Analiza statystyczna właściwości mechanicznych mieszanek trójskładnikowych betonów o dużej wytrzymałości

• Autorzy: Robinson J. , Srisanthi V. G.

Identyfikatory

DOI

10.32047/CWB.2022.27.6.2

Warianty tytułu

EN

Statistical analysis on mechanical behaviour of ternary blended high strength concrete

• Języki publikacji: PL EN

Abstrakty

PL

Rosnące zapotrzebowanie na beton o dużej wytrzymałości [BDW] w budownictwie zwiększa zużycie cementu, co powoduje problemy środowiskowe. Ostatnie badania wykazują, że wykorzystanie materiałów cementowych w betonie może skutecznie zmniejszyć objętość cementu. W niniejszej pracy przygotowano trójskładnikowe mieszanki cementu, krzemionki i popiołu lotnego w celu uzyskania BDW. W tym przypadku cement został częściowo zastąpiony odpowiednio: pyłem krzemionkowym - 0, 2,5, 5, 7,5 i 10% oraz popiołem lotnym - 0, 5, 10 i 15%. W celu określenia kompatybilności zaczynu cementowego z super-plastyfikatorem opartym na eterze polikarboksylanowym [PCE], przeprowadzono badanie metodą mini stożka opadowego. Obliczono gęstość ziaren kruszyw w celu zmniejszenia porów i poprawy rozmieszczenia cząstek w BDW. Przeprowadzono badania doświadczalne i uzyskano ostateczną wytrzymałość na ściskanie 71,55 MPa, po 28 dniach twardnienia. Badania mikrostruktury przeprowadzono przy użyciu skaningowego mikroskopu elektronowego i spektroskopii rentgenowskiej z dyspersją energii, aby poznać podstawowy mechanizm i udział składników chemicznych wpływających na zmianę właściwości mieszanki w różnych etapach. Przeprowadzono analizę regresji wielokrotnej [ARW] w celu symulacji projektu mieszanki, aby wspomóc przewidywanie wytrzymałości na ściskanie betonu o dużej wytrzymałości.

EN

The growing demand for high strength concrete [HSC] in the construction industry increases the usage of cement, resulting in environmental issues. Recent studies are showing that the utilization of cementitious materials in concrete can effectively reduce the volume of cement. In the present study, ternary blended combinations were prepared using cement, silica fume, and fly ash to attain the HSC. Here, cement was partially replaced by silica fume [2.5, 5, 7.5, and 10%] and fly ash [5, 10, and 15%], respectively. Mini slump cone test was conducted to identify the compatibility of cement paste with polycarboxylate ether [PCE] based superplasticizer. The packing density of aggregates was calculated to reduce the voids and improve the particle distribution in HSC. An experimental investigation was carried out, and the ultimate compressive strength was obtained as 71.55 MPa at 28 days of curing. Multi linear regression analysis was conducted to simulate the mix design for aiding the prediction of compressive strength of the HSC.

Słowa kluczowe

PL

beton o dużej wytrzymałości; pył krzemionkowy; popiół lotny; analiza statystyczna; właściwości mechaniczne; metoda mini stożka opadowego; gęstość ziaren; rozmieszczenie ziaren; analiza mikrostruktury; analiza regresji wielokrotnej

EN

high strength concrete; silica fume; fly ash; statistical analysis; mechanical properties; mini slump test; grain density; grain arrangement; microstructure analysis; multi linear regression analysis

• Wydawca: Fundacja Cement, Wapno, Beton
• Czasopismo: Cement Wapno Beton
• Rocznik: 2022
• Tom: R. 27, nr 6
• Strony: 386--402
• Opis fizyczny: Bibliogr. 36 poz., il., tab.

Twórcy

autor

Robinson J.

• Department of Civil Engineering, Akshaya College of Engineering and Technology, Coimbatore, India

autor

Srisanthi V. G.

• Department of Civil Engineering, Coimbatore Institute of Technology, Coimbatore, India

Bibliografia

• 1. C. Deepa, K. SathiyaKumari, V.P. Sudha, Prediction of the compressive strength of high performance concrete mix using tree based modeling. Int. J. Comput. Appl. 6(5), 18-24 (2010). https://doi.org/10.5120/1076-1406
• 2. Indian standards guidelines to concrete mix proportioning, IS 10262 (2019), Bureau of Indian Standards, New Delhi, India.
• 3. C. Sudha, K. Divya Krishnan, P.T. Ravichandran, P.R. Kannan Rajkumar, Strength Characteristics of high strength concrete using M-sand, Indian J. Sci. Technol. 9(41) (2016). https://doi.org/10.17485/ijst/2016/v9i41/95864
• 4. A.K.H. Kwan, L.G. Li, W.W.S. Fung, Wet packing of blended fine and coarse aggregate, Mater. Struct. 45(6) 817-828 (2012). https://doi.org/10.1617/s11527-011-9800-3
• 5. L.G. Li, A.K.H. Kwan, Packing density of concrete mix under dry and wet conditions, Powder Technol. 253, 514-521 (2014). https://doi.org/10.1016/j.powtec.2013.12.020
• 6. H.M.B. Miranda, F.A. Batista, M. de Lurdes Antunes, J. Neves, Influence of laboratory aggregate compaction method on the particle packing of stone mastic asphalt, Constr. Build. Mater. 259, 119699 (2020). https://doi.org/10.1016/j.conbuildmat.2020.119699
• 7. A. Ajay, K.P. Ramaswamy, M. Nazeer, A study on compatibility of superplasticizers with high strength blended cement paste, IOP Conf. Earth Environ. Sci. 491(1), 012043 (2020). https://doi.org/10.1088/1755-1315/491/1/012043
• 8. C. Jayasree, R. Gettu, Experimental study of the flow behaviour of superplasticized cement paste, Mater. Struct. 41(9), 1581-1593 (2008). https://doi.org/10.1617/s11527-008-9350-5
• 9. I. B. Muhit, S.S. Ahmed, M.M. Amin, M.T. Raihan, Effects of silica fume and fly ash as partial replacement of cement on water permeability and strength of high-performance concrete. 4th Int. Conf. Adv. Civil Eng. AETACE, Association of Civil and Environmental Engineers, (2013).
• 10. N.K. Verma, Influence of partial replacement of cement by industrial waste on properties of concrete, Recent Trends in Civil Engineering. Lect. Notes Civ. Eng. 77, 693-713 (2021). https://doi.org/10.1007/978-981-15-5195-6_54
• 11. T. Nochaiya, W. Wongkeo, A. Chaipanich, Utilization of fly ash with silica fume and properties of Portland cement-fly ash-silica fume concrete. Fuel, 89(3), 768-774 (2010). https://doi.org/10.1016/j.fuel.2009.10.003
• 12. V. Prakash, K. Chandrasekar, P. Vinoth, Partial replacement of silica fume and fly ash in pervious concrete, Int. J. Eng. Res. Technol., 5(5), 1823-1825 (2018).
• 13. U.S. Ansari, I.M. Chaudhri, N.P. Ghuge, R.R. Phatangre, High performance concrete with partial replacement of cement by alccofine and fly ash. Indian Res. Trans. 5(2), 19-23 (2015).
• 14. J. Snehavi, A. Yashwanth, Experimental study on partial replacement of cement by fly ash, silica fume and sand with quarry dust. Int. J. Sci. Res. 7(5), 582-585 (2018).
• 15. A.S. Adithya Saran, P. Magudeswaran, SEM analysis on sustainable high performance concrete, Int. J. Innov. Res. Sci. Eng. Techn. 6(6), 10237-10246 (2017). https://doi.org/10.15680/IJIRSET.2017.0606016
• 16. M.K. Rao, C.N.S. Kumar, Influence of fly ash on hydration compounds of high-volume fly ash concrete. AIMS Mater. Sci. 8(2), 301-320 (2021). https://doi.org/10.3934/matersci.2021020
• 17. D. Maruthachalam, R.K. Rajalaxmi, B.G. Vishnuram, Statistical modeling of fiber reinforced high performance concrete. Int. J. Sci. Eng. Res. 3(6), 1-5 (2012).
• 18. F. Khademi, S.M. Jamal, N. Deshpande, S. Londhe, Predicting strength of recycled aggregate concrete using artificial neural network, adaptive neuro-fuzzy inference system and multiple linear regression. Int. J. Sustain. Built Env. 5(2), 355-369 (2016).
• 19. N. Deshpande, S. Londhe, S. Kulkarni, Modeling compressive strength of recycled aggregate concrete by artificial neural network, model tree and non-linear regression. Int. J. Sustain. Built Env. 3(2), 187-198 (2014). https://doi.org/10.1016/j.ijsbe.2014.12.002
• 20. I. Padmanaban, S. Kandasamy, S.C. Natesan, Statistical modeling of high and low volume of fly ash compressive strength concrete, Int. J. Appl. Eng. Res. 4(7), 1161-1167 (2009).
• 21. D. Sathyan, A.K. Balakrishnan, S.M. Mohandas, Temperature influence on rheology of superplasticized pozzolana cement and modeling using RKS algorithm,. J. Mater. Civil Eng. 30(9), 04018221 (2018). https://doi.org/10.1061/(ASCE)MT.1943-5533.0002406
• 22. C.W. Chase, Demand-driven forecasting: a structured approach to forecasting, 2 ed., John Wiley & Sons, Hoboken, New Jersey, 2013.
• 23. S. Charhate, M. Subhedar, N. Adsul, Prediction of concrete properties using multiple linear regression and artificial neural network. J. Soft Comput. Civ. Eng. 2(3), 27-38 (2018).
• 24. M.F.M. Zain, S.M. Abd, Multiple regression model for compressive strength prediction of high performance concrete. J. Appl. Sci. 9(1), 155-160 (2009). https://doi.org/10.3923/jas.2009.155.160
• 25. Indian standards specification on ordinary portland cement - 53 Grade, IS 12269 (2013), Bureau of Indian Standards, New Delhi, India.
• 26. Indian standards specification on silica fume, IS 15388 (2003), Bureau of Indian Standards, New Delhi, India.
• 27. Indian standards specification on pulverized fuel ash, IS 3812 (2003), Bureau of Indian Standards, New Delhi, India.
• 28. Indian standard specification on coarse and fine aggregate for concrete, IS 383 (2016), Bureau of Indian Standards, New Delhi, India.
• 29. Indian standard specification on concrete admixture, IS 9103 (1999), Bureau of Indian Standards, New Delhi, India.
• 30. Indian standard code of practice for plain and reinforced concrete, IS 456 (2000), Bureau of Indian Standards, New Delhi, India.
• 31. The user manual SPSS, https://www.westga.edu/academics/research/vrc/assets/docs/spss_basics.pdf
• 32. Indian standard code of practice for methods of test for aggregates for concrete, IS 2386-3 (1963), Bureau of Indian Standards, New Delhi, India.
• 33. Indian standard code of practice for methods of sampling and analysis of concrete, IS 1199 (1959), Bureau of Indian Standards, New Delhi, India.
• 34. Indian standard code of practice for methods of tests for strength of concrete, IS 516 (1959), Bureau of Indian Standards, New Delhi, India.
• 35. Indian standard code of practice for splitting tensile strength of concrete - Method of test, IS 5816 (1999), Bureau of Indian Standards, New Delhi, India.
• 36. Indian standard code of practice for specification for apparatus for flexural testing of concrete, IS 9399 (1979), Bureau of Indian Standards, New Delhi, India.