 317-329. https://doi.org/10.1016/j.engfracmech.2014.12.001
Hosseini, A., & Mostofinejad, D. (2013). Experimental investigation into bond behavior of CFRP sheets attached to concrete using EBR and EBROG techniques. Composites Part B: Engineering, 51, 130-139. https://doi.org/10.1016/j.compositesb.2013.03.003
Hosseini, A., & Mostofinejad, D. (2014). Effective bond length of FRP-to-concrete adhesively-bonded joints: Experimental evaluation of existing models. International Journal of Adhesion and Adhesives, 48, 150-158. https://doi.org/10.1016/j.ijadhadh.2013.09.022
Iqbal, S., Ullah, N., & Ali, A. (2018). Engineering, technology & applied science research. In Engineering, Technology & Applied Science Research, 8. ETASR. Retrieved from https://www.etasr.com/index.php/ETASR/article/view/1989
Irshidat, M. R., & Al-Saleh, M. H. (2016). Effect of using carbon nanotube modified epoxy on bond–slip behavior between concrete and FRP sheets. Construction and Building Materials, 105, 511-518. https://doi.org/10.1016/j.conbuildmat.2015.12.183
Izumo, K., Saeki, N., Fukao, M., & Horiguchi, T. (1999). Bond behavior and strength between fiber sheets and concrete. Transactions of the Japan Concrete Institute, 21, 423-430.
Jafari, S., & Mahini, S. S. (2017). Lightweight concrete design using gene expression programing. Construction and Building Materials, 139, 93-100. https://doi.org/10.1016/j.conbuildmat.2017.01.120
Japan Concrete Institute (JCI). (2003). Technical report of technical committee on retrofit technology.
Khalifa, A., Gold, W. J., Nanni, A., & M.I., A. A. (1998). Contribution of externally bonded FRP to shear capacity of RC flexural members. Journal of Composites for Construction, 2(4), 195-202. https://doi.org/10.1061/(ASCE)1090-0268(1998)2:4(195)
Ko, H., Matthys, S., Palmieri, A., & Sato, Y. (2014). Development of a simplified bond stress-slip model for bonded FRPconcrete interfaces. Construction and Building Materials, 68, 142-157. https://doi.org/10.1016/j.conbuildmat.2014.06.037
Koza, J. (1994). Genetic programming as a means for programming computers by natural selection. Statistics and Computing, 4(2), 87-112. https://doi.org/10.1007/BF00175355
Lim, J. C., Karakus, M., & Ozbakkaloglu, T. (2016). Evaluation of ultimate conditions of FRP-confined concrete columns using genetic programming. Computers & Structures, 162, 28-37. https://doi.org/10.1016/j.compstruc.2015.09.005
Lu, X. Z., Teng, J. G., Ye, L. P., & Jiang, J. J. (2005). Bond-slip models for FRP sheets/plates bonded to concrete. Engineering Structures, 27(6), 920-937. https://doi.org/10.1016/j.engstruct.2005.01.014
Mansouri, I., Azmathulla, H. M., & Hu, W. J. (2018). Gene expression programming application for prediction of ultimate axial strain of FRP-confined concrete. Elektronički Časopis Građevinskog Fakulteta Osijek, 9(16), 64-76. https://doi.org/10.13167/2018.16.6
Maeda, T., Asano, Y., Sato, Y., Ueda, T., & Kakuta, Y. (1999). A study on bond mechanism of carbon fiber sheet. In Proceedings of the Third International Symposium on Non-Metallic (FRP) Reinforcement for Concrete Structures (pp. 279-286). Japan: Japan Concrete Institute.
Mazzotti, C., Ferracuti, B., & Bilotta, A. (2012). Sensitivity of FRP-concrete bond behavior to modification of the experimental set-up. In VI International Conference of FRP Composites in Civil Engineering.
Ming, Z., & Ansari, F. (2004). Bond properties of FRP fabrics and concerete joints. In 13th World Conference on Earthquake Engineering. Vancouver, B.C., Canada.
Mostofinejad, D., Mofrad, M. H., Hosseini, A., & Mofrad, H. H. (2018). Investigating the effects of concrete compressive strength, CFRP thickness and groove depth on CFRP-concrete bond strength of EBROG joints. Construction and Building Materials, 189, 323-337. https://doi.org/10.1016/j.conbuildmat.2018.08.203
Mousavi, S. M., Aminian, P., Gandomi, A. H., Alavi, A. H., & Bolandi, H. (2012). A new predictive model for compressive strength of HPC using gene expression programming. Advances in Engineering Software, 45(1), 105-114. https://doi.org/10.1016/j.advengsoft.2011.09.014
Murad, Y. (2018a). The influence of CFRP orientation angle on the shear strength of RC beams. The Open Construction & Building Technology Journal, 12. https://doi.org/10.2174/1874836801812010269
Murad, Y. (2018b). An experimental study on flexural strengthening of RC beams using CFRP sheets. International Journal of Engineering and Technology (UAE), 7, 2075-2080. https://doi.org/10.14419/ijet.v7i4.16546
Nazari, A., & Torgal, P. F. (2013). Modeling the compressive strength of geopolymeric binders by gene expression programming-GEP. Expert Systems with Applications, 40(14), 5427-5438. https://doi.org/10.1016/j.eswa.2013.04.014
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