Characterization and prediction of permanent deformation properties of unbound granular materials for Pavement ME Design. (30th November 2017)

• Record Type: Journal Article
• Authors: Gu, Fan; Zhang, Yuqing; Luo, Xue; Sahin, Hakan; Lytton, Robert L.
• Is Part Of: Construction & building materials. Volume 155(2017)
• Page Start: 584
• Page End: 592
• Publication Date: 2017-11-30
• Subjects: Unbound granular material -- Permanent deformation -- Performance prediction -- Pavement ME Design; Building materials -- Periodicals; 624.18
• DOI: 10.1016/j.conbuildmat.2017.08.116
• Languages: English
• ISSNs: 0950-0618

Abstract

Highlights: Morphological properties are correlated to the permanent deformation behavior of UGM. A series of performance-related base course properties are identified. The permanent deformation of UGM are accurately predicted by the developed models. The prediction accuracy of the developed models are validated. Abstract: The objective of this study is to characterize and predict the permanent deformation properties of unbound granular materials (UGMs) for Pavement ME Design. First, laboratory repeated load triaxial (RLT) tests are conducted on the UGMs from 11 quarries in Texas to measure the permanent strain curves. The shakedown theory is applied to evaluate the permanent deformation behavior of the selected UGMs. It is found that using Werkmeister's criteria to define the shakedown range boundaries is not suitable for the selected UGMs. Under this circumstance, new criteria are proposed to redefine the shakedown range boundaries for the flexible base materials in Texas. The new criteria are consistent with the current Texas flexible base specification in terms of aggregate classification. Second, the mechanistic-empirical design guide (MEPDG) model is used to determine the permanent deformation properties of the selected UGMs on the basis of the measured permanent strain curves. The determined permanent deformation properties are assigned as target values for the development of permanent deformation prediction models. Third, a series of performance-related base course properties are used to comprehensively characterize the UGMs, which include the dry density, moisture content, aggregate gradation, morphological properties, percent fines content, and methylene blue value. These performance-related base course properties are assigned as the inputs of the permanent deformation prediction models. Fourth, a multiple regression analysis is conducted to develop the prediction models for permanent deformation properties using these performance-related properties. The developed models are capable of accurately predicting the permanent deformation properties of UGMs. Compared to other prediction models (e.g., simple indicators-based models and Pavement ME Design models), the developed models have the highest prediction accuracy. It is also found that the Pavement ME model-predicted permanent strains are much lower than those measured from the RLT tests. This demonstrates that the current Pavement ME Design software substantially underestimates the rutting that occurs in base course. Finally, the developed prediction models are validated by comparing the predicted and measured permanent strains of other four base materials. The obtained R-squared value of 0.81 indicates that the developed models have a desirable accuracy in the prediction of permanent deformation properties of UGMs.