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Mid-America Transportation Center

Investigation of Asphalt Pavement Analyzer (APA) Testing Program in Nebraska


Researchers

  • Principal Investigator: Yong Rak Kim (ykim3@unl.edu (402)472-1727)
  • Project Status
    In Progress
    Sponsors & Partners
  • Nebraska Department of Roads
  • About this Project
    Brief Project Description & Background
    The Asphalt Pavement Analyzer (APA) has been widely used in many states as a straightforward method to evaluate Hot Mix Asphalt (HMA) rutting potential in mix design and Quality Control (QC)-Quality Assurance (QA) applications. The APA is more advantageous than other testing methods that have been proposed from Strategic Highway Research Program (SHRP) studies, because the APA testing and corresponding data analyses are relatively simple, rapid, and easy to perform. The primary objective of this research is to seek for better understanding and potential improvements of current APA testing program incorporated with Superpave specifications implemented in Nebraska. To this end, comprehensive literature review including careful investigations of APA data available from both Nebraska (approximately 4-year data) and other states will be conducted to find critical experimental factors affecting APA performance and to monitor sensitivity of APA results to mix design variables so that one can minimize currently-observed high testing variability and lack of correlations with actual field performance. Successful research will end up with a form of guidelines that can direct appropriate scope in use of APA techniques as a potential rutting performance-predicting indicator.
    Research Objective
    The primary objective of this research is to seek for better understanding and potential improvements of current APA testing program incorporated with Superpave specifications implemented in Nebraska.
    Potential Benefits
    Successful research will end up with a form of guidelines that can direct appropriate scope in use of APA techniques as a potential rutting, which will be beneficial to state DOTs.
    Abstract
    The Asphalt Pavement Analyzer (APA) has been widely used to evaluate hot-mix asphalt (HMA) rutting potential in mix design and quality control – quality assurance (QC-QA) applications, because the APA testing and its data analyses are relatively simple, rapid, and easy. However, as demonstrated in many studies and also experienced by the state of Nebraska, APA testing is in question due to its high testing variability and a lack of sufficient correlation with actual filed performance. The primary objective of this research was to find critical materials and/or mixture design factors affecting APA test results so as to eventually improve the current APA testing program in Nebraska. In addition to that, development of models to predict APA rut performance with given properties of HMA mixture ingredients and mixture design characteristics were also attempted. To find variables affecting APA rut results and the extent of these variables, SP-4 mixture data from Nebraska and HMA mixture data from Kentucky were statistically analyzed using the multiple linear regression method considering six factors (binder PG, aggregate gradation, nominal maximum aggregate size, aggregate angularity, air voids in mixture, and asphalt content in mixture) as probable candidates for significantly affecting APA rut results. For a detailed characterization of gradation effects, three indicators (gradation density, fineness modulus, and restricted zone) were considered and each of them was used for each statistical analysis. Results from analyses demonstrated that the binder PG was the only variable that always shows significant impact on APA rut results, which is in good agreement with other studies. Predicting models developed through the results of multiple linear regression analysis and the artificial neural network technique presented a relatively low level of model adequacy which can be observed by the coefficients of determination and cross-plots between predicted APA rut values and the measured APA rut data. More data would be helpful to confirm the findings from this research and also to develop a better prediction model.
    Project Amount
    $ 70,049