Mechanistic Modeling to Evaluate Structural Performance of Bituminous Pavements with Inelastic Deformation and Fatigue Damage of Mixtures
- Additional Document Info
- View All
© 2016 American Society of Civil Engineers. This study modeled structural performance of bituminous pavements with inelastic deformation and fatigue damage. Two major distresses, namely rutting and fatigue damage, of typical bituminous pavements were modeled by extending the pavement analysis using nonlinear damage approach (PANDA), a recently-developed finite-element approach to model damage-associated pavement performance, by incorporating main features in the PANDA with a fracture mechanics approach so as to improve the capability in predicting rate-dependent localized behavior of bituminous mixtures in pavement structures. More specifically, the Schapery's nonlinear viscoelasticity and Perzyna-type viscoplasticity featured in the PANDA were used to characterize recoverable and irrecoverable deformation of bituminous paving mixtures, and damage of bituminous mixtures due to multiple microscale and macroscale cracks was characterized using the cohesive zone fracture law, which was incorporated with a relevant fracture test such as a semicircular bend test. To apply the modeling approach to real structures, laboratory tests with two typical bituminous mixtures were conducted to characterize the material properties necessary for the model. Then, model simulation results presenting the two primary structural damage modes, rutting and fatigue cracking, were compared to actual monitored field performance. Simulation results demonstrated that the model can successfully account for the effect of key design variables such as paving materials, structural layer configuration, loading condition, and environmental conditions (such as temperature) on the pavement performance with damage. This implies the potential power and efficacy of this mechanistic modeling approach for the analysis and design of bituminous materials and pavement structures.
author list (cited authors)
You, T., Im, S., Kim, Y., & Little, D. N.