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Dislocation Modelling of Crystalline Plasticity

  • C. Teodosiu
Part of the International Centre for Mechanical Sciences book series (CISM, volume 376)

Abstract

The aim of this lecture is to review some significant aspects of the dislocation modelling of the large deformation plasticity of single crystals and crystalline aggregates, by making use of an internal-variable approach.

For single-crystal plasticity, the most important internal variables are the dislocation densities on various glide planes. Their evolution is governed by balance equations involving production and annihilation rates. Dislocation interactions determine in a basically anisotropic way the slip rates and the evolution of the critical shear stresses.

Recently, dislocation-based models of continuum plasticity have been employed for the simulation of inhomogeneously deformed crystalline aggregates. Such simulations may help understanding the influence of the crystallographic mismatch across grain boundaries and of the difference in size between neighbouring grains on the heterogeneity of plastic deformation and possibly on strain localization and damage.

One of the most striking features of the microstructural organization inside the grains is that dislocations evolve towards some steady-state microstructures, provided that a sufficient amount of monotonous deformation is allowed for along the same strain path. Reversed deformation and changes in the strain path generally tend to the modification or dissolution of preformed microstructures and the formation of new ones that correspond to the last deformation mode. The lecture will focus on the attempts to model such processes and their contribution to plastic anisotropy, by means of internal variables associated to the strength and polarity of dislocation structures.

Keywords

Slip System Dislocation Structure Slip Rate Strain Path Critical Shear Stress 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Wien 1997

Authors and Affiliations

  • C. Teodosiu
    • 1
  1. 1.LPMTM-CNRSUniversity of Paris-NordVilletaneuseFrance

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