Calibration of pavement ME rutting model for geogrid stabilized roadways

Abstract

Many transportation agencies started implementing Mechanistic-Empirical (ME) approach for designing and analyzing new and rehabilitated pavements. Although the widely popular empirical design approach based on 1993 AASHTO Design Guide is still in practice, the need for performance-based design and accurate prediction of pavement distresses throughout the service life led to the adoption of the ME approach. The two major steps associated with the ME approach are the computation of pavement stress–strain responses using mechanistic analysis and estimation of pavement distresses using empirical analysis. Layered Elastic Analysis (LEA) or Finite Element Analysis (FEA) is normally utilized for mechanistic analysis whereas regression analysis is typically used for empirical analysis. Although the empirical models (i.e., transfer functions) were calibrated using the Long Term Pavement Performance (LTPP) dataset, these models do not consider the benefits of geogrid stabilization. Research and field studies had shown improvement in pavement performance when the pavement is stabilized with geogrids. This paper aims at incorporating the effect of geogrid in one of the distress models – more specifically, the rutting model – of AASHTOWare Pavement ME. Model calibration factors were developed based on the recent full-scale accelerated pavement test conducted at the research facility of the US Army Corps of Engineers. Two types of punched and drawn triangular aperture geogrids were utilized in the full-scale test. Pavement surface deformations measured during the trafficking period were used for calibrating the rutting model. The calibrated rutting model was validated with the LTPP and Louisiana Transportation Research Center (LTRC) dataset.