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A 3D Image Correlation Algorithm for Tracking Movement of Aggregates in X-ray CT Images of Asphalt Mixtures Captured during Compaction

  • M. Emin Kutay
  • Nelson Gibson
  • Xinjun Li
Part of the RILEM Bookseries book series (RILEM, volume 8)

Abstract

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.

Keywords

Asphalt Mixture Normalize Cross Correlation Compaction Level Asphalt Sample Asphalt Pave Technologist 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© RILEM 2013

Authors and Affiliations

  1. 1.Department of Civil and Environmental EngineeringMichigan State UniversityEast LansingUSA
  2. 2.Federal Highway Administration Turner-Fairbank Highway Research CenterMcLeanUSA
  3. 3.SES Group & Associates, Inc. Turner-Fairbank Highway Research CenterMcLeanUSA

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