Development and validation of a pavement temperature profile prediction model in a mechanistic-empirical design framework

An accurate temperature prediction tool is an important part of any mechanistic-empirical (M-E) pavement design and performance prediction method. In this paper, a one-dimensional finite control volume (FCV) model is introduced that predicts the temperature within a pavement structure as a function of time and depth. The main input data required for the model are continuous time series of air temperature for conductive heat transfer, solar radiation for radiative heat transfer, and wind speed for convective heat transfer. The heat balance equation for each control volume of the FCV model is solved using an implicit scheme. To validate the numerical model, comparisons were made to measured temperature data from four test sections in Sweden located in regions with different climatic conditions. A good agreement was obtained between the calculated and measured temperature values within the asphalt layer, and temperature in the granular layers with the values of the coefficient of determination R² ranging from 0.866 to 0.979. The model is therefore suitable to be implemented as a pavement temperature prediction tool in M-E design.