The main objective of the thesis is to develop a knowledge base for the design of asphalt concrete mixtures suiting various types and causes of pavement distress and to develop supporting guidelines for the selection of aggregate types, gradation and binder contents for desirable mixture properties.
To achieve this objective, a two-level model was developed. The upper-level is a Factorial Experimental Design Model (FEDM) for the pavement condition evaluation. It can be used as a prediction tool to estimate the Pavement Condition Index (PCI), and determine the percentages of the types of distresses (Load, Environmental, Others). The upper-level model was calibrated by considering 4 factors with different levels: pavement type (two types), age (three levels), ESAL (three levels) and structural number (three levels). The range of the various levels and the rationale for level selection were presented.
The lower level is an FEDM model to estimate the various mixture properties (such as the stability, loss of stability, rutting resistance, etc.) considering the variations in the aggregate sources (three sources), aggregate gradation (three gradations) and binder content (three levels). The statistical significance of all the developed FEDM models were discussed in details, and conclusions on how to improve the fitness of these models were made. The interaction effects among the factors of the various models were also discussed.
The data to calibrate the upper-level FEDM model were collected by investigating the highway construction records at Dubai Municipality, calculating the traffic measures (ESAL) and assessing (cross referencing) the pavement condition index as well as the different types of distresses. The data to calibrate the lower-level sets of models were collected by carrying out a set of experiments using the Marshall testing device, the Gyratory compactor and the Asphalt Pavement Analyzer. The experimental design, the preparation of the specimens, the procedures of the various experiments, and the results were also discussed in details.
The main contribution of this research work is the development of these FEDM models that can be used in a systematic way to predict pavement performance, and to identify of the most probable distress causes. Hence, design the mixtures with focus on enhancing the mix properties to “resist” the identified most probable distress causes
