CIAM-UTC-REG36
Research Team
PI: Linbing Wang, Virginia Polytechnic Institute and State University
Co-PI: Shihui Shen, Penn State Altoona
Funding Sources
Virginia Tech Federal Share: $66,022
Virginia Tech Match Share $66,022
Penn State Altoona Federal Share: $63,898
Penn State Altoona Match: $63,979
Total Project Cost: $259,921
Agency ID or Contract Number
69A3551847103
Start and End Dates
03/03/2021 — 03/02/2023
Project Description
Objectives: The proposed research will develop an innovative method to use Inverse Approach to characterize three fundamental properties (the elastic modulus, the yielding strength, and an internal loading transfer parameter to represent mastics-aggregate skeleton interaction). These three parameters represent the rutting resistances of asphalt so that different scales of simulative tests and SPT tests can have a common basis for comparison and evaluation purposes.
Significance: Simulative tests have complicated contact and boundary conditions. It is hard to calculate fundamental material properties such as modulus and yielding strength from simulative tests. Nevertheless, there are about 1500 units of simulative testing devices in the world. A method to calculate fundamental material properties such as modulus and yielding strength will significantly enhance the capability of simulative testing and have important impacts on the paving industry by saving testing costs, better screening problematic mixes, and more accurately predicting mix performances.
Potential Impacts on State of Practice: Due to the non-representative specimen stress-strain field of simple performance tests, the SPT test results have limitations in that models using SPT test results do not realistically predict the performance of asphalt pavement in the field. Simulative tests are traditionally used as a pass-fail test to evaluate asphalt mixes before they can be used for construction projects. If fundamental material properties can be calculated from simulative tests, the evaluations of mix designs can be integrated into pavement design by supplying the required parameters characterized from simulative tests for pavement design.