Lessons Learned from the Application of the CalME Asphalt Fatigue Model to Experimental Data from the CEDEX Test Track

Predicting asphalt fatigue evolution in the field is difficult. Very few models are effective for this complex process, and even less where actual damage levels, determined from structural evaluations, can be efficiently incorporated to improve previous performance predictions. One model evaluated, CalME (California Mechanistic-Empirical Software for Structural Design of Flexible Pavements), incorporates an incremental-recursive procedure based on mechanistic-empirical principles and was used to study and reproduce the deterioration process at the CEDEX Test Track. Experimental data for this evaluation came from four full-depth pavements tested over 28 months at the track, during which bearing capacity and surface cracking data was collected. This provided detailed information regarding asphalt layer deterioration under changing environmental conditions. Special attention was paid to the accumulation of damage as a function of loads and temperature and how this damage, together with aging and post-compaction under traffic, determine the stiffness of the asphalt layer. This paper presents experimental evidence that supports the ability of the CalME model to reproduce the main aspects of asphalt performance in flexible pavements and to predict future asphalt mixture performance, after recalibration from field data. The model was initially calibrated from laboratory fatigue tests and later recalibrated based on FWD tests conducted at an early stage of the deterioration process. After this early recalibration, the model was able to predict future asphalt layer deterioration until an ultimate damage level was reached.