INTERPRETING CONCRETE COMPRESSIVE STRENGTH THROUGH MIX PROPORTIONS AND CURING AGE

Authors

  • Dr. Oliver J. Harrington Department of Civil Engineering and Construction Materials, Westborough Institute of Technology, Manchester, United Kingdom
  • Prof. Sofia M. Petrovic Department of Structural Materials and Engineering, Danube Technical University, Belgrade, Serbia
  • Dr. Daniel K. Weber Institute of Construction Analytics and Materials Science, Alpine University of Applied Sciences, Zurich, Switzerland

DOI:

https://doi.org/10.69980/645dt871

Keywords:

Concrete compressive strength, Mix proportions, Curing age, Regression analysis, Grouped cross-validation

Abstract

The relationship between the compressive strength of concrete and the proportion of the mix and curing age of the concrete allows for understanding and a transparent interpretation of the concrete performance in the laboratory. These relationships were investigated in this study through experimental concrete data with 188 observations. Three repeats were removed and 185 observations were arranged into 47 operational mix groups. Descriptive analysis, correlation assessment, multiple linear regression and ridge regression techniques have been used and the degree of predictiveness assessed by grouped cross validation. The positive adjusted associations of total amount of binder with strength, and of the log of curing age with strength, and the negative associations of water/binder ratio and fly ash replacement fraction with strength were significant. The confidence intervals for GGBS, metakaolin and recycled aggregate fractions were found to contain zero. These values were 0.843 for ordinary regression, and 0.844 for ridge regression in the validation set, respectively. Logarithmic age gave better prediction than did untransformed age; there was no improvement provided by the tested composition–age interaction. Similar predictive outcomes were generated using sensitivity analyses. These results justify the use of interpretable regression for estimating the strength variation under specific conditions in the laboratory. However, since the predictions are dependent on one another, and the composition is limited, there is a lack of interpretability until it is separately validated prior to general use.

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Published

2024-09-25