Filtering by
- All Subjects: Transportation
- All Subjects: dynamic modulus
- All Subjects: Thermoplastic composites
- Genre: Academic theses
- Genre: Masters Thesis
- Creators: Mamlouk, Michael
- Member of: Theses and Dissertations
Asphalt concrete is the most recycled material in the United States and its reclamation allows the positive reuse of the constituent aggregates and asphalt binder, contributing to the long-term sustainability of the transportation infrastructure; decreasing costs, and the total energy and greenhouse emissions embodied into new materials and infrastructure. Although the national trends in Reclaimed Asphalt Pavements (RAP) usage are encouraging, the environmental conditions in Phoenix, Arizona are extreme and needs further consideration.
The objective of this research study was to evaluate the viability of using RAP in future pavement maintenance and rehabilitation projects for the City. Agencies in the State of Arizona have been slow adopting the use of RAP as a regular practice. While the potential benefits are great, there is some concern on the impact to long-term pavement performance.
RAP millings were sampled from the city’s stockpiles; processed RAP and virgin materials were provided by a local plant. Two asphalt binders were used: PG 70-10 and PG 64-16. RAP variability was evaluated by aggregate gradations; extracted and recovered binder was tested for properties and grading.
A mixture design procedure based on the City’s specifications was defined to establish trial blends. RAP incorporation was based on national and local practices. Four different RAP contents were studied 10%, 15%, 25%, and 25% content with a softer binder, in addition to a control mix (0% RAP).
Performance tests included: dynamic modulus to evaluate stiffness; Flow Number, to assess susceptibility for permanent deformation (rutting); and Tensile Strength Ratio as a measure of susceptibility to moisture damage.
Binder testing showed very stiff recovered asphalts and variable contents with a reasonable variability on aggregate gradations. Performance test results showed slightly higher modulus as RAP content increases, showing a slight improvement related to rutting as well. For moisture damage potential, all mixtures performed well showing improvement for RAP mixtures in most cases.
Statistical analysis showed that 0%, 10%, 15% and 25% with softer binder do not present significant statistical difference among mixtures, indicating that moderate RAP contents are feasible to use within the City paving operations and will not affect greatly nor negatively the pavement performance.
The objective of the research is to test the use of 3D printed thermoplastic to produce fixtures which affix instrumentation to asphalt concrete samples used for Simple Performance Testing (SPT). The testing is done as part of materials characterization to obtain properties that will help in future pavement designs. Currently, these fixtures (mounting studs) are made of expensive brass and cumbersome to clean with or without chemicals.
Three types of thermoplastics were utilized to assess the effect of temperature and applied stress on the performance of the 3D printed studs. Asphalt concrete samples fitted with thermoplastic studs were tested according to AASHTO & ASTM standards. The thermoplastics tested are: Polylactic acid (PLA), the most common 3D printing material; Acrylonitrile Butadiene Styrene (ABS), a typical 3D printing material which is less rigid than PLA and has a higher melting temperature; Polycarbonate (PC), a strong, high temperature 3D printing material.
A high traffic volume Marshal mix design from the City of Phoenix was obtained and adapted to a Superpave mix design methodology. The mix design is dense-graded with nominal maximum aggregate size of ¾” inch and a PG 70-10 binder. Samples were fabricated and the following tests were performed: Dynamic Modulus |E*| conducted at five temperatures and six frequencies; Flow Number conducted at a high temperature of 50°C, and axial cyclic fatigue test at a moderate temperature of 18°C.
The results from SPT for each 3D printed material were compared to results using brass mounting studs. Validation or rejection of the concept was determined from statistical analysis on the mean and variance of collected SPT test data.
The concept of using 3D printed thermoplastic for mounting stud fabrication is a promising option; however, the concept should be verified with more extensive research using a variety of asphalt mixes and operators to ensure no bias in the repeatability and reproducibility of test results. The Polycarbonate (PC) had a stronger layer bonding than ABS and PLA while printing. It was recommended for follow up studies.
In this research effort, a reliability framework is developed using Monte Carlo simulation for predicting the fatigue life of AC material using the S-VECD model. The reliability analysis reveals that the fatigue life prediction is very sensitive to the uncertainty in the input variables. FAM testing in similar loading conditions as AC, and upscaling of AC modulus and damage response using FAM properties from a relatively simple homogenized continuum approach shows promising results. The FAM phase fatigue life prediction and upscaling of FAM results to AC show more reliable fatigue life prediction than the fatigue life prediction of AC material using its experimental data. To assess the sensitivity of fatigue life prediction model to uncertainty in the input variables, a parametric sensitivity study is conducted on the S-VECD model. Overall, the findings from this research show promising results both in terms of upscaling FAM to AC properties and the reliability of fatigue prediction in AC using experimental data on FAM.
Road networks are valuable assets that deteriorate over time and need to be preserved to an acceptable service level. Pavement management systems and pavement condition assessment have been implemented widely to routinely evaluate the condition of the road network, and to make recommendations for maintenance and rehabilitation in due time and manner. The problem with current practices is that pavement evaluation requires qualified raters to carry out manual pavement condition surveys, which can be labor intensive and time consuming. Advances in computing capabilities, image processing and sensing technologies has permitted the development of vehicles equipped with such technologies to assess pavement condition. The problem with this is that the equipment is costly, and not all agencies can afford to purchase it. Recent researchers have developed smartphone applications to address this data collection problem, but only works in a restricted set up, or calibration is recommended. This dissertation developed a simple method to continually and accurately quantify pavement condition of an entire road network by using technologies already embedded in new cars, smart phones, and by randomly collecting data from a population of road users. The method includes the development of a Ride Quality Index (RQI), and a methodology for analyzing the data from multi-factor uncertainty. It also derived a methodology to use the collected data through smartphone sensing into a pavement management system. The proposed methodology was validated with field studies, and the use of Monte Carlo method to estimate RQI from different longitudinal profiles. The study suggested RQI thresholds for different road settings, and a minimum samples required for the analysis. The implementation of this approach could help agencies to continually monitor the road network condition at a minimal cost, thus saving millions of dollars compared to traditional condition surveys. This approach also has the potential to reliably assess pavement ride quality for very large networks in matter of days.