Steel and Composite Structures

  • 제35권3호
  • /
  • Pages.415-437
  • /
  • 2020
  • /
  • 1229-9367(pISSN)
  • /
  • 1598-6233(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Predicting the axial compressive capacity of circular concrete filled steel tube columns using an artificial neural network

  • Nguyen, Mai-Suong T. (Department of Civil and Environmental Engineering, Sejong University) ;
  • Thai, Duc-Kien (Department of Civil and Environmental Engineering, Sejong University) ;
  • Kim, Seung-Eock (Department of Civil and Environmental Engineering, Sejong University)
  • 투고 : 2019.12.24
  • 심사 : 2020.04.10
  • 발행 : 2020.05.10
⟨ 이전 논문 다음 논문 ⟩

초록

Circular concrete filled steel tube (CFST) columns have an advantage over all other sections when they are used in compression members. This paper proposes a new approach for deriving a new empirical equation to predict the axial compressive capacity of circular CFST columns using the Artificial Neural Network (ANN). The developed ANN model uses 5 input parameters that include the diameter of circular steel tube, the length of the column, the thickness of steel tube, the steel yield strength and the compressive strength of concrete. The only output parameter is the axial compressive capacity. Training and testing the developed ANN model was carried out using 219 available sets of data collected from the experimental results in the literature. An empirical equation is then proposed as an important result of this study, which is practically used to predict the axial compressive capacity of a circular CFST column. To evaluate the performance of the developed ANN model and the proposed equation, the predicted results are compared with those of the empirical equations stated in the current design codes and other models. It is shown that the proposed equation can predict the axial compressive capacity of circular CFST columns more accurately than other methods. This is confirmed by the high accuracy of a large number of existing test results. Finally, the parametric study result is analyzed for the proposed ANN equation to consider the effect of the input parameters on axial compressive strength.

키워드

과제정보

This research described in this paper was financially supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (No.2018R1A2A2A05018524 and No. 2019R1A4A1021702).

참고문헌

  1. Abed, F., Alhamaydeh, M. and Abdalla, S. (2013), "Experimental and numerical investigations of the compressive behavior of concrete filled steel tubes (CFSTs)", J. Constr. Steel Res., 80, 429-439. https://doi.org/10.1016/j.jcsr.2012.10.005.
  2. AIJ. Recommendations for design and construction of concrete filled steel tubular structures, (1997). Architectural Institute of Japan, Tokyo.
  3. Altun, F., Kisi, O. and Aydin, K. (2008), "Predicting the compressive strength of steel fiber added lightweight concrete using neural network", Comput. Mater. Sci., 42(2), 259-265. https://doi.org/10.1016/j.commatsci.2007.07.011
  4. American concrete institute, (1962), ACI 318. Building code requirements for structural concrete and commentary (Vol. 552). USA.
  5. Aslani, F., Lloyd, R., Uy, B., Kang, W.H. and Hicks, S., (2016), "Statistical calibration of safety factors for flexural stiffness of composite columns", Steel Compos. Struct., 20(1), 127-145. https://doi.org/10.12989/scs.2016.20.1.127.
  6. Aslani, F., Uy, B., Tao, Z. and Mashiri, F., (2015), "Predicting the axial load capacity of high-strength concrete filled steel tubular columns", Steel Compos. Struct., 19(4), 967-993. https://doi.org/10.12989/scs.2015.19.4.967.
  7. Aslani, F., Uy, B., Wang, Z. and Patel, V., (2016), "Confinement models for high strength short square and rectangular concretefilled steel tubular columns", Steel Compos. Struct., 22(5), 937-974. https://doi.org/10.12989/scs.2016.22.5.937.
  8. Beck, A.T., de Oliveira, W.L.A., De Nardim, S. and ElDebs, A.L. H. C., (2009), "Reliability-based evaluation of design code provisions for circular concrete-filled steel columns", Eng. Struct., 31(10), 2299-2308. https://doi.org/10.1016/j.engstruct.2009.05.004.
  9. Cheng, M.Y. and Cao, M.T. (2014), "Evolutionary multivariate adaptive regression splines for estimating shear strength in reinforced-concrete deep beams", Eng. Appl. Artif. Intell., 28, 86-96. https://doi.org/10.1016/j.engappai.2013.11.001
  10. Dantas, A.T.A., Batista Leite, M. and De Jesus Nagahama, K. (2013), "Prediction of compressive strength of concrete containing construction and demolition waste using artificial neural networks", Constr. Build. Mater., 38, 717-722. https://doi.org/10.1016/j.conbuildmat.2012.09.026.
  11. Das, S. and Choudhury, S. (2019), "Influence of effective stiffness on the performance of RC frame buildings designed using displacement-based method and evaluation of column effective stiffness using ANN", Eng. Struct., 197, 109354. https://doi.org/10.1016/j.engstruct.2019.109354.
  12. Duan, Z.H., Kou, S.C. and Poon, C.S. (2013), "Prediction of compressive strength of recycled aggregate concrete using artificial neural networks", Constr. Build. Mater., 40, 1200-1206. https://doi.org/10.1016/j.conbuildmat.2012.04.063.
  13. Ekmekyapar, T. and Ghanim Hasan, H. (2019), "The influence of the inner steel tube on the compression behaviour of the concrete filled double skin steel tube (CFDST) columns", Mar. Struct., 66, 197-212. https://doi.org/10.1016/j.marstruc.2019.04.006.
  14. Eurocode 4: Design of composite steel and concrete structures. Part 1.1, General rules and rules for buildings. EN 1994-1-1:2004, (2004). Brussels.
  15. Furlong, R.W. (1967), "Strength of steel-encased concrete beam columns", J. Struct. Div.
  16. Giakoumelis, G. and Lam, D. (2004), "Axial capacity of circular concrete-filled tube columns", J. Constr. Steel Res., 60(7), 1049-1068. https://doi.org/10.1016/j.jcsr.2003.10.001.
  17. Goode, C.D. (2008), "Composite Columns-1819 Tests on Concrete-Filled Steel Tube Columns Compared with Eurocode 4", Inst. Struct. Eng., 86, 33-38.
  18. Gupta, P.K., Sarda, S.M. and Kumar, M.S. (2007), "Experimental and computational study of concrete filled steel tubular columns under axial loads", J. Constr. Steel Res., 63(2), 182-193. https://doi.org/10.1016/j.jcsr.2006.04.004
  19. Hasan, H.G., Ekmekyapar, T. and Shehab, B.A. (2019), "Mechanical performances of stiffened and reinforced concretefilled steel tubes under axial compression", Mar. Struct., 65, 417-432. https://doi.org/10.1016/j.marstruc.2018.12.008.
  20. Hayashi, F. (1990), Study on mechanical behavior of circular confined concrete column under axial compression. Kyushu University.
  21. Hwang, H.J., Baek, J.W., Kim, J.Y. and Kim, C.S. (2019), "Prediction of bond performance of tension lap splices using artificial neural networks", Eng. Struct., 198, 109535. https://doi.org/10.1016/j.engstruct.2019.109535.
  22. Ioffe, S. (2017), "Batch renormalization: Towards reducing minibatch dependence in batch-normalized models", Proceedings of the 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA.
  23. Kang, J.Y., Choi, B.I. and Lee, H.J. (2006), "Application of artificial neural network for predicting plain strain fracture toughness using tensile test results", Fatigue Fract. Eng. Mater. Struct., 29(4), 321-329. https://doi.org/10.1111/j.1460-2695.2006.00994.x.
  24. Ketkar, N., (2017), Deep Learning with Python-A Hands-on Introduction. https://doi.org/10.1007/978-1-4842-2766-4.
  25. Larocca, C.B., Farias, C.T.T., Simas Filho, E.F. and Silva, I.C. (2018), "Wall thinning characterization of composite reinforced steel tube using frequency-domain PEC technique and neural networks", J. Nondestruct. Eval., 37(3), 1-8. https://doi.org/10.1007/s10921-018-0477-1.
  26. Lee, S. and Lee, C. (2014), "Prediction of shear strength of FRP-reinforced concrete flexural members without stirrups using artificial neural networks", Eng. Struct., 61, 99-112. https://doi.org/10.1016/j.engstruct.2014.01.001.
  27. Li, Y., Han, L., Xu, W. and Tao, Z. (2016), "Circular concreteencased concrete-filled steel tube (CFST) stub columns subjected to axial compression", Mag. Concr. Res., 68(19), 995-1010. https://doi.org/10.1680/jmacr.15.00359.
  28. Lin, C.Y. (1988), "Axial capacity of concrete infilled cold-formed steel columns", Proceedings of the 9th International Specialty Conference on Cold-Formed Steel Structures, 443-457. St. Louis, Missouri, U.S.A.
  29. Luat, N.V., Lee, K. and Thai, D.K. (2020), "Application of artificial neural networks in settlement prediction of shallow foundations on sandy soils", Geomech. Eng., 20(5), 385-397. https://doi.org/10.12989/gae.2020.20.5.385.
  30. Luat, N.V., Lee, J., Lee, D.H. and Lee, K. (2020), "GS-MARS method for predicting the ultimate load-carrying capacity of rectangular CFST columns under eccentric loading", Comput. Concret., 25(1), 1-14. https://doi.org/10.12989/cac.2020.25.1.001.
  31. Luksha, L.K. and Nesterovich, A.P. (1991), "Strength testing of large-diameter concrete filled steel tubular members", Proceedings of the Third International Conference on Steel-Concrete Composite Structures, ASCCS, Fukuoka, 67-70.
  32. Moon, J., Kim, J.J., Lee, T.H. and Lee, H.E. (2014), "Prediction of axial load capacity of stub circular concrete-filled steel tube using fuzzy logic", J. Constr. Steel Res., 101, 184-191. https://doi.org/10.1016/j.jcsr.2014.05.011
  33. Nikoo, M., Zarfam, P. and Sayahpour, H. (2013), "Determination of compressive strength of concrete using Self Organization Feature Map (SOFM)", Eng. Comput., 31(1), 113-121. https://doi.org/10.1007/s00366-013-0334-x.
  34. Oliveira, W.L.A. (2008), Theoretical-experimental analysis of circular concrete filled steel columns, Doctoral thesis. Sao Carlos School.
  35. O'Shea, M.D. and Bridge, R.Q. (2000), "Design of Circular Thin-Walled Concrete Filled Steel Tubes", J. Struct. Eng., 126(11), 1295-1303. https://doi.org/10.1061/(ASCE)0733-9445(2000)126:11(1295)
  36. Knowles, R.B. and Park, R. (1970), "Axial load design for concrete filled steel tubes", J. Struct. Div., 96(10), 2125-2153. https://doi.org/10.1061/JSDEAG.0002720
  37. Sakino, K., Nakahara, H., Morino, S. and Nishiyama, I. (2004), "Behavior of centrally loaded concrete-filled steel-tube short columns", J. Struct. Eng., 130(2), 180-188. https://doi.org/10.1061/(asce)0733-9445(2004)130:2(180)
  38. Salani, H.J. and Sims, J.R. (1964), "Behavior of Mortar Filled Steel Tubes in Compression", J. Proceedings, 1271-1284.
  39. Schneider, S.P. (1998), "Axially loaded concrete-filled steel tubes", J. Struct. Eng., 124(10), 1125-1138. https://doi.org/10.1061/(ASCE)0733-9445(1999)125:10(1202).
  40. Shanmugam, N.E. and Lakshmi, B. (2001), "State of the art report on steel-concrete composite columns", J. Constr. Steel Res., 57(10), 1041-1080. https://doi.org/10.1016/S0143-974X(01)00021-9.
  41. Tang, C.W. (2017), "Fire resistance of high strength fiber reinforced concrete filled box columns", Steel Compos. Struct., 23(5), 611-621. https://doi.org/10.12989/scs.2017.23.5.611.
  42. Tao, Z., Han, L.H. and Wang, L.L. (2007), "Compressive and flexural behaviour of CFRP-repaired concrete-filled steel tubes after exposure to fire", J. Constr. Steel Res., 63(8), 1116-1126. https://doi.org/10.1016/j.jcsr.2006.09.007.
  43. Tomii, M. (1977), "Experimental studies on concrete filled steel tubular stud columns under concentric loading", Proceedings of the International Colloquium on Stability of Structures Under Static and Dynamic Loads, 718-741. Washington, DC.
  44. Uy, B. (2001), "Strength of short concrete filled high strength steel box columns", J. Constr. Steel Res., 57(2), 113-134. https://doi.org/10.1016/S0143-974X(00)00014-6.
  45. Varma, A.H., Ricles, J.M., Sause, R. and Lu, L.W. (2002), "Seismic behavior and modeling of high-strength composite concrete-filled steel tube (CFT) beam-columns", J. Constr. Steel Res., 58(5-8), 725-758. https://doi.org/10.1016/S0143-974X(01)00099-2.
  46. Wang, L., Cao, X.X., Ding, F.X., Luo, L., Sun, Y., Liu, X.M., and Su, H.L. (2018), "Composite action of concrete-filled double circular steel tubular stub columns", Steel Compos. Struct., 29(1), 77-90. https://doi.org/10.12989/scs.2018.29.1.077.
  47. Xiao, Y. (1989), Experimental Study and Analytical Modeling of Triaxial Compressive Behavior of Confined Concrete, Ph.D. Thesis, Kyushu University, Fukuoka, Japan.
  48. Yamamoto, T., Kawaguchi, J. and Morino, S., (2000), "Scale Effects on Compressive Behavior of Concrete-Filled Steel Tube Short Columns", Compos. Constr. Steel Concr. IV, 25, 27-44. https://doi.org/10.1061/40616(281)76.
  49. Yaseen, Z.M., Tran, M.T., Kim, S., Bakhshpoori, T. and Deo, R.C. (2018), "Shear strength prediction of steel fiber reinforced concrete beam using hybrid intelligence models: A new approach", Eng. Struct., 177, 244-255. https://doi.org/10.1016/j.engstruct.2018.09.074
  50. Yoshioka, K., Inai, E., Hukumoto,N., Kai, M. and Murata, Y. (1995), "Compressive Tests on CFT Short Columns Part 1: Circular CFT Columns", Proceedings of the 2nd Jt. Tech. Coord. Comm. Compos. Hybrid Struct. Phase 5 Compos. Hybrid Struct.
  51. Yu, Q., Tao, Z. and Wu, Y.X. (2008), "Experimental behaviour of high performance concrete-filled steel tubular columns", Thin-Wall. Struct., 46(4), 362-370. https://doi.org/10.1016/j.tws.2007.10.001
  52. Zeghiche, J. and Chaoui, K. (2005), "An experimental behaviour of concrete-filled steel tubular columns", J. Constr. Steel Res., 61(1), 53-66. https://doi.org/10.1016/j.jcsr.2004.06.006.

피인용 문헌

  1. A neuro-fuzzy approach to predict the shear contribution of end-anchored FRP U-jackets vol.26, pp.5, 2020, https://doi.org/10.12989/cac.2020.26.5.397
  2. A Machine Learning-Based Model for Predicting Atmospheric Corrosion Rate of Carbon Steel vol.2021, 2020, https://doi.org/10.1155/2021/6967550
  3. Predicting the splitting tensile strength of concrete using an equilibrium optimization model vol.39, pp.1, 2020, https://doi.org/10.12989/scs.2021.39.1.081
  4. Ultimate axial capacity prediction of CCFST columns using hybrid intelligence models - a new approach vol.40, pp.3, 2021, https://doi.org/10.12989/scs.2021.40.3.461