# Prediction of the Punching Load Strength of SCS Slabs with Stud-Bolt Shear Connectors Using Numerical Modeling and GEP Algorithm

Document Type : Regular Paper

Authors

1 Civil Engineering Department, Faculty of Maritime Engineering, Chabahar Maritime University, Chabahar, Iran

2 Civil Engineering and Architectural Department, Faculty of Engineering, University of Torbat Heydarieh, Torbat Heydarieh, Iran

3 Civil Engineering Department, Sistan and Baluchestan University, Zahedan, Iran

Abstract

Using bolt shear connectors in Steel-Concrete-Steel (SCS) slabs is very important due to producing a complete steel plates connection and adjusting the sandwich thickness desirably. Therefore, in the present research, a numerical study is conducted on the flexural behavior of SCS sandwich slabs with stud-bolt shear connectors under the effect of the quasi-static concentrated load. For this purpose, first, the experimental specimens extracted from the previously published study were numerically modeled and quasi-statically analyzed using explicit dynamic analysis. Then based on the tests, the models were validated. Subsequently, the effect of the parameters, including the thickness of steel plates, stud-bolts diameter, the concrete core thickness, center-to-center distance of stud-bolt connectors, and the concrete core strength was evaluated based on the numerical models on the failure modes and the force-displacement curve. Finally, using the experimental setup and gene expression programming (GEP) algorithm, several numerical models were planned to predict the maximum strength of the slabs and a simple relation was proposed. The maximum strength resulting from the proposed relation and numerical models had an acceptable agreement with an error of 11% based on mean absolute percentage error (MAPE).

Keywords

Main Subjects

#### References

[1]     Mahdavi N, Salimi M, Ghalehnovi M. Experimental study of octagonal steel columns filled with plain and fiber concrete under the influence of compressive axial load with eccentricity. J Rehabil Civ Eng 2021;9:01–18. https://doi.org/10.22075/JRCE.2020.17989.1345.
[2]     Saberi H, Zadeh VK, Mokhtari A, Saberi V. Investigating of the effect of concrete confinement on the axial performance of circular concrete filled double-skin steel tubular (CFDST) long columns. J Rehabil Civ Eng 2020;8:43–59. https://doi.org/10.22075/JRCE.2020.19167.1362.
[3]     Solomon SK, Smith DW, Cusens AR. Flexural tests of steel-concrete-steel sandwiches. Mag Concr Res 1976;28:13–20. https://doi.org/10.1680/macr.1976.28.94.13.
[4]     Wang Z, Yan J, Lin Y, Fan F, Yang Y. Mechanical properties of steel-UHPC-steel slabs under concentrated loads considering composite action. Eng Struct 2020;222:111095.
[5]     Guo YT, Tao MX, Nie X, Qiu SY, Tang L, Fan JS. Experimental and Theoretical Studies on the Shear Resistance of Steel-Concrete-Steel Composite Structures with Bidirectional Steel Webs. J Struct Eng (United States) 2018;144:1–14. https://doi.org/10.1061/(ASCE)ST.1943-541X.0002182.
[6]     Xie M, Foundoukos N, Chapman JC. Static tests on steel-concrete-steel sandwich beams. J Constr Steel Res 2007;63:735–50. https://doi.org/10.1016/j.jcsr.2006.08.001.
[7]     Xie M, Chapman JC. Developments in sandwich construction. J Constr Steel Res 2006;62:1123–33. https://doi.org/10.1016/j.jcsr.2006.06.025.
[8]     Leekitwattana M, Boyd SW, Shenoi RA. An alternative design of steel-concrete-steel sandwich beam. Science (80- ) 2010:1–10.
[9]     Leekitwattana M. Analysis of an alternative topology for steel-concrete-steel sandwich beams incorporating inclined shear connectors 2011.
[10]   Sohel KMA, Richard Liew JY, Koh CG. Numerical modelling of lightweight Steel‐Concrete‐Steel sandwich composite beams subjected to impact. Thin-Walled Struct 2015;94:135–46. https://doi.org/10.1016/j.tws.2015.04.001.
[11]   Yan JB, Hu H, Wang T. Flexural behaviours of steel-UHPC-steel sandwich beams with J-hook connectors. J Constr Steel Res 2020;169:106014. https://doi.org/10.1016/j.jcsr.2020.106014.
[12]   Yousefi M, Ghalehnovi M. Push-out test on the one end welded corrugated-strip connectors in steel-concrete-steel sandwich structure. Steel Compos Struct 2017;24:23–35. https://doi.org/10.12989/scs.2017.24.1.023.
[13]   Yousefi M, Ghalehnovi M. Finite element model for interlayer behavior of double skin steel-concrete-steel sandwich structure with corrugated-strip shear connectors. Steel Compos Struct 2018;27:123–33. https://doi.org/10.12989/scs.2018.27.1.123.
[14]   Ghalehnovi M, Yousefi M, Karimipour A, de Brito J, Norooziyan M. Investigation of the Behaviour of Steel-Concrete-Steel Sandwich Slabs with Bi-Directional Corrugated-Strip Connectors. Appl Sci 2020;10:8647. https://doi.org/10.3390/app10238647.
[15]   Mohammad Golmohammadi, Mansour Ghalehnovi. Investigation on the interlayer shear behavior on steel-concrete-steel sandwich structure with high strength stud bolt connectors. Concr Res Q J 2017;10:45–31. https://doi.org/10.22124/jcr.2017.2556.
[16]   Yan C, Wang Y, Zhai X, Meng L. Strength assessment of curved steel-concrete-steel sandwich shells with bolt connectors under concentrated load. Eng Struct 2020;212:110465. https://doi.org/10.1016/j.engstruct.2020.110465.
[17]   Golmohammadi M, Ghalehnovi M. Testing and numerical modelling of Steel-Concrete-Steel with stud bolts connectors subject to push-out loading. J Rehabil Civ Eng 2018;0:1–15. https://doi.org/10.22075/jrce.2018.12432.1214.
[18]   Karimipour A, Ghalehnovi M, Golmohammadi M, de Brito J. Experimental Investigation on the Shear Behaviour of Stud-Bolt Connectors of Steel-Concrete-Steel Fibre-Reinforced Recycled Aggregates Sandwich Panels. Materials (Basel) 2021;14:5185. https://doi.org/10.3390/ma14185185.
[19]   Yousefi M, Hashem Khatibi S. Experimental and numerical study of the flexural behavior of steel–concrete-steel sandwich beams with corrugated-strip shear connectors. Eng Struct 2021;242:112559. https://doi.org/10.1016/j.engstruct.2021.112559.
[20]   Li C-H, Yan J-B, Guan H-N. Finite element analysis on enhanced C-channel connectors in SCS sandwich composite structures. Structures 2021;30:818–37. https://doi.org/10.1016/j.istruc.2021.01.050.
[21]   Golmohammadi M, Ghalehnovi M, Yousefi M. Experimental Investigation of Steel-concrete-steel Slabs with Stud Bolt Connectors Subjected to Punching Loading. AUT J Civ Eng 2019;3:93–106. https://doi.org/10.22060/AJCE.2018.14763.5496.
[22]   Shakeri MS. The Relation between Deposited Weight and Quality of Coating in EPD Method Derived by Genetic programming. Comput Eng Phys Model 2021. https://doi.org/https://doi.org/10.22115/CEPM.2020.239389.1117.
[23]   Jahangir H, Rezazadeh Eidgahee D. A new and robust hybrid artificial bee colony algorithm – ANN model for FRP-concrete bond strength evaluation. Compos Struct 2021;257:113160. https://doi.org/10.1016/j.compstruct.2020.113160.
[24]   Naderpour H, Mirrashid M. A computational model for Compressive Strength of Mortars Admixed with Mineral Materials,. Comput Eng Phys Model 2018;1:16–25.
[25]   Shaffiee Haghshenas S, Shaffiee Haghshenas S, Abduelrhman MA, Zare S, Mikaeil R. Identifying and Ranking of Mechanized Tunneling Project’s Risks by Using A Fuzzy Multi-Criteria Decision Making Technique. J Soft Comput Civ Eng 2022;6:29–45. https://doi.org/10.22115/scce.2022.305718.1366.
[26]   Khademi A, Behfarnia K, Kalman Šipoš T, Miličević I. The Use of Machine Learning Models in Estimating the Compressive Strength of Recycled Brick Aggregate Concrete. Comput Eng Phys Model 2021;4:1–25. https://doi.org/10.22115/cepm.2021.297016.1181.
[27]   Emami H, Emami S. Application of whale optimization algorithm combined with adaptive neuro-fuzzy inference system for estimating suspended sediment load. J Soft Comput Civ Eng 2021;5. https://doi.org/10.22115/SCCE.2021.281972.1300.
[28]   Feng D-C, Chen S-Z, Azadi Kakavand MR, Taciroglu E. Probabilistic model based on Bayesian model averaging for predicting the plastic hinge lengths of reinforced concrete columns. J Eng Mech 2021;147:4021066.
[29]   Azadi Kakavand MR, Sezen H, Taciroglu E. Data-driven models for predicting the shear strength of rectangular and circular reinforced concrete columns. J Struct Eng 2021;147:4020301.
[30]   Rezazadeh Eidgahee D, Jahangir H, Solatifar N, Fakharian P, Rezaeemanesh M. Data-driven estimation models of asphalt mixtures dynamic modulus using ANN, GP and combinatorial GMDH approaches. Neural Comput Appl 2022;34:17289–314. https://doi.org/10.1007/s00521-022-07382-3.
[31]   Azadi Kakavand MR, Allahvirdizadeh R. Enhanced empirical models for predicting the drift capacity of less ductile RC columns with flexural, shear, or axial failure modes. Front Struct Civ Eng 2019;13:1251–70.
[32]   Naderpour H, Rezazadeh Eidgahee D, Fakharian P, Rafiean AH, Kalantari SM. A new proposed approach for moment capacity estimation of ferrocement members using Group Method of Data Handling. Eng Sci Technol an Int J 2020;23:382–91. https://doi.org/10.1016/j.jestch.2019.05.013.
[33]   Darvishan E. The punching shear capacity estimation of FRP-strengthened RC slabs using artificial neural network and group method of data handling. J Rehabil Civ Eng 2021;9:102–13.
[34]   Jahangir H, Khatibinia M, Mokhtari Masinaei M. Damage detection in prestressed concrete slabs using wavelet analysis of vibration responses in the time domain. J Rehabil Civ Eng 2022;10:37–63.
[35]   Hibbitt” K&, Inc S. ABAQUS, S.M. and Manual, E.U.s. Pawtucket, RI, USA 2010.
[36]   Azadi Kakavand MR, Taciroglu E. An enhanced damage plasticity model for predicting the cyclic behavior of plain concrete under multiaxial loading conditions. Front Struct Civ Eng 2020;14:1531–44.
[37]   Azadi Kakavand MR, Neuner M, Schreter M, Hofstetter G. A 3D continuum FE-model for predicting the nonlinear response and failure modes of RC frames in pushover analyses. Bull Earthq Eng 2018;16:4893–917.
[38]   Hibbitt K& S. ABAQUS User’s Manual. ABAQUS/CAE User’s Man 2012:1–847.
[39]   Popovics S. A numerical approach to the complete stress-strain curve of concrete. Cem Concr Res 1973;3:583–99. https://doi.org/10.1016/0008-8846(73)90096-3.
[40]   Thorenfeldt E. Mechanical properties of high-strength concrete and applications in design. Symp. Proceedings, Util. High-Strength Concr. Norway, 1987, 1987.
[41]   Code C-FM. Comité euro-international du béton. Bull d’information 1993;213:214.
[42]   Lee J, Fenves GL. Plastic-damage model for cyclic loading of concrete structures. J Eng Mech 1998;124:892–900.
[43]   Ferreira C. Gene Expression Programming in Problem Solving. Soft Comput. Ind., London: Springer London; 2002, p. 635–53. https://doi.org/10.1007/978-1-4471-0123-9_54.
[44]   Muñoz D. Thesis Discovering unknown equations that describe large data sets using genetic programming techniques. Masters Thesis, Linköping Inst Technol 2005.
[45]   Kleppmann W. Statistische Versuchsplanung. Mas. Handb. Qual., vol. 158, München: Carl Hanser Verlag GmbH & Co. KG; 2014, p. 499–522. https://doi.org/10.3139/9783446439924.022.
[46]   Fakhrian S, Behbahani H, Mashhadi S. Predicting post-fire behavior of green geopolymer mortar containing recycled concrete aggregate via gep approach. J Soft Comput Civ Eng 2020;4:22–45. https://doi.org/10.22115/SCCE.2020.220919.1182.

### History

• Receive Date: 14 March 2022
• Revise Date: 06 August 2022
• Accept Date: 21 September 2022