Characterization of Permanent Deformation Using AMPT Repeated-Load-Triaxial and RSCH Tests for Mechanistic-Empirical Design and Practical Considerations

2016 ◽  
Vol 28 (12) ◽  
pp. 04016169 ◽  
Author(s):  
Yuan He ◽  
John Harvey ◽  
Junwen Zhou ◽  
Angela Liu
Author(s):  
Intikhab Haidar ◽  
Charles W. Schwartz ◽  
Sadaf Khosravifar

The past two decades have seen significant efforts to standardize a series of simplified test methods to characterize the dynamic modulus (DM) and repeated load permanent deformation (RLPD) performance characteristics of asphalt mixtures using the asphalt mixtures performance tester (AMPT). While the current AASHTO T 79 test specifications for the AMPT are faster and easier to perform than their preceding research grade test protocols, there is still reluctance among highway agencies and industry to conduct performance testing using the AMPT. One significant reason is the lengthy process of sample preparation and testing for the DM and RLPD tests. Two studies to expedite this process are reported here. First, the potential for abbreviating the DM testing procedure was examined. It provides the option to fully exclude testing at 40°C by adding an additional frequency of 0.01 Hz at 20°C. This approach reduces time for testing as well as for sample conditioning at high temperature. Second, the possibility of reducing the total number of required specimens was evaluated. The variation of the DM under repetitive testing and the appropriateness of performing the RLPD test on samples already tested for DM were evaluated. The results showed that specimen damage or densification because of DM testing is insignificant. As a consequence, DM test specimens can be re-used for RLPD testing, reducing the required number of samples from 12 to 9.


2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Wendel S. Cabral ◽  
Suelly H. A. Barroso ◽  
Samuel A. Torquato

The decreasing supply of soils with geotechnical parameters suitable for pavement designs is a visible problem in our environment. In order to establish more efficient designs and adequate construction criteria, it is essential to understand the performance of materials. This is a study of the permanent deformation (PD) of soil used in pavement layers, obtaining prediction models through the technique of artificial neural networks, in addition to the design of pavement structures using mechanistic-empirical and empirical methods. The multistage repeated load triaxial (RLT) test, as well as numerical analyses of stresses and displacements using the CAP3D program, was used. The results showed that both the test procedure and the prediction models performed satisfactorily in obtaining PD behavior. Moreover, designs using the methods adopted resulted in distinct structures, that is, thickness different from the granular pavement layers. It was concluded that the model and test procedure exhibit significant potential for characterizing and modeling the PD of granular materials.


Author(s):  
Kazi Moinul Islam ◽  
Sarah Gassman ◽  
Md Mostaqur Rahman

The resilient modulus (MR) of subgrade material is an important parameter in pavement design using the Mechanistic-Empirical Pavement Design Guide (MEPDG) and has a significant influence on pavement performance. MR can be obtained indirectly from falling weight deflectometer (FWD) data using a back-calculation tool (i.e., AASHTOWare 2017) or from empirical correlations with soil index properties. MR can also be obtained directly using repeated load triaxial tests (AASHTO T 307-99, 2017). In this study, the field test program included FWD tests and soil sampling. These field tests were performed on six asphalt pavement sections in South Carolina, U.S., to estimate the MR of the subgrade soil. This study involved extensive laboratory characterization of subgrade soils collected from underneath the pavement sections. Laboratory characterization included index tests (sieve analysis, Atterberg limits, specific gravity, moisture content, and standard Proctor density tests) on bulk samples and repeated load triaxial tests on thin-walled tube samples to obtain a direct measure of MR. Results show that the MR values found from the FWD data have similar trends to the laboratory-measured MR values. However, results from lab testing were 33%–75% lower than the back-calculated MR. Laboratory-measured MR, and back-calculated MR were used to determine a C-factor of 0.33, 0.25, and 0.29 for coarse-grained, fine-grained, and all types of soils, respectively. This parameter can be used to estimate resilient modulus for MEPDG Level 2 design inputs across South Carolina and similar geologic regions. The research studies will be facilitated by the local calibration and implementation of the MEPDG.


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