Comparison of three state-of-the-art crystal plasticity based deformation twinning models for magnesium alloys

In magnesium alloys, deformation twinning and its interactions with dislocation slip are responsible for a sigmoidal shape stress-strain behavior and an asymmetrical tension-compression yield strength in magnesium alloys. The sensitivity of twinning to the underlying microstructure renders the crystal plasticity method the most commonly adopted modeling approach for magnesium-twinning. This paper compares three state-of-the-art crystal plasticity-based twinning models from the literature, namely the elastic-viscoplastic self-consistent twinning-detwinning (EVPSC-TDT) model, crystal plasticity finite element model based on enhanced predomi-nate twin reorientation approach (CPFE-ePTR), and the crystal plasticity finite element model based on discrete twinning approach (CPFE-DT). A polycrystalline microstructure is simulated with all three methods to compare the resulting stress-strain curves and lattice strains to those from the experimentally measured data. All three methods showed the capability of capturing the experimental results with different levels of accuracy. The EVPSC-TDT method avoids solving the finite element matrices and showed the highest computational efficiency. The CPFE-ePTR model shows a higher accuracy in capturing the lattice strain. The CPFE-DT relies on high -resolution finite element mesh and is much slower than the other two methods, but it captured the local deformation concentration and stress reversal phenomena near the twin band, which was not possible with the other two methods. Based on the comparison, guidance for the selection of the appropriate model based on the specific modeling target is provided in this paper.

Automated summary

This paper compares three crystal plasticity-based modeling approaches for twinning in magnesium alloys and analyzes their accuracy and computational efficiency in simulating stress-strain behavior and lattice strains. The findings provide guidance for selecting an appropriate model based on specific modeling targets.