基于晶体塑性有限元的TWIP钢冷轧行为模拟研究
RESEARCH ON SIMULATION OF COLD ROLLING BEHAVIOR OF TWIP STEEL BASED ON CRYSTAL PLASTICITY FINITE ELEMENT METHOD
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摘要: 孪生诱导塑性(twinning-induced plasticity, TWIP)钢作为先进高强度钢, 因高强度与优异延展性在汽车领域应用潜力巨大. 冷轧是提升其强度的关键手段, 其变形过程中的微观组织演变、织构变化及变形异质性对性能影响显著, 而现有实验手段在动态追踪、表征等方面存在局限, 需借助模拟方法深入探究. 因此, 本文采用考虑孪生机制的唯象晶体塑性模型开展了TWIP钢冷轧行为仿真, 通过引入网格重划分技术有效解决了网格畸变引发的数值失稳问题. 晶体塑性模拟所得冷轧过程织构演变规律与实验结果一致, 晶体塑性模拟表明, 在TWIP钢的冷轧变形过程中, 高平均取向差(kernel average misorientation, KAM)区域呈现Goss织构占比较高而Brass和Copper织构占比较低的特征, 低KAM值区域则相反. 研究进一步发现, 轧制过程中晶粒变形程度表现为3种典型模式: 晶粒内部变形异质性大导致破碎且取向分散; 变形异质性小使晶粒保持完整且内部取向集中; 晶粒分裂为若干变形均匀且取向集中的子区域, 各区域间取向差异显著并呈现晶粒细化现象. 此外, 晶粒取向在轧制过程中存在规律性旋转: 大部分晶粒向 \bar\text1 , 1, 1和0, 0, 1平行于轧制方向旋转, 在反极图中最终取向集中分布于 \bar\text1 , 1, 1和0, 0, 1两方向连线附近, 其中 \bar\text1 , 1, 1方向取向最为密集; 在平行于轧制厚度方向上, 在反极图中晶粒最终取向集中分布于0, 1, 1与 \bar\text1 , 1, 2的连线附近. 综上, 本文通过晶体塑性有限元方法结合网格重划分技术, 系统揭示了TWIP钢冷轧过程中变形异质性的动态演化规律, 阐明了微观结构(如晶粒取向、织构组分)的演变规律, 为理解材料塑性变形与性能调控的关联提供了参考.Abstract: Twinning-induced plasticity (TWIP) steel, as an advanced high-strength steel, has great potential in the automotive field due to its high strength and excellent ductility. Cold rolling is a key method to improve its strength; the evolution of microstructure, changes in texture, and deformation heterogeneity during its deformation process have a significant impact on its properties. However, existing experimental methods have limitations in dynamic tracking and characterization, so it is necessary to use simulation methods for in-depth exploration. Therefore, in this paper, a phenomenological crystal plasticity model considering the twinning mechanism is used to simulate the cold rolling behavior of TWIP steel. By introducing mesh remeshing technology, the numerical instability problem caused by mesh distortion is effectively solved. The texture evolution law of the cold rolling process obtained by crystal plasticity simulation is consistent with the experimental results. The crystal plasticity simulation shows that during the cold rolling deformation of TWIP steel, regions with high kernel average misorientation (KAM) values are characterized by a relatively high proportion of Goss texture and relatively low proportions of Brass and Copper textures, while the opposite is true for regions with low KAM values. The study further found that the degree of grain deformation during the rolling process exhibits three typical modes: significant deformation heterogeneity inside the grains leads to their fragmentation and scattered orientations; minor deformation heterogeneity allows the grains to remain intact with concentrated internal orientations; and the grains split into several sub-regions with uniform deformation and concentrated orientations, where there are significant orientation differences between the sub-regions and grain refinement occurs. In addition, there is a regular rotation of grain orientations during the rolling process: most grains rotate such that their \bar\text1 , 1, 1 and 0, 0, 1 directions are parallel to the rolling direction (x). In the inverse pole figure, the final orientations are concentrated near the line connecting these two directions, among which the \bar\text1 , 1, 1 direction exhibits the highest orientation density; in the direction parallel to the rolling normal direction, the final orientations of grains in the inverse pole figure are concentrated near the line connecting the 0, 1, 1 and \bar\text1 , 1, 2 directions. In summary, by combining the crystal plasticity finite element method with mesh remeshing technology, this study systematically reveals the dynamic evolution law of deformation heterogeneity during the cold rolling process of TWIP steel, clarifies the evolution laws of microstructures (such as grain orientation and texture components), and provides a reference for understanding the correlation between the plastic deformation of materials and performance regulation.
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