An efficient model for predicting the dynamic performance of fine aggregate matrix

Zhen Leng, Zhifei Tan, Peng Cao, Yuan Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Fine aggregate matrix (FAM) refers to the mixture of asphalt binder and fine aggregate in asphalt mixture. The viscoelastic properties, such as the complex modulus of FAM, directly affect the performance of asphalt pavement. In this study, finite element (FE) simulation by coupling random aggregate distribution algorithm and steady-state dynamic (SSD) analysis was applied to predict the complex modulus of FAM. Both the dynamic moduli and phase angles of FAM were predicted and compared with those obtained from laboratory tests. The modeling and testing results indicated that the complex interface layer between asphalt mastic and aggregate can significantly affect the viscoelastic performance of FAMs. Considering the interface layer into the FE model can improve the prediction accuracy. Besides, the simulation results showed that the SSD method is 576 times more efficient in predicting the dynamic moduli and phase angles of FAMs than the conventional transient dynamic method, indicating its high potential for multi-scale modeling of asphalt mixture.

Original languageEnglish
JournalComputer-Aided Civil and Infrastructure Engineering
DOIs
Publication statusAccepted/In press - 2021

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Computational Theory and Mathematics

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