Calibration and validation of a rutting model based on shear stress to strength ratio for asphalt pavements. (15th September 2017)

• Record Type: Journal Article
• Authors: Kim, Won Jae; Le, Van Phuc; Lee, Hyun Jong; Phan, Huy Thien
• Is Part Of: Construction & building materials. Volume 149(2017)
• Page Start: 327
• Page End: 337
• Publication Date: 2017-09-15
• Subjects: Rutting model -- Shear stress -- Shear strength -- Asphalt pavement -- Cohesion -- Internal friction angle; Building materials -- Periodicals; 624.18
• DOI: 10.1016/j.conbuildmat.2017.05.053
• Languages: English
• ISSNs: 0950-0618

Abstract

Highlights: A rutting model in power law form was proposed. The model considers shear stress to strength ratio. Predictive equations for cohesion (c) and internal friction angle (ϕ) were developed. A rutting model was calibrated and validated using field rutting data. The model accurately estimate rut depths under varying load and environmental conditions. Abstract: In this study, a rutting model in power law form was proposed considering the shear stress to strength ratio which can be calculated in terms of cohesion (c) and internal friction angle (ϕ) for different asphalt mixtures. Predictive equations for c and ϕ were first developed from laboratory testing at a reference temperature of 50 °C using multiple regression analyses considering asphalt binder, aggregate and volumetric properties of different asphalt mixes. The predictive c and ϕ equations were found to have correlation coefficients of 0.87 and 0.86 respectively. The rutting model considers the number of load cycles (N), shear strength ratio, temperature and load duration as main parameters of the permanent strain wherein the coefficients were determined using tri-axial compressive strength and repeated load permanent deformation testing. It was calibrated using field rutting data from twenty-six Westrack pavement sections. Moreover, the rutting model was validated using field performance data obtained from Korean national highways' long term pavement performance database. It was found from the validation that the model can accurately estimate rut depths under varying load and environmental conditions in the fields.