Structural Engineering and Mechanics

  • 제84권1호
  • /
  • Pages.1-16
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  • 2022
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  • 1225-4568(pISSN)
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  • 1598-6217(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Classification method for failure modes of RC columns based on key characteristic parameters

  • Yu, Bo (School of Civil Engineering and Architecture, Guangxi University) ;
  • Yu, Zecheng (School of Civil Engineering and Architecture, Guangxi University) ;
  • Li, Qiming (Power China Central China Electric Power Engineering Co, Ltd.) ;
  • Li, Bing (School of Civil and Environmental Engineering, Nanyang Technological University)
  • 투고 : 2021.11.11
  • 심사 : 2022.05.24
  • 발행 : 2022.10.10
⟨ 이전 논문 다음 논문 ⟩

초록

An efficient and accurate classification method for failure modes of reinforced concrete (RC) columns was proposed based on key characteristic parameters. The weight coefficients of seven characteristic parameters for failure modes of RC columns were determined first based on the support vector machine-recursive feature elimination. Then key characteristic parameters for classifying flexure, flexure-shear and shear failure modes of RC columns were selected respectively. Subsequently, a support vector machine with key characteristic parameters (SVM-K) was proposed to classify three types of failure modes of RC columns. The optimal parameters of SVM-K were determined by using the ten-fold cross-validation and the grid-search algorithm based on 270 sets of available experimental data. Results indicate that the proposed SVM-K has high overall accuracy, recall and precision (e.g., accuracy>95%, recall>90%, precision>90%), which means that the proposed SVM-K has superior performance for classification of failure modes of RC columns. Based on the selected key characteristic parameters for different types of failure modes of RC columns, the accuracy of SVM-K is improved and the decision function of SVM-K is simplified by reducing the dimensions and number of support vectors.

키워드

과제정보

The financial support received from the National Natural Science Foundation of China (Grant Nos. 51738004, 52278162 and 62266005), the Guangxi Science Fund for Distinguished Young Scholars (2019GXNSFFA245004) and the Innovation Project of Guangxi Graduate Education (YCBZ2022011) is gratefully acknowledged.

참고문헌

  1. Aktas, G. and Ozerdem, M.S. (2016), "Prediction of behavior of fresh concrete exposed to vibration using artificial neural networks and regression model", Struct. Eng. Mech., 60(4), 655-665. https://doi.org/10.12989/sem.2016.60.4.655.
  2. ASCE/SEI 41-17 (2017), Seismic Evaluation and Retrofit of Existing Buildings, The American Society of Civil Engineering; Reston, Virginia.
  3. Berry, M., Parrish, M. and Eberhard, M. (2004), "PEER structural performance database user's manual", University of California, Berkeley, CA.
  4. Cui, J.D., Han, X.L., Gong, H.J. and Ji, J. (2018), "Deformation limits of reinforced concrete columns and their experimental verification", J. Tongji Univ. (Nat. Sci.), 46(5), 593-603.
  5. Dai, K.Y., Lu, D.G. and Yu, X.H. (2021), "Experimental investigation on the seismic performance of corroded reinforced concrete columns designed with low and high axial load ratios", J. Build. Eng., 44, 102615. https://doi.org/10.1016/j.jobe.2021.102615.
  6. Engin, S., Ozturk, O. and Okay, F. (2015), "Estimation of ultimate torque capacity of the SFRC beams using ANN", Struct. Eng. Mech., 53(5), 939-956. https://doi.org/10.12989/sem.2015.53.5.939.
  7. Esaki, F. (1996), "Reinforcing effect of steel plate hoops on ductility of R/C square column", Proceedings of the 11th World Conference on Earthquake Engineering, Pergamon, Mexico, June.
  8. Feng, D.C., Liu, Z.T., Wang, X.D., Jiang Z.M. and Liang, S.X. (2020), "Failure mode classification and bearing capacity prediction for reinforced concrete columns based on ensemble machine learning algorithm", Adv. Eng. Inform., 45, 101126. https://doi.org/10.1016/j.aei.2020.101126.
  9. Foody, G.M. (2020), "Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification", Remote Sens. Environ., 239, 111630. https://doi.org/10.1016/j.rse.2019.111630.
  10. Gao, X.L. and Lin, C. (2021), "Prediction model of the failure mode of beam-column joints using machine learning methods", Eng. Fail. Anal., 120, 105072. https://doi.org/10.1016/j.engfailanal.2020.105072.
  11. Ghee, A.B., Priestley, M.J.N. and Paulay, T. (1989), "Seismic shear strength of circular reinforced concrete columns", ACI Struct. J., 86(1), 45-59. https://doi.org/10.14359/2634
  12. Gu, Y.Y. (2003), "Study on residual shear strength of reinforced concrete bridge columns under strong seismic ground movement", M.S. Dissertation, Fuzhou University, Fuzhou.
  13. Guo, Y., Zhang, Z. and Tang, F. (2021), "Feature selection with kernelized multi-class support vector machine", Pattern Recognit., 117, 107988. https://doi.org/10.1016/j.patcog.2021.107988.
  14. Hoang, N.D., Nguyen, Q.L. and Bui, D.T. (2018), "Image processing-based classification of asphalt pavement cracks using support vector machine optimized by artificial bee colony", J. Comput. Civil Eng., 32(5), 04018037. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000781.
  15. Hu, Y. and Castro-Lacouture, D. (2019), "Clash relevance prediction based on machine learning", J. Comput. Civil Eng., 33(2), 04018060. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000810.
  16. Huang, M.L., Hung, Y.H., Lee, W.M. and Jiang, B.R. (2014), "SVM-RFE based feature selection and Taguchi parameters optimization for multiclass SVM classifier", Sci. World J., 2014, Article ID 795624. https://doi.org/10.1155/2014/795624.
  17. Ikeda, A. (1968), "A list of past experimental results of reinforced concrete columns", Rep., Training Institute for Engineering Teachers, Yokohama National Univ., Building Research Institute, Ministry of Construction, Tokyo, Japan.
  18. Kim, S.E., Vu, Q.V., Papazafeiropoulos, G., Kong, Z. and Truong, V.H. (2020). "Comparison of machine learning algorithms for regression and classification of ultimate load-carrying capacity of steel frames", Steel Compos. Struct., 37(2), 193-209. https://doi.org/10.12989/scs.2020.37.2.193.
  19. Lam, S.S.E., Wu, B., Wong, Y.L., Wang, Z.Y., Liu, Z.Q. and Li, C.S. (2003), "Drift capacity of rectangular reinforced concrete columns with low lateral confinement and high-axial load", J. Struct. Eng., 129(6), 733-742. https://doi.org/10.1061/(ASCE)0733-9445(2003)129:6(733).
  20. Li, Y.A., Huang, Y.T. and Hwang, S.J. (2014), "Seismic response of reinforced concrete short columns failed in shear", ACI Struct. J., 111(4), 945-954. https://doi.org/10.14359/51686780.
  21. Lin, K.Y., Lin, T.K. and Lin, Y. (2020), "Real-time seismic structural response prediction system based on support vector machine", Earthq. Struct., 18(2), 163-170. https://doi.org/10.12989/eas.2020.18.2.163.
  22. Lynn, A.C. (2001), "Seismic evaluation of existing reinforced concrete building columns", Ph.D. Dissertation, University of California, Berkeley.
  23. Ma, Y. and Gong, J.X. (2018), "Probability identification of seismic failure modes of reinforced concrete columns based on experimental observations", J. Earthq. Eng., 22(10), 1881-1899. https://doi.org/10.1080/13632469.2017.1309603.
  24. Mangalathu, S. and Jeon, J.S. (2018), "Classification of failure mode and prediction of shear strength for reinforced concrete beam-column joints using machine learning techniques", Eng. Struct., 160, 85-94. https://doi.org/10.1016/j.engstruct.2018.01.008.
  25. Mangalathu, S. and Jeon, J.S. (2019), "Machine learning-based failure mode recognition of circular reinforced concrete bridge columns: Comparative study", J. Struct. Eng., 145(10), 04019104. https://doi.org/10.1061/(ASCE)ST.1943-541X.0002402.
  26. Mangalathu, S., Hwang, S.H. and Jeon, J.S. (2020), "Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach", Eng. Struct., 219, 110927. https://doi.org/10.1016/j.engstruct.2020.110927.
  27. Mangalathu, S., Karthikeyan, K., Feng, D.C. and Jeon, J.S. (2022), "Machine-learning interpretability techniques for seismic performance assessment of infrastructure systems", Eng. Struct., 250, 112883. https://doi.org/10.1016/j.engstruct.2021.112883.
  28. Mirrashid, M. and Naderpour, H. (2020), "Recent trends in prediction of concrete elements behavior using soft computing (2010-2020)", Arch. Comput. Meth. Eng., 28(4), 3307-3327. https://doi.org/10.1007/s11831-020-09500-7.
  29. Mirrashid, M. and Naderpour, H. (2021), "Innovative computational intelligence-based model for vulnerability assessment of RC frames subject to seismic sequence", J. Struct. Eng., 147(3), 04020350. https://doi.org/10.1061/(asce)st.1943-541x.0002921.
  30. Mohri, M., Rostamizadeh, A. and Talwalkar, A. (2018), Foundations of Machine Learning, The MIT Press, Cambridge, MA, USA.
  31. Molnar, C. (2022), Interpretable Machine Learning, leanpub.com.
  32. Naderpour, H. and Mirrashid, M. (2019), "Classification of failure modes in ductile and non-ductile concrete joints", Eng. Fail. Anal., 103, 361-375. https://doi.org/10.1016/j.engfailanal.2019.04.047.
  33. Naderpour, H., Mirrashid, M. and Parsa, P. (2021), "Failure mode prediction of reinforced concrete columns using machine learning methods", Eng. Struct., 248, 113263. https://doi.org/10.1016/j.engstruct.2021.113263.
  34. Nakamura, T. and Yoshimura, M. (2002), "Gravity load collapse of reinforced concrete columns with brittle failure modes", J. Asian Arch. Build. Eng., 1(1), 21-27. https://doi.org/10.3130/jaabe.1.21
  35. Ning, C.L. and Feng, D.C. (2019), "Probabilistic indicator to classify the failure mode of reinforced-concrete columns", Mag. Concrete Res., 71(14), 734-748. https://doi.org/10.1680/jmacr.17.00097.
  36. Ousalem, H. (2006), "Experimental and analytical study on axial load collapse assessment and retrofit of reinforced concrete columns", Ph.D. Dissertation, University of Tokyo, Tokyo.
  37. Ousalem, H., Kabeyasawa, T., Tasai, A. and Iwamoto, J. (2003), "Effect of hysteretic reversals on lateral and axial capacities of reinforced concrete columns", Proc. JPN Concrete Inst., 25(2), 367-372.
  38. Ousalem, H., Kabeyasawa, T., Tasai, A. and Ohsugi, Y. (2002), "Experimental study on seismic behavior of reinforced concrete columns under constant and variable axial loadings", Proc. JPN Concrete Inst., 24(2), 229-234.
  39. Pham, T.P. and Li, B. (2014), "Seismic performance of reinforced concrete columns with plain longitudinal reinforcing bars", ACI Struct. J., 111(3), 561-572. https://doi.org/10.14359/51686572.
  40. Qi, Y.L., Han, X.L. and Ji, J. (2013), "Failure mode classification of reinforced concrete column using Fisher method", J. Central. South Univ., 20, 2863-2869. https://doi.org/10.1007/s11771-013-1807-1.
  41. Ramirez, H. and Jirsa, J.O. (1980), "Effect of axial load on shear behavior of short RC columns under cyclic lateral deformations", PMFSEL Rep. No.80-1, University of Texas, Austin, TX.
  42. Seitllari, A. and Naser, M.Z. (2019), "Leveraging artificial intelligence to assess explosive spalling in fire-exposed RC columns", Comput. Concrete, 24(3), 271-282. https://doi.org/10.12989/cac.2019.24.3.271.
  43. Sun, H., Burton, H.V. and Huang, H. (2021), "Machine learning applications for building structural design and performance assessment: State-of-the-art review", J. Build. Eng., 33, 101816. https://doi.org/10.1016/j.jobe.2020.101816.
  44. Sun, Z.C. and Guo, X. (2020), "Experimental study on influence of reinforced concrete matching degree on failure mode of frame columns", China Civil Eng. J., 53(S2), 80-86.
  45. Sun, Z.G., Li, H.N., Wang, D.S. and Si, B.J. (2015), "Discrimination criterion governing flexural-shear failure modes and improved seismic analysis model for RC bridge piers", China J. Highw. Transp., 28(6), 42-50.
  46. Tran, C.T.N. (2010), "Experimental and analytical studies on the seismic behavior of reinforced concrete columns with light transverse reinforcement", Ph.D. Dissertation, Nanyang Technological University, Singapore.
  47. Tran, C.T.N. and Li, B. (2015), "Experimental studies on the backbone curves of reinforced concrete columns with light transverse reinforcement", J. Perform. Constr. Facil., 29(5), 04014126. https://doi.org/10.1061/(ASCE)CF.1943-5509.0000626.
  48. Tran, C.T.N., Nguyen, X.H., Nguyen, H.C. and Vu, N.S. (2020), "Strut-and-tie model for shear capacity of corroded reinforced concrete columns", Adv. Concrete Constr., 10(3), 185-193. https://doi.org/10.12989/acc.2020.10.3.185.
  49. Umemura, H. and Endo, T. (1970), "A list of past experimental results of reinforced concrete columns", Report, Umemura Laboratory, Tokyo University, Building Research Institute, Ministry of Construction, Tokyo, Japan.
  50. Wan, H.T., Han, X.L. and Ji, J. (2010), "Analyses of reinforced concrete columns by performance-based design method", J. Central South Univ. (Sci. Technol.), 41(4), 1584-1589.
  51. Wang, Z.Y., Wu, B., Lin, S.S., Li, H. and Huang, Y.L. (2001), "Seismic performance of reinforced concrete frame columns in Hong Kong", J. Harbin Univ. Civil Eng. Arch., 34(2), 6-11.
  52. Wibowo, A., Wilson, J.L., Lam, N.T.K. and Gad, E.F. (2014), "Drift performance of lightly reinforced concrete columns", Eng. Struct., 59, 522-535. https://doi.org/10.1016/j.engstruct.2013.11.016.
  53. Yalcin, C. (1997), "Seismic evaluation and retrofit of existing reinforced concrete bridge columns", Ph.D. Dissertation, University of Ottawa, Ottawa.
  54. Yavuz, G. (2019), "Determining the shear strength of FRP-RC beams using soft computing and code methods", Comput. Concrete, 23(1), 49. https://doi.org/10.12989/cac.2019.23.1.049.
  55. Yoshimura, K., Kikcuri, K. and Kuroki, M. (1991), "Seismic shear strengthening method for existing R/C short columns", ACI Symposium Publication, 128, 1065-1080. https://doi.org/10.14359/2922.
  56. Yoshimura, M. and Nakamura, T. (2003), "Axial collapse of reinforced concrete short columns", Proceedings of the 5th U.S.-Japan Workshop on Performance-Based Earthquake Engineering Methodology for Reinforced Concrete Building Structures, Hakone, Japan, September.
  57. Yoshimura, M., Takaine, Y. and Nakamura, T. (2003), "Collapse drift of reinforced concrete columns", Proceedings of the 5th U.S.-Japan Workshop on Performance-Based Earthquake Engineering Methodology for Reinforced Concrete Building Structures, Hakone, Japan, September.
  58. Yu, B., Ding, Z.H., Liu, S.B. and Li, B. (2021), "Theoretical and practical models for shear strength of corroded reinforced concrete columns", Struct. Eng. Mech., 79(5), 565-578. https://doi.org/10.12989/sem.2021.79.5.565.
  59. Yu, B., Yu, Z.C., Li, B., Li, Q.M. and Ning, C.L. (2022), "Probabilistic classification criterion for failure modes of reinforced concrete columns", J. Earthq. Eng., 1-21. https://doi.org/10.1080/13632469.2022.2041506.
  60. Zhou, X. and Tuck, D.P. (2007), "MSVM-RFE: Extensions of SVM-RFE for multiclass gene selection on DNA microarray data", Bioinform., 23(9), 1106-1114. https://doi.org/10.1093/bioinformatics/btm284.
  61. Zhu, L., Elwood, K.J. and Haukaas, T. (2007), "Classification and seismic safety evaluation of existing reinforced concrete columns", J. Struct. Eng., 133(9), 1316-1330. https://doi.org/10.1061/(ASCE)0733-9445(2007)133:9(1316).