A Neuro-Fuzzy Model for Punching Shear Prediction of Slab-Column Connections Reinforced with FRP

Document Type : Regular Article


Faculty of Civil Engineering, Semnan University, Semnan, Iran


In this article, one of the robust systems of soft computing namely adaptive neuro-fuzzy inference system (ANFIS) is used to estimate the punching shear capacity of the concrete column-slab connections reinforced with FRP. For this purpose, a collection of experimental tests was used to train and test the ANFIS model. Five parameters including the area section of the column, Young’s modulus of the FRP bars, the effective flexural depth of the slab, FRP reinforcement ratio and also the compressive strength of concrete are used as inputs of the neuro-fuzzy system to estimate the considered output. The whole structure of the ANFIS also presented in mathematical steps. The obtained results of the created model of this paper indicated that the proposed ANFIS structure with a suitable accuracy could be used as a predictive model to determine the punching shear capacity of the considered elements. Also, the formulated model of the ANFIS in this paper can easily apply for codes and other researches.


Google Scholar


Main Subjects

[1]     Valerio P, Ibell TJ, Darby AP. Shear assessment and strengthing of contiguous beam-and-slab concrete bridges using FRP bars 2005.
[2]     Kumar R, Roy AB. Punching Shear Behaviour of FRP Strengthened Flat Slab With and Without Geo-Grid 2017.
[3]     Tanjeem Khan M, Raja M, Sawood Ansari M, Maaz Ansari A, Rahim Saud K, H. Momin U, et al. Experimental Investigation of Punching Shear on FRP Strengthened Slab. Int J Adv Sci Res Eng 2018;4:191–203. doi:10.31695/IJASRE.2018.32740.
[4]     Theodorakopoulos DD, Swamy RN. A design model for punching shear of FRP-reinforced slab-column connections. Cem Concr Compos 2008;30:544–55. doi:10.1016/j.cemconcomp.2007.10.003.
[5]     Zhang YX, Zhu Y. A new shear-flexible FRP-reinforced concrete slab element. Compos Struct 2010;92:730–5. doi:10.1016/j.compstruct.2009.09.013.
[6]     Polak MA, Lawler N. Application of FRP for Punching Shear Retrofit of Concrete Slab-Column Connections. Adv. FRP Compos. Civ. Eng., Berlin, Heidelberg: Springer Berlin Heidelberg; 2011, p. 854–7. doi:10.1007/978-3-642-17487-2_188.
[7]     Nguyen-Minh L, Rovňák M. Punching Shear Resistance of Interior GFRP Reinforced Slab-Column Connections. J Compos Constr 2013;17:2–13. doi:10.1061/(ASCE)CC.1943-5614.0000324.
[8]     Abdullah A, Bailey CG, Wu ZJ. Tests investigating the punching shear of a column-slab connection strengthened with non-prestressed or prestressed FRP plates. Constr Build Mater 2013;48:1134–44. doi:10.1016/j.conbuildmat.2013.07.012.
[9]     ElGendy M. Punching shear behaviour of slab-column edge connections reinforced with fibre-reinforced polymer (FRP) composite bars. MSc thesis, Department of Civil Engineering, The University of Manitoba, Winnipeg, MB, Canada, 2014.
[10]    Sayed A. Punching shear behaviour of FRP-reinforced concrete interior slab-column connections. Department of Civil Engineering, The University of Manitoba, Winnipeg, MB, Canada, 2015.
[11]    Saleh H, Abdouka K, Al-Mahaidi R, Kalfat R. Strengthening of slab–column connections against punching shear using FRP materials: state-of-the-art review. Aust J Struct Eng 2018;19:188–206. doi:10.1080/13287982.2018.1462901.
[12]    Kheyroddin A, Mirrashid M, Arshadi H. An Investigation on the Behavior of Concrete Cores in Suspended Tall Buildings. Iran J Sci Technol Trans Civ Eng 2017;41:383–8. doi:10.1007/s40996-017-0075-y.
[13]    Jafari M, Mirrashid M, Vahidnia A. Prediction of chloride penetration in the concrete containing magnetite aggregates by Adaptive Neural Fuzzy Inference System (ANFIS). 7th Internatinal Symp. Adv. Sci. Technol. (5thsastech), Bandare Abbas, Iran, 2013.
[14]    Mirrashid M. Earthquake magnitude prediction by adaptive neuro-fuzzy inference system (ANFIS) based on fuzzy C-means algorithm. Nat Hazards 2014;74:1577–93. doi:10.1007/s11069-014-1264-7.
[15]    Naderpour H, Mirrashid M. Shear Strength Prediction of RC Beams Using Adaptive Neuro-Fuzzy Inference System. Sci Iran 2018:0–0. doi:10.24200/sci.2018.50308.1624.
[16]    Naderpour H, Mirrashid M. An innovative approach for compressive strength estimation of mortars having calcium inosilicate minerals. J Build Eng 2018;19:205–15. doi:10.1016/j.jobe.2018.05.012.
[17]    Naderpour H, Rafiean AH, Fakharian P. Compressive strength prediction of environmentally friendly concrete using artificial neural networks. J Build Eng 2018;16:213–9. doi:10.1016/j.jobe.2018.01.007.
[18]    Naderpour H, Vahdani R, Mirrashid M. Soft Computing Research in Structural Control by Mass Damper (A review paper). 4st Int. Conf. Struct. Eng. Tehran, Iran, 2018.
[19]    Mirrashid M. Comparison Study of Soft Computing Approaches for Estimation of the Non-Ductile RC Joint Shear Strength. Soft Comput Civ Eng 2017;1:12–28. doi:10.22115/scce.2017.46318.
[20]    Mirrashid M, Bigdeli S. Genetic Algorithm for Prediction the Compressive Strength of Mortar Containing Wollastonite. 1st Natl. Congr. Counstruction Eng. Proj. Assessment, Gorgan, Iran, 2014.
[21]    Mirrashid M, Givehchi M, Miri M, Madandoust R. Performance investigation of neuro-fuzzy system for earthquake prediction. Asian J Civ Eng 2016;17:213–23.
[22]    Mirrashid M, Jafari M, Akhlaghi A, Vahidnia A. Prediction of compressive strength of concrete containing magnetite aggregates using Adaptive Neural Fuzzy Inference System (ANFIS) n.d.
[23]    Naderpour H, Mirrashid M. Application of Soft Computing to Reinforced Concrete Beams Strengthened with Fibre Reinforced Polymers: A State-of-the-Art Review. Comput Tech Civ Struct Eng 2015;38:305–23.
[24]    Naderpour H, Mirrashid M. Compressive Strength of Mortars Admixed with Wollastonite and Microsilica. Mater Sci Forum 2017;890:415–8. doi:10.4028/www.scientific.net/MSF.890.415.
[25]    Naderpour H, Mirrashid M. Ultimate Capacity Prediction of Concrete Slabs Reinforced with FRP Bars. 3rd Int. 7th Natl. Conf. Mod. Mater. Struct. Civ. Eng. Bu-Ali Sina Univ. Hamedan, IRAN, 2018.
[26]    Naderpour H, Mirrashid M. Application of group method of data handling to Estimate the Shear Strength of RC Beams Reinforced with FRP Bars. 3rd Int. 7th Natl. Conf. Mod. Mater. Struct. Civ. Eng. Bu-Ali Sina Univ. Hamedan, IRAN, 2018.
[27]    Metwally IM. Prediction of punching shear capacities of two-way concrete slabs reinforced with FRP bars. HBRC J 2013;9:125–33. doi:10.1016/j.hbrcj.2013.05.009.
[28]    Hassan MAW. Punching Shear Behaviour of Concrete Two-way Slabs Reinforced with Glass Fiber-reinforced Polymer (GFRP) Bars. University of Sherbrooke, 2013.
[29]    Jang J-SR. ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans Syst Man Cybern 1993;23:665–85. doi:10.1109/21.256541.