A new Monte Carlo model for predicting the mechanical properties of fiber yarns

Xiaoding Wei, Matthew Ford, Rafael A. Soler-Crespo, Horacio D. Espinosa*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Understanding the complicated failure mechanisms of hierarchical composites such as fiber yarns is essential for advanced materials design. In this study, we developed a new Monte Carlo model for predicting the mechanical properties of fiber yarns that includes statistical variation in fiber strength. Furthermore, a statistical shear load transfer law based on the shear lag analysis was derived and implemented to simulate the interactions between adjacent fibers and provide a more accurate tensile stress distribution along the overlap distance. Simulations on two types of yarns, made from different raw materials and based on distinct processing approaches, predict yarn strength values that compare favorably with experimental measurements. Furthermore, the model identified very distinct dominant failure mechanisms for the two materials, providing important insights into design features that can improve yarn strength.

Original languageEnglish (US)
Pages (from-to)325-335
Number of pages11
JournalJournal of the Mechanics and Physics of Solids
Volume84
DOIs
StatePublished - Nov 1 2015

Keywords

  • Fiber rupture
  • Fiber yarns
  • Hierarchical composites
  • Monte Carlo
  • Shear load transfer
  • Weibull statistics

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering

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