Evaluation of Hot Mix Asphalt Moisture Sensitivity Using the Nottingham Asphalt Test Equipment, TR-555, 2010

Pavements are subjected to different stresses during their design lives. A properly designed pavement will perform adequately during its design life, and the distresses will not exceed the allowable limits; however, there are several factors that can lead to premature pavement failure. One such factor is moisture sensitivity. AASHTO T 283 is the standard test used in the moisture susceptibility evaluation of asphalt mixtures, but the results of the test are not very representative of the expected behavior of asphalt mixtures. The dynamic modulus test measures a fundamental property of the mixture. The results of the dynamic modulus test can be used directly in the Mechanistic-Empirical Pavement Design Guide (MEPDG) and are considered a very good representation of the expected field performance of the mixture. Further research is still needed to study how the dynamic modulus results are affected by moisture. The flow number test was studied in previous research as a candidate test for moisture-susceptibility evaluation, but the results of that research were not favorable. This research has four main objectives. The first objective of this research is to evaluate the usefulness of the dynamic modulus and flow number tests in moisture-susceptibility evaluation. The second objective is to compare the results to those achieved using the AASHTO T 283 test. The third objective is to study the effect of different methods of sample conditioning and testing conditions. The fourth objective of the research is to study the variability in the test results.

Pavement Thickness Design for Local Roads in Iowa, TR-586, 2010

Three pavement design software packages were compared with regards to how they were different in determining design input parameters and their influences on the pavement thickness. StreetPave designs the concrete pavement thickness based on the PCA method and the equivalent asphalt pavement thickness. The WinPAS software performs both concrete and asphalt pavements following the AASHTO 1993 design method. The APAI software designs asphalt pavements based on pre-mechanistic/empirical AASHTO methodology. First, the following four critical design input parameters were identified: traffic, subgrade strength, reliability, and design life. The sensitivity analysis of these four design input parameters were performed using three pavement design software packages to identify which input parameters require the most attention during pavement design. Based on the current pavement design procedures and sensitivity analysis results, a prototype pavement design and sensitivity analysis (PD&SA) software package was developed to retrieve the pavement thickness design value for a given condition and allow a user to perform a pavement design sensitivity analysis. The prototype PD&SA software is a computer program that stores pavement design results in database that is designed for the user to input design data from the variety of design programs and query design results for given conditions. The prototype Pavement Design and Sensitivity Analysis (PA&SA) software package was developed to demonstrate the concept of retrieving the pavement design results from the database for a design sensitivity analysis. This final report does not include the prototype software which will be validated and tested during the next phase.

Investigation of AASHTOWare Pavement ME Design/DARWin-ME Performance Prediction Models for Iowa Pavement Analysis and Design, 2015

The Mechanistic-Empirical Pavement Design Guide (MEPDG) was developed under National Cooperative Highway Research Program (NCHRP) Project 1-37A as a novel mechanistic-empirical procedure for the analysis and design of pavements. The MEPDG was subsequently supported by AASHTO’s DARWin-ME and most recently marketed as AASHTOWare Pavement ME Design software as of February 2013. Although the core design process and computational engine have remained the same over the years, some enhancements to the pavement performance prediction models have been implemented along with other documented changes as the MEPDG transitioned to AASHTOWare Pavement ME Design software. Preliminary studies were carried out to determine possible differences between AASHTOWare Pavement ME Design, MEPDG (version 1.1), and DARWin-ME (version 1.1) performance predictions for new jointed plain concrete pavement (JPCP), new hot mix asphalt (HMA), and HMA over JPCP systems. Differences were indeed observed between the pavement performance predictions produced by these different software versions. Further investigation was needed to verify these differences and to evaluate whether identified local calibration factors from the latest MEPDG (version 1.1) were acceptable for use with the latest version (version 2.1.24) of AASHTOWare Pavement ME Design at the time this research was conducted. Therefore, the primary objective of this research was to examine AASHTOWare Pavement ME Design performance predictions using previously identified MEPDG calibration factors (through InTrans Project 11-401) and, if needed, refine the local calibration coefficients of AASHTOWare Pavement ME Design pavement performance predictions for Iowa pavement systems using linear and nonlinear optimization procedures. A total of 130 representative sections across Iowa consisting of JPCP, new HMA, and HMA over JPCP sections were used. The local calibration results of AASHTOWare Pavement ME Design are presented and compared with national and locally calibrated MEPDG models.