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Review article

Asphalt Pavement Temperature Prediction Models: A Review

Ibrahim AdwanDepartment of Civil Engineering, Universiti Kebangsaan Malaysia, UKM, Bangi 43600, Selangor, MalaysiaAbdalrhman MiladDepartment of Civil Engineering, Universiti Kebangsaan Malaysia, UKM, Bangi 43600, Selangor, MalaysiaZubair Ahmed MemonDepartment of Engineering Management, College of Engineering, Prince Sultan University (PSU), Riyadh 11586, Saudi ArabiaIswandaru WidyatmokoDepartment of Civil Engineering, Universitas Pertamina, Daerah Khusus Ibukota Jakarta 12220, IndonesiaNuryazmin Ahmat ZanuriFundamental Engineering Studies Programme, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, MalaysiaNaeem Aziz MemonDepartment of Civil Engineering, Mehran University of Engineering & Technology, Jamshoro 76062, PakistanNur Izzi Md. YusoffDepartment of Civil Engineering, Universiti Kebangsaan Malaysia, UKM, Bangi 43600, Selangor, Malaysia
2021en
ABI

Abstract

The performance of bituminous materials is mainly affected by the prevailing maximum and minimum temperatures, and their mechanical properties can vary significantly with the magnitude of the temperature changes. The given effect can be observed from changes occurring in the bitumen or asphalt mixture stiffness and the materials’ serviceable life. Furthermore, when asphalt pavement layer are used, the temperature changes can be credited to climatic factors such as air temperature, solar radiation and wind. Thus in relevance to the discussed issue, the contents of this paper displays a comprehensive review of the collected existing 38 prediction models and broadly classifies them into their corresponding numerical, analytical and statistical models. These models further present different formulas based on the climate, environment, and methods of data collection and analyses. Corresponding to which, most models provide reasonable predictions for both minimum and maximum pavement temperatures. Some models can even predict the temperature of asphalt pavement layers on an hourly or daily basis using the provided statistical method. The analytical models can provide straight-forward solutions, but assumptions on boundary conditions should be simplified. Critical climatic and pavement factors influencing the accuracy of predicting temperature were examined. This paper recommends future studies involving coupled heat transfer model for the pavement and the environment, particularly consider to be made on the impact of surface water and temperature of pavements in urban areas.

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Cited by 30 references