Steel and Composite Structures

  • 제34권1호
  • /
  • Pages.155-170
  • /
  • 2020
  • /
  • 1229-9367(pISSN)
  • /
  • 1598-6233(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Identification of the most influencing parameters on the properties of corroded concrete beams using an Adaptive Neuro-Fuzzy Inference System (ANFIS)

  • Shariati, Mahdi (Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University) ;
  • Mafipour, Mohammad Saeed (School of Civil Engineering, College of Engineering, University of Tehran) ;
  • Haido, James H. (Department of Civil Engineering, College of Engineering, University of Duhok) ;
  • Yousif, Salim T. (Department of Civil Engineering, Al-Qalam University College) ;
  • Toghroli, Ali (Institute of Research and Development, Duy Tan University) ;
  • Trung, Nguyen Thoi (Division of Computational Mathematics and Engineering, Institute for Computational Science, Ton Duc Thang University) ;
  • Shariati, Ali (Institute of Research and Development, Duy Tan University)
  • 투고 : 2019.03.25
  • 심사 : 2019.09.15
  • 발행 : 2020.01.10
⟨ 이전 논문 다음 논문 ⟩

초록

Different parameters potentially affect the properties of corroded reinforced concrete beams. However, the high number of these parameters and their dependence cause that the effectiveness of the parameters could not be simply identified. In this study, an adaptive neuro-fuzzy inference system (ANFIS) was employed to determine the most influencing parameters on the properties of the corrosion-damaged reinforced concrete beams. 207 ANFIS models were developed to analyze the collected data from 107 reinforced concrete (RC) beams. The impact of 23 input parameters on nine output factors was investigated. The results of the paper showed the order of influence of each input parameter on the outputs and revealed that the input parameters regarding the uncorroded properties of concrete beams are the most influencing factors on the corresponding corroded properties of the beams.

키워드

참고문헌

  1. Abdalla, J.A., et al. (2007), "Modeling and simulation of shear resistance of R/C beams using artificial neural network", J. Franklin Institute, 344(5), 741-756. https://doi.org/10.1016/j.jfranklin.2005.12.005
  2. Abedini, M., et al. (2017), "Evaluation of concrete structures reinforced with fiber reinforced polymers bars: A review", J. Asian Scientific Res., 7(5), 165.DOI: 10.18488/journal.2.2017.75.165.175.
  3. Abedini, M., et al. (2019), "Large deflection behavior effect in reinforced concrete columns exposed to extreme dynamic loads", engrXiv: 32. DOI: http://dx.doi.org/10.31224/osf.io/6n5fs.
  4. Abraham, A. (2005), Adaptation of fuzzy inference system using neural learning. Fuzzy systems engineering, Springer: 53-83.
  5. Altoubat, S., et al. (2016), "Laboratory simulation of corrosion damage in reinforced concrete", Int. J. Concrete Struct. Mater., 10(3), 383. https://doi.org/10.1007/s40069-016-0138-7
  6. Arabnejad Khanouki, M.M., et al. (2010). "Investigation of seismic behaviour of composite structures with concrete filled square steel tubular (CFSST) column by push-over and timehistory analyses", Proceedings of the 4th International Conference on Steel & Composite Structures.
  7. Arabnejad Khanouki, M.M., et al. (2011), "Behavior of through beam connections composed of CFSST columns and steel beams by finite element studying", Adv. Mater. Res., 168: 2329-2333. DOI:http://dx.doi.org/10.4028/www.scientific.net/AMR.168-170.2329.
  8. Arabnejad Khanouki, M.M., et al. (2016). "Investigation of through beam connection to concrete filled circular steel tube (CFCST) column", J. Constr. Steel Res., 121, 144-162. DOI: https://doi.org/10.1016/j.jcsr.2016.01.002.
  9. Azad, A.K., et al. (2007), "Residual strength of corrosiondamaged reinforced concrete beams", ACI Mater. J., 104(1), 40.
  10. Berto, L., et al. (2008), "Numerical modelling of bond behaviour in RC structures affected by reinforcement corrosion", Eng. Struct., 30(5), 1375-1385. https://doi.org/10.1016/j.engstruct.2007.08.003
  11. Berto, L., et al. (2009), "Seismic assessment of existing RC structures affected by degradation phenomena", Struct. Saf., 31(4), 284-297. https://doi.org/10.1016/j.strusafe.2008.09.006
  12. Bossio, A., et al. (2017), Evaluation of seismic behavior of corroded reinforced concrete structures", Proceedings of the 15th International Forum World Heritage and Disaster, Capri, Italy.
  13. Bossio, A., et al. (2018), "An overview of assessment and retrofit of corroded reinforced concrete structures", Procedia Structural Integrity, 11, 394-401. https://doi.org/10.1016/j.prostr.2018.11.051
  14. Bossio, A., et al. (2015), "Modeling of concrete cracking due to corrosion process of reinforcement bars", Cement Concrete Res., 71, 78-92. https://doi.org/10.1016/j.cemconres.2015.01.010
  15. Broomfield, J. (1997), Corrosion of steel in concrete. UK: E & FN Spon, Chapman & Hall.
  16. Cabrera, J. (1996), "Deterioration of concrete due to reinforcement steel corrosion", Cement Concrete Compos., 18(1), 47-59. https://doi.org/10.1016/0958-9465(95)00043-7
  17. Castel, A., et al. (2011), Modelling the stiffness reduction of corroded reinforced concrete beams after cracking. Modelling of Corroding Concrete Structures, Springer: 219-230.
  18. Cavaco, E.S. (2009), Robustness of corroded reinforced concrete structures.
  19. Cohen, P., et al. (2014), Applied multiple regression/correlation analysis for the behavioral sciences, Psychology Press.
  20. Committee, A. and Standardization, I.O.f. (2008), Building code requirements for structural concrete (ACI 318-08) and commentary, American Concrete Institute.
  21. Coronelli, D. and Gambarova, P. (2004), "Structural assessment of corroded reinforced concrete beams: modeling guidelines", J. Struct. Eng., 130(8), 1214-1224. https://doi.org/10.1061/(asce)0733-9445(2004)130:8(1214)
  22. Daie, M., et al. (2011), "A new finite element investigation on prebent steel strips as damper for vibration control", Int. J. Phys. Sci., 6(36), 8044-8050. DOI: https://doi.org/10.5897/ijps11.1585.
  23. Davoodnabi, S.M., et al. (2019), "Behavior of steel-concrete composite beam using angle shear connectors at fire condition", Steel Compos. Struct., 30(2), 141-147. DOI: https://doi.org/10.12989/scs.2019.30.2.141.
  24. Fernandez, I. and Berrocal, C.G. (2019), "Mechanical properties of 30 year-old naturally corroded steel reinforcing bars", Int. J. Concrete Struct. Mater., 13(1), 9. https://doi.org/10.1186/s40069-018-0308-x
  25. Hamdia, K.M., et al. (2015), "Predicting the fracture toughness of PNCs: A stochastic approach based on ANN and ANFIS", Comput. Mater. Sci., 102, 304-313. DOI: https://doi.org/10.1016/j.commatsci.2015.02.045.
  26. Hamidian, M., et al. (2012), "Application of Schmidt rebound hammer and ultrasonic pulse velocity techniques for structural health monitoring", Scientific Res. Essays, 7(21), 1997-2001. DOI: http://dx.doi.org/10.5897/SRE11.1387.
  27. Heydari, A. and Shariati, M. (2018), "Buckling analysis of tapered BDFGM nano-beam under variable axial compression resting on elastic medium", Struct. Eng. Mech., 66(6), 737-748. DOI: https://doi.org/10.12989/sem.2018.66.6.737.
  28. Hosseinpour, E., et al. (2018), "Direct shear behavior of concrete filled hollow steel tube shear connector for slim-floor steel beams", Steel Compos. Struct., 26(4), 485-499. DOI: https://doi.org/10.12989/scs.2018.26.4.485.
  29. Huang, R. and Yang, C. (1997), "Condition assessment of reinforced concrete beams relative to reinforcement corrosion", Cement Concrete Compos., 19(2), 131-137. https://doi.org/10.1016/S0958-9465(96)00050-9
  30. Imam, A., et al. (2015), "Residual strength of corroded reinforced concrete beams using an adaptive model based on ANN", Int. J. Concrete Struct. Mater., 9(2), 159-172. https://doi.org/10.1007/s40069-015-0097-4
  31. Imam, A. and Azad, A.K. (2016), "Prediction of residual shear strength of corroded reinforced concrete beams", Int. J. Adv. Struct. Eng., 8(3), 307-318. https://doi.org/10.1007/s40091-016-0133-x
  32. Imperatore, S., et al. (2012), Mechanical behaviour of corroded rebars in reinforced concrete elements. Mechanics, Models and Methods in Civil Engineering, Springer: 207-220.
  33. Ismail, M., et al. (2018). "Strengthening of bolted shear joints in industrialized ferrocement construction." Steel and Composite Structures 28(6): 681-690. https://doi.org/10.12989/SCS.2018.28.6.681
  34. Jalali, A., et al. (2012), "Seismic performance of structures with pre-bent strips as a damper", Int. J. Phys. Sci., 7(26), 4061-4072.
  35. Jang, J.S. (1993), "ANFIS: adaptive-network-based fuzzy inference system", IEEE T. Syst. Man, Cy., 23(3), 665-685. https://doi.org/10.1109/21.256541
  36. Kallias, A.N. and Rafiq, M.I. (2010), "Finite element investigation of the structural response of corroded RC beams", Eng. Struct., 32(9), 2984-2994. https://doi.org/10.1016/j.engstruct.2010.05.017
  37. Katebi, J., et al. (2019), "Developed comparative analysis of metaheuristic optimization algorithms for optimal active control of structures", Engineering with Computers: 1-20.
  38. Kazerani, S., et al. (2014), "Seismic behavior of drilled beam section in moment connections", Numer. Method. Civil Eng., 1(2), 21-28.
  39. Khan, I., et al. (2011), Mechanical behavior of long-term corroded reinforced concrete beam. Modelling of Corroding Concrete Structures, Springer: 243-258.
  40. Khan, I., et al. (2012), "Structural performance of a 26-year-old corroded reinforced concrete beam", Eur. J. Environ. Civil Eng., 16(3-4), 440-449. https://doi.org/10.1080/19648189.2012.667992
  41. Khorami, M., et al. (2017), "Evaluation of the seismic performance of special moment frames using incremental nonlinear dynamic analysis", Struct. Eng. Mech., 63(2), 259-268. DOI: https://doi.org/10.12989/sem.2017.63.2.259.
  42. Khorramian, K., et al. (2017), "Numerical analysis of tilted angle shear connectors in steel-concrete composite systems", Steel Compos. Struct., 23(1), 67-85. DOI: https://doi.org/10.12989/scs.2017.23.1.067.
  43. Khorramian, K., et al. (2015), "Behavior of tilted angle shear connectors", PLoS One 10(12), e0144288. DOI: https://doi.org/10.1371/journal.pone.0144288.
  44. Khorramian, K., et al. (2016), "Behavior of Tilted Angle Shear Connectors (vol 10, e0144288, 2015)", PLoS One, 11(2).
  45. Kim, H.R., et al. (2016). "Evaluation of bond properties of reinforced concrete with corroded reinforcement by uniaxial tension testing", Int. J. Concrete Struct. Mater., 10(3), 43-52. https://doi.org/10.1007/s40069-016-0152-9
  46. Li, D., et al. (2019), "Application of polymer, silica-fume and crushed rubber in the production of Pervious concrete", Smart Struct. Syst., 23(2), 207-214. DOI: https://doi.org/10.12989/sss.2019.23.2.207.
  47. Lu, C., et al. (2017), "A numerical study on the impact resistant capacity of RC beams with corroded reinforcement", Procedia Eng., 210, 341-348. https://doi.org/10.1016/j.proeng.2017.11.086
  48. Luo, Z., et al. (2019), "Computational and experimental analysis of beam to column joints reinforced with CFRP plates", Steel Compos. Struct., 30(3), 271-280. DOI: http://dx.doi.org/10.12989/scs.2019.30.3.271.
  49. Ma, Y., et al. (2014), "Fatigue life prediction for aging RC beams considering corrosive environments", Eng. Struct., 79, 211-221. https://doi.org/10.1016/j.engstruct.2014.07.039
  50. Maia, L. and Alves, S. (2017), "Low durability of concrete elements due to steel corrosion-cases wherein the steel reinforcing bars acted as an internal clock bomb", Procedia Struct. Integrity, 5, 139-146. https://doi.org/10.1016/j.prostr.2017.07.082
  51. Mansouri, I., et al. (2016). "Strength prediction of rotary brace damper using MLR and MARS", Struct. Eng. Mech., 60(3), 471-488. https://doi.org/10.12989/sem.2016.60.3.471
  52. Mansouri, I., et al. (2019). "Analysis of influential factors for predicting the shear strength of a V-shaped angle shear connector in composite beams using an adaptive neuro-fuzzy technique", J. Intel. Manufact., 30(3), 1247-1257. https://doi.org/10.1007/s10845-017-1306-6
  53. Milovancevic, M., et al. (2019), "UML diagrams for dynamical monitoring of rail vehicles", Physica A: Statistical Mechanics and its Applications, 53, 121169. https://doi.org/10.1016/j.physa.2019.121169
  54. Mohammadhassani, M., et al. (2014), "An experimental study on the failure modes of high strength concrete beams with particular references to variation of the tensile reinforcement ratio", Eng. Fail. Anal., 41, 73-80. DOI: https://doi.org/10.1016/j.engfailanal.2013.08.014.
  55. Mohammadhassani, M., et al. (2015), "Fuzzy modelling approach for shear strength prediction of RC deep beams", Smart Struct. Syst., 16(3), 497-519. DOI: https://doi.org/10.12989/sss.2015.16.3.497.
  56. Mohammadhassani, M., et al. (2014). "Ductility and strength assessment of HSC beams with varying of tensile reinforcement ratios", Struct. Eng. Mech., 48(6), 833-848. DOI: https://doi.org/10.12989/sem.2013.48.6.833.
  57. Mohammed, A., et al. (2018), "Simplified finite element model for evaluation of ultimate capacity of corrosion-damaged reinforced concrete beam-columns", Int. J. Adv. Struct. Eng., 10(4), 381-400. https://doi.org/10.1007/s40091-018-0204-2
  58. Najarkolaie, K.F., et al. (2017), "Realistic behavior of infilled steel frames in seismic events: experimental and analytical study", Bull. Earthq. Eng., 15(12), 5365-5392.DOI:10.1007/s10518-017-0173-z.
  59. Nasrollahi, S., et al. (2018), "Investigation of pipe shear connectors using push out test", Steel Compos. Struct., 27(5), 537-543. DOI: http://dx.doi.org/10.12989/scs.2018.27.5.537.
  60. Nosrati, A., et al. (2018), "Portland cement structure and its major oxides and fineness", Smart Struct. Syst., 22(4), 425-432. DOI: https://doi.org/10.12989/sss.2018.22.4.425.
  61. Ou, Y.C., et al. (2012), "Cyclic performance of large-scale corroded reinforced concrete beams", Earthq. Eng. Struct. D., 41(4), 593-604. https://doi.org/10.1002/eqe.1145
  62. Oyado, M., et al. (2011), "Bending performance of reinforced concrete member deteriorated by corrosion", Struct. Infrastruct. Eng., 7(1-2), 121-130. https://doi.org/10.1080/15732471003588510
  63. Paul, S.C. and Van Zijl, G.P.A.G. (2017), "Corrosion deterioration of steel in cracked SHCC", Int. J. Concrete Struct. Mater., 11(3), 557-572. https://doi.org/10.1007/s40069-017-0205-8
  64. Rodriguez, J., et al. (1997), "Load carrying capacity of concrete structures with corroded reinforcement", Constr. Build. Mater., 11(4), 239-248. https://doi.org/10.1016/S0950-0618(97)00043-3
  65. Sadeghipour Chahnasir, E., et al. (2018), "Application of support vector machine with firefly algorithm for investigation of the factors affecting the shear strength of angle shear connectors", Smart Struct. Syst., 22(4), 413-424. DOI: http://dx.doi.org/10.12989/sss.2018.22.4.413.
  66. Safa, M., et al. (2016), "Potential of adaptive neuro fuzzy inference system for evaluating the factors affecting steelconcrete composite beam's shear strength", Steel Compos Struct., 21(3), 679-688. DOI: https://doi.org/10.12989/scs.2016.21.3.679.
  67. Sajedi, F. and Shariati, M. (2019), "Behavior study of NC and HSC RCCs confined by GRP casing and CFRP wrapping", Steel Compos. Struct., 30(5), 417-432. DOI: https://doi.org/10.12989/scs.2019.30.5.417.
  68. Sari, P.A., et al. (2018), "An intelligent based-model role to simulate the factor of safe slope by support vector regression", Eng. Comput., 1-11.
  69. Sedghi, Y., et al. (2018), "Application of ANFIS technique on performance of C and L shaped angle shear connectors", Smart Struct. Syst., 22(3), 335-340. DOI: https://doi.org/10.12989/sss.2018.22.3.335.
  70. Sen, R., et al. (1999), "Durability of carbon fiber-reinforced polymer/epoxy/concrete bond in marine environment", Struct. J., 96(6), 906-914.
  71. Shah, S., et al. (2016), "Behavior of steel pallet rack beam-tocolumn connections at elevated temperatures", Thin Wall. Struct., 106, 471-483. DOI: https://doi.org/10.1016/j.tws.2016.05.021.
  72. Shahabi, S., et al. (2016), "Numerical analysis of channel connectors under fire and a comparison of performance with different types of shear connectors subjected to fire", Steel Compos. Struct., 20(3), 651-669. DOI: https://10.12989/scs.2016.20.3.651.
  73. Shahabi, S., et al. (2016), "Performance of shear connectors at elevated temperatures-A review", Steel Compos. Struct., 20(1), 185-203. DOI: https://doi.org/10.12989/scs.2016.20.1.185.
  74. Shannag, M.J. and Al-Ateek, S.A. (2006), "Flexural behavior of strengthened concrete beams with corroding reinforcement", Constr. Build. Mater., 20(9), 834-840. https://doi.org/10.1016/j.conbuildmat.2005.01.059
  75. Shao, Z., et al. (2019), "Estimating the Friction Angle of Black Shale Core Specimens with Hybrid-ANN Approaches", Measurement.
  76. Shao, Z. and Vesel, A. (2015). "Modeling the packing coloring problem of graphs", Appl. Math. Model., 39(13), 3588-3595. https://doi.org/10.1016/j.apm.2014.11.060
  77. Shao, Z., et al. (2018). "Kriging Empirical Mode Decomposition via support vector machine learning technique for autonomous operation diagnosing of CHP in microgrid", Appl. Therm. Eng., 145, 58-70. https://doi.org/10.1016/j.applthermaleng.2018.09.028
  78. Shariat, M., et al. (2018), "Computational Lagrangian Multiplier Method by using for optimization and sensitivity analysis of rectangular reinforced concrete beams", Steel Compos. Struct., 29(2), 243-256. DOI: https://doi.org/10.12989/scs.2018.29.2.243.
  79. Shariati, A., et al. (2012), "Investigation of channel shear connectors for composite concrete and steel T-beam", Int. J. Phys. Sci., 7(11), 1828-1831. DOI: 10.5897/IJPS11.1604.
  80. Shariati, A., et al. (2012), "Various types of shear connectors in composite structures: A review", Int. J. Phys. Sci., 7(22), 2876-2890.
  81. Shariati, A., et al. (2014), "Experimental assessment of angle shear connectors under monotonic and fully reversed cyclic loading in high strength concrete", Constr. Build. Mater., 52, 276-283. DOI: http://dx.doi.org/10.1016/j.conbuildmat.2013.11.036.
  82. Shariati, M. (2013), Behaviour of C-shaped Shear Connectors in Stell Concrete Composite Beams, Jabatan Kejuruteraan Awam, Fakulti Kejuruteraan, Universiti Malaya.
  83. Shariati, M., et al. (2011), "Assessing the strength of reinforced concrete structures through Ultrasonic Pulse Velocity and Schmidt Rebound Hammer tests", Scientific Res. Essays, 6(1), 213-220.
  84. Shariati, M., et al. (2010), "Experimental and analytical study on channel shear connectors in light weight aggregate concrete. Proceedings of the 4th International Conference on Steel & Composite Structures, 21 - 23 July, 2010, Sydney, Australia, Research Publishing Services.
  85. Shariati, M., et al. (2011). "Experimental and numerical investigations of channel shear connectors in high strength concrete", Proceedings of the 2011 world congress on advances in structural engineering and mechanics (ASEM'11+).
  86. Shariati, M., et al. (2015), "Behavior of V-shaped angle shear connectors: experimental and parametric study", Mater. Struct., 49(9), 3909-3926. DOI: 10.1617/s11527-015-0762-8.
  87. Shariati, M., et al. (2016), "Comparative performance of channel and angle shear connectors in high strength concrete composites: An experimental study", Constr. Build. Mater., 120, 382-392. DOI: https://doi.org/10.1016/j.conbuildmat.2016.05.102.
  88. Shariati, M., et al. (2012), "Behaviour of C-shaped angle shear connectors under monotonic and fully reversed cyclic loading: An experimental study", Mater. Design, 41, 67-73. DOI: https://doi.org/10.1016/j.matdes.2012.04.039.
  89. Shariati, M., et al. (2012), "Fatigue energy dissipation and failure analysis of channel shear connector embedded in the lightweight aggregate concrete in composite bridge girders", Proceedings of the 5th International Conference on Engineering Failure Analysis, 1-4 July 2012, Hilton Hotel, The Hague, The Netherlands.
  90. Shariati, M., et al. (2013), "Comparison of behaviour between channel and angle shear connectors under monotonic and fully reversed cyclic loading", Constr. Build. Mater., 38, 582-593. DOI: https://doi.org/10.1016/j.conbuildmat.2012.07.050.
  91. Shariati, M., et al. (2014), "Fatigue energy dissipation and failure analysis of angle shear connectors embedded in high strength concrete", Eng. Fail. Anal., 41, 124-134. DOI: https://doi.org/10.1016/j.engfailanal.2014.02.017.
  92. Shariati, M., et al. (2017), "Assessment of stiffened angle shear connector under monotonic and fully reversed cyclic loading", Proceedings of the 5th International Conference on Advances in Civil, Structural and Mechanical Engineering-CSM 2017.
  93. Shariati, M., et al. (2019), "Application of waste tire rubber aggregate in porous concrete", Smart Struct. Syst., 24(4), 553-566. DOI: https://doi.org/10.12989/sss.2018.22.4.553.
  94. Shariati, M., et al. (2019), "Application of a Hybrid Artificial Neural Network-Particle Swarm Optimization (ANN-PSO) Model in Behavior Prediction of Channel Shear Connectors Embedded in Normal and High-Strength Concrete", Appl. Sciences, 9(24), 5534. https://doi.org/10.3390/app9245534
  95. Shariati, M., et al. (2019). "Application of Extreme Learning Machine (ELM) and Genetic Programming (GP) to design steel-concrete composite floor systems at elevated temperatures", Steel Compos. Struct., 33(3), 319-332. DOI: https://doi.org/10.12989/scs.2014.33.3.319.
  96. Shariati, M., et al. (2019). "Moment-rotation estimation of steel rack connection using extreme learning machine", Steel Compos. Struct., 31(5), 427-435.DOI: https://doi.org/10.12989/scs.2019.31.5.427.
  97. Shetty, A., et al. (2015), "Experimental and numerical investigation on flexural bond strength behavior of corroded NBS RC beam", Int. J. Adv. Struct. Eng. (IJASE), 7(3), 223-231. https://doi.org/10.1007/s40091-015-0093-6
  98. Shi, X., et al. (2019), "Viscoelastic analysis of silica nanoparticlepolymer nanocomposites", Compos. Part B: Eng., 158, 169-178. https://doi.org/10.1016/j.compositesb.2018.09.084
  99. Sinaei, H., et al. (2011), "Numerical investigation on exterior reinforced concrete Beam-Column joint strengthened by composite fiber reinforced polymer (CFRP)", Int. J. Phys. Sci., 6(28), 6572-6579.
  100. Sinaei, H., et al. (2012), "Evaluation of reinforced concrete beam behaviour using finite element analysis by ABAQUS", Scientific Res. Essays, 7(21), 2002-2009.
  101. Song, L., et al. (2019), "Experimental and analytical investigation of the fatigue flexural behavior of corroded reinforced concrete beams", Int. J. Concrete Struct. Mater., 13(1), 24. https://doi.org/10.1186/s40069-019-0340-5
  102. Tahmasbi, F., et al. (2016), "Shear capacity of C-Shaped and Lshaped angle shear connectors", PLoS One, 11(8), e0156989. DOI: https://doi.org/10.1371/journal.pone.0156989.
  103. Tahmasebi, P. and Hezarkhani, A. (2010), "Comparison of optimized neural network with fuzzy logic for ore grade estimation", Aus. J. Basic Appl. Sci., 4(5), 764-772.
  104. Tahmasebi, P. and Hezarkhani, A. (2012), "A hybrid neural networks-fuzzy logic-genetic algorithm for grade estimation", Comput. Geosci., 42, 18-27. https://doi.org/10.1016/j.cageo.2012.02.004
  105. Tai, V.V., et al. (2017). "Modified genetic algorithm-based clustering for probability density functions", J. Stat. Comput. Simul., 87(10), 1964-1979. DOI: https://doi.org/10.1080/00949655.2017.1300663.
  106. Thang, L.D., et al. (2016), "A new design approach based on differential evolution algorithm for geometric optimization of magnetorheological brakes", Smart Mater. Struct., 25(12).
  107. Toghroli, A. (2015), Applications of the ANFIS and LR models in the prediction of shear connection in composite beams/Ali Toghroli, University of Malaya.
  108. Toghroli, A., et al. (2018), "Evaluation of the parameters affecting the Schmidt rebound hammer reading using ANFIS method", Comput Concret, 21(5), 525-530. DOI: https://doi.org/10.12989/cac.2018.21.5.525.
  109. Toghroli, A., et al. (2014), "Prediction of shear capacity of channel shear connectors using the ANFIS model", Steel Compos. Struct., 17(5), 623-639. DOI: https://doi.org/10.12989/scs.2014.17.5.623.
  110. Toghroli, A., et al. (2017), "Investigation on composite polymer and silica fume-rubber aggregate pervious concrete", Proceedings of the 5th International Conference on Advances in Civil, Structural and Mechanical Engineering - CSM 2017, Zurich, Switzerland.
  111. Toghroli, A., et al. (2018), "A review on pavement porous concrete using recycled waste materials", Smart Struct. Syst., 22(4), 433-440. DOI: https://doi.org/10.12989/sss.2018.22.4.433.
  112. Toghroli, A., et al. (2016), "Potential of soft computing approach for evaluating the factors affecting the capacity of steel-concrete composite beam", J. Intel. Manufact., 1-9. DOI: 10.1007/s10845-016-1217-y.
  113. Torres-Acosta, A.A., et al. (2007), "Residual flexure capacity of corroded reinforced concrete beams", Eng. Struct., 29(6), 1145-1152. https://doi.org/10.1016/j.engstruct.2006.07.018
  114. Trung, N.T., et al. (2019), "Moment-rotation prediction of precast beam-to-column connections using extreme learning machine", STRUCTURAL ENGINEERING AND MECHANICS 70(5), 639-647. DOI: https://doi.org/10.12989/sem.2019.70.5.639.
  115. Vanluchene, R. and Sun, R. (1990), "Neural networks in structural engineering", Comput.-Aided Civil Infrastruct. Eng., 5(3), 207-215. https://doi.org/10.1111/j.1467-8667.1990.tb00377.x
  116. Vidal, T., et al. (2007). "Corrosion process and structural performance of a 17 year old reinforced concrete beam stored in chloride environment", Cement Concrete Res., 37(11), 1551-1561. https://doi.org/10.1016/j.cemconres.2007.08.004
  117. Wang, X.H. (2008), "Modeling the flexural carrying capacity of corroded RC beam", J. Shanghai Jiaotong Univ., (Science) 13(2), 129-135. https://doi.org/10.1007/s12204-008-0129-1
  118. Waszczyszyn, Z. and Ziemianski, L. (2001), "Neural networks in mechanics of structures and materials-new results and prospects of applications", Comput. Struct., 79(22-25), 2261-2276. https://doi.org/10.1016/S0045-7949(01)00083-9
  119. Wei-liang, J. and Z. Yu-xi (2001), "Effect of corrosion on bond behavior and bending strength of reinforced concrete beams", J. Zhejiang University-Science, 2(3), 298-308. https://doi.org/10.1631/jzus.2001.0298
  120. Wei, X., et al. (2018), "Distribution of shear force in perforated shear connectors", Steel Compos. Struct., 27(3), 389-399. DOI: http://dx.doi.org/10.12989/scs.2018.27.3.389.
  121. Wu, X., et al. (1992), "Use of neural networks in detection of structural damage", Comput. Struct., 42(4), 649-659. https://doi.org/10.1016/0045-7949(92)90132-J
  122. Xie, Q., et al. (2019), "An experimental study on the effect of CFRP on behavior of reinforce concrete beam column connections", Steel Compos. Struct., 30(5), 433-441. DOI: https://doi.org/10.12989/scs.2019.30.5.433.
  123. Xu, C., et al. (2019), "Using genetic algorithms method for the paramount design of reinforced concrete structures", Struct. Eng. Mech., 71(5), 503-513. DOI: https://doi.org/10.12989/sem.2019.71.5.503.
  124. Yamamoto, T., et al. (2011), Systematic laboratory test on structural performance of corroded reinforced concrete and its utilization in practice. Modelling of Corroding Concrete Structures, Springer: 113-124.
  125. Yan, X., et al. (2017). "Experimental studies on mechanical properties of corroded steel bars after elevated temperature", Procedia Eng., 210, 622-629. https://doi.org/10.1016/j.proeng.2017.11.122
  126. Zandi, Y., et al. (2018), "Computational investigation of the comparative analysis of cylindrical barns subjected to earthquake", Steel Compos. Struct., 28(4), 439-447. DOI: https://doi.org/10.12989/scs.2018.28.4.439.
  127. Zhou, S., et al. (2019), "Degradation behavior of concrete under corrosive coal mine environment", Int. J. Mining Sci. Technol., 29(2), 307-312. https://doi.org/10.1016/j.ijmst.2018.12.001
  128. Zhu, W. and Francois, R. (2014), "Corrosion of the reinforcement and its influence on the residual structural performance of a 26-year-old corroded RC beam", Constr. Build. Mater., 51, 461-472. https://doi.org/10.1016/j.conbuildmat.2013.11.015
  129. Ziaei-Nia, A., et al. (2018), "Dynamic mix design optimization of high-performance concrete", Steel Compos. Struct., 29(1), 67-75. DOI: https://doi.org/10.12989/scs.2018.29.1.67.

피인용 문헌

  1. Elevated temperature resistance of concrete columns with axial loading vol.9, pp.4, 2020, https://doi.org/10.12989/acc.2020.9.4.355
  2. Computational analysis of three dimensional steel frame structures through different stiffening members vol.35, pp.2, 2020, https://doi.org/10.12989/scs.2020.35.2.187
  3. Influence of porosity and cement grade on concrete mechanical properties vol.10, pp.5, 2020, https://doi.org/10.12989/acc.2020.10.5.393
  4. Prediction of total sediment load: A case study of Wadi Arbaat in eastern Sudan vol.26, pp.6, 2020, https://doi.org/10.12989/sss.2020.26.6.781
  5. Knowledge-Based Prediction of Load-Carrying Capacity of RC Flat Slab through Neural Network and FEM vol.2021, 2020, https://doi.org/10.1155/2021/4528945
  6. The prediction of compressive strength and non-destructive tests of sustainable concrete by using artificial neural networks vol.27, pp.1, 2020, https://doi.org/10.12989/cac.2021.27.1.021
  7. Ionic liquid coated magnetic core/shell CoFe2O4@SiO2 nanoparticles for the separation/analysis of trace gold in water sample vol.10, pp.3, 2020, https://doi.org/10.12989/anr.2021.10.3.295
  8. Optimization algorithms for composite beam as smart active control of structures using genetic algorithms vol.27, pp.6, 2020, https://doi.org/10.12989/sss.2021.27.6.1041
  9. Computer simulation for stability performance of sandwich annular system via adaptive tuned deep learning neural network optimization vol.11, pp.1, 2021, https://doi.org/10.12989/anr.2021.11.1.083
  10. Smart estimation of automatic approach in enhancing the road safety under AASHTO Standard specification and STM vol.79, pp.3, 2021, https://doi.org/10.12989/sem.2021.79.3.389
  11. Investigating the effect of using three pozzolans separately and in combination on the properties of self-compacting concrete vol.11, pp.2, 2020, https://doi.org/10.12989/anr.2021.11.2.141
  12. Application of multi-hybrid metaheuristic algorithm on prediction of split-tensile strength of shear connectors vol.28, pp.2, 2020, https://doi.org/10.12989/sss.2021.28.2.167
  13. Analyzing shear strength of steel-concrete composite beam with angle connectors at elevated temperature using finite element method vol.40, pp.6, 2020, https://doi.org/10.12989/scs.2021.40.6.853
  14. Hybridization of metaheuristic algorithms with adaptive neuro-fuzzy inference system to predict load-slip behavior of angle shear connectors at elevated temperatures vol.278, 2020, https://doi.org/10.1016/j.compstruct.2021.114524
  15. Adaptive neuro fuzzy evaluation of energy and non‐energy material productivity impact on sustainable development based on circular economy and gross domestic product vol.31, pp.1, 2020, https://doi.org/10.1002/bse.2878
  16. Bilinear elasto-dynamical response of SDOF system under sinusoidal loading vol.7, pp.1, 2022, https://doi.org/10.1007/s41062-021-00640-8