PREDICTING COMPRESSIVE STRENGTH OF CONCRETE FOR VARYING WORKABILITY USING REGRESSION MODELS
Author(s) -
Palika Chopra,
Rajendra Kumar Sharma,
Maneek Kumar
Publication year - 2014
Publication title -
international journal of engineering and applied sciences
Language(s) - English
Resource type - Journals
eISSN - 1309-7997
pISSN - 1309-0267
DOI - 10.24107/ijeas.251233
Subject(s) - compressive strength , regression analysis , linear regression , curing (chemistry) , cement , predictive modelling , materials science , nonlinear regression , statistics , mathematics , composite material
A mathematical analysis, using statistical techniques, for prediction of compressive strength of concrete was performed for the concrete strength data obtained from experimental work conducted under standard conditions in the laboratory. The data on compressive strength was obtained separately for concrete mixes proportioned for medium and high workability. The variables used in the prediction models were the mix proportioning elements, which include water-cement ratio, aggregates to cement ratio, etc. The multiple non-linear regression models developed in this work yielded excellent CODs for prediction of compressive strength at different curing ages (28, 56 and 91 days). The regression model developed for experimental data was compared with those developed by other researchers as well. In general, it was found that both the models developed as a part of this study could predict the compressive strength at 28 and 91 days with more than 95% accuracy. Also, it can be concluded that for better prediction 91 days strength for both medium and high workability mixes, it is desirable to consider the 28 and 56 days strengths in the regression equations
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