DOI QR코드

DOI QR Code

Soft computing-based estimation of ultimate axial load of rectangular concrete-filled steel tubes

  • Asteris, Panagiotis G. (Computational Mechanics Laboratory, School of Pedagogical and Technological Education) ;
  • Lemonis, Minas E. (Computational Mechanics Laboratory, School of Pedagogical and Technological Education) ;
  • Nguyen, Thuy-Anh (University of Transport Technology) ;
  • Le, Hiep Van (Institute of Research and Development, Duy Tan University) ;
  • Pham, Binh Thai (University of Transport Technology)
  • Received : 2021.01.19
  • Accepted : 2021.04.19
  • Published : 2021.05.25

Abstract

In this study, we estimate the ultimate load of rectangular concrete-filled steel tubes (CFST) by developing a novel hybrid predictive model (ANN-BCMO) which is a combination of balancing composite motion optimization (BCMO) - a very new optimization technique and artificial neural network (ANN). For this aim, an experimental database consisting of 422 datasets is used for the development and validation of the ANN-BCMO model. Variables in the database are related with the geometrical characteristics of the structural members, and the mechanical properties of the constituent materials (steel and concrete). Validation of the hybrid ANN-BCMO model is carried out by applying standard statistical criteria such as root mean square error (RMSE), coefficient of determination (R2), and mean absolute error (MAE). In addition, the selection of appropriate values for parameters of the hybrid ANN-BCMO is conducted and its robustness is evaluated and compared with the conventional ANN techniques. The results reveal that the new hybrid ANN-BCMO model is a promising tool for prediction of the ultimate load of rectangular CFST, and prove the effective role of BCMO as a powerful algorithm in optimizing and improving the capability of the ANN predictor.

Keywords

References

  1. Abambres, M., Rajana, K., Tsavdaridis, K.D. and Ribeiro, T.P. (2019), "Neural Network-Based Formula for the Buckling Load Prediction of I-Section Cellular Steel Beams", Computers, 8, 2. https://doi.org/10.3390/computers8010002.
  2. 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, 213-221. https://doi.org/10.1007/s40999-016-0096-0
  3. Akbar, H., Suryana, N. and Sahib, S. (2011), "Training neural networks using Clonal Selection Algorithm and Particle Swarm Optimization: A comparisons for 3D object recognition", Proceedings of the 2011 11th International Conference on Hybrid Intelligent Systems (HIS).
  4. Al-Khaleefi, A.M., Terro, M.J., Alex, A.P. and Wang, Y. (2002), "Prediction of fire resistance of concrete filled tubular steel columns using neural networks", Fire Saf. J., 37, 339. https://doi.org/10.1016/S0379-7112(01)00065-0
  5. Ali, F., Nadjai, A. and Goodfellow, N. (2016), "Experimental and numerical study on the performance of hollow and concrete-filled elliptical steel columns subjected to severe fire", Fire Mater., 40, 635-652. https://doi.org/10.1002/fam.2316.
  6. Ali, F. and McKinney, J. (2014), "Artificial Neural Networks for the Spalling Classification & Failure Prediction Times of High Strength Concrete Columns", Fire Eng., 5, 203-214. https://doi.org/10.1260/2040-2317.5.3.203.
  7. Apostolopoulou, M., Armaghani, D.J., Bakolas, A., Douvika, M.G., Moropoulou, A. and Asteris, P.G. (2019), "Compressive strength of natural hydraulic lime mortars using soft computing techniques", Procedia Struct. Integrity, 17, 914-923. https://doi.org/10.1016/j.prostr.2019.08.122.
  8. Apostolopoulou, M., Asteris, P.G., Armaghani, D.J., Douvika, MG., Lourenco, P.B., Cavaleri, L., Bakolas, A. and Moropoulou, A. (2020), "Mapping and holistic design of natural hydraulic lime mortars", Cement Concrete Res., 136, 106167, https://doi.org/10.1016/j.cemconres.2020.106167.
  9. Aqil, M., Kita, I., Yano, A. and Nishiyama, S. (2007), "A comparative study of artificial neural networks and neuro-fuzzy in continuous modeling of the daily and hourly behaviour of runoff", J. Hydrology, 337, 22-34. https://doi.org/10.1016/j.jhydrol.2007.01.013.
  10. Arani, K.S., Zandi, Y., Pham, B.T., Muazu, M.A., Katebi, J., Mohammadhassani, M., Khalafi, S., Mohamad, E.T., Wakil, K. and Khorami, M. (2019), "Computational optimized finite element modeling of mechanical interaction of concrete with fiber reinforced polymer", Comput. Concrete, 23, 61-68. https://doi.org/10.12989/cac.2019.23.1.061.
  11. 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. Integrity, 17, 924-933. https://doi.org/10.1016/j.prostr.2019.08.123
  12. Armaghani, D.J. and Asteris, P.G. (2020), "A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength", Neural Comput. Appl., https://doi.org/10.1007/s00521-020-05244-4.
  13. Asgari, M., Babaee, A. and Jamshidi, M. (2018), "Multi-objective optimization of tapered tubes for crashworthiness by surrogate methodologies", Steel Compos. Struct., 27(4), 427-438. https://doi.org/10.12989/Scs.2018.27.4.427.
  14. Aslani, F., Uy, B., Tao, Z. and Mashiri, F. (2015), "Behaviour and design of composite columns incorporating compact high-strength steel plates", J. Constr. Steel Res., 107, 94-110. https://doi.org/10.1016/j.jcsr.2015.01.005.
  15. Asteris, P.G. and Mokos, V.G. (2019), "Concrete compressive strength using artificial neural networks", Neural Comput. Appl., 32, 11807. https://doi.org/10.1007/s00521-019-04663-2.
  16. Asteris, P.G. and Nikoo, M. (2019), "Artificial bee colony-based neural network for the prediction of the fundamental period of infilled frame structures", Neural Comput. Appl., 31, 4837-4847. https://doi.org/10.1007/s00521-018-03965-1.
  17. Asteris, P.G., Apostolopoulou, M., Skentou, A.D. and Moropoulou, A. (2019a). "Application of artificial neural networks for the prediction of the compressive strength of cement-based mortars", Comput. Concrete, 24, 329-345. https://doi.org/10.12989/cac.2019.24.4.329
  18. Asteris, P.G., Armaghani, D.J., Hatzigeorgiou, G.D., Karayannis, C.G. and Pilakoutas, K. (2019b). "Predicting the shear strength of reinforced concrete beams using Artificial Neural Networks", Comput. Concrete, 24, 469-488. https://doi.org/10.12989/cac.2019.24.5.469.
  19. Asteris, P.G., Moropoulou, A., Skentou, A.D., Apostolopoulou, M., Mohebkhah, A., Cavaleri, L., Rodrigues, H. and Varum, H. (2019c), "Stochastic vulnerability assessment of masonry structures: concepts modeling and restoration aspects", Appl. Sci., 9, 243. https://doi.org/10.3390/app9020243
  20. Baig, M.N., Fan, J. and Nie, J. (2006), "Strength of concrete filled steel tubular columns", Tsinghua Sci. Technol., 11, 657-666. https://doi.org/10.1016/S1007-0214(06)70248-6
  21. Battiti, R. (1992), "First- and Second-Order Methods for Learning: Between Steepest Descent and Newton's Method", Neural Comput., 4, 141-166. https://doi.org/10.1162/neco.1992.4.2.141.
  22. Bayat, M., Ghorbanpour, M., Zare, R., Jaafari, A. and Pham, B.T. (2019), "Application of artificial neural networks for predicting tree survival and mortality in the Hyrcanian forest of Iran", Comput. Electron. Agricult., 164, 104929. https://doi.org/10.1016/j.compag.2019.104929.
  23. Behnam, A. and Esfahani, M.R. (2018), "Prediction of biaxial bending behavior of steel-concrete composite beam-columns by artificial neural network", Iran Univ. Sci. Technol., 8, 381-399.
  24. Bergmann, R. (1994), "Load Introduction in Composite Columns Filled With High Strength Concrete", (Eds., Holgate A. Grundy and Wong), Tubular Structures VI, Proceedings of the Sixth International Symposium on Tubular Structures. Melbourne, Australia: A. A. Balkema, Rotterdam, The Netherlands. 373-380.
  25. Bradford, M.A., Loh, H.Y. and Uy, B. (2002), "Slenderness limits for filled circular steel tubes", J. Constr. Steel Res., 58, 243-252. https://doi.org/10.1016/S0143-974X(01)00043-8
  26. Bridge, R.Q. (1976), Concrete filled steel tubular columns. Sydney, Australia: School of Civil Engineering, University of Sydney. https://trove.nla.gov.au/work/35477622?q&versionId=44129332.
  27. Brownlee, J. (2016), Master Machine Learning Algorithms: Discover How They Work and Implement Them From Scratch, Machine Learning Mastery.
  28. Capillon, R., Desceliers, C. and Soize, C. (2016), "Uncertainty quantification in computational linear structural dynamics for viscoelastic composite structures", Comput. Method. Appl. M., 305, 154-172. https://doi.org/10.1016/j.cma.2016.03.012.
  29. Caprili, S. and Salvatore, W. (2015), "Cyclic behaviour of uncorroded and corroded steel reinforcing bars", Constr. Build. Mater., 76, 168-186. https://doi.org/10.1016/j.conbuildmat.2014.11.025.
  30. Chang, X., Wei, Y.Y. and Yun, Y.C. (2012). "Analysis of steel-reinforced concrete-filled-steel tubular (SRCFST) columns under cyclic loading", Constr. Build. Mater., 28, 88-95. https://doi.org/10.1016/j.conbuildmat.2011.08.033
  31. Chapman, J.C. and Neogi, P.K. (1964). Research on concrete-filled tubular columns. London: Engineering Structures Laboratories, Civil Engineering Dept., Imperial College.
  32. Chen, C.C., Ko, J.W., Huang, G.L. and Chang, Y.M. (2012), "Local buckling and concrete confinement of concrete-filled box columns under axial load", J. Constr.l Steel Res., 78, 8-21. https://doi.org/10.1016/j.jcsr.2012.06.006.
  33. Choi, K.K. and Xiao, Y. (2009), "Analytical studies of concrete-filled circular steel tubes under axial compression", J. Struct. Eng., 136, 565-573. https://doi.org/10.1061/(asce)st.1943-541x.0000156
  34. Dai, X. and Lam, D. (2010), "Numerical modelling of the axial compressive behaviour of short concrete-filled elliptical steel columns", J. Constr. Steel Res., 66, 931-942. https://doi.org/10.1016/j.jcsr.2010.02.003
  35. Dao, D.V., et al. (2020), "A spatially explicit deep learning neural network model for the prediction of landslide susceptibility", CATENA, 188, 104451. https://doi.org/10.1016/j.catena.2019.104451.
  36. Dao, D.V., Adeli, H., Ly, H.B., Le, L.M., Le, V.M., Le, T.T. and Pham, B.T. (2020b), "A Sensitivity and Robustness Analysis of GPR and ANN for High-Performance Concrete Compressive Strength Prediction Using a Monte Carlo Simulation", Sustainability, 12, 830. https://doi.org/10.3390/su12030830.
  37. Ding, F., Fang, C., Bai, Y. and Gong, Y. (2014). "Mechanical performance of stirrup-confined concrete-filled steel tubular stub columns under axial loading", J. Constr. Steel Res., 98, 146-157. https://doi.org/10.1016/j.jcsr.2014.03.005.
  38. Du, K.L. and Swamy, M.N. (2013), Neural networks and statistical learning. Springer Science & Business Media.
  39. Du, Y., Chen, Z. and Xiong, M.X. (2016), "Experimental behavior and design method of rectangular concrete-filled tubular columns using Q460 high-strength steel", Constr. Build. Mater., 125, 856-872. https://doi.org/10.1016/j.conbuildmat.2016.08.057.
  40. Du, Y., Chen, Z., Zhang, C. and Cao, X. (2017). "Research on axial bearing capacity of rectangular concrete-filled steel tubular columns based on artificial neural networks", Front. Comput. Sci., 11, 863-873. https://doi.org/10.1007/s11704-016-5113-6
  41. Duan, J., Asteris, P.G., Nguyen, H. Bui, X.N. and Moayedi, H. (2020), "A Novel Artificial Intelligence Technique to Predict Compressive Strength of Recycled Aggregate Concrete Using ICA-XGBoost Model", Eng. With Comput., https://doi.org/10.1007/s00366-020-01003-0.
  42. Dundu, M. (2016). "Column buckling tests of hot-rolled concrete filled square hollow sections of mild to high strength steel", Eng. Struct., 127, 73-85. https://doi.org/10.1016/j.engstruct.2016.08.039.
  43. Fam, A., Qie, F.S. and Rizkalla, S. (2004), "Concrete-filled steel tubes subjected to axial compression and lateral cyclic loads", J. Struct. Eng., 130, 631-640. https://doi.org/10.1061/(asce)0733-9445(2004)130:4(631)
  44. Fong, M., Chan, S.L. and Uy, B. (2011). "Advanced design for trusses of steel and concrete-filled tubular sections", Engineering Structures, 33, 3162-3171. https://doi.org/10.1016/j.engstruct.2011.08.002.
  45. Furlong, R.W. (1967), "Strength of Steel-Encased Concrete Beam Columns", J. Struct. Division, 93, 113-124. https://doi.org/10.1061/JSDEAG.0001761
  46. Ghannam, S., Jawad, Y.A. and Hunaiti, Y. (2004), "Failure of lightweight aggregate concrete-filled steel tubular columns", Steel Compo. Struct., 4, 1-8. https://doi.org/10.12989/scs.2004.4.1.001.
  47. Giakoumelis, G. and Lam, D. (2004), "Axial capacity of circular concrete-filled tube columns", J. Constr.l Steel Res., 60, 1049-1068. https://doi.org/10.1016/j.jcsr.2003.10.001
  48. Goel, T. and Tiwary, A. (2018), "Finite Element Modeling of Circular Concrete Filled Steel Tube (CFST)", Indian J. Sci. Technol., 11, 1-9. https://doi.org/10.17485/ijst/2018/v11i34/130853.
  49. Goldstein, A., Kapelner, A., Bleich, J. and Pitkin, E. (2015), "Peeking inside the black box: Visualizing statistical learning with plots of individual conditional expectation", J. Comput. Graphical Stat., 24, 44-65. https://doi.org/10.1080/10618600.2014.907095
  50. Grauers, M. (1993), "Composite columns of hollow steel sections filled with high strength concrete." Ph.D. dissertation, Chalmers University.
  51. Guilleminot, J., Le, T.T. and Soize, C. (2013), "Stochastic framework for modeling the linear apparent behavior of complex materials: Application to random porous materials with interphases", Acta Mechanica Sinica. 29, 773-782. https://doi.org/10.1007/s10409-013-0101-7.
  52. Gupta, R., Gijzen van, M.B. and Vuik, C.K. (2013), "Efficient Two-Level Preconditioned Conjugate Gradient Method on the GPU", Proceedings of the High Performance Computing for Computational Science - VECPAR 2012, (Eds., O. Marques M. Dayde and K.) Nakajima. https://doi.org/10.1007/978-3-642-38718-0_7.
  53. Han, L.H. (2002), "Tests on stub columns of concrete-filled RHS sections", J. Constr. Steel Res., 58, 353-372. https://doi.org/10.1016/S0143-974X(01)00059-1.
  54. Han, L.H. and Yang, Y.F. (2001), "Influence of concrete compaction on the behavior of concrete filled steel tubes with rectangular sections", Adv. Struct. Eng., 4, 93-100. https://doi.org/10.1260/1369433011502381
  55. Han, L.H. and Yang, Y.F. (2003), "Analysis of thin-walled steel RHS columns filled with concrete under long-term sustained loads", Thin-Wall. Struct., 41, 849-870. https://doi.org/10.1016/S0263-8231(03)00029-6.
  56. Han, L.H. and Yao, G.H. (2003), "Influence of concrete compaction on the strength of concrete-filled steel RHS columns", Journal of Constructional Steel Research, 59, 751-767. https://doi.org/10.1016/S0143-974X(02)00076-7.
  57. Han, L.H., Hou, C. and Wang, Q.L. (2012), "Square concrete filled steel tubular (CFST) members under loading and chloride corrosion: experiments", J. Constr. Steel Res., 71, 11-25. https://doi.org/10.1016/j.jcsr.2011.11.012
  58. Han, L.H., Huo, J.S. and Wang, Y.C. (2005), "Compressive and flexural behaviour of concrete filled steel tubes after exposure to standard fire", J. Constr. Steel Res., 61, 882-901. https://doi.org/10.1016/j.jcsr.2004.12.005
  59. Han, L.H., Tao, Z. and Liu, W. (2004), "Effects of Sustained Load on Concrete-Filled Hollow Structural Steel Columns", J. Struct. Eng., 130, 1392-1404. https://doi.org/10.1061/(ASCE)0733-9445(2004)130:9(1392).
  60. Han, L.H., Li, W. and Bjorhovde, R. (2014), "Developments and advanced applications of concrete-filled steel tubular (CFST) structures: Members", J. Constr. Steel Res.,100, 211-228. https://doi.org/10.1016/j.jcsr.2014.04.016
  61. Hasanzadehshooiili, H., Lakirouhani, A. and Sapalas, A. (2012), "Neural network prediction of buckling load of steel arch-shells." Arch. Civil Mech. Eng., 12, 477-484. https://doi.org/10.1016/j.acme.2012.07.005.
  62. Hun, D.A., Guilleminot, J., Yvonnet, J. and Bornert, M. (2019), "Stochastic multiscale modeling of crack propagation in random heterogeneous media", Int. J. Numer. Method. Eng., 119, 1325-1344. https://doi.org/10.1002/nme.6093.
  63. Ibanez, C., Hernandez-Figueirido, D. and Piquer, A. (2021), "Effect of steel tube thickness on the behaviour of CFST columns: Experimental tests and design assessment", Eng. Struct., 230, 111687. https://doi.org/10.1016/j.engstruct.2020.111687.
  64. Jegadesh, J. and Jayalekshmi, S. (2015), "A Review on Artificial Neural Network Concepts in Structural Engineering Applications", Int. J. Appl. Civil Environ. Eng., 1, 6-11.
  65. Jegadesh, S. and Jayalekshmi, S. (2015b), "Application of artificial neural network for calculation of axial capacity of circular concrete filled steel Tubular Columns", Int. J. Earth Sci. Eng., 8, 35-42.
  66. Kayacan, E. and Khanesar, M.A. (2015), Fuzzy Neural Networks for Real Time Control Applications: Concepts, Modeling and Algorithms for Fast Learning. 1. Butterworth-Heinemann.
  67. Khan, M., Uy, B., Tao, Z. and Mashiri, F. (2017), "Concentrically loaded slender square hollow and composite columns incorporating high strength properties", Eng. Struct., 131, 69-89. https://doi.org/10.1016/j.engstruct.2016.10.015.
  68. Khan, M., Uy, B., Tao, Z. and Mashiri, F. (2017b). "Behaviour and design of short high-strength steel welded box and concrete-filled tube (CFT) sections", Eng. Struct., 147, 458-472. https://doi.org/10.1016/j.engstruct.2017.06.016.
  69. Khanouki, M.M.A., Ramli Sulong, N.H., Shariati, M. and Tahir, M.M. (2016). "Investigation of through beam connection to concrete filled circular steel tube (CFCST) column", J. Constr. Steel Res., 121, 144-162. https://doi.org/10.1016/j.jcsr.2016.01.002.
  70. Knowles, R.B. and Park, R. (1969), "Strength of Concrete Filled Steel Tubular Columns", J. Struct. Division, 95, 2565-2588. https://doi.org/10.1061/JSDEAG.0002425
  71. Krishan, A.L., Chernyshova, E.P. and Sabirov, R.R. (2016), "Calculating the Strength of Concrete Filled Steel Tube Columns of Solid and Ring Cross-Section", Procedia Eng., 150, 1878-1884. https://doi.org/10.1016/j.proeng.2016.07.186
  72. Lam, D. and Williams, C.A. (2004), "Experimental study on concrete filled square hollow sections", Steel Compos. Struct., 4(2), 95-112. https://doi.org/10.12989/scs.2004.4.2.095.
  73. Lam, D., Yang, J. and Dai, X. (2019), "Finite element analysis of concrete filled lean duplex stainless steel columns", Structures, 21, 150-155. https://doi.org/10.1016/j.istruc.2019.01.024.
  74. Le, T.T. (2015), "Stochastic modeling in continuum mechanics, of the inclusion-matrix interphase from molecular dynamics simulations", Ph.D. dissertation, University of Paris-Est Marne-la-Vallee.
  75. Le, M.V., Yvonnet, J., Feld, N. and Detrez, F. (2020), "The Coarse Mesh Condensation Multiscale Method for parallel computation of heterogeneous linear structures without scale separation", Comput. Method. Appl. M., 363, 112877. https://doi.org/10.1016/j.cma.2020.112877.
  76. Le, T.T., Guilleminot, J. and Soize, C. (2016), "Stochastic continuum modeling of random interphases from atomistic simulations. Application to a polymer nanocomposite", Comput. Method. Appl. M., 303, 430-449. https://doi.org/10.1016/j.cma.2015.10.006.
  77. Le, T.T., Guilleminot, J. and Soize, C. (2015), "Stochastic continuum modeling of random interphases from atomistic simulations", Euromech 559, Multi-scale computational methods for bridging scales in materials and structures, Eindhoven, The Netherlands
  78. Le-Duc, T., Nguyen, Q.H. and Nguyen-Xuan, H. (2020), "Balancing composite motion optimization", Information Sciences, 520, 250-270. https://doi.org/10.1016/j.ins.2020.02.013.
  79. 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. St. Louis, Missouri, U.S.A.
  80. Liu, S., Ding, X., Li, X., Liu, Y. and Zhao, S. (2019). "Behavior of Rectangular-Sectional Steel Tubular Columns Filled with High-Strength Steel Fiber Reinforced Concrete Under Axial Compression", Materials, 12, 2716. https://doi.org/10.3390/ma12172716
  81. Ly, H.B., Le, L.M., Duong, H.T., Nguyen, T.C., Pham, T.A., Le, T.T., Le, V.M., Nguyen-Ngoc, L. and Pham, B.T. (2019), "Hybrid Artificial Intelligence Approaches for Predicting Critical Buckling Load of Structural Members under Compression Considering the Influence of Initial Geometric Imperfections", Appl. Sci., 9, 2258. https://doi.org/10.3390/app9112258.
  82. Ly, H.B., Le, L.M., Phi, L.V., Phan, V.H., Tran, V. Q., Pham, B.T., Le, T.T. and Derrible, S. (2019b), "Development of an AI Model to Measure Traffic Air Pollution from Multisensor and Weather Data", Sensors, 19, 4941. https://doi.org/10.3390/s19224941.
  83. Ly, H.B., Le, T. T., Le, L.M., Tran, V.Q., Le, V.M., Vu, H.L.T., Nguyen, Q.H. and Pham, B.T. (2019c). "Development of Hybrid Machine Learning Models for Predicting the Critical Buckling Load of I-Shaped Cellular Beams." Applied Sciences, 9, 5458. https://doi.org/10.3390/app9245458.
  84. Ly, H.B., Monteiro, E., Le, T.T., Le, V.M., Dal, M., Regnier, G. and Pham, B.T. (2019d), "Prediction and Sensitivity Analysis of Bubble Dissolution Time in 3D Selective Laser Sintering Using Ensemble Decision Trees", Materials, 12, 1544. https://doi.org/10.3390/ma12091544.
  85. Ly, H., Pham, B.T., Le, L.M., Tien-Thinh Le, T.T., Le, V.M. and Asteris, P.G. (2020), "Estimation of axial load-carrying capacity of concrete-filled steel tubes using surrogate models", Neural Comput. Appl., https://doi.org/10.1007/s00521-020-05214-w.
  86. Marquardt, D. (1963), "An Algorithm for Least-Squares Estimation of Nonlinear Parameters", J. Soc. Ind. Appl. Math., 11, 431-441. https://doi.org/10.1137/0111030.
  87. MathWorks The. (2018), MATLAB. Natick, Massachusetts: The MathWorks Inc.
  88. Matsui, C., Tsuda, K., Ozaki, I. and Ishibashi, Y. (1997), "Strength of Slender Concrete Filled Steel Tubular Columns", J. Struct. Constr. Eng. (Transactions of AIJ), 62, 137-144. https://doi.org/10.3130/aijs.62.137_1.
  89. Moller, M.F. (1993), "A scaled conjugate gradient algorithm for fast supervised learning", Neural Networks, 6, 525-533. https://doi.org/10.1016/S0893-6080(05)80056-5.
  90. Molnar, C. (2019), Interpretable Machine Learning. Lulu.com.
  91. Montavon, G., Rupp, M., Gobre, V., Vazquez-Mayagoitia, A., Hansen, K., Tkatchenko, A., Muller, K.R. and Lilienfeld von, O.A. (2013), "Machine learning of molecular electronic properties in chemical compound space", New J. Phys., 15, 095003. https://doi.org/10.1088/1367-2630/15/9/095003.
  92. Mursi, M. and Uy, B. (2004), "Strength of slender concrete filled high strength steel box columns", J. Constr. Steel Res., 60, 1825-1848. https://doi.org/10.1016/j.jcsr.2004.05.002.
  93. Nguyen, M.S.T., Thai, D.K. and Kim, S.E. (2020), "Predicting the axial compressive capacity of circular concrete filled steel tube columns using an artificial neural network', Steel Compos. Struct., 35(3), 415-437. https://doi.org/10.12989/scs.2020.35.3.415.
  94. Pearson, K. (1895), "Note on Regression and Inheritance in the Case of Two Parents", Proceedings of the Royal Society of London, 58, 240-242. https://doi.org/10.1098/rspl.1895.0041.
  95. Pham, B.T., Jaafari, A., Prakash, I. and Bui, D.T. (2019), "A novel hybrid intelligent model of support vector machines and the MultiBoost ensemble for landslide susceptibility modeling", Bull. Eng. Geol. Environ., 78, 2865-2886. https://doi.org/10.1007/s10064-018-1281-y.
  96. Pham, B.T., et al. (2019b), "Development of artificial intelligence models for the prediction of Compression Coefficient of soil: An application of Monte Carlo sensitivity analysis", Science of The Total Environ., 679, 172-184. https://doi.org/10.1016/j.scitotenv.2019.05.061.
  97. Pham, B.T., Le, L.M., Le, T.T., Bui, K.T.T., Le, V.M., Ly, H.B. and Prakash, I. (2020), "Development of advanced artificial intelligence models for daily rainfall prediction", Atmos. Res., 237, 104845. https://doi.org/10.1016/j.atmosres.2020.104845.
  98. Pokharel, T., Yao, H., Goldsworthy, H.M. and Gad, E.F. (2016), "Experimental and analytical behaviour of cogged bars within concrete filled circular tubes", Steel Compos. Struct., 20(5), 1067-1085. https://doi.org/10.12989/SCS.2016.20.5.1067.
  99. Powell, M.J.D. (1977), "Restart procedures for the conjugate gradient method", Math. Program., 12, 241-254. https://doi.org/10.1007/BF01593790.
  100. Qi, C., Fourie, A., Chen, Q. and Zhang, Q. (2018). "A strength prediction model using artificial intelligence for recycling waste tailings as cemented paste backfill", J. Cleaner Production, 183, 566-578. https://doi.org/10.1016/j.jclepro.2018.02.154.
  101. Qi, C., Ly, H.B., Chen, Q., Le, T.T., Le, V.M. and Pham, B.T. (2020). "Flocculation-dewatering prediction of fine mineral tailings using a hybrid machine learning approach", Chemosphere, 244, 12545. https://doi.org/10.1016/j.chemosphere.2019.125450.
  102. Qi, C., Tang, X., Dong, X., Chen, Q., Fourie, A. and Liu, E. (2019), "Towards Intelligent Mining for Backfill: A genetic programming-based method for strength forecasting of cemented paste backfill", Minerals Eng., 133, 69-79. https://doi.org/10.1016/j.mineng.2019.01.004.
  103. Raghuwanshi, N.S., Singh, R. and Reddy, L.S. (2006), "Runoff and Sediment Yield Modeling Using Artificial Neural Networks: Upper Siwane River, India", J. Hydrologic Eng., 11, 71-79. https://doi.org/10.1061/(ASCE)1084-0699(2006)11:1(71).
  104. 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, 2802. https://doi.org/10.3390/app9142802.
  105. Rumelhart, D.E., Hinton, G.E. and Williams, R.J. (1986), "Learning representations by back-propagating errors", Nature, 323, 533-536. https://doi.org/10.1038/323533a0.
  106. Sakino, K. and Hayashi, H. (1991), "Behavior of Concrete Filled Steel Tubular Stub Columns under Concentric Loading", Proceedings of the 3rd Int. Conf. on Steel-Concrete Composite Structures. Fukuoka, Japan.
  107. Sakino, K., Morino, H., Nakaharaand, S. and Nishiyama, I. (2004), "Behavior of Centrally Loaded Concrete-Filled Steel-Tube Short Columns", J. Struct. Eng., 130, 180-188. https://doi.org/10.1061/(ASCE)0733-9445(2004)130:2(180).
  108. Sarir, P., Chen, J., Asteris, P.G., Armaghani, D.J. and Tahir, M.M. (2019), "Developing GEP tree-based, neuro-swarm, and whale optimization models for evaluation of bearing capacity of concrete-filled steel tube columns", Eng. with Comput., https://doi.org/10.1007/s00366-019-00808-y.
  109. Sarir, P., Shen, S.L., Wang, Z.F., Chen, J., Horpibulsuk, S. and Pham, B.T. (2019b), "Optimum model for bearing capacity of concrete-steel columns with AI technology via incorporating the algorithms of IWO and ABC", Eng. with Comput., 1-11.
  110. Schneider, S.P. (1998), "Axially loaded concrete-filled steel tubes", J. Struct. Eng., 124, 1125-1138. https://doi.org/10.1061/(ASCE)0733-9445(1998)124:10(1125)
  111. Shakir-Khalil, H. and Zeghiche, J. (1989), "Experimental Behaviour of Concrete-Filled Rolled Rectangular Hollow-Section Columns", The Structural Engineer, 67, 346-353.
  112. Shakir-Khalil, H. and Mouli, M. (1990), "Further Tests on Concrete-Filled Rectangular Hollow-Section Columns", The Structural Engineer, 68, 405-413.
  113. Soize, C. (Ed.) (2012), Stochastic Models of Uncertainties in Computational Mechanics. Reston, VA: ASCE.
  114. Soize, C., Desceliers, C., Guilleminot, J., Le, T.T., Nguyen, M.T., Perrin, G., Allain, J.M., Gharbi, H., Duhamel, D. and Funfschilling, C. (2015), "Stochastic representations and statistical inverse identification for uncertainty quantification in computational mechanics", Proceedings of the UNCECOMP 2015, 1st ECCOMAS Thematic International Conference on Uncertainty Quantification in Computational Sciences and Engineering.
  115. Song, T.Y., Tao, Z., Han, L.H. and Uy, B. (2017), "Bond behavior of concrete-filled steel tubes at elevated temperatures", J. Struct. Eng., 143, 04017147. https://doi.org/10.1061/(ASCE)ST.1943-541X.0001890
  116. Staber, B., Guilleminot, J., Soize, C., Michopoulos, J. and Iliopoulos, A. (2019), "Stochastic modeling and identification of a hyperelastic constitutive model for laminated composites", Comput. Method. Appl. M., 347, 425-444. https://doi.org/10.1016/j.cma.2018.12.036.
  117. 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.
  118. Tao, Z., Han, L.H. and Wang, D.Y. (2007), "Experimental behaviour of concrete-filled stiffened thin-walled steel tubular columns", Thin-Wall. Struct., 45, 517-527. https://doi.org/10.1016/j.tws.2007.04.003.
  119. Tao, Z., Song, T.Y., Uy, B. and Han, L.H. (2016). "Bond behavior in concrete-filled steel tubes", J. Constr. Steel Res., 120, 81-93. https://doi.org/10.1016/j.jcsr.2015.12.030
  120. Tao, Z., Brian, U.Y., Han, L.H. and He, S.H. (2008), "Design of concrete-filled steel tubular members according to the Australian Standard AS 5100 model and calibration", Australian J. Struct. Eng., 8, 197-214. https://doi.org/10.1080/13287982.2008.11464998
  121. Taormina, R., Chau, K. and Sethi, R. (2012), "Artificial neural network simulation of hourly groundwater levels in a coastal aquifer system of the Venice lagoon", Eng. Appl. Artif. Intel., 25, 1670-1676. https://doi.org/10.1016/j.engappai.2012.02.009.
  122. Taylor, R. (1990), "Interpretation of the Correlation Coefficient: A Basic Review", J. Diagnostic Medical Sonography, 6, 35-39. https://doi.org/10.1177/875647939000600106.
  123. Tomii, M. and Sakino, K. (1979), "Experimental studies on the ultimate moment of concrete filled square steel tubular beam-columns", T. Architect. Inst. Japan, 55-65.
  124. Tran, V.L., Thai, D.K. and Kim, S.E. (2019), "Application of ANN in predicting ACC of SCFST column", Compos. Struct., 228, 111332. https://doi.org/10.1016/j.compstruct.2019.111332.
  125. Tran, V.P., Guilleminot, J., Brisard, S. and Sab, K. (2016), "Stochastic modeling of mesoscopic elasticity random field", Mech. Mater., 93, 1-12. https://doi.org/10.1016/j.mechmat.2015.10.007.
  126. Tran, V.P., Brisard, S., Guilleminot, J. and Sab, K. (2018), "Mori-Tanaka estimates of the effective elastic properties of stress-gradient composites", Int. J. Solid. Struct., 146, 55-68. https://doi.org/10.1016/j.ijsolstr.2018.03.020.
  127. Uy, B. (2001), "Strength of short concrete filled high strength steel box columns", J. Constr. Steel Res., 57, 113-134. https://doi.org/10.1016/S0143-974X(00)00014-6.
  128. Varma, A.H., Ricles, J.M., Sause R. and Lu, L.W. (2004), "Seismic Behavior and and Design of High-Strength Square Concrete-Filled Steel Tube Beam Columns", J. Struct. Eng., 130, 169-179. https://doi.org/10.1061/(ASCE)0733-9445(2004)130:2(169).
  129. Vasugi, K. and Elavenil, S. (2019), "Confinement of concrete by stainless steel tubular sections - A review", Int. J. Eng. Adv. Technol., 8, 468-472. https://doi.org/10.35940/ijeat.F1086.0986S319
  130. Vos de, N.J. and Rientjes, T.H.M. (2008), "Multiobjective training of artificial neural networks for rainfall-runoff modeling", Water Resour. Res., 44. https://doi.org/10.1029/2007WR006734.
  131. Vrcelj, Z. and Uy, B. (2002), "Behaviour and Design of Steel Square Hollow Sections Filled With High Strength Concrete", Australian J. Struct. Eng., 3, 153-170. https://doi.org/10.1080/13287982.2002.11464902.
  132. Wei, H., Du, Y. and Wang, H.J. (2012), "Seismic Behavior of Concrete Filled Circular Steel Tubular Columns Based on Artificial Neural Network", Adv. Mater. Res., 502, 189-192. https://doi.org/10.4028/www.scientific.net/amr.502.189
  133. Xiao, Y.F. (2012), "Approach of Concrete-Filled Steel Tube Ultrasonic Method Based on ANN", Appl. Mech. Mater., 105, 1611-1615. https://doi.org/10.4028/www.scientific.net/AMM.105-107.1611
  134. Xiong, M.X., Xiong, D.X. and Liew, J.Y.R. (2017), "Axial performance of short concrete filled steel tubes with high- and ultra-high- strength materials", Eng. Struct., 136, 494-510. https://doi.org/10.1016/j.engstruct.2017.01.037.
  135. Yamamoto, T., Kawaguchi, J. and Morino, S. (2002), "Experimental study of scale effects on the compressive behavior of short concrete-filled steel tube columns", Composite Construction in Steel and Concrete IV. 879-890.
  136. Yang, Y.F. and Han, L.H. (2012), "Concrete filled steel tube (CFST) columns subjected to concentrically partial compression", Thin-Wall. Struct., 50, 147-156. https://doi.org/10.1016/j.tws.2011.09.007.
  137. Yao, X., Liu, Y. and Lin, G. (1999), "Evolutionary programming made faster", IEEE T. Evolu. Comput., 3, 82-102. https://doi.org/10.1109/4235.771163.
  138. Young, B. (2008), "Experimental and numerical investigation of high strength stainless steel structures", J. Constr. Steel Res., 64, 1225-1230. https://doi.org/10.1016/j.jcsr.2008.05.004
  139. Yu, M., Zha, X., Ye, J. and Li, Y. (2013), "A unified formulation for circle and polygon concrete-filled steel tube columns under axial compression", Eng. Struct., 49, 1-10. https://doi.org/10.1016/j.engstruct.2012.10.018
  140. Yu, Q., Tao, Z. and Wu, Y.X. (2008), "Experimental behaviour of high performance concrete-filled steel tubular columns", Thin-Wall. Struct., 46, 362-370. https://doi.org/10.1016/j.tws.2007.10.001.
  141. Yu, Z., Ding, F. and Cai, C.S. (2007), "Experimental behavior of circular concrete-filled steel tube stub columns", J. Constr. Steel Res., 63, 165-174. https://doi.org/10.1016/j.jcsr.2006.03.009
  142. Zhao, O., Rossi, B., Gardner, L. and Young, B. (2015), "Behaviour of structural stainless steel cross-sections under combined loading-Part I: Experimental study", Eng. Struct., 89, 236-246. https://doi.org/10.1016/j.engstruct.2014.11.014
  143. Zhu, A., Zhang, X., Zhu, H., Zhu, J. and Lu, Y. (2017), "Experimental study of concrete filled cold-formed steel tubular stub columns", J. Constr. Steel Res., 134, 17-27. https://doi.org/10.1016/j.jcsr.2017.03.003.

Cited by

  1. Stacking Ensemble Tree Models to Predict Energy Performance in Residential Buildings vol.13, pp.15, 2021, https://doi.org/10.3390/su13158298