Statistical Modelling and Prediction of Compressive Strength of Concrete
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The matrix mixture of concrete can be made to have high compressive strength. In the present paper, statistical model was built-up to predict the compressive strength of concrete containing different matrix mixtures at fixed age or at different age of 1, 3, 7, 28, 56, 90 and 180 days. The model examines eight different parameters for the matrix mixture that includes: time, water, cement, metakaolin (MK), silica fume (SF), sand (S), aggregate (A) and superplasticizer (SP). This research addresses the effect of the matrix mixture of concrete on the compressive strength, where this information will help the cement industry in producing the required concrete strength. The results from the predicted model have high correlation to the experimental results for the concrete compressive strength.
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References
R. Demirboga, I. Orung and R. Gul, "Effects of expanded perlite aggregate and mineral admixtures on the compressive strength of low-density concrete," Cement and Concrete Research, vol. 31, no. 11, pp. 1627-1632, 2001.
J. Ortiz, A. Aguado, L. Agullo and T. Garcia, "Influence of environmental temperatures on the concrete compressive strength: Simulation of hot and cold weather conditions," Cement and Concrete Research, vol. 35, no. 10, pp. 1970-1979, 2005.
A. Colak, "A new model for the estimation of compressive strength of Portland cement concrete," Cement and Concrete Research, vol. 36, no. 7, pp. 1409-1413, 2006.
J. del Viso, J. Carmona and G. Ruiz, "Shape and size effects on the compressive strength of high-strength concrete," Cement and Concrete Research, vol. 38, no. 3, pp. 386-395, 2008.
S. Bhanja and B. Sengupta, "Investigations on the compressive strength of silica fume concrete using statistical methods," Cement and Concrete Research, vol. 32, no. 9, pp.1391-1394, 2002.
R. Sahin, R. Demirboga, H. Uysal and R. Gul, "The effects of different cement dosages, slumps and pumice aggregate ratios on the compressive strength and densities of c," Cement
and Concrete Research, vol. 33, no. 8, pp. 1245-1249, 2003.
N. Hong-Guang and J.-Z. Wang, "Prediction of compressive strength of concrete by neural networks," Cement and Concrete Research, vol. 30, no. 8, pp. 1245-1250, 2000.
M. Saridemir, "Prediction of compressive strength of concretes containing metakaolin and silica fume by artificial neural networks," Advances in Engineering Softwares, vol. 40, no.5, pp. 350-355, 2009.
M. Sarıdemir, "Predicting the compressive strength of mortars containing metakaolin by artificial neural networks and fuzzy logic," Advances in Engineering Software, vol. 40, no. 9, pp. 920-927, 2009.
Z. H. Duan, S. C. Kou and C. S. Poon, "Prediction of compressive strength of recycled aggregate concrete using artificial neural networks," Construction and Building Materials, 2012.
J.-S. C. Chou and C.-F. Tsai, "Concrete compressive strength analysis using a combined classification and regression technique," Automation in Construction, vol. 24, pp. 52-60, 2012.
S.-H. Chao, A. E. Naaman and G. J. Parra-Montesions, "Bond behavior of reinforcing bars in tensile strain-hardening fiber-reinforced cement composite," ACI Structural Journal, vol. 106, no. 6, pp. 897-906, 2009.
C. Poon, S. Kou and L. Lam, "Compressive strength, chloride diffusivity and pore structure of high performance metakaolin and silica fume concrete," Construction and Building Materials, vol. 20, no. 10, pp. 858-865, 2006.
H. Wong and H. Abdul Razzak, "Efficiency of calcined kaolin and silica fume as cement replacement material for strength performance," Cement Concrete Research, vol. 35, no. 4, pp. 696-702, 2005.
A. M. Neville, Creep of concrete: plain, reinforced and prestressed, Amsterdam: North-Holland Publishing Company, 1970.
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