Asphalt Materials Characterization in Support of Implementation of the Proposed Mechanistic-empirical Pavement Design Guide

Report No: 07-CR10

Published in 2007

About the report:

The proposed Mechanistic-Empirical Pavement Design Guide (MEPDG) procedure is an improved methodology for pavement design and evaluation of paving materials. Since this new procedure depends heavily on the characterization of the fundamental engineering properties of paving materials, a thorough material characterization of mixes used in Virginia is needed to use the MEPDG to design new and rehabilitated flexible pavements. The primary objective of this project was to perform a full hot-mix asphalt (HMA) characterization in accordance with the procedure established by the proposed MEPDG to support its implementation in Virginia. This objective was achieved by testing a sample of surface, intermediate, and base mixes. The project examined the dynamic modulus, the main HMA material property required by the MEPDG, as well as creep compliance and tensile strength, which are needed to predict thermal cracking. In addition, resilient modulus tests, which are not required by the MEPDG, were also performed on the different mixes to investigate possible correlations between this test and the dynamic modulus. Loose samples for 11 mixes (4 base, 4 intermediate, and 3 surface mixes) were collected from different plants across Virginia. Representative samples underwent testing for maximum theoretical specific gravity, asphalt content using the ignition oven method, and gradation of the reclaimed aggregate. Specimens for the various tests were then prepared using the Superpave gyratory compactor with a target void in total mix (VTM) of 7% ± 1% (after coring and/or cutting). The investigation confirmed that the dynamic modulus test is an effective test for determining the mechanical behavior of HMA at different temperatures and loading frequencies. The test results showed that the dynamic modulus is sensitive to the mix constituents (aggregate type, asphalt content, percentage of recycled asphalt pavement, etc.) and that even mixes of the same type (SM-9.5A, IM-19.0A, and BM 25.0) had different measured dynamic modulus values because they had different constituents. The level 2 dynamic modulus prediction equation reasonably estimated the measured dynamic modulus; however, it did not capture some of the differences between the mixes captured by the measured data. Unfortunately, the indirect tension strength and creep tests needed for the low-temperature cracking model did not produce very repeatable results; this could be due to the type of extensometers used for the test. Based on the results of the investigation, it is recommended that the Virginia Department of Transportation use level 1 input data to characterize the dynamic modulus of the HMA for projects of significant impact. The dynamic modulus test is easy to perform and gives a full characterization of the asphalt mixture. Level 2 data (based on the default prediction equation) could be used for smaller projects pending further investigation of the revised prediction equation incorporated in the new MEPDG software/guide. In addition, a sensitivity analysis is recommended to quantify the effect of changing the dynamic modulus on the asphalt pavement design. Since low-temperature cracking is not a widespread problem in Virginia, use of level 2 or 3 indirect tensile creep and strength data is recommended at this stage.

Disclaimer Statement:The contents of this report reflect the views of the author(s), who is responsible for the facts and the accuracy of the data presented herein. The contents do not necessarily reflect the official views or policies of the Virginia Department of Transportation, the Commonwealth Transportation Board, or the Federal Highway Administration. This report does not constitute a standard, specification, or regulation. Any inclusion of manufacturer names, trade names, or trademarks is for identification purposes only and is not to be considered an endorsement.

Authors

Other Authors

Gerardo W. Flintsch, Amara Loulizi, Khaled A.  Galal

Last updated: November 25, 2023

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