Crystal Plasticity Analysis of the Relation between Micro‐Texture and Surface Ridging for a 21%Cr Ferritic Stainless Steel

Zhang, Chi; Xu, Yujie; Zhang, Liwen; Zhou, Xiaoguang

doi:10.1002/srin.202070101

Cited by 3 publications

(1 citation statement)

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“…Although crystal plasticity finite element method has been widely used, the effects of grain morphology (e. g. size and shape) are ignored by most of works [16–20]. Therefore, the statistically equivalent representations of grain structures in the crystal plasticity finite element model constructed by researches are mostly simple geometrical units, such as cubes and regular hexagons [19, 21–24].…”

Section: Introductionmentioning

confidence: 99%

Modeling and analysis of grain morphology effects on deformation response based on crystal plasticity finite element method

Zhao

et al. 2022

Materialwissenschaft Werkst

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In order to investigate the grain morphology effects on deformation response at macro‐ and micro‐scale in polycrystalline metal, a method considering grain size and shape effects is proposed based on the classical crystal plasticity finite element method in this paper. A grain morphology controlled polycrystalline geometry model consisting of grain shape models and grain size transition models is developed based on Voronoi diagram. Grain size effect is introduced into the classical crystal plasticity constitutive model quantitatively on the basis of Hall‐Petch type relationship. With the aid of the method, grain aggregate finite element meshes with different mean grain sizes are established to simulate the deformation response of polycrystalline pure copper. The predicted values of flow stresses show good agreement with experimental ones. Finally, a set of grain aggregate finite element meshes with same mean grain size but different grain distributions are developed to simulate the uniaxial tension processes of polycrystalline pure copper. The results shown that the effects of grain morphology on the macro‐scale deformation response are insignificant under a large number of grains with random morphology and orientation. When the grain distributions changes regularly along the x direction, the maximum decrease of flow stress data is 10 MPa.

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Section: Introductionmentioning

confidence: 99%