This thesis consists of two parts. The first part includes analyses of the
correlation between the results of two Aggregate Imaging System (AIMS) units. These
analyses have led to refinements of the AIMS analysis methods of angularity and
texture, which resulted in reduced variability in the results and better correlation between
the two AIMS units. The refined analysis methods were used to establish a database of
the shape characteristics of about 100 aggregate samples from the state of Texas and to
propose a new method for the classification of aggregates based on their shape
characteristics. This new method of classification is for use in the Texas Department of
Transportation (TxDOT) wet weather accident reduction program (WWARP). The use
of AIMS texture index and variability in texture within an aggregate source is proposed
instead of the British Polish Value (BPV) for classifying aggregates used in pavement
surfaces.
The second part of the thesis investigates the relationship between shape
characteristics and asphalt pavement skid resistance. Many states have implemented wet
weather accident reduction programs aimed at maintaining acceptable levels of pavement skid resistance. Proper aggregate selection before construction aids in
maintaining acceptable levels of skid resistance throughout the life of the pavement.
Several predictive models of pavement skid resistance have been developed over
the years. Some of these models account for the influence of aggregate characteristics
on pavement skid resistance, primarily through incorporating the results of the BPV test
in the model. However, the BPV test is known to have high variability and dependence
on experimental factors that are not related to the actual aggregate resistance to
polishing. AIMS offers a method to measure aggregate shape characteristics directly in
a relatively short period of time. The new method for relating aggregate shape
characteristics to pavement skid resistance was verified by relating skid resistance
measurements from field test sections to measured aggregate properties from the
laboratory. This methodology is expected to be the basis for further study to form a
more comprehensive and verified model for the prediction of pavement skid resistance
that incorporates measured aggregate properties from the AIMS system.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-1086 |
| Date | 15 May 2009 |
| Creators | Luce, Anthony David |
| Contributors | Masad, Eyad |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | electronic, application/pdf, born digital |
Page generated in 0.0024 seconds