Viscoelastic finite element modeling of asphalt pavement behavior under overloaded traffic conditions

The performance of asphalt pavements is significantly reduced due to overloading of vehicles, leading to increased rutting and cracking, and costs of maintenance, especially in developing countries like Pakistan, where the limits of axle loadings are not well enforced. Local conditions, weak subgrades, variable materials and atypical traffic limit the use of conventional designs and point to the need of sophisticated mechanistic prediction tools. This study develops a validated three-dimensional (3D) viscoelastic finite element model (FEM) in Abaqus to assess pavement responses under overloaded traffic. The model features an improved rectangular-semicircular tire contact approximation that more closely represents real contact geometry than conventional circular assumptions, Prony series coefficients from uniaxial stress relaxation tests for time-dependent asphalt behavior, cyclic moving loads derived from axle load frequency distributions obtained through Weigh-in-Motion (WIM) monitoring on Pakistan's National Highway, with peak loads representing the most severe overloading events recorded across all vehicle classes and regionally calibrated layered properties. Validation against benchmarks achieved 95% agreement in stress distributions, deformations, and rut depths. Results show overloading markedly intensifies distress relative to legal loads. For 2-axle trucks, stress rises 157% and rutting depth 125%. The 3-axle configuration is the most damaging with 250% and 190% increase in stress and rutting, respectively. The coalescence of inter-axle stress bulbs results in continuous high-strain corridors, thus accelerating the time-dependent creep deformation in the linear viscoelastic framework. Four-axle configurations give the best redistribution and mitigation, with the benefits diminishing with more than four axles, as additional wheels redistribute, rather than reduce, the strains beyond the material limits, while rut accumulation continues. The results show that axle multiplication has its limits in terms of gross overloading. The model sets a solid foundation for forecasting distress in nascent networks, and suggests rigorous enforcement, targeted high strain maintenance and local data input to mechanistic-empirical designs to enhance resilience and sustainability.