Influence of Mix Proportions on the Compressive Strength of Concrete: A Statistical Analysis of 1030 Concrete Mixtures
DOI:
https://doi.org/10.55544/jrasb.icaces.20Keywords:
compressive strength, water-binder ratio, supplementary cementitious materials, curing age, statistical regression, concrete mix proportions, sustainable development goalsAbstract
The compressive strength of concrete is governed by a complex interaction of its constituent proportions, the water-to-binder ratio, the use of supplementary cementitious materials, and the age of curing. This study presents a statistical investigation of these relationships using a consolidated dataset of 1030 concrete mixtures containing eight measured parameters: cement, ground granulated blast-furnace slag, fly ash, water, superplasticiser, coarse aggregate, fine aggregate, and curing age. Engineered parameters including the water-to-binder ratio, total binder content, and supplementary cementitious material replacement level were derived to interpret strength behaviour through established concrete technology principles. Descriptive statistics, Pearson and Spearman correlation analysis, banded grouping, and ordinary least-squares regression were employed. The results confirm the classical inverse relationship between the water-to-binder ratio and strength, with mean strength declining from 52.96 MPa at ratios below 0.35 to 17.67 MPa at ratios above 0.65. Cement content and curing age emerged as the strongest positive determinants of strength, while water content showed the strongest negative association. A logarithmic strength-age relationship was observed, and a multi-parameter empirical equation explained approximately 62 percent of the variance in compressive strength. The findings reaffirm fundamental mix-design principles on a large heterogeneous dataset and provide a transparent, practitioner-usable predictive equation for preliminary proportioning. By demonstrating that moderate replacement of cement with industrial by-products such as slag and fly ash can maintain compressive strength, the work supports the United Nations Sustainable Development Goals relating to resilient infrastructure (SDG 9), sustainable cities and communities (SDG 11), and responsible consumption and production (SDG 12).
Downloads
References
[1] Abrams, D.A. (1918). Design of concrete mixtures. Bulletin No. 1, Structural Materials Research Laboratory, Lewis Institute, Chicago, pp. 1-20.
[2] Neville, A.M. (2011). Properties of concrete. (5th ed.). Harlow: Pearson Education Limited.
[3] Mehta, P.K., & Monteiro, P.J.M. (2014). Concrete: Microstructure, properties, and materials. (4th ed.). New York: McGraw-Hill Education.
[4] Yeh, I.C. (1998). Modeling of strength of high-performance concrete using artificial neural networks. Cement and Concrete Research, 28(12), 1797-1808. DOI: 10.1016/S0008-8846(98)00165-3.
[5] Lothenbach, B., Scrivener, K., & Hooton, R.D. (2011). Supplementary cementitious materials. Cement and Concrete Research, 41(12), 1244-1256. DOI: 10.1016/j.cemconres.2010.12.001.
[6] Bharatkumar, B.H., Narayanan, R., Raghuprasad, B.K., & Ramachandramurthy, D.S. (2001). Mix proportioning of high performance concrete. Cement and Concrete Composites, 23(1), 71-80. DOI: 10.1016/S0958-9465(00)00071-8.
[7] Popovics, S. (1990). Analysis of the concrete strength versus water-cement ratio relationship. ACI Materials Journal, 87(5), 517-529.
[8] Wassermann, R., Katz, A., & Bentur, A. (2009). Minimum cement content requirements: a must or a myth? Materials and Structures, 42(7), 973-982. DOI: 10.1617/s11527-008-9436-0.
[9] Siddique, R. (2004). Performance characteristics of high-volume Class F fly ash concrete. Cement and Concrete Research, 34(3), 487-493. DOI: 10.1016/j.cemconres.2003.09.002.
[10] Snedecor, G.W., & Cochran, W.G. (1989). Statistical methods. (8th ed.). Ames: Iowa State University Press.
[11] Chou, J.S., & Pham, A.D. (2013). Enhanced artificial intelligence for ensemble approach to predicting high performance concrete compressive strength. Construction and Building Materials, 49, 554-563. DOI: 10.1016/j.conbuildmat.2013.08.078.
[12] Young, B.A., Hall, A., Pilon, L., Gupta, P., & Sant, G. (2019). Can the compressive strength of concrete be estimated from knowledge of the mixture proportions? New insights from statistical analysis and machine learning methods. Cement and Concrete Research, 115, 379-388. DOI: 10.1016/j.cemconres.2018.09.006.
[13] Bureau of Indian Standards. (2019). IS 10262: Concrete mix proportioning - guidelines. (2nd revision). New Delhi: BIS.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Ibrahim Siddique, Sphurty Raman
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
10.55544/jrasb
editor@jrasb.com or mailtojrasb@gmail.com | 
+91-8874396939
This work is licensed under a 