Framework to Improve the Pavement ME Design Unbound Aggregate Rutting Model by Using Field Data

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The AASHTOWare Pavement ME Design and the Guide for Mechanistic–Empirical Design of New and Rehabilitated Pavement Structures provide a methodology for analyzing response and predicting rutting performance of unbound granular pavement layers. However, this methodology has been reported to have low sensitivity to the properties of the base and subbase and the subgrade. The primary objective of this paper is to provide a framework for improving the prediction ability of the Pavement ME Design rutting model for unbound aggregate pavement layers. This goal was achieved by using accelerated testing data from full-scale pavement test sections constructed with different aggregate materials. These test sections were loaded to failure by using the accelerated transportation loading assembly at the University of Illinois. Nonlinear finite element solutions of the pavement test sections were studied so that stress-dependent modulus characterization models could be used for the anisotropic unbound aggregate base and isotropic subgrade. This approach enabled prediction of realistic stress states and accurate pavement responses. Realistic stress states and the use of a shear stress ratio concept were incorporated into the proposed framework needed to improve the rutting predictions of the Pavement ME Design damage model. Finally, a definite correlation appeared to exist between shear stress ratio values and the shift factors that were proposed for the adjustment of the model’s predicted rut depths so they would match the field-measured performance trends. The framework studied in this paper is applicable to the three-parameter Tseng–Lytton rutting model, the original version of the Pavement ME Design damage model, for the modifications needed to generate improved granular layer rut predictions throughout pavement design service life.