• Title of article

    Numerical fracture analysis on the specimen size dependency of asphalt concrete using a cohesive softening model

  • Author/Authors

    Kim، نويسنده , , Hyunwook and Wagoner، نويسنده , , Michael P. and Buttlar، نويسنده , , William G.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2009
  • Pages
    9
  • From page
    2112
  • To page
    2120
  • Abstract
    Cracking in asphalt concrete is one of the major causes of structural and functional deterioration of pavement systems. Various experimental and numerical approaches with typical specimen size have been applied to analyze the fracture mechanism of asphalt concrete but the specimen size dependency on the fracture has an important role. Herein, the clustered discrete element method (DEM) approach was applied into the investigation of size effect on fracturing of asphalt concrete based on a disk-shaped compact tension (DC(T)) test. A bilinear cohesive softening model was implemented into the DEM framework to enable simulation of crack initiation and propagation in asphalt concrete. The laboratory tests were conducted for specimen sizes of asphalt concrete varying from 100 to 450 mm. Micromechanical fracture modeling approach was also applied to investigate the heterogeneous fracture behaviors for different specimen sizes. Image processing procedure was conducted to determine the microstructure of asphalt specimen and to project it into the numerical mesh. The specimen size dependency of asphalt concrete was captured by the developed experimental fracture test and the clustered DEM fracture model was able to accurately predict the size-dependent fracture behavior when considering viscoelasticity and heterogeneity.
  • Keywords
    Asphalt Concrete , fracture , Size effect , Discrete element method , cracking , heterogeneous , Disk-shaped compact tension , image processing
  • Journal title
    Construction and Building Materials
  • Serial Year
    2009
  • Journal title
    Construction and Building Materials
  • Record number

    1629465