Advances in Computational Design

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Application of ANFIS to the design of elliptical CFST columns

  • Received : 2021.05.18
  • Accepted : 2023.04.27
  • Published : 2023.04.25
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Abstract

Elliptical concrete-filled steel tubular (CFST) column is widely used in modern structures for both aesthetical appeal and structural performance benefits. The ultimate axial load is a critical factor for designing the elliptical CFST short columns. However, there are complications of geometric and material interactions, which make a difficulty in determining a simple model for predicting the ultimate axial load of elliptical CFST short columns. This study aims to propose an efficient adaptive neuro-fuzzy inference system (ANFIS) model for predicting the ultimate axial load of elliptical CFST short columns. In the proposed method, the ANFIS model is used to establish a relationship between the ultimate axial load and geometric and material properties of elliptical CFST short columns. Accordingly, a total of 188 experimental and simulation datasets of elliptical CFST short columns are used to develop the ANFIS models. The performance of the proposed ANFIS model is compared with that of existing design formulas. The results show that the proposed ANFIS model is more accurate than existing empirical and theoretical formulas. Finally, an explicit formula and a Graphical User Interface (GUI) tool are developed to apply the proposed ANFIS model for practical use.

Keywords

References

  1. ACI 318 (2014), Building code requirements for structural concrete, ACI 318-14, American Concrete Institute, U.S.A.
  2. Ahmadi, M., Naderpour, H. and Kheyroddin, A. (2014), "Utilization of artificial neural networks to prediction of the capacity of CCFT short columns subject to short term axial load", Arch. Civil Mech. Eng., 14(3), 510-517. https://doi.org/10.1016/j.acme.2014.01.006
  3. Ahmadi, M., Naderpour, H. and Kheyroddin, A. (2017), "ANN model for predicting the compressive strength of circular steel-confined concrete", Int. J. Civil Eng., 15(2), 213-221. https://doi.org/10.1007/s40999-016-0096-0
  4. Ahmed, M., Ci, J., Yan, X. F. and Chen, S. (2021), "Nonlinear analysis of elliptical concrete-filled stainless steel tubular short columns under axial compression", Structures, 32, 1374-1385. https://doi.org/10.1016/j.istruc.2021.03.095
  5. Ahmed, M. and Liang, Q.Q. (2020), "Computational simulation of elliptical concrete-filled steel tubular short columns including new confinement model", J. Constr. Steel Res., 174, 106294. https://doi.org/10.1016/j.jcsr.2020.106294
  6. ANFIS GUI tool (2023), Application of ANFIS to the design of elliptical CFST columns, Vinh University, Nghe An, Vietnam. https://github.com/VietLinhTran/Application-of-ANFIS-to-the-design-of-elliptical-CFST-columns
  7. Armaghani, D.J. and Asteris, P.G. (2021), "A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength", Neural Comput. Appl., 33(9), 4501-4532. https://doi.org/10.1007/s00521-020-05244-4
  8. Armaghani, D.J., Hatzigeorgiou, G.D., Karamani, C., Skentou, A., Zoumpoulaki, I. and Asteris, P.G. (2019), "Soft computing-based techniques for concrete beams shear strength", Procedia Struct. Integr., 17, 924-933. https://doi.org/10.1016/j.prostr.2019.08.123
  9. AS 5100.6 (2004), Bridge design-Steel and composite construction, AS 5100.6-2004, Standards Australia International Ltd GPO Box 5420, Sydney, NSW 2001, Australia.
  10. Asteris, P.G., Lemonis, M.E., Nguyen, T.A., Le, H.V. and Pham, B.T. (2021), "Soft computing-based estimation of ultimate axial load of rectangular concrete-filled steel tubes", Steel Compos. Struct., 39(4), 471-491. https://doi.org/10.12989/scs.2021.39.4.471
  11. Asteris, P.G. and Mokos, V.G. (2020), "Concrete compressive strength using artificial neural networks", Neural Comput. Appl., 32(15), 11807-11826. https://doi.org/10.1007/s00521-019-04663-2
  12. Cai, B., Pan, G. and Fu, F. (2020), "Prediction of the postfire flexural capacity of RC beam using GA-BPNN machine learning", J. Perform. Constr. Facilities, 34(6), 04020105. https://doi.org/10.1061/(ASCE)CF.1943-5509.0001514
  13. Chan, T.M. and Gardner, L. (2008), "Compressive resistance of hot-rolled elliptical hollow sections", Eng. Struct., 30(2), 522-532. https://doi.org/10.1016/j.engstruct.2007.04.019
  14. Chan, T.M., Gardner, L. and Law, K.H. (2010), "Structural design of elliptical hollow sections: A review", Proceedings of the Institution of Civil Engineers: Structures and Buildings, 163(6), 391-402. https://doi.org/10.1680/stbu.2010.163.6.391
  15. Chan, T.M., Huai, Y. and Wang, W. (2015), "Experimental investigation on lightweight concrete-filled cold-formed elliptical hollow section stub columns", J. Constr. Steel Res., 115, 434-444. https://doi.org/10.1016/j.jcsr.2015.08.029
  16. Chiu, S.L. (1994), "Fuzzy model identification based on cluster estimation", J. Intell. Fuzzy Syst., 2(3), 267-278. https://doi.org/10.3233/IFS-1994-2306
  17. Cook, R., Lapeyre, J., Ma, H. and Kumar, A. (2019), "Prediction of compressive strength of concrete: Critical comparison of performance of a hybrid machine learning model with standalone models", J. Mater. Civil Eng., 31(11), 1-15. https://doi.org/10.1061/(asce)mt.1943-5533.0002902
  18. Dai, X. and Lam, D. (2010a), "Axial compressive behaviour of stub concrete-filled columns with elliptical stainless steel hollow sections", Steel Compos. Struct., 10(6), 517-539. https://doi.org/10.12989/scs.2010.10.6.517
  19. Dai, X. and Lam, D. (2010b), "Numerical modelling of the axial compressive behaviour of short concrete-filled elliptical steel columns", J. Constr. Steel Res., 66(7), 931-942. https://doi.org/10.1016/j.jcsr.2010.02.003
  20. Dauji, S. (2020), "Prediction of concrete spall damage under blast: Neural approach with synthetic data", Comput. Concr., 26(6), 533-546. https://doi.org/10.12989/cac.2020.26.6.533
  21. Ding, F.X., Yu, Z.W., Bai, Y. and Gong, Y.Z. (2011), "Elasto-plastic analysis of circular concrete-filled steel tube stub columns", J. Constr. Steel Res., 67(10), 1567-1577. https://doi.org/10.1016/j.jcsr.2011.04.001
  22. Duan, J., Asteris, P.G., Nguyen, H., Bui, X.N. and Moayedi, H. (2021), "A novel artificial intelligence technique to predict compressive strength of recycled aggregate concrete using ICA-XGBoost model", Eng. Comput., 37(4), 3329-3346. https://doi.org/10.1007/s00366-020-01003-0
  23. Espinos, A., Gardner, L., Romero, M.L. and Hospitaler, A. (2011), "Fire behaviour of concrete filled elliptical steel columns", Thin Wall. Struct., 49(2), 239-255. https://doi.org/10.1016/j.tws.2010.10.008
  24. Eurocode 4 (2011), Design of composite steel and concrete structures - Part 1-1: General rules and rules for buildings, 1(2005), The European Union.
  25. Guneyisi, E.M., Gultekin, A. and Mermerdas, K. (2016), "Ultimate capacity prediction of axially loaded CFST short columns", Int. J. Steel Struct., 16(1), 99-114. https://doi.org/10.1007/s13296-016-3009-9
  26. Hassanein, M.F., Patel, V.I., El Hadidy, A.M., Al Abadi, H. and Elchalakani, M. (2018), "Structural behaviour and design of elliptical high-strength concrete-filled steel tubular short compression members", Eng. Struct., 173, 495-511. https://doi.org/10.1016/j.engstruct.2018.07.023
  27. Ipek, S. and Guneyisi, E.M. (2019), "Ultimate axial strength of concrete-filled double skin steel tubular column sections.", Adv. Civil Eng., 2019, 6493037. https://doi.org/10.1155/2019/6493037
  28. Jamaluddin, N., Lam, D., Dai, X. H. and Ye, J. (2013), "An experimental study on elliptical concrete filled columns under axial compression", J. Constr. Steel Res., 87, 6-16. https://doi.org/10.1016/j.jcsr.2013.04.002
  29. Jang, J.R. (1993), "ANFIS: adaptive-network-based fuzzy inference system", IEEE T. Syst. Man Cybernet., 23(3), 665-685. https://doi.org/10.1109/21.256541
  30. Kar, S. and Biswal, K.C. (2020), "FRP shear contribution prediction for U-wrapped RC T-beams using a soft computing tool", Structures, 27, 1093-1104. https://doi.org/10.1016/j.istruc.2020.06.023
  31. Kar, S., Pandit, A.R. and Biswal, K.C. (2020), "Prediction of FRP shear contribution for wrapped shear deficient RC beams using adaptive neuro-fuzzy inference system (ANFIS)", Structures, 23, 702-717. https://doi.org/10.1016/j.istruc.2019.10.022
  32. Keshavarzi, A., Sarmadian, F., Shiri, J., Iqbal, M., Tirado-Corbala, R. and Omran, E.S.E. (2017), "Application of ANFIS-based subtractive clustering algorithm in soil Cation Exchange Capacity estimation using soil and remotely sensed data", Measurement, 95, 173-180. https://doi.org/10.1016/j.measurement.2016.10.010
  33. Lam, D., Gardner, L. and Burdett, M. (2010), "Behaviour of axially loaded concrete filled stainless steel elliptical stub columns", Adv. Struct. Eng., 13(3), 493-500. https://doi.org/10.1260/1369-4332.13.3.493
  34. Liang, Q.Q. (2009), "Performance-based analysis of concrete-filled steel tubular beam-columns, Part I: Theory and algorithms", J. Constr. Steel Res., 65(2), 363-372. https://doi.org/10.1016/j.jcsr.2008.03.007
  35. Liu, F., Wang, Y. and Chan, T.M. (2017), "Behaviour of concrete-filled cold-formed elliptical hollow sections with varying aspect ratios", Thin Wall. Struct., 110, 47-61. https://doi.org/10.1016/j.tws.2016.10.013
  36. Liu, X.C. and Zha, X.X. (2011), "Study on behavior of elliptical concrete filled steel tube members I: Stub and long columns under axial compression", Prog. Steel Build. Struct., 1, 8-14.
  37. 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. Concr., 25(1), 1-14. https://doi.org/10.12989/cac.2020.25.1.001
  38. Ly, H.B., Pham, B.T., Le, L.M., Le, T.T., Le, V.M. and Asteris, P.G. (2021), "Estimation of axial load-carrying capacity of concrete-filled steel tubes using surrogate models", Neural Comput. Appl., 33(8), 3437-3458. https://doi.org/10.1007/s00521-020-05214-w
  39. Mamdani, E.H. and Assilian, S. (1975), "An experiment in linguistic synthesis with a fuzzy logic controller", Int. J. Man Mach. Stud., 7(1), 1-13. https://doi.org/10.1016/S0020-7373(75)80002-2
  40. Mander, J.B., Priestley, M.J.N. and Park, R. (1988), "Theoretical stress-strain model for confined concrete", J. Struct. Eng., 114(8), 1804-1826. https://doi.org/10.1061/(asce)0733-9445(1988)114:8(1804)
  41. Mirrashid, M. (2014), "Earthquake magnitude prediction by adaptive neurofuzzy inference system (ANFIS) based on fuzzy C-means algorithm", Natural Hazards, 74(3), 1577-1593. https://doi.org/10.1007/s11069-014-1264-7
  42. 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
  43. Moon, J., Roeder, C.W., Lehman, D.E. and Lee, H.E. (2012), "Analytical modeling of bending of circular concrete-filled steel tubes", Eng. Struct., 42, 349-361. https://doi.org/10.1016/j.engstruct.2012.04.028
  44. Naderloo, L., Alimardani, R., Omid, M., Sarmadian, F., Javadikia, P., Torabi, M.Y. and Alimardani, F. (2012), "Application of ANFIS to predict crop yield based on different energy inputs", Measure. J. Int. Measure. Confederat., 45(6), 1406-1413. https://doi.org/10.1016/j.measurement.2012.03.025
  45. Nguyen, V.Q., Tran, V.L., Nguyen, D.D., Sadiq, S. and Park, D. (2022), "Novel hybrid MFO-XGBoost model for predicting the racking ratio of the rectangular tunnels subjected to seismic loading", Transp. Geotech., 37, 100878. https://doi.org/10.1016/j.trgeo.2022.100878
  46. Patel, V.I., Uy, B., Prajwal, K.A. and Aslani, F. (2016), "Confined concrete model of circular, elliptical and octagonal CFST short columns", Steel Compos. Struct., 22(3), 497-520. https://doi.org/10.12989/scs.2016.22.3.497
  47. Ren, Q., Li, M., Zhang, M., Shen, Y. and Si, W. (2019), "Prediction of ultimate axial capacity of square concrete-filled steel tubular short columns using a hybrid intelligent algorithm", Appl. Sci., 9(14). https://doi.org/10.3390/app9142802
  48. Sadrmomtazi, A., Sobhani, J. and Mirgozar, M.A. (2013), "Modeling compressive strength of EPS lightweight concrete using regression, neural network and ANFIS", Constr. Build. Mater., 42(2), 205-216. https://doi.org/10.1016/j.conbuildmat.2013.01.016
  49. Sarir, P., Chen, J., Asteris, P.G., Armaghani, D.J. and Tahir, M.M. (2021), "Developing GEP tree-based, neuro-swarm, and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns", Eng. Comput., 37(1), 1-19. https://doi.org/10.1007/s00366-019-00808-y
  50. Shariati, M., Mafipour, M.S., Haido, J.H., Yousif, S.T., Toghroli, A., Trung, N.T. and Shariati, A. (2020), "Identification of the most influencing parameters on the properties of corroded concrete beams using an Adaptive Neuro-Fuzzy Inference System (ANFIS)", Comput. Concr., 25(1), 155-170. https://doi.org/10.12989/cac.2020.25.1.083
  51. Sheehan, T., Dai, X.H., Chan, T.M. and Lam, D. (2012), "Structural response of concrete-filled elliptical steel hollow sections under eccentric compression", Eng. Struct., 45, 314-323. https://doi.org/10.1016/j.engstruct.2012.06.040
  52. Shen, Q., Wang, J., Wang, W. and Wang, J. (2015), "Axial compressive behavior and bearing capacity calculation of ECFST columns based on numerical analysis", Prog. Steel Build. Struct., 17(6), 68-78. https://doi.org/10.13969/j.cnki.cn31-1893.2015.06.009
  53. Sklar, S., Fish, D. and Simpson Stern, C. (2017), "Reflections", Text Perform. Quarter., 37(2), 169-170. https://doi.org/10.1080/10462937.2017.1349256
  54. Sugeno, M. (1985), "An introductory survey of fuzzy control", Inform. Sci., 36(1-2), 59-83. https://doi.org/10.1016/0020-0255(85)90026-X
  55. Sun, G., Hasanipanah, M., Bakhshandeh Amnieh, H. and Foong, L.K. (2020), "Feasibility of indirect measurement of bearing capacity of driven piles based on a computational intelligence technique", Measure. J. Int. Measure. Confederat., 156, 107577. https://doi.org/10.1016/j.measurement.2020.107577
  56. Systemes, D. (2014), Abaqus version 6.14-4 documentation. Waltham, MA: Dassault Systems Simulia Corporation.
  57. Tran, V.L., Ahmed, M. and Gohari, S. (2023), "Prediction of the ultimate axial load of circular concrete-filled stainless steel tubular columns using machine learning approaches", Struct. Concr., 2023. https://doi.org/10.1002/suco.202200877
  58. Tran, V.L. and Kim, J.K. (2023a), "Innovative formulas for reinforcing bar bonding failure stress of tension lap splice using ANN and TLBO", Constr. Build. Mater., 369, 130500. https://doi.org/10.1016/j.conbuildmat.2023.130500
  59. Tran, V.L. and Kim, J.K. (2023b), "Ensemble machine learning-based models for estimating the transfer length of strands in PSC beams", Exp. Syst. Appl., 221, 119768. https://doi.org/10.1016/j.eswa.2023.119768
  60. Tran, V.L. and Kim, S.E. (2020), "Efficiency of three advanced data-driven models for predicting axial compression capacity of CFDST columns", Thin Wall. Struct., 152, 106744. https://doi.org/10.1016/j.tws.2020.106744
  61. Tran, V.L., Thai, D.K. and Kim, S.E. (2019a), "Application of ANN in predicting ACC of SCFST column", Compos. Struct., 228. https://doi.org/10.1016/j.compstruct.2019.111332
  62. Tran, V.L., Thai, D.K. and Kim, S.E. (2019b), "A new empirical formula for prediction of the axial compression capacity of CCFT columns", Steel Compos. Struct., 33(2), 181-194. https://doi.org/10.12989/scs.2019.33.2.181
  63. Uenaka, K. (2014), "Experimental study on concrete filled elliptical/oval steel tubular stub columns under compression", Thin Wall. Struct., 78, 131-137. https://doi.org/10.1016/j.tws.2014.01.023
  64. Umrao, R.K., Sharma, L.K., Singh, R. and Singh, T.N. (2018), "Determination of strength and modulus of elasticity of heterogenous sedimentary rocks: An ANFIS predictive technique", Measure. J. Int. Measure. Confederat., 126, 194-201. https://doi.org/10.1016/j.measurement.2018.05.064
  65. Vahidi, E.K., Malekabadi, M.M., Rezaei, A., Roshani, M.M. and Roshani, G.H. (2017), "Modeling of mechanical properties of roller compacted concrete containing RHA using ANFIS", Comput. Concr., 19(4), 435-442. https://doi.org/10.12989/cac.2017.19.4.435
  66. Vakhshouri, B. and Nejadi, S. (2018), "Prediction of compressive strength of self-compacting concrete by ANFIS models", Neurocomputing, 280, 13-22. https://doi.org/10.1016/j.neucom.2017.09.099
  67. Xue, X. and Zhou, H. (2018), "Neuro-fuzzy based approach for estimation of concrete compressive strength", Comput. Concr., 21(6), 697-703. https://doi.org/10.12989/cac.2018.21.6.697
  68. Yang, H., Lam, D. and Gardner, L. (2008), "Testing and analysis of concrete-filled elliptical hollow sections", Eng. Struct., 30(12), 3771-3781. https://doi.org/10.1016/j.engstruct.2008.07.004
  69. Yang, H., Liu, F., Chan, T. and Wang, W. (2017), "Behaviours of concrete-filled cold-formed elliptical hollow section beam-columns with varying aspect ratios", Thin Wall. Struct., 120, 9-28. https://doi.org/10.1016/j.tws.2017.08.018
  70. Yaylaci, E.U., Yaylaci, M., Olmez, H. and Birinci, A. (2020), "Artificial neural network calculations for a receding contact problem", Comput. Concr., 25(6), 551-563. https://doi.org/10.12989/cac.2020.25.6.551
  71. Zha, X., Gong, G. and Liu, X. (2013), "Study on behavior of concrete filled elliptical steel tube members part I: Short and long columns under axial compression", Group Org. Manag., 38(4), 90-107. http://en.cnki.com.cn/Article_en/CJFDTotal-JZJZ201101005.htm 101005.htm
  72. Zhao, X.L. and Packer, J.A. (2009), "Tests and design of concrete-filled elliptical hollow section stub columns", Thin Wall. Struct., 47(6-7), 617-628. https://doi.org/10.1016/j.tws.2008.11.004
  73. Zorlu, K., Gokceoglu, C., Ocakoglu, F., Nefeslioglu, H.A. and Acikalin, S. (2008), "Prediction of uniaxial compressive strength of sandstones using petrography-based models", Eng. Geol., 96(3-4), 141-158. https://doi.org/10.1016/j.enggeo.2007.10.009