Pavement temperature prediction: Theoretical models and critical affecting factors

Abstract

Pavement temperature field is driven by climatic factors such solar radiation, air temperature, wind, and among others. Accurate prediction of pavement temperature field is critical for pavement design, winter road maintenance, and near-surface microclimate environment. This paper provides a comprehensive review of existing models developed for predicting pavement temperature. The analytical models provide straightforward solutions but require simplified assumptions of boundary conditions. Finite Difference Method (FDM) and Finite Volume Method (FVM) can be superior to Finite element method (FEM) in terms of computational efficiency. However, FEM and FVM are considered better than FDM when dealing with the problems with complex geometries. The critical climatic and pavement factors affecting the accuracy of temperature prediction were discussed. The short-wave radiation at pavement surface can be either measured or calculated with solar constant and the location of sun. Convection coefficient is usually calculated with empirical equations involving wind velocity. The net long-wave radiation can be either calculated with the sky temperature, or use a different factor describing the pavement surface absorptivity for longwave radiation instead of pavement surface emissivity. The measured solar radiation and time-dependent wind speed should be used for pavement temperature prediction model. When calculating pavement surface energy exchange with empirical equations, calibration of parameters is highly recommended. Cautions should be taken when determining albedo and emissivity, with the consideration of pavement surface type (material) and condition (age). Thermal properties of pavement materials vary depending on thermal properties of each component and material composition. It is recommended that coupled heat transfer model for pavement and environment, consideration of surface water effect, and pavement temperature in urban areas need to be further studied.