A 3D Image Correlation Algorithm for Tracking Movement of Aggregates in X-ray CT Images of Asphalt Mixtures Captured during Compaction
The current state of knowledge on development of asphalt mixtures’ microstructure during compaction is very limited. Such knowledge can lead to better understanding of the differences and similarities between the laboratory and field compactors and the internal structure of HMAs they produce. This paper presents a 3D image correlation algorithm that computes the 3D displacements of aggregates in an asphalt sample during compaction. Microstructural evolution of aggregates in asphalt mixtures during compaction were tracked by using X-ray CT images that were acquired at different compaction levels in the Superpave gyratory compactor. The procedure involved compaction of the asphalt sample to a specified compaction level, cooling down and scanning using X-ray CT. This process was repeated at different compaction levels. The x-, y- and z-direction displacements at various points inside the asphalt mixture were calculated using the 3D image correlation algorithm. It was observed that, in addition to downward movement of aggregates within the HMA, the displacement vectors also showed torsional movement in the tangential and radial direction with respect to the center of the specimen. It was also observed that the strain in z-direction was approximately constant within the sample during compaction between the gyrations 8 and 30. However, as the number of the gyrations increased, strain in z-direction became non-uniform with depth, where higher strain was observed at the top and bottom plates as compared to the central portion.
KeywordsAsphalt Mixture Normalize Cross Correlation Compaction Level Asphalt Sample Asphalt Pave Technologist
Unable to display preview. Download preview PDF.
- Buchanan, M.S., Brown, E.R.: Effect of Superpave gyratory compac-tor type on compacted hot-mix asphalt density. Transportation Research Record: Journal of the Transportation Research Board, No. 1671, 50–60 (2001)Google Scholar
- Hunter, A.E., Airey, G.D., Collop, A.C.: Aggregate Orientation and Segregation in Laboratory-Compacted Asphalt Samples. Transportation Research Record: Journal of the Transportation Research Board, No. 1891, 8–15 (2004)Google Scholar
- Kalcheff, I.V., Tunnicliff, D.G.: Effects of Crushed Stone Aggregate Size and Shape on Properties of Asphalt Concrete. Journal of the Association of Asphalt Paving Technologists 51, 453–483 (1982)Google Scholar
- Kutay, M.E., Aydilek, A.H., Masad, E.: Estimation of Directional Permeability of HMA Based on Numerical Simulation of Micro-scale Water Flow. Transportation Research Record: Journal of the Transportation Research Board, No. 2001, 29–36 (2007b)Google Scholar
- Partl, M.N., Flisch, A., Jönsson, M.: Comparison of Laboratory Compaction Methods Using X-ray Computer Tomography. RMPD 8(2) (2007)Google Scholar
- Prowell, B.D., Zhang, J., Brown, E.R.: Aggregate Properties and the Per-formance of Superpave-Designed Hot Mix Asphalt. Transportation Research Board, NCHRP Report 539 (2005)Google Scholar
- Saadeh, S., Tashman, L., Masad, E., Mogawer, W.: Spatial and directional distribution of aggregates in asphalt mixes. Journal of Testing and Evaluation 30(6), 1–9 (2002)Google Scholar
- Stephens, J.E., Sinha, K.C., Tashman, L., Masad, E., Peterson, B., Saleh, H.: Internal Structure Analysis of Asphalt Mixes to Improve the Simulation of Superpave Gyratory Compaction to Field Conditions. Journal of the Association of Asphalt Paving Technologists 70, 605–645 (1978, 2001)Google Scholar
- Tashman, L., Masad, E., Peterson, B., Saleh, H.: Internal Structure Analysis of Asphalt Mixes to Improve the Simulation of Superpave Gyratory Compaction to Field Conditions. Journal of the Association of Asphalt Paving Technologists 70, 605–645 (2001)Google Scholar
- Trucco, E., Verri, A.: Introductory Techniques for 3-D Computer Vision, 343 p. Prentice Hall, New Jersey (1998)Google Scholar