A statistical model for predicting the mechanical properties of nanostructured metals with bimodal grain size distribution

Linli Zhu, San-Qiang Shi, Ke Lu, Jian Lu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

46 Citations (Scopus)

Abstract

A statistical analysis is employed to investigate the mechanical performance of nanostructured metals with bimodal grain size distribution. The contributions of microcracks in the plastic deformation are accounted for in the mechanism-based plastic model used to describe the strength and ductility of the bimodal metals. The strain-based Weibull probability distribution function and percolation analysis of microcracked solids are applied to predict the failure behavior of the bimodal metals. The numerical results show that the proposed model can describe the mechanical properties of the bimodal metals, including yield strength, strain hardening and uniform elongation. These predictions agree well with the experimental results. The stochastic approaches adopted in the proposed model successfully capture the failure behavior of bimodal coppers that are sensitive to grain size and the volume fraction of coarse grains in addition to the corresponding threshold for percolation. These results will benefit the optimization of both strength and ductility by controlling constituent fractions and the size of the microstructures in materials.
Original languageEnglish
Pages (from-to)5762-5772
Number of pages11
JournalActa Materialia
Volume60
Issue number16
DOIs
Publication statusPublished - 1 Sep 2012

Keywords

  • Bimodal grain size distribution
  • Ductility
  • Percolation model
  • Strength
  • Weibull probability distribution

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Ceramics and Composites
  • Polymers and Plastics
  • Metals and Alloys

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