01660214

Component

Temperature can significantly affect the performance of asphalt pavements with thick asphalt layer (>30 cm). For a successful pavement design, it is vital to accurately predict pavement temperatures at various depths. However, most previous researches focused on conventional asphalt pavements, of which the asphalt thickness is less than 30 cm. Their proposed models are applicable in top layers, but may not be so effective for temperature predictions at deeper depths. As a result, the primary objective of this research was to develop a statistical model to predict temperatures at deep depths. Three test sites were selected and instrumented with a number of sensors and a data logger to record the pavement temperature hourly. Also, all test sections can provide meteorological monitoring to collect hourly air temperatures and hourly total solar radiation. The recorded meteorological conditions were found to have cumulative effect on the measured pavement temperatures at various depths. On basis of their relationship, a statistical regression was performed, and the temperature prediction model was determined as a function of depth, average air temperature and total solar radiation calculated in the cumulative time. For improvement of applicability, historical mean monthly air temperatures were also incorporated into the model. The improved model was validated by applying it to additional sites for which the measured pavement temperatures and meteorological data were available. Also, by comparing with existing models, the model was testified to be more effective for asphalt pavements with thick asphalt layer, promising its potential use.

This paper was sponsored by TRB committee AFD60 Standing Committee on Design and Rehabilitation of Asphalt Pavements. Alternate title: Statistical Temperature Prediction Models for Asphalt Pavement with Thick Asphalt Layer.

18-03435

English

18p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; Maps; References; Tables

Asphalt pavements; Atmospheric temperature; Depth; Mathematical models; Mathematical prediction; Solar radiation; Temperature; Test sections; Validation; Weather conditions

Asphalt layer thickness

Highways; Pavements

Transportation Research Board Annual Meeting 2018 Paper #18-03435

TRIS, TRB, ATRI

Jan 8 2018 10:50AM