This study presents a computational fracture modeling approach for predicting highly nonlinear viscoelastic cracking, such as fatigue damage, in asphalt mixtures and pavements. The modeling approach is presented and validated against field performance data from the FHWA-Accelerated Loading Facility (ALF) performance test sections. To that end, five mixtures differing either in the type of binder used or the amount of reclaimed asphalt pavement and reclaimed asphalt shingles were selected to assess their linear viscoelastic behavior, fracture properties, and field performance. A nonlinear viscoelastic cohesive zone fracture model was used along with a Gaussian distribution damage evolution to characterize the mixture fracture properties through a numerical-experimental calibration process. Individual mixture characteristics were then used as inputs to analyze the ALF pavement structure, and the fatigue response was predicted and compared with the field performance data for model validation. Although there are several model limitations to improve, the good agreement in performance rank order among test lanes demonstrates the capability and validity of the modeling approach. This implies that the computational modeling approach attempted in this study could potentially be used to analyze and design pavements in a mechanistic manner. This could be done with just a few laboratory tests for mixture properties such as viscoelastic dynamic modulus and cohesive zone fracture parameters.
Finite Element Modeling of FHWA-Accelerated Loading Facility Test Sections With Fatigue Damage Using a Nonlinear Viscoelastic Cohesive Zone Integrated With Gaussian Damage Evolution
Transportation Research Record: Journal of the Transportation Research Board
Transportation Research Record: Journal of the Transportation Research Board ; 2677 , 1 ; 1524-1537
2022-07-07
Article (Journal)
Electronic Resource
English
Transportation Research Record | 2002
|Performance Prediction of Louisiana Accelerated Loading Facility Test Sections
Transportation Research Record | 2000
|Performance Prediction of Louisiana Accelerated Loading Facility Test Sections
Online Contents | 2000
|