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Prediction of the effects of fly ash and silica fume on the setting time of Portland cement with fuzzy logic

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Abstract

Fuzzy logic has recently been widely used to model in many areas of civil engineering applications. Especially as a result of the findings of experimental studies with fuzzy logic to predict good results have been obtained. In this study, Portland cement is composed of fly ash and silica fume with determined proportional. By this procedure, eight different mixtures were prepared and the effect of cement was investigated on the starting and finishing time of the setting. According to the results obtained in the setting time and finishing, all the mixing ratio of the prolonged period of time was determined. Also, by using fuzzy logic method, prediction model was formed based on the quantity of fly ash and silica fume to predict the initial and final setting times of cement, which could not be determined with experimental approaches. The experimental results are compared with the fuzzy logic results, and the correlation coefficients for the initial and final setting time are found 0.96 and 0.92, respectively. These results show that the developed model can be successfully applied in the cement industry.

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References

  1. Fu X, Wang Z, Tao W, Yang C, Hou W, Dong Y, Wu X (2002) Studies on blended cement with a large amount of fly ash. Cem Concr Res 32(79):1153–1159

    Article  Google Scholar 

  2. Worrell E, Martin N, Price L (2000) Potentials for energy efficiency improvement in the US cement industry. Energy 25(12):1189–1214

    Article  Google Scholar 

  3. Yilmaz B, Ucar A, Oteyaka B, Uz V (2007) Properties of zeolitic tuff (clinoptilolite) blended Portland cement. Build Environ 42:3808–3815

    Article  Google Scholar 

  4. Yilmaz B (2008) A study on the effects of diatomite blend in natural pozzolan blended cements. Adv Cement Res 20:13–21

    Article  Google Scholar 

  5. Yildiz S, Balaydin I, Ulucan Z (2007) The Effect of rice husk ash on concrete strength. Sci Eng J Fırat Univ 19(1):85–91 (in Turkish)

    Google Scholar 

  6. Aruntas HY, Tokyay M (1996) The availability of diatomite as pozzolanic materials in the production of blended cement. Cem Concr World 1(4):3–41 (in Turkish)

    Google Scholar 

  7. Shiqun L, Della MR (1986) Investigation of relations between porosity, pore structure, and C1− diffusion of fly ash and blended cement pastes. Cem Concr Res 16(5):749–759

    Article  Google Scholar 

  8. Prigione SG (1987) Portland-zeolite-cement for minimizing alkali-aggregate expansion. Cem Concr Res 17(3):404–410

    Article  Google Scholar 

  9. Saraswathy V, Muralidharan S, Thangavel K, Srinivasan S (2003) Influence of activated fly ash on corrosion-resistance and strength of concrete. Cem Concr Compos 25(7):673–680

    Article  Google Scholar 

  10. Homwuttiwong CS, Sirivivatnanon V (2004) Influence of fly ash fineness on strength, drying shrinkage and sulfate resistance of blended cement mortar. Cem Concr Res 34(7):1087–1092

    Article  Google Scholar 

  11. Simsek O (2000) Building materials II. Ankara University Press, Ankara (in Turkish)

    Google Scholar 

  12. TS EN 197-1 (2002) Cement- Part 1: compositions and conformity criteria for common cements. Turkish Standards, Ankara. (in Turkish)

  13. Celik MH, Simsek O, Sancak E (2001) The effect of silica fumes to initial and final of setting time of cement. J Polytech 4(4):55–60 (in Turkish)

    Google Scholar 

  14. Simsek O, Dur A, Yaprak H (2004) Properties of mortars added silica fume and superplasticizer. J Polytech 7(2):168–178 (in Turkish)

    Google Scholar 

  15. Celik MH, Aruntas HY, Baran Y (2003) () The effect of Seyitömer and Cayirhan thermal power plant fly ashes to initial and final setting time of PC-FA pastes. J Polytech 6(1):397–409 (in Turkish)

    Google Scholar 

  16. Dorum A, Tekin I (2004) The effect of distilled water to pressure strength and setting time of the fly ash replaced in cement paste. J Polytech 7(3):243–250 (in Turkish)

    Google Scholar 

  17. Guler I, Tunca A, Gulbandilar E (2008) Detection of traumatic brain injuries using fuzzy logic algorithm. Expert Syst Appl 34(2):1312–1317

    Article  Google Scholar 

  18. Ozgan E, Yildiz K (2009) Prediction the effect of chrome magnesit brick dust on the starting and finishing setting time of Portland cement with fuzzy logic. J Fac Eng Architect Gazi Univ 24(2):257–264 (in Turkish)

    Google Scholar 

  19. Sarıdemir M (2009) Prediction of compressive strength of concretes containing metakaolin and silica fume by artificial neural Networks. Adv Eng Softw 40:350–355

    Article  MATH  Google Scholar 

  20. Tanyildızi H (2009) Fuzzy logic model for the prediction of bond strength of high-strength lightweight concrete. Adv Eng Softw 40:161–169

    Article  MATH  Google Scholar 

  21. Topcu IB, Saridemir M (2008) Prediction of compressive strength of concrete containing fly ash using artificial neural networks and fuzzy logic. Comput Mater Sci 41:305–311

    Article  Google Scholar 

  22. Saridemir M (2009) Predicting the compressive strength of mortars containing metakaolin by artificial neural networks and fuzzy logic. Adv Eng Softw 40(9):920–927

    Article  MATH  Google Scholar 

  23. Ozcan F, Atiş CD, Karahan O, Uncuoglu E, Tanyildiz H (2009) Comparison of artificial neural network and fuzzy logic models for prediction of long-term compressive strength of silica fume concrete. Adv Eng Softw 40(9):856–863

    Article  Google Scholar 

  24. Subaşı S (2009) Prediction of mechanical properties of cement containing class C fly ash by using artificial neural network and regression technique. Sci Res Essay 4(4):289–297

    Google Scholar 

  25. Subasi S, Beycioglu A, Sancak E, Sahin I (2012) Rule-based Mamdani type fuzzy logic model for the prediction of compressive strength of silica fume included concrete using non-destructive test results. Neural Comput Appl. doi:10.1007/s00521-012-0879-4

    Google Scholar 

  26. Nazari A (2012) Utilizing ANFIS for prediction water absorption of light weight geopolymers produced from waste materials. Neural Comput Appl. doi:10.1007/s00521-012-0934-1

  27. Subasi A, Yilmaz AS, Binici H (2009) Prediction of early heat of hydration of plain and blended cements using neuro-fuzzy modelling techniques. Expert Syst Appl 36:4940–4950

    Article  Google Scholar 

  28. TS EN 196-3 (2002) Methods of testing cement-part 3: Determination of setting time and soundness. Turkish Standards, Ankara (in Turkish)

  29. Hsu YL, Lee CH, Kreng VB (2010) The applications of fuzzy Delphi method and fuzzy AHP in lubricant regenerative technology selection. Expert Syst Appl 37:419–425

    Article  Google Scholar 

  30. Ajayi AO, Aderounmu GA, Soriyan HA, David A (2010) An intelligent quality of service brokering model for e-commerce. Expert Syst Appl 37:816–823

    Article  Google Scholar 

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Acknowledgments

The authors express their gratitude to Bursa Cement Plant executives, Quality Control Chief Sabiha KAN, and the staff for their invaluable contributions on this study.

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Authors and Affiliations

  1. Department of Computer Engineering, Faculty of Engineering, Dumlupinar University, Merkez Campus, 43100, Kutahya, Turkey

    Eyyup Gulbandilar

  2. Department of Civil Engineering, Faculty of Technology, Duzce University, 81620, Duzce, Turkey

    Yilmaz Kocak

Authors
  1. Eyyup Gulbandilar
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  2. Yilmaz Kocak
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Correspondence to Eyyup Gulbandilar.

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Gulbandilar, E., Kocak, Y. Prediction of the effects of fly ash and silica fume on the setting time of Portland cement with fuzzy logic. Neural Comput & Applic 22, 1485–1491 (2013). https://doi.org/10.1007/s00521-012-1049-4

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  • DOI: https://doi.org/10.1007/s00521-012-1049-4

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