Evaluation of Selected Empirical Models for Asphalt Pavement Temperature Prediction in a Tropical Climate: The Case of Ghana

Abstract

Asphalt pavement temperature has several applications, including pavement structural design and evaluation, asphalt mixture design, asphalt binder grade determination and material aging characterization. However, available asphalt pavement temperature prediction models were mostly developed for temperate climatic conditions. Before such models are adopted for use in a tropical climate to facilitate advanced pavement engineering, their applicability must be verified. This study evaluated five empirical asphalt pavement temperature prediction models: the Lukanen (BELLS 3), Park, Diefenderfer, and Taamneh models, all developed in the United States, and the Asefzadeh model, formulated in Canada, to ascertain their prediction accuracy in a tropical climate, using the West African country Ghana as a case study. The results of such a model evaluation study will justify the adoption of existing models for local application or the development of new ones suitable for tropical climates. In this study, in situ asphalt pavement temperature data were measured at two sites for eight months: Kumasi and Tamale in the Forest and Savannah climatic zones, respectively. The measured pavement temperature data were compared with predicted pavement temperatures using the two independent-samples t-test, the coefficient of determination, the line of equality, and three error statistics (mean bias error, mean percentage error and root mean square error). It was found that the Park model provided a more accurate pavement temperature prediction in both climatic zones. The other models either over-predicted or under-predicted asphalt pavement temperature with significant error margins. However, there is a need to improve the prediction accuracy of the Park model as considerable over-prediction occurred at a temperature of at least 47 °C or a local model developed.