Modeling adiabatic temperature rise during concrete hydration: A data mining approach

This paper presents a data mining approach for modeling the adiabatic temperature rise during concrete hydration. The model was developed based on experimental data obtained in the last thirty years for several mass concrete constructions in Brazil, including some of the hugest hydroelectric power plants in operation in the world. The input of the model is a variable data set corresponding to the binder physical and chemical properties and concrete mixture proportions. The output is a set of three parameters that determine a function which is capable to describe the adiabatic temperature rise during concrete hydration. The comparison between experimental data and modeling results shows the accuracy of the proposed approach and that data mining is a potential tool to predict thermal stresses in the design of massive concrete structures.

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