High-compactability asphalt mix design framework based on binary aggregate packing

Tianhao Yan, Kristen Cash, Mugurel Turos, Mihai Marasteanu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

High compactability is desired for asphalt mixtures to ensure adequate field density and, therefore, the overall quality of asphalt pavements. However, compactability is typically not considered in standard mix design procedures, and existing methods for improving compactability are largely empirical. This paper proposes a mix design framework that considers the compactability of mixtures, anchored by a rational method to adjust aggregate gradation. The method is developed based on the binary aggregate packing model. The proposed mix design is applied to modify four traditional Superpave mixtures into high-compactability mixtures, to demonstrate the concept. The proposed method is compared with two empirical methods used to adjust aggregate gradation: the maximum density line (MDL) and the Bailey method. The results show that the proposed method provides a theoretical explanation of the two empirical methods and reveals their limitations. Mechanical properties related to rutting resistance, low-temperature cracking, and structural capacity of the mixtures are checked by laboratory performance tests to validate the high-compactability mix designs. The results show that, due to their denser aggregate packing, the high-compactability mixtures outperform the traditional Superpave mixtures. Therefore, the proposed high-compactability mix design framework provides a rational and practical approach to improve the field density and the overall quality of asphalt pavements.

Original languageEnglish (US)
Article number131315
JournalConstruction and Building Materials
Volume383
DOIs
StatePublished - Jun 20 2023

Bibliographical note

Publisher Copyright:
© 2023 Elsevier Ltd

Keywords

  • Asphalt mix design
  • Bailey method
  • Binary aggregate packing
  • Compactability
  • Maximum density line

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