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Influence of Subgrade Resilient Modulus Selection Methodology on AASHTOWare Pavement ME Design
The resilient modulus (MR) value that is selected to represent the subgrade soil layer in a pavement layer profile significantly influences the predicted pavement performance using the new guide for AASHTOWare pavement mechanistic-empirical design (PMED). MR can be measured through non-destructive field tests [i.e., falling weight deflectometer (FWD)] or laboratory repeated triaxial load tests on remolded or undisturbed samples. In this study, FWD tests were performed on 11 asphalt pavement sections across the state of South Carolina to estimate the MR of the subgrade soil using the AASHTOWare 2017 back-calculation tool. Undisturbed samples were extracted from the same pavement locations using a thin-walled Shelby tube, and tested in the laboratory using AASHTO T307-99 to obtain the MR. Index tests (sieve analysis, Atterberg limits, specific gravity, moisture content, and standard Proctor density tests) were performed to obtain PMED Level 1 design input parameters. A correlation was developed between the FWD back-calculated MR and laboratory-measured MR to facilitate an estimate of MR (using a C-factor) for PMED Level 2 design inputs for South Carolina and similar geologic regions. The influence of the subgrade modulus selection methodology was evaluated by comparing the pavement performance results from PMED trial designs using MR found by four different methods.
Influence of Subgrade Resilient Modulus Selection Methodology on AASHTOWare Pavement ME Design
The resilient modulus (MR) value that is selected to represent the subgrade soil layer in a pavement layer profile significantly influences the predicted pavement performance using the new guide for AASHTOWare pavement mechanistic-empirical design (PMED). MR can be measured through non-destructive field tests [i.e., falling weight deflectometer (FWD)] or laboratory repeated triaxial load tests on remolded or undisturbed samples. In this study, FWD tests were performed on 11 asphalt pavement sections across the state of South Carolina to estimate the MR of the subgrade soil using the AASHTOWare 2017 back-calculation tool. Undisturbed samples were extracted from the same pavement locations using a thin-walled Shelby tube, and tested in the laboratory using AASHTO T307-99 to obtain the MR. Index tests (sieve analysis, Atterberg limits, specific gravity, moisture content, and standard Proctor density tests) were performed to obtain PMED Level 1 design input parameters. A correlation was developed between the FWD back-calculated MR and laboratory-measured MR to facilitate an estimate of MR (using a C-factor) for PMED Level 2 design inputs for South Carolina and similar geologic regions. The influence of the subgrade modulus selection methodology was evaluated by comparing the pavement performance results from PMED trial designs using MR found by four different methods.
Influence of Subgrade Resilient Modulus Selection Methodology on AASHTOWare Pavement ME Design
Islam, Kazi Moinul (author) / Gassman, Sarah L. (author)
Geo-Congress 2022 ; 2022 ; Charlotte, North Carolina
Geo-Congress 2022 ; 192-204
2022-03-17
Conference paper
Electronic Resource
English
Influence of Subgrade Resilient Modulus Selection Methodology on AASHTOWare Pavement ME Design
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