Towards an improved prediction of asphalt pavement rutting through thermal-mechanical coupled constitutive modelling

ABSTRACT

To predict accurately the evolution of asphalt pavement rutting, an advanced numerical modelling process was proposed and successfully implemented through the finite element software ABAQUS. In the process, a thermal-visco-elastic-plastic constitutive model for asphalt mixture was derived into numerical form and compiled using the user-defined material subroutine (UMAT). To apply realistic traffic loading, a mathematical form of loading model was proposed according to the tire-pavement interaction and realised through the user-defined load subroutine (DLOAD). Besides, a heat transfer model was calculated before the mechanical calculation, and the results of the pavement temperature field were used as the boundary condition for the mechanical calculation. A few case simulations were conducted using the numerical process and the results indicate that the severe rutting at pavement intersections or parking lots is due to not only the longer loading time but also the deeper plastic deformation region. In addition, the numerical model is capable of quantitatively identifying the critical temperature at which the pavement rutting starts to grow rapidly; accordingly, a new criterion for taking strategies to avoid or slow down the rutting distress of the pavement can be proposed, which is of great significance for the practice.

KEYWORDS:

• Visco-elastic
• visco-plastic
• rutting
• temperature field
• nonlinear traffic load

Disclosure statement

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

Additional information

Funding

The authors would like to acknowledge the financial support provided by National Natural Science Foundation of China (grant number 51878164, 51922030, 52208430), Natural Science Foundation of Jiangsu Province (SBK2021042206), Research Development Project by Department of Transportation of Shandong Province [grant number 2018B51,2020B63]; National Key Research and Development Program of China [grant number SQ2020YFA070207].