Dynamic modulus prediction of asphalt concrete mixtures through computational micromechanics

Pravat Karki, Yong Rak Kim, Dallas N. Little

Research output: Contribution to journalArticlepeer-review

45 Scopus citations


This paper presents a computational micromechanics modeling approach to predict the dynamic modulus of asphalt concrete mixtures. The modeling uses a finite element method combined with the micromechanical representative volume element (RVE) of mixtures and laboratory tests that characterize the properties of individual mixture constituents. The model treats asphalt concrete mixtures as heterogeneous with two primary phases: a linear viscoelastic fine aggregate matrix (FAM) phase and a linear elastic aggregate phase. The mechanical properties of each phase were experimentally obtained by conducting constitutive tests: oscillatory torsion tests for the viscoelastic FAM phase and quasistatic nanoindentation tests for the elastic aggregate particles. Material properties of each mixture phase were then used in the finite element simulation of two-dimensional mixture microstructures obtained from digital image processes of asphalt concrete mixtures. Model simulations were compared with the experimental dynamic moduli of asphalt concrete mixtures. Simulation results indicated that the micromechanical approach based on the mixture microstructure and phase properties could fairly predict the overall mixture properties that are typically obtained from laboratory mixture tests. Furthermore, the RVE dimension of 60 mm might be used to predict the undamaged viscoelastic stiffness characteristics of asphalt concrete mixtures with reduced computing efforts.

Original languageEnglish (US)
Pages (from-to)1-9
Number of pages9
JournalTransportation Research Record
StatePublished - 2015
Externally publishedYes

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Mechanical Engineering


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