Abstract

A finite-element-based macro/micro crystal plasticity model is presented for large deformation of metals. The model development is based on the updated Lagrangian approach for large plastic deformation, coupled with a micromechanical description of multisurface plastic flows associated with individual single crystals. The macroscopic Lagrangian description of deformation processes uses either the hypoelastoplasticity formulation, with the incremental objective stress-time integration scheme, or the hyperelastoplasticity formulation, with the total formulation based on multiplicative decomposition. The macroscopic stress is linked to the microstructural behavior of crystals by tracking the motion of each active dislocation in slip systems underlining the plastic deformation. The microscopic treatment entails a multisurface-type stress-update algorithm, which ensures the plastic deformation defined by each slip system to be on the local yield surface. During each increment, the number of slip systems active during deformation is determined by either the single-value decomposition (SVD) technique or the diagonal-shift method. Simulations using these types of microscale models can be computationally intensive, especially when a large number of crystals are applied. For these cases, a parallel computing algorithm can be particularly efficient, and numerical tests show that, for these cases, which often are used in simulations for more realistic deformation processes, the computational time approaches asymptotically the theoretical limit of the parallel processing. The parallel macro/micro model is checked with various benchmark deformation and micromechanical testing problems reported in literature. Numerical simulations are carried out and results are compared with measurements of individual crystallite orientations made intermittently during the deformation of a low-angle bicrystal and a two-dimensional columnar-grained, multicrystal aluminum sample in channel-die compression. Texture development in a copper sample being flat-rolled under commercial operating conditions is also predicted using the micro/macro model and is compared with the measured data. For all these cases, the macro/micro model predictions are in reasonably good agreement with experimental measurements.

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