Stochastic reconstruction and microstructure modeling of SMC chopped fiber composites

Yi Li, Zhangxing Chen, Lingxuan Su, Wei Chen, Xuejun Jin, Hongyi Xu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

23 Scopus citations


To establish an integrated Processing-Microstructure-Property workflow for the prediction of material behaviors, this paper presents a new stochastic pseudo-3D microstructure reconstruction method for Sheet Molding Compounds (SMC) chopped fiber composites. The proposed method captures the bi-level microstructural features of SMC composites. At the higher level, a Voronoi diagram-based algorithm is developed to reconstruct the unique substructure features of SMC fiber tows. The geometry of Voronoi cells is adjusted by a Simulated Annealing (SA) algorithm to match the geometrical statistics of the real fiber tows. At the lower level, the algorithm assigns fiber orientation to each Voronoi cell (which represents a fiber tow). The fiber orientation angles are recovered from a statistical fiber orientation tensor. The proposed method is employed to establish a multi-layer pseudo-3D SMC Representative Volume Element (RVE) model for Finite Element Analysis (FEA) of SMC microstructure. This model enables the prediction of mechanical properties based on the material processing information (e.g. fiber orientation tensor obtained from compression molding simulation), and the microstructure information obtained from microscopic imaging for an SMC composite. The predicted properties are successfully validated by experimental tensile tests.

Original languageEnglish (US)
Pages (from-to)153-164
Number of pages12
JournalComposite Structures
StatePublished - Sep 15 2018


  • Fiber tow
  • Microstructure reconstruction
  • Orientation tensor
  • RVE
  • SMC composites

ASJC Scopus subject areas

  • Ceramics and Composites
  • Civil and Structural Engineering


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