Crumb rubber use in asphalt mixtures using wet process technology has been in practice for years in the United States with good performance history; however, it has some drawbacks that include the need for special blending equipment, high rubber-binder temperatures, and longer waiting time at mixing plants. Pre-treated crumb rubber technologies are emerging as a new method to produce asphalt rubber mixtures in the field. A new crumb rubber modifier known as Reacted and Activated Rubber (RAR) is one such technology. RAR (industrially known as “RARX”) acts like an Enhanced Elastomeric Asphalt Extender to improve the engineering properties of the binder and mixtures. It is intended to be used in a dry mixing process with the purpose of simplifying mixing at the asphalt plant. The objective of this research study was first to perform a Superpave mix design for determination of optimum asphalt content with 35% RAR by weight of binder; and secondly, analyse the performance of RAR modified mixtures prepared using the dry process against Crumb Rubber Modified (CRM) mixtures prepared using the wet process by conducting various laboratory tests. Performance Grade (PG) 64-22 binder was used to fabricate RAR and CRM mixtures and Performance Grade (PG) 70-10 was used to fabricate Control mixtures for this study. Laboratory tests included: Dynamic Modulus Test, Flow Number Test, Tensile Strength Ratio, Axial Cyclic Fatigue Test and C* Fracture Test. Observations from test results indicated that RAR mixes prepared through the dry process had excellent fatigue life, moisture resistance and cracking resistance compared to the other mixtures.
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.
This study examines the methodology for converting protected, permissive, and protected/permissive left-turn operation to flashing yellow arrow left-turn operation. This study addresses construction-related considerations, including negative offsets, lateral traffic signal head position, left-turn accident rates, crash modification factors and crash reductions factors. A total of 85 intersections in Glendale, Arizona were chosen for this study. These intersections included 45 “arterial to arterial” intersections (a major road intersecting with a major road) and 40 “arterial to collector” intersections (a major road intersecting with a minor road).
This thesis is a clinical study of the field conversion to flashing yellow arrow traffic signals and is not a study of the merits of flashing yellow arrow operation. This study included six categories: 1. High accident intersections (for inclusion in Highway Safety Improvement Program (HSIP) funding); 2. Signal head modifications only; 3. Signal head replacement with median modifications; 4. Signal head and mast arm replacement; 5. Signal head, signal pole and mast arm replacement; and 6. Intersections where flashing yellow arrow operation is not recommended. Compliance with the Manual on Uniform Traffic Control Devices (MUTCD) played a large part in determining conversion costs because the standard for lateral position of the left-turn traffic signal greatly influenced the construction effort. Additionally, the left-turning vehicle’s sight distance factored into cost considerations. It’s important for agencies to utilize this study to understand all of the financial commitments and construction requirements for conversion to flashing yellow arrow operation, and ultimately to appreciate that the process is not purely a matter of swapping traffic signal heads.
Load associated fatigue cracking is one of the major distress types occurring in flexible pavements. Flexural bending beam fatigue laboratory test has been used for several decades and is considered an integral part of the Superpave advanced characterization procedure. One of the most significant solutions to sustain the fatigue life for an asphaltic mixture is to add sustainable materials such as rubber or polymers to the asphalt mixture. A laboratory testing program was performed on three gap-graded mixtures: unmodified, Asphalt Rubber (AR) and polymer-modified. Strain controlled fatigue tests were conducted according to the AASHTO T321 procedure. The results from the beam fatigue tests indicated that the AR and polymer-modified gap graded mixtures would have much longer fatigue lives compared to the reference (unmodified) mixture. In addition, a mechanistic analysis using 3D-Move software coupled with a cost-effectiveness analysis study based on the fatigue performance on the three mixtures were performed. Overall, the analysis showed that the AR and polymer-modified asphalt mixtures exhibited significantly higher cost-effectiveness compared to unmodified HMA mixture. Although AR and polymer-modification increases the cost of the material, the analysis showed that they are more cost effective than the unmodified mixture.
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.