01506446

Component

https://doi.org/10.3141/2457-05

Performance-related specifications base pay rates on tests that measure and predict the performance of the mixture. This study evaluated several methods for predicting the rutting resistance of asphalt mixtures. The mixtures and field performance data came from the National Center for Asphalt Technology test track. The pavement sections evaluated were part of an experiment that focused on warm-mix asphalt, high-content reclaimed asphalt pavement (50%), and a combination of the two. One method involved using the dynamic moduli of the mixtures in confined and unconfined conditions. The ranking of the mixtures predicted from both conditions was good compared with the observed ranking from the track but was more reasonable with the confined data. These predictions were compared with common current tests such as the asphalt pavement analyzer and the Hamburg wheel tracker tests. From the ranking of rut depths, these tests did not appear able to distinguish subtler changes to material properties needed for a performance-related specification. Another method employed a viscoplastic shift model implemented within the layered viscoelastic continuum damage program to predict the rut depth. The predicted rut depths were biased 2.5 mm higher than those measured in the field when all three layers (175 mm) of asphalt were used to predict the rut depth, but the ranking matched the field quite well. The results from the top two layers (100 mm) of asphalt were less biased but were more variable than the three-layer results. The results suggest that all pavement layers should be evaluated for predicting rut depths, not just the top two layers.

01551907

14-0659

English

pp 41–50

2014

Transportation Research Record: Journal of the Transportation Research Board

9780309295444

Print

Figures (5) ; References (14) ; Tables (1)

Asphalt mixtures; Dynamic modulus of elasticity; Pavement layers; Pavement performance; Reclaimed asphalt pavements; Rutting; Test tracks; Warm mix paving mixtures

Highways; Materials; Pavements; I23: Properties of Road Surfaces; I31: Bituminous Binders and Materials

TRIS, TRB, ATRI

Jan 27 2014 2:18PM

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• Backcalculation of Asphalt Concrete Modulus Master Curve from Field-Measured Falling Weight Deflectometer Data: Using a New Time Domain Viscoelastic Dynamic Solution and Genetic Algorithm
• Backcalculation Procedure for Bonded Concrete Overlays of Asphalt Pavement
• Comparative Testing of Lasers for Ride Quality Measurement on Hot-Mix Asphalt Pavements
• Establishment of Relationship Between Pavement Surface Friction and Mixture Design Properties
• Evaluation of Widely Used Hydroplaning Risk Prediction Methods Using Florida’s Past Crash Data
• Incorporating Surface Microtexture in the Prediction of Skid Resistance of Flexible Pavements
• Influence of Aggregate Base Layer Variability on Pavement Performance
• Measurement of Pavement Roughness Using Android-Based Smartphone Application
• Pavement Raveling Detection and Measurement from Synchronized Intensity and Range Images
• Scaling Relationships of Dissipation-Induced Pavement–Vehicle Interactions
• Study of Cornering Maneuvers of a Pneumatic Tire on Asphalt Pavement Surfaces Using the Finite Element Method
• Subgrade and Foundation Dynamic Performance Evaluation by Means of Lightweight Deflectometer Tests
• Surface Drainage Evaluation for Rigid Pavements Using an Inertial Measurement Unit and 1-mm Three-Dimensional Texture Data