New theoretical framework for temperature-effect integration into asphalt concrete pavement life prediction with respect to Australian pavement conditions

Abstract

The aim of this study is to introduce a new theoretical framework for incorporating the effects of temperature fluctuations into current pavement design approaches by using the cumulative damage concept. Until now, the effective temperature (Teff ) concept, which can integrate the effects of seasonal or monthly temperature fluctuations within a given annual temperature into pavement design, has been utilised, in conjunction with the dynamic modulus (|E*) master curve to determine the representative modulus for an asphalt layer in pavement design. The effective temperature concept is then used to aid the prediction of an asphalt concrete pavement’s service life by assuming that the effective temperature is constant throughout a pavement design period (approximately 20–40 years). However, this assumption is not particularly valid in some countries such as Australia, where the effect of climate change can cause significant fluctuations in temperature during a given pavement design period. In this newly proposed framework, the current effective temperature concept is modified to obtain a so-called optimum effective temperature (TOPT ). From this, the effect of temperature fluctuations during a given design period can be taken into account by using statistically based methods. First, a pavement design scenario was established to demonstrate the new concept. Historical climate data from four study areas in Western Australia was taken and a 10 mm dense graded asphalt mix was used as the basis for pavement design inputs with local material properties and traffic data. Results indicated that optimum pavement design sections, determined according to the new framework considering temperature fluctuations, provided thinner and thicker pavement sections with the cumulative damages (D value) closer to 1 than those of the traditional design approach. The study outcome would result in a more reliable pavement life prediction, leading to saving in construction and maintenance costs.