4.7 Article

Numerical evaluation of effective elastic properties of composites reinforced by spatially randomly distributed short fibers with certain aspect ratio

期刊

COMPOSITE STRUCTURES
卷 131, 期 -, 页码 843-851

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.compstruct.2015.06.045

关键词

Elastic properties; Finite element analysis (FEA); Numerical homogenization; Periodic boundary condition; Short-fiber composites

资金

  1. National Nature Science Foundation of China [51221001, 51472203]
  2. Doctorate Foundation of Northwestern Polytechnical University [CX201312]
  3. Short-term Over-sea Visiting Scholar Program of Gradual School at Northwestern Polytechnical University

向作者/读者索取更多资源

The effective elastic properties of composites reinforced by spatially randomly distributed short cylindrical fibers with certain aspect ratio are investigated using the numerical homogenization method. A modified RSA algorithm is proposed to generate the periodic RVEs. The periodic boundary conditions are introduced and the periodic RVEs thus created are analyzed to obtain the mechanical properties of composites by using the FE package ABAQUS. The ABAQUS Python Interface is used to introduce the periodic boundary conditions and to obtain the average stresses and strains of RVEs. The simulation results show that the periodic boundary conditions guarantee the continuity of strain and stress fields on the boundaries of RVEs. In the case of the fiber aspect ratio of 15 and fiber volume fraction of 10%, it is sufficient to consider the size of RVE as L/l= 2.5, in which an approximately random fiber orientation exists. The effective elastic properties of composites obtained by the numerical homogenization agreeing well with those obtained from the traditional equations for composites based on the Halpin-Tsai estimation and with those measured from the uniaxial tensile experiments shows the validation of the numerical homogenization for effective elastic properties of composites reinforced by spatially randomly distributed short fibers. (C) 2015 Elsevier Ltd. All rights reserved.

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