Contact mechanics based solution to predict modulus of asphalt materials with high porosities

Journal Article (2021)
Author(s)

Hong Zhang (TU Delft - Pavement Engineering)

Kumar Anupam (TU Delft - Pavement Engineering)

Tom Scarpas (Khalifa University of Science and Technology, TU Delft - Pavement Engineering)

Cor Kasbergen (TU Delft - Pavement Engineering)

Sandra Erkens (TU Delft - Pavement Engineering)

Research Group
Pavement Engineering
DOI related publication
https://doi.org/10.1016/j.matdes.2021.109752 Final published version
More Info
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Publication Year
2021
Language
English
Research Group
Pavement Engineering
Journal title
Materials and Design
Volume number
206
Article number
109752
Pages (from-to)
1-18
Downloads counter
296
Collections
Institutional Repository
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Abstract

Asphalt mixtures with high porosities (known as porous asphalt (PA) mixes) are becoming a popular choice among road authorities as it provides better skid resistance while also reducing tire-pavement noises. Towards the design and manufacture of PA mix pavement, the evaluation of the mechanical properties of PA mixes is of great importance. To predict the mechanical properties of PA mixes, micromechanical models have been considered as an effective tool. In most research studies, continuum-based micromechanical models, i.e. the Self-consistent model, the Mori-Tanaka model, etc. are widely used to predict the stiffness of asphalt mixtures. However, the limitation of these models is that they cannot describe the characteristics of individual particles and thus they cannot provide accurate predictions. On the other hand, the discrete-based micromechanical model (DBMM) which simulates a granular material as an assembly of bonded particles seems to be a promising alternative. Limited research studies have focused on studying the utilization and the applicability of this model for asphalt mixes. Therefore, this paper aims to propose a framework to use DBMM and to evaluate its performance in estimating a PA mix's stiffness. Based on the obtained results, both the merits and limitations of this model were highlighted.