Computers and Concrete

  • 제6권2호
  • /
  • Pages.155-165
  • /
  • 2009
  • /
  • 1598-8198(pISSN)
  • /
  • 1598-818X(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Clustering-based identification for the prediction of splitting tensile strength of concrete

  • 투고 : 2008.09.11
  • 심사 : 2008.12.12
  • 발행 : 2009.04.25
⟨ 이전 논문 다음 논문 ⟩

초록

Splitting tensile strength (STS) of high-performance concrete (HPC) is one of the important mechanical properties for structural design. This property is related to compressive strength (CS), water/binder (W/B) ratio and concrete age. This paper presents a clustering-based fuzzy model for the prediction of STS based on the CS and (W/B) at a fixed age (28 days). The data driven fuzzy model consists of three main steps: fuzzy clustering, inference system, and prediction. The system can be analyzed directly by the model from measured data. The performance evaluations showed that the fuzzy model is more accurate than the other prediction models concerned.

키워드

참고문헌

  1. Akkurt, S., Tayfur, G. and Can, S. (2004), "Fuzzy logic model for the prediction of cement compressive strength", Cement Concrete Res. 34, 1429-1433. https://doi.org/10.1016/j.cemconres.2004.01.020
  2. Ayyub, B.M. and Klir, G.J. (2006), Uncertainty Modelling and Analysis in Engineering and the Sciences. CRC Press, Boca Raton.
  3. Babuska, R. (1998), Fuzzy Modelling for Control, Kluwer Academic, USA.
  4. Bezdek, J.C., Ehrlich, R. and Full, W. (1984), "FCM: the fuzzy c-means clustering algorithm", Comput. Geosci., 10(2-3), 191-203. https://doi.org/10.1016/0098-3004(84)90020-7
  5. Carino, N.J. and Clifton, J.R. (1990), "Outline of a National plan on High-Performance Concrete: Report on the NIST/ACI Workshop", NISTIR 4465, Nat. Inst.of Stds. and Tech., Gaithersburg, MD.
  6. Choi, Y. and Yuan, R.L. (2005), "Experimental relationships between splitting tensile strength and compressive strength of GFRC and PFRC", Cement Concrete Res. 35, 1587-1591. https://doi.org/10.1016/j.cemconres.2004.09.010
  7. Committee Euro-International du Beton (CEB-FIP) (1993), CEB-FIP Model Code 1990, London: Thomas Telford.
  8. Jain, A. and Dubes, R. (1988), Algorithms for Clustering Data, Prentice Hall.
  9. Jang, J-S.R., Sun, C.T. and Mizutani, E. (1997), Neuro-fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Prentice Hall International (UK), London.
  10. Jantzen, J. (2007), Foundations of Fuzzy Control. John Wiley and Sons, Chichester.
  11. Larrard, FDe. and Malier, Y. (1992), "Engineering properties of very high performance concrete", in: Y. Malier (ed.), High Performance Concrete: From Material to Structure, E&FN Spon, London, 85-114.
  12. Meeks, K.W. and Carino, N.J. (1999), "Curing of High-Performance Concrete: Report of the State-of-the-Art. NISTIR 6295", Nat. Inst. of Stds. and Tech., Gaithersburg, MD.
  13. Mindess, S. and Young, J.F. (1981), Concrete, Englewood Cliffs, NJ: Prentice-Hall.
  14. Piegat, A. (2001), Fuzzy Modelling and Control, Physica-Verlag, Heidelberg.
  15. Setnes, M., Babuska, R. and Verbruggen, H.B. (1998), "Transparent fuzzy modelling", Int. J. Hum.-Comput. St. 49, 159-179. https://doi.org/10.1006/ijhc.1998.0197
  16. Song, P.S. and Hwang, S. (2004), "Mechanical properties of high-strength steel fiber-reinforced concrete", Constr. Build. Mater., 18, 669-673. https://doi.org/10.1016/j.conbuildmat.2004.04.027
  17. Sousa, J.M.C. and Kaymak, U. (2002), Fuzzy Decision Making in Modelling and control, World Scientific, Singapore.
  18. Russell, H.G. (1999), "ACI Defines High-Performance Concrete", Concrete Int. 21(2), 56-57.
  19. Takagi, H. and Sugeno, M. (1985), "Fuzzy identification of systems and its applications to modelling and control", IEEE T. Syst. Man. Cy., 15, 116-132.
  20. Tutmez, B., Tercan, A.E. and Kaymak, U. (2007), "Fuzzy modelling for reserve estimation based on spatial variability", Math. Geol., 39(1), 87-111. https://doi.org/10.1007/s11004-006-9066-4
  21. Zain, M.F.M., Mahmud, H.B., Ilham, A. and Faizal, M. (2002), "Prediction of splitting tensile strength of high-performance concrete", Cement Concrete Res. 32, 251-1258. https://doi.org/10.1016/S0008-8846(02)00768-8
  22. Zia, P., Leming, M.L., Ahmad, S.H., Schemmel, J.J., Elliott, R.P. and Naaman A.E. (1993), "Mechanical behavior of high-performance concretes", Volume 1: Summary Report SHRP-C-361, National Research Council, Washington.

피인용 문헌

  1. Use of partial least squares analysis in concrete technology vol.13, pp.2, 2014, https://doi.org/10.12989/cac.2014.13.2.173
  2. Use of uncertain numbers for appraising tensile strength of concrete vol.46, pp.4, 2013, https://doi.org/10.12989/sem.2013.46.4.447
  3. Comparison of measurement uncertainty calculation methods on example of indirect tensile strength measurement vol.12, pp.6, 2009, https://doi.org/10.12989/gae.2017.12.6.871
  4. Effect of ground granulated blast furnace slag on time-dependent tensile strength of concrete vol.23, pp.2, 2009, https://doi.org/10.12989/cac.2019.23.2.133