Study on Adiabatic Temperature Rise Reflecting Hydration Degree of Concrete

The thermal model and the relevant parameters of concrete are the most important issues to study the space-time characteristics of temperature field, which are also the theoretical foundation of temperature control and crack prevention for the mass concrete structures. In this research, the improved adiabatic temperature rise test is carried out, and the temperature variation of fly ash concrete is analyzed. Furthermore, a thermal model of concrete considering the hydration degree is established based on the existing achievements. Meanwhile, the thermal conductivity and specific heat of concrete are measured via three approaches: by treating the parameters as constant values, by computing the parameters as variables of the degree of hydration, and by back-analyzing the parameters through BP neural network. Finally, the thermal parameters determined by different methodologies are substituted into the thermal model, respectively, and the finite element analysis of the concrete specimen is performed. By comparing simulated temperatures with various measured results, it can be found that the numerical analysis results of parameters calculated by BP neural network are closest to the measured values in the whole curing ages. Therefore, BP neural network method is an effective way to calculate the thermal parameters, and BP inversion algorithm provides a new way for accurately study the temperature profile of mass concrete structures.