Modeling the surface stored thermal energy in asphalt concrete pavements

Abstract

Regression analysis is used to develop models for minimal daily pavement sur-face temperature, using minimal daily air temperature, day of the year, wind speed and solar radiation as predictors, based on data from Awbari, Libya. Re-sults were compared with the existing SHRP and LTPP models. This paper also presents the models to predict surface pavement temperature depending on the days of the year using neural networks. Four annual periods are defined and new models are formulated for each period. Models using neural networks are formed on the basis of data gathered on the territory of the Republic of Serbia and are valid for that territory.