Concrete undergoes time-dependent deformations that must be considered in the design of reinforced/prestressed high-performance concrete (HPC) bridge girders.In this research,experiments on the creep and shrinkage properties of a HPC mix were conducted for 500 days.The test results obtained from this research were compared to different models to determine which model was the better one.The CEB-90 model was found better in predicting time-dependent strains and deformations for the above HPC mix.However,in a far zone,some deviation was observed,and to get a better model,the experimental data base was used along with the CEB-90 model database to train the neural network.The developed Artificial Neural Network (ANN) model will serve as a more rational as well as computationally efficient model in predicting creep coefficient and shrinkage strain.
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