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Structural Engineering and Mechanics
  Volume 45, Number 6, March25 2013, pages 837-851

Prediction of compressive strength of concrete using multiple regression model
H.S. Chore and N.L. Shelke

    In construction industry, strength is a primary criterion in selecting a concrete for a particular application. The concrete used for construction gains strength over a long period of time after pouring the concrete. The characteristic strength of concrete is defined as the compressive strength of a sample that has been aged for 28 days. Neither waiting for 28 days for such a test would serve the rapidity of construction, nor would neglecting it serve the quality control process on concrete in large construction sites. Therefore, rapid and reliable prediction of the strength of concrete would be of great significance. On this backdrop, the method is proposed to establish a predictive relationship between properties and proportions of ingredients of concrete, compaction factor, weight of concrete cubes and strength of concrete whereby the strength of concrete can be predicted at early age. Multiple regression analysis was carried out for predicting the compressive strength of concrete containing Portland Pozolana cement using statistical analysis for the concrete data obtained from the experimental work done in this study. The multiple linear regression models yielded fairly good correlation coefficient for the prediction of compressive strength for 7, 28 and 40 days curing. The results indicate that the proposed regression models are effectively capable of evaluating the compressive strength of the concrete containing Portaland Pozolana Cement. The derived formulas are very simple, straightforward and provide an effective analysis tool accessible to practicing engineers.
Key Words
    concrete; compressive strength; admixture; regression analysis; predicted strength; predictive tools
H.S. Chore and N.L. Shelke: Department of Civil Engineering, Datta Meghe College of Engineering, Sector-3, Airoli, Navi Mumbai- 400 708, India

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