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Simultaneous Prediction of Bendability and Deep Drawability Using Orientation Distribution Function for Aluminum Alloy Sheets

机译:使用铝合金板材的取向分布函数同时预测弯曲性和深度拉伸性

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Sheet metal formability is generally affected by crystallographic texture. In particular, bendability and deep-drawability of aluminum and its alloys are closely related to the recrystallization texture of the rolled sheets. It is necessary to quantitatively predict them from a viewpoint of texture control. This paper described a method for simultaneous prediction of both the bendability and the deep-drawability on the basis of the average Taylor factor as a polycrystal calculated by using an orientation distribution function. The normalized Taylor factor (M-n-value) and the r-value were used as measures of bendability and deep-drawability, respectively. The predicted results from ideal orientations demonstrated that {001}100 orientation had excellent bendability and poor deep-drawability, whereas {111}110 orientation had poor bendability and excellent deep-drawability. The predicted results for some aluminum alloys suggested that conventional cold-rolled and annealed sheets would be favorable to bendability, and the addition of asymmetric warm rolling after cold rolling would lead to improved deep-drawability.
机译:金属板材成形性通常受晶体纹理的影响。特别地,铝及其合金的弯曲性和深拉伸性与轧制板的再结晶纹理密切相关。从纹理控制的角度来看,必须定量地预测它们。本文描述了一种通过使用取向分布函数计算的平均泰勒因子的平均泰勒因子来同时预测弯曲性和深拉伸性的方法。将归一化泰勒因子(M-N值)和R值分别用作可弯曲性和深拉伸性的测量。理想取向的预测结果证明{001}& 100&取向具有出色的弯曲性和深层拉伸性差,而{111}& 110&定位趋向性差和极佳的深层可污垢。一些铝合金的预测结果表明,传统的冷轧和退火片是有利的,并且在冷轧后添加不对称的温暖轧制将导致改善的深拉伸性。

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