DOI QR코드

DOI QR Code

Prediction of the bond strength of ribbed steel bars in concrete based on genetic programming

  • Received : 2013.07.12
  • Accepted : 2014.07.03
  • Published : 2014.09.30

Abstract

This paper presents the application of multi-gene genetic programming (MGP) technique for modeling the bond strength of ribbed steel bars in concrete. In this regard, the experimental data of 264 splice beam tests from different technical papers were used for training, validating and testing the model. Seven basic parameters affecting on the bond strength of steel bars were selected as input parameters. These parameters are diameter, relative rib area and yield strength of steel bar, minimum concrete cover to bar diameter ratio, splice length to bar diameter ratio, concrete compressive strength and transverse reinforcement index. The results show that the proposed MGP model can be alternative approach for predicting the bond strength of ribbed steel bars in concrete. Moreover, the performance of the developed model was compared with the building codes' empirical equations for a complete comparison. The study concludes that the proposed MGP model predicts the bond strength of ribbed steel bars better than the existing building codes' equations. Using the proposed MGP model and building codes' equations, a parametric study was also conducted to investigate the trend of the input variables on the bond strength of ribbed steel bars in concrete.

Keywords

References

  1. ACI Committee 408 (2003), "Bond and development of straight reinforcing bars in tension (408R-03)", American Concrete Institute, Farmington Hills, Mich., 49.
  2. ACI Committee 318 (2008), "Building code requirements for structural concrete (318-08)", American Concrete Institute, Farmington Hills, Mich., 430 pp.
  3. Azizinamini, A., Pavel, R., Hatfield, E. and Ghosh, S.K. (1996), "Behavior of spliced reinforcing bars embedded in high strength concrete", ACI. Struct. J., 96(5), 826-835.
  4. CSA Standard A23.3 (2004), "Design of concrete structures for buildings", Canadian Standards Association, Toronto, Ontario, Canada., 240.
  5. Cevik, A., Gugas, M.T., Guzelbey, I.H. and Filiz, H. (2010), "Soft computing based formulation for strength enhancement of CFRP confined concrete cylinders", Adv. Eng. Softw., 41(4), 527-536. https://doi.org/10.1016/j.advengsoft.2009.10.015
  6. Choi, O.C., Ghaffari, H.H., Darwin, D. and Mccabe, S.L. (1990), Bond of Epoxy-Coated Reinforcement to Concrete: Bar Parameters, SM Report No. 25, University of Kansas Center for Research, Lawrence, Kansas., 217 pp.
  7. Choi, O.C., Ghaffari, H.H., Darwin, D. and Mccabe, S.L. (1991), "Bond of epoxy-coated reinforcement: bar parameters", ACI. Mater. J., 88(2), 207-217.
  8. CEB-FIP (1990), "Model Code for Concrete Structures", Comite Euro-International du Beton, c/o Thomas Telford, London .
  9. Darwin, D., Tholen, M.L., Idun, E.K. and Zuo, J. (1996a), "Splice strength of high relative rib area reinforcing bars", ACI. Struct. J., 93(1), 95-107.
  10. Darwin, D., Zuo, J., Tholen, M.L. and Idun, E.K. (1996b), "Development length criteria for conventional and high relative rib area reinforcing bars", ACI. Struct. J., 93(3), 347-359.
  11. Darwin, D., Barham, S., Kozul, R. and Luan, S. (2001), "Fracture energy of high-strength concrete", ACI. Mater. J., 98(5), 410-417.
  12. Dias, W.P.S. and Pooliyadda, S.P. (2001), "Neural networks for predicting properties of concretes with admixtures", Constr. Build. Mater., 15(7), 371-379. https://doi.org/10.1016/S0950-0618(01)00006-X
  13. Dahou, Z., Sbartai, Z.M., Castel, A. and Ghomari, F. (2009), "Artificial neural network model for steelconcrete bond prediction", Eng. Struct., 31(8), 1724-1733. https://doi.org/10.1016/j.engstruct.2009.02.010
  14. EC2 (2004), "Design of concrete structures-Part 1.1: general rules and rules for buildings (EC2)", European Committee for Standardization Eurocode 2, Brussels, Belgium., 225 pp.
  15. Ferguson, P.M. and Thompson, J.N. (1965), "Development length for large high strength reinforcing bars", ACI. J. Proc., 62(1), 71-94.
  16. Golafshani, E.M., Rahai, A. and Sebt, M.H. (2014), "Artificial neural network and genetic programming for predicting the bond strength of GFRP bars in concrete", Mater. Struct., DOI 10.1617/s11527-014-0256-0.
  17. 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. https://doi.org/10.1016/j.conbuildmat.2012.04.046
  18. Hacha, R.E., Agroudy, H.E. and Rizkalla, S.H. (2012), "Bond characteristics of high-strength steel reinforcement", ACI. Struct. J., 103(6), 771-782.
  19. Harajli, M.H. and Mabsout, M.E. (2002), "Evaluation of bond strength of steel reinforcing bars in plain and fiber-reinforced concrete", ACI. Struct. J., 99(4), 509-517.
  20. Harajli, M.H., Hamad, B.S. and Rteil, A.A. (2004), "Effect of confinement on bond strength between steel bars and concrete", AC.I Struct. J., 101(5), 595-603.
  21. Hester, C.J., Salamizavaregh, S., Darwin, D. and Mccable, A.L. (1991), "Bond of epoxy-coated reinforcement to concrete: splices", SL report 91-1, University of Kansas Center for Research, Lawrence., 66 pp.
  22. Hester, C.J., Salamizavaregh, S., Darwin, D. and Mccable, A.L. (1993), "Bond of epoxy-coated reinforcement to concrete: splices", ACI. Struct. J., 90(1), 89-102.
  23. Hinchliffe, M.P., Willis, M.J., Hiden, H.G., Tham, M.T., McKay, B and Barton, G.W. (1996), "Modelling chemical process systems using a multi-gene genetic programming algorithm", Proceedings of the First Annual Conference in Genetic Programming, MIT Press Cambridge, MA, USA.
  24. Hassan, T.K., Lucier G.W. and Rizkalla, S.H. (2012), "Splice strength of large diameter, high strength steel reinforcing bars", Constr. Build. Mater., 26(1), 216-225.
  25. Ichinose, T., Kanayama, Y, Inoune, Y. and Bolander, J.E. (2004), "Size effect on bond strength of deformed bars", Constr. Build. Mater., 18(7), 549-558. https://doi.org/10.1016/j.conbuildmat.2004.03.014
  26. JSCE (2007), "Standard specification for concrete structures: design (JSCE)", Japan Society of Civil Engineers, Tokyo, Japan., 503 pp.
  27. 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. https://doi.org/10.1016/j.advengsoft.2011.02.002
  28. Kose, M.M. and Kayadelen, C. (2010), "Modeling of transfer length of prestressing strands using genetic programming and neuro-fuzzy", Adv. Eng. Softw., 41(2), 315-322. https://doi.org/10.1016/j.advengsoft.2009.06.013
  29. Koza, J.R. (1992), Genetic Programming: on the Programming of Computers by Means of Natural Selection, MIT Press Cambridge, MA, USA.
  30. Lutz, L.A. and Gergely, P. (1967), "Mechanics of bond and slip of deformed bars in concrete", ACI. J. Proc., 64(11), 711-721.
  31. Mathey, R. and Watstein, D. (1961), "Investigation of bond in beam and pull-Out specimens with high-yieldstrength deformed bars", ACI. J. Proc., 58(9), 1071-1090.
  32. Mousavi, S.M., Aminian, P., Gandomi, A.H., Alavi, A.H. and Bolandi, H. (2012), "A new predictive model for compressive strength of HPC using gene expression programming", Adv. Eng. Softw.., 45(1), 105-114. https://doi.org/10.1016/j.advengsoft.2011.09.014
  33. Orangun, C., Jirsa, J.O. and Breen, J.E. (1977), "A reevaluation of test data on development length and splices", ACI. J. Proc., 74(3), 114-122.
  34. Ozbay, E., Gesoglu, M. and Guneyisi, E. (2008), "Empirical modeling of fresh and hardened properties of self-compacting concretes by genetic programming", Constr. Build. Mater., 22(8), 1831-1840. https://doi.org/10.1016/j.conbuildmat.2007.04.021
  35. Perez, J.L., Cladera, A., Rabual, J.R. and Abella, F.M. (2010), "Optimization of existing equations using a new Genetic Programming algorithm: Application to the shear strength of reinforced concrete beams", Adv. Eng. Software., 50, 82-96.
  36. Perez, J.L., Cladera, A., Rabual, J.R. and Abella, F.M. (2012), "Optimal adjustment of EC-2 shear formulation for concrete elements without web reinforcement using Genetic Programming", J. Eng. Struct., 32(11), 3452-3466.
  37. Perez, J.L., Vieito, I., Rabunal, J. and Martinez-Abella, F. (2013), Genetic Programming to Improvement FIB Model, Lecture notes in computer science., In Advances in Computational Intelligence., Springer Berlin Heidelberg., 7902, 463-470.
  38. Ramezanianpour, A.A. and Davarpanah, A. (2002), "Concrete properties estimation and mix design optimization based on neural networks", Proceedings of the World Conference on concrete materials and structures (WCCNS), Kualalumpur, Malaysia.
  39. Rezansoff, T., Konkankar, U.S. and Fu, Y.C. (1991), Confinement limits for tension lap splices under static loading, ReportNo.S7N 0W0, University of Saskatchewan.
  40. Saridemir, M. (2010), "Genetic programming approach for prediction of compressive strength of concretes containing rice husk ash", Constr. Build. Mater., 24(10), 1911-1919. https://doi.org/10.1016/j.conbuildmat.2010.04.011
  41. Searson, D. (2009), "Genetic programming & symbolic regression for MATLAB (GPTIPS)", http://gptips.sourceforge.net.
  42. Seliem, H.M., Hosny, A., Rizkalla, S., Zia, P., Briggs, M., Miller, S., Darwin, D., Browning, J., Glass, G.M., Hoyt, K., Donnelly, K. and Jirsa, J.O. (2009), "Bond characteristics of ASTM A1035 steel reinforcing bars", ACI. Struct. J., 106(4), 530-539.
  43. Sonebi, M. and Cevik, A. (2009), "Genetic programming based formulation for fresh and hardened properties of self-compacting concrete containing pulverised fuel ash", Constr. Build. Mater., 23(7), 2614-2622. https://doi.org/10.1016/j.conbuildmat.2009.02.012
  44. Tanyildizi, H. (2009), "Fuzzy logic model for the prediction of bond strength of high-strength lighweight concrete", Adv. Eng. Softw., 40(3), 161-169. https://doi.org/10.1016/j.advengsoft.2007.05.013
  45. Tanyildizi, H. and Cevik, A. (2010), "Modeling mechanical performance of lightweight concrete containing silica fume exposed to high temperature using genetic programming", Constr. Build. Mater., 24(12), 2612-2618. https://doi.org/10.1016/j.conbuildmat.2010.05.001
  46. Tepfers, R. (1973), "A theory of bond applied to overlapping tensile reinforcement splices for deformed bars", publication 73:2, division of concrete structures, Goteborg, Sweden, Chalmers University of Technology., 328 pp.
  47. Untrauer, R.E. (1965), "Discussion of development length for large high strength reinforcing bars", ACI. J. Proc., 62(9), 1153-1154.
  48. Zuo, J. and Darwin, D. (1998), Bond Strength of High Relative Rib Area Reinforcing Bars, SM Report No. 46, University of Kansas Center for Research, Lawrence, Kansas, USA., 350 pp.
  49. Zuo, J. and Darwin, D. (2000), "Splice strength of conventional and high relative rib area bars in normal and high-strength concrete", ACI. Struct. J., 97(4), 630-641.

Cited by

  1. Implementation of bond-slip effects on behaviour of slabs in structures vol.16, pp.2, 2015, https://doi.org/10.12989/cac.2015.16.2.311
  2. Local bond stress-slip behavior of reinforcing bars embedded in lightweight aggregate concrete vol.16, pp.3, 2015, https://doi.org/10.12989/cac.2015.16.3.449
  3. Influence of ground pumice powder on the bond behavior of reinforcement and mechanical properties of self-compacting mortars vol.20, pp.3, 2014, https://doi.org/10.12989/cac.2017.20.3.283
  4. Prediction of creep in concrete using genetic programming hybridized with ANN vol.21, pp.5, 2014, https://doi.org/10.12989/cac.2018.21.5.513
  5. Local bond-slip behavior of medium and high strength fiber reinforced concrete after exposure to high temperatures vol.66, pp.4, 2014, https://doi.org/10.12989/sem.2018.66.4.477
  6. Local bond-slip behavior of fiber reinforced LWAC after exposure to elevated temperatures vol.73, pp.4, 2020, https://doi.org/10.12989/sem.2020.73.4.437
  7. A new formulation for strength characteristics of steel slag aggregate concrete using an artificial intelligence-based approach vol.27, pp.4, 2014, https://doi.org/10.12989/cac.2021.27.4.333
  8. Efficient soft computing techniques for the prediction of compressive strength of geopolymer concrete vol.28, pp.2, 2014, https://doi.org/10.12989/cac.2021.28.2.221