Non-linear models for the prediction of specified design strengths of concretes development profile

Different concrete structures are designed according to their concrete strength requirements. Consequently, concrete strength is one of the prime properties of concrete structures. In this study, compressive strength behavioral pattern of seven design strength concretes 21 MPa, 24 MPa, 28 MPa, 31 MP...

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Bibliographic Details
Main Authors: M. Aminul Haque, Md. Rasel-Ul-Alam
Format: Article
Language:English
Published: Taylor & Francis Group 2018-08-01
Series:HBRC Journal
Online Access:http://www.sciencedirect.com/science/article/pii/S1687404816300153
Description
Summary:Different concrete structures are designed according to their concrete strength requirements. Consequently, concrete strength is one of the prime properties of concrete structures. In this study, compressive strength behavioral pattern of seven design strength concretes 21 MPa, 24 MPa, 28 MPa, 31 MPa, 35 MPa, 38 MPa and 42 MPa at curing ages of 3, 7, 14, 21, 28, 56, 90 and 180 days was examined. In order to evaluate the long term effects on compressive strength of target design concretes, 360 cylindrical samples were cast. On the basis of the existing experimental tested strength data, a polynomial equation based model having 2 degrees with fractional power of 0.5 degree interval of each term was found to have acceptable correlation for describing the compressive strength gaining profile with the tested concrete ages. Correlation of proposed model was justified against the statistical point of view for examining the best fit profile with the observations. Apart from the correlation approach, the accuracy of the proposed model was validated with corresponding experimental observations of target design concretes followed by the model parameters estimation with 95% confidence interval. From the predicted results, the study revealed that proposed polynomial equation based model possessed strong potential for predicting 3, 7, 14, 21, 28, 56, 90 and 180 days compressive strength of design concretes with high accuracy and trivial error rates. Keywords: Compressive strength, Strength prediction, Model correlation, Model validation
ISSN:1687-4048