Prediction of time-dependent effects in concrete structures using early measurement data

The purpose of the present paper is to propose a method which uses early measurement data to reduce the uncertainty of the long-term prediction of time-dependent effects due to creep and shrinkage of concrete. Reduction of uncertainty of the long-term prediction of time-dependent effects is achieved using Bayesian statistical inference. In Bayesian statistics, prior prediction contains the uncertainties with regard to creep and shrinkage of concrete. Prior predictions of time-dependent effects due to creep and shrinkage of concrete are used with the information obtained from early measurement data to develop updated predictions. The results of numerical analyses show that the width of mean ± two standard deviations for updated predictions of time-dependent effects is less than half of that of mean ± two standard deviations for prior predictions. Therefore, the adoption of the approach developed in this study would reduce the uncertainty of prediction of time-dependent effects due to creep and shrinkage and greatly improve the long-term serviceability of concrete structures such as prestressed concrete bridges.