• Title of article

    Bridging the length scales through nonlocal hierarchical multiscale modeling scheme

  • Author/Authors

    Rahman، نويسنده , , R. and Foster، نويسنده , , J.T.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2014
  • Pages
    15
  • From page
    401
  • To page
    415
  • Abstract
    In the current work the nonlocal multiscale bottom-up peridynamic framework is modified (i.e. extended PFHMM) in order to upscale the nonlocally interacting models at different length scales. The generalized scheme was implemented to a complex heterogeneous polymer: ultra high molecular weight polyethylene (UHMWPE). Using extended PFHMM, the atomistic model of UHMWPE was linked with the coarser peridynamic (PD) representative unitcells. Different phases (e.g. highly oriented unidirectional, amorphous or semicrystalline) of UHMWPE were blended during upscaling of polyethylene (PE) microfibrils. In literature, a thorough theoretical investigation on the deformation mechanism of highly oriented UHMWPE microfibrils is not available. So the current work also rigorously discussed the role of different loading conditions (such as torsion, tension and compression), pre-existing damages and aspect ratios on the stiffness as well as the strength of the UHMWPE microfibrils by using molecular dynamics (MD) simulation. Through MD simulation, the effect of complex-loading condition on the strength reduction was also investigated. Cauchy–Born rule was applied through extended PFHMM in order to link the deformation from atomistic scale models with the macroscale UHMWPE representative unitcells. Finally, a slightly modified AIREBO potential was used to show that the unidirectional UHMWPE is independent of strain rate. The results had reasonable agreement with the experimental results. The current work can be considered to be a building block for multiscale modeling of complex heterogeneous materials.
  • Keywords
    Molecular dynamics , Nonlocal multiscale modeling , Polymer
  • Journal title
    Computational Materials Science
  • Serial Year
    2014
  • Journal title
    Computational Materials Science
  • Record number

    1693103