Determination of model inputs for coupled diffusion-kinetics aging model to characterize field aging gradient and evolution in asphalt pavements

ABSTRACT

The accurate characterisation of field aging in asphalt pavements is important to evaluate and predict pavement performance. The coupled diffusion-kinetics aging model (CDKAM) has been developed to analyse the field aging gradient in asphalt pavements by considering the combined effects of UV radiation and thermal conditions. However, the methodology to determine model inputs shall be refined, and this model also needs to be assessed for its efficacy in characterising the aging evolution of asphalt pavements. In this paper, the determination and optimisation of model inputs for CDKAM using the k-n power function are developed first. Then, CDKAM was used to analyse the evolution of the non-uniform aging gradient in asphalt pavements. The results showed that the inputs for CDKAM could be obtained and optimised from the k-n power function. CDKAM could well capture the non-uniform aging gradient and evolution in asphalt pavements. The back-calculated CDKAM inputs, such as diffusion coefficient ($\overline{D}$) and thermal source term ($\overline{TST}$), are time- and source-dependent parameters. The values of $\overline{D}$ and $\overline{TST}$ decrease as aging time increases when an asphalt binder becomes stiffer. Overall, CDKAM could work as an analytical aging model to characterise the aging evolution of non-uniform aging gradients in asphalt pavements .

KEYWORDS:

• Asphalt pavement
• aging model
• diffusion
• kinetics
• aging evolution

Acknowledgments

The contents of this paper and the statements made herein only reflect the views of the authors who are solely responsible for the facts and accuracy of the data presented herein. The authors would like to acknowledge the support from the California State University System Research, Scholarly & Creative Activities (RSCA) Grant Program on this work. Sincerely thank Dr. Fan Yin for discussing the work and providing invaluable comments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All data, models, and code generated or used during the study appear in the submitted article.

Additional information

Funding

This work was supported by California State University System Research, Scholarly & Creative Activities (RSCA ) Grant Program.