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Scientific Publication Citing Dragonfly

Characterization of the air void content of fine aggregate matrices within asphalt concrete mixtures

Alexis Jair Enríquez-Leon (1), Thiago Delgado de Souza (1), Francisco Thiago Sacramento Aragao (1), Andre Maues Brabo Pereira (2), Liebert Parreiras Nogueira (3)
Construction and Building Materials, 300, September 2021. DOI: 10.1016/j.conbuildmat.2021.124214

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Keywords

Fine aggregate matrix; Air void; X-ray micro-computed tomography; Digital image processing; Artificial intelligence

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Abstract

Fine aggregate matrix (FAM) has been regarded as a key constituent of asphalt mixtures. Several attempts focusing on the proper fabrication and characterization of FAM have been pursued in the last decades. However, there are still some limitations that require further investigations. One of those shortcomings is how to define the air void (AV) content to produce isolated FAM testing specimens that are representative of those comprising asphalt concrete (AC) mixtures. This paper suggests a criterion to select the AV content to fabricate isolated FAM testing specimens based on a comprehensive examination of this AC phase using X-ray micro-computed tomography tests and digital image processing with artificial intelligence techniques. The results indicate that the proposed procedure can provide key insights into the volumetric characteristics of FAM mixtures. This may in turn contribute with the improvement of FAM design protocols and result in more accurate characterizations of the behavior of this relevant constituent of asphalt mixtures, where relevant damage phenomena occur.

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How Our Software Was Used

Dragonfly was used for the segmentation and 3D rendering of micro-CT data.

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Author Affiliation

(1) Civil Engineering Program – COPPE, Federal University of Rio de Janeiro, Rio de Janeiro 21941-596, Brazil.
(2) Institute of Computing, Fluminense Federal University, Rio de Janeiro 24210-240, Brazil.
(3) Department of Biomaterials, University of Oslo, Oslo 0455, Norway

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