Moisture induced damage in Hot Mix Asphalt (HMA) mixture is a prevalent problem all over the world. It is one of the leading causes of premature failures in asphalt pavements and a significant concern to the paving industry. It is, therefore, necessary to identify mixes that are susceptible to moisture damage during the mix design process. Extensive research has been carried out by several researchers over the years to develop a reliable and practical laboratory test procedure that can simulate field moisture damage conditions and that can make predictions that are likely to correlate to field performance. However, it is inferred from literature that no single laboratory test method can accurately predict the moisture induced damage performance HMA mixtures. The objectives of the present study are to: Develop a framework that considers different test methods to predict the moisture induced damage of Hot Mix Asphalt (HMA); Develop a suitable machine learning method to achieve significantly high accuracy in predicting the moisture damage potential of Hot Mix Asphalt (HMA); and develop a tool (App) for use by practicing engineers to identify HMA mixes that are likely to be susceptible to moisture induced damage. A total of 35 in-plant produced asphalt mixtures with known field performance were sampled, and compacted in the laboratory, and the compacted samples were subjected to mechanical tests before and after moisture conditioning with the Moisture Induced Stress Tester (MiST). In addition, the effluent from the MiST was checked for Dissolved Organic Carbon (DOC) content and gradation of dislodged aggregates. Fourier-Transform Infrared Spectroscopy (FTIR) analysis of the asphalt extracted from HMA samples was performed to observe changes in the functional groups before and after the MiST test. Statistical analysis showed that seismic modulus and indirect tensile strength were effective in distinguishing poor-performing mixes from the well-performing mixes. Principal component analysis was conducted on the test data, and a reduced set of dimensions that were capable of explaining significant variance in the data was identified. The significant test properties were used to develop machine-learning models with two supervised classification approaches. The k-nearest neighbor model was found to be very accurate in differentiating the mixes. The use of MiST conditioning, specified physical tests, and machine learning methods are recommended for the identification of moisture-susceptible hot mix asphalt. Contribution of this Work The major contribution of this work is the creation of a framework or a system that combines appropriate test methods and suitable machine learning models to achieve high accuracy (84%) in predicting the moisture damage potential of Hot Mix Asphalt (HMA). A secondary contribution is that this study, for the first time, combines the principles of Artificial Intelligence (AI), in the form of Machine Learning (ML), with the field of pavement performance, specifically for the evaluation of mixes that are subjected to moisture damage. Finally, the work provides users with a highly accurate ML model as well as an app, which can be used and further improved.

Thesis (M.S.)--Auburn University, 2007. / Abstract. Vita. Includes bibliographic references (ℓ. 128-132)

This study investigated the influence of material properties on fatigue life through laboratory fatigue testing of eleven Superpave hot mix asphalt (HMA) mixtures in use at the Virginia Smart Road. Mixtures were sampled from the plant and produced in the laboratory to investigate the influence of production method. Specimens were cut from the in-situ pavement and compacted in the laboratory to evaluate the influence of compaction method. Third point beam fatigue testing was performed at 25ºC and 10Hz. Additional testing at frequencies of 1 Hz and 5Hz, and at 10 Hz including rest periods of 0.4sec and 0.9sec were performed for one mixture to explore the impact of frequency and rest periods. Analyses were performed on the strain-life relationships and predicted endurance strain limits for the mixtures. Investigation of strain-life relationships for several mixtures indicated that small differences in mixture volumetrics due to the production method have minimal impact on the laboratory fatigue performance of HMA. Comparisons of expected fatigue performance for one mixture indicated that shorter fatigue lives (under the same strain conditions) may be expected for laboratory-compacted specimens when compared to field-compacted specimens, despite visual observation of damage (surface cracking) in the field-compacted specimens. Testing performed on one mixture to determine the influence of different loading frequencies showed that fatigue life was independent of the requencies tested. Investigation of rest period inclusion indicated no differences in fatigue life for loading conducted at 10 Hz frequency and no rest period, 0.4sec rest period, or 0.9sec rest period. The evaluation of specimens cut from the in-situ pavement indicated that location within the lane and orientation did not significantly affect laboratory fatigue performance. The effect of aggregate size was considered; however, results were inconclusive. Using predictive strain-life fatigue equations, the benefits of polymer-modification of binders and use of SMA were shown for mixtures produced in the laboratory according to the job mix formula and to match the plant-produced volumetrics. Evaluation of the predicted fatigue strain endurance limit was performed using an energy-based and an empirical method. The energy method was shown to estimate significantly higher endurance limit strains for mixtures. / Ph. D.

Permeability of hot mix asphalt (HMA) is a property that is important to the pavement's durability. Measuring permeability along with density will give a better indication of a pavement's durability than density alone. The presence of water for extended periods of time in the pavement is directly linked to early deterioration. The first goal of this research is to study the anisotropic nature of hot mix asphalt permeability within the lab, which required the development of a horizontal permeameter. This method is inexpensive and suitable for a lab technician to use and analyze. A series of samples with different air void contents were used to observe how the ratio of vertical to horizontal permeability changes with air void content. The second goal was to develop a modified field permeameter to study the water-pavement contact area effect on field permeability. A reliable sealing system was created that is consistent and is not detrimental to the pavement surface. The results of the study show that larger contact areas yield increasing influence of vertical flow, which represents the one dimensional assumption of Darcy's Law falling head method. The third goal was to validate the results by simulating the field permeability test with a finite element model. A number of simulations with different permeability values and anisotropic permeability ratios were conducted. The horizontal and vertical flows were observed within the test area to analyze the flow pattern and influence of the directional permeability. The results matched the trends found in the field permeability study. / Master of Science

This study aims to understand intermingling process between rejuvenators and aged asphalt binders in reclaimed asphalt pavement (RAP) materials during RAP recycling operations in pavement construction. This study presents results of a laboratory study on the use of rejuvenators to recycle age hardened asphalt binders in RAP. Laboratory Hot Mix Asphalt (HMA) samples were prepared with RAP millings from one specific pavement and a commercial rejuvenator, with 80 to 90 percent RAP content. The following mixes with various amount of the rejuvenator were evaluated: a control mix prepared from burned RAP aggregate and virgin asphalt binder, another control mix prepared with heated RAP, a recycled RAP mix with 1% rejuvenator (at the weight of the total mix), a recycled RAP mix with 0.5% rejuvenator, and a recycled RAP mix with 0.5% rejuvenator and 0.5% virgin asphalt binder. Dynamic modulus test results of laboratory prepared samples were obtained for a range of temperatures over an eleven-week period of accelerated aging at 60ºC in an inert gas oven and a conventional convection oven. Accelerated aging protocol was used to evaluate the intermingling process associated with diffusion mechanism between the rejuvenator and aged asphalt binder while an argon inert gas oven provides an environment where oxidation-related ageing and hardening in rejuvenated asphalt binders can be eliminated. The dynamic modulus data of six distinct mixes were statistically analyzed and compared to the results reported in the literature for virgin and low percentage recycled mixes. Collected data suggest that the use of rejuvenator is a viable option for recycling HMA with high RAP material content.

Thesis(M.S.)--Auburn University, 2006. / Abstract. Vita. Includes bibliographic references.

Thesis(M.S.)--Auburn University, 2005. / Abstract. Vita. Includes bibliographic references (p.61-62).

Thesis--Auburn University, 2009. / Abstract. Vita. Includes bibliographical references (p. 148-153).

Thesis (Ph. D.)--Worcester Polytechnic Institute. / Keywords: Ndesign; Mix Design; Film Thickness; Low Volume Roads; VMA; Hot Mix Asphalt. Includes bibliographical references (p. 63-65).

Thesis (Ph. D.)--Worcester Polytechnic Institute. / Keywords: characterization; test protocol; finite element method; performance curve; thermocouple; rutting; strain gauge; MMLS3; fatigue; instrumentation. Includes bibliographical references (p. 117-119).