Two stochastic mean-field polycrystal plasticity methods

Michael R. Tonks, John F. Bingert, Curt A. Bronkhorst, Eric N. Harstad, Daniel A. Tortorelli

Research output: Contribution to journalArticlepeer-review

Abstract

In this work, we develop two mean-field polycrystal plasticity models in which the crystal velocity gradients Lc are approximated stochastically. Through comprehensive CPFEM analyses of an idealized tantalum polycrystal, we verify that the Lc tend to follow a normal distribution and surmise that this is due to the crystal interactions. We draw on these results to develop the stochastic Taylor model (STM) and the stochastic no-constraints model (SNCM), which differ in the manner in which the crystal strain rates Dc = frac(1, 2) (Lc + Lc T) are prescribed. Calibration and validation of the models are performed using data from tantalum compression experiments. Both models predict the compression textures more accurately than the fully constrained model (FCM), and the SNCM predicts them more accurately than the STM. The STM is extremely computationally efficient, only slightly more expensive than the FCM, while the SNCM is three times more computationally expensive than the STM.

Original languageEnglish (US)
Pages (from-to)1230-1253
Number of pages24
JournalJournal of the Mechanics and Physics of Solids
Volume57
Issue number8
DOIs
StatePublished - Aug 2009

Keywords

  • Crystal plasticity finite element analysis
  • Mean-field models
  • Polycrystal plasticity
  • Stochastic models
  • Texture modeling

ASJC Scopus subject areas

  • Condensed Matter Physics
  • Mechanics of Materials
  • Mechanical Engineering

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