4.5 Article

A new framework for understanding aggregate structure in asphalt mixtures

Journal

INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING
Volume 22, Issue 9, Pages 1090-1106

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/10298436.2019.1660340

Keywords

Aggregate structure; packing density; coordination number; discrete element method; compactability; asphalt mixture

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The study developed a framework to define the aggregate structure of asphalt mixtures when fine and coarse aggregate stockpiles are blended. Through 3D discrete element simulation, the proposed analytical model was validated to successfully determine the particle structure of binary and multi-sized asphalt mixture gradations, and can be used to better design asphalt mixtures for improved performance.
Aggregate size distribution is an important parameter in asphalt mixture design and performance. The main objective of this study is to develop a framework to define the aggregate structure of asphalt mixtures when fine and coarse aggregate stockpiles are blended. To develop this framework, an analytical model for binary mixtures is proposed. The model considers the effect of size ratio and air volume between the particles on the aggregate structure and packing density of binary mixtures. Based on this model, three aggregate structures, namely coarse pack (CP), dense pack (DP) and fine pack (FP), are defined. The model is validated using a series of 3D discrete element simulation. Furthermore, the simulation of multi-sized aggregate blends using two representative sizes for fine and coarse stockpiles was carried out to apply the proposed analytical model to actual aggregate blends. In order to assess how well the model applies to asphalt mixtures, compaction parameters including compaction slope (CS), initial density (N-ini), locking point and compaction energy index (CEI) were analyzed. The numerical simulations verify the proposed analytical model can satisfactorily determine the particle structure of binary and multi-sized asphalt mixture gradations and can be used to better design asphalt mixtures for improved performance.

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