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A thermomechanical coupling between a hyper-viscoelastic tire and a representative pavement layer was conducted to assess the effect of various temperature profiles on the mechanical behavior of a rolling truck tire. The two deformable bodies, namely the tire and pavement layer, were subjected to steady-state-uniform and non-uniform temperature profiles to identify the significance of considering temperature as a variable in contact-stress prediction. A myriad of ambient, internal air, and pavement-surface conditions were simulated, along with combinations of applied tire load, tire-inflation pressure, and traveling speed. Analogous to winter, the low temperature profiles induced a smaller tire-pavement contact area that resulted in stress localization. On the other hand, under high temperature conditions during the summer, higher tire deformation resulted in lower contact-stress magnitudes owing to an increase in the tire-pavement contact area. In both conditions, vertical and longitudinal contact stresses are impacted, while transverse contact stresses are relatively less affected. This behavior, however, may change under a non-free-rolling condition, such as braking, accelerating, and cornering. By incorporating temperature into the tire-pavement interaction model, changes in the magnitude and distribution of the three-dimensional contact stresses were manifested. This would have a direct implication on the rolling resistance and near-surface behavior of flexible pavements.

Researchers have been studying wide-base tires for over two decades, but no evidence has been provided regarding the net benefit of this tire technology. In this study, a comprehensive approach is used to compare new-generation wide-base tires (NG-WBT) with the dual-tire assembly (DTA). Numerical modeling, prediction methods, experimental measurements, and environmental impact assessment were combined to provide recommendations about the use of NG-WBT. A finite element approach, considering variables usually omitted in the conventional analysis of flexible pavement was utilized for modeling. Five hundred seventy-six cases combining layer thickness, material properties, tire load, tire inflation pressure, and pavement type (thick and thin) were analyzed to obtained critical pavement responses. A prediction tool, known as ICT-Wide, was developed based on artificial neural networks to obtain critical pavement responses in cases outside the finite element analysis matrix. The environmental impacts were determined using life cycle assessment. Based on the bottom-up fatigue cracking, permanent deformation, and international roughness index, the life cycle energy consumption, cost, and green-house gas (GHG) emissions were estimated. To make the outcome of this research effort useful for state departments of transportation and practitioners, a modification to AASHTOWare is proposed to account for NG-WBT. The revision is based on two adjustment factors, one accounting for the discrepancy between the AASHTOware approach and the finite element model of this study, and the other addressing the impact of NG-WBT.