Prediction of Texture and Formability of Continuous Cast Aluminum Alloys

肯塔基州大学材料研究部授予该奖项的目的是开发一种数学模型，用于量化连续铸造（CC）铝合金板材中作为工艺参数函数的织构演变。 该模型将显示合金成分、热轧工艺和均匀化处理对冷轧和退火过程中织构演变的影响。 凭借该奖项，翟教授将定量研究连续铸造AA 3000系列铝合金板材冷轧过程中织构和显微组织的演变，以及退火过程。 合金成分、初始织构和显微组织对这些铝合金织构演变的影响将被量化。 此外，定量的分析关系，描述了在连续铸造过程中的织构和显微组织的演变，以预测其成形性的铝合金板将进行研究。 在织构和成形性研究中，如何足够准确地预测金属板材热机械加工过程中的晶体织构演变，并通过考虑织构和微观结构参数来量化其成形性一直是一个挑战。 已经尝试使用基于物理的模型或经验方程来量化铝合金退火期间的织构演变，但是理论预测与实验结果之间仍然存在很大差异。 改进后的方法将通过在欧拉空间中唯一定义各织构分量的区域来量化织构体积分数，并精确量化连续铸造铝合金退火和冷轧过程中织构的演变。 该建模项目的成功将为从力学各向异性的角度以及从极限应变考虑准确预测可成形性铺平道路，并且在连续铸造铝合金的加工的优化中将是有价值的。该研究项目将帮助美国铝工业通过量化热机械加工过程中和之后的织构演变和板材成形性以及优化加工参数来显着改善连续铸造铝合金的成形性。 通过这项研究和教育计划培养的本科生和研究生将为他们在铝行业的职业生涯做好准备。 将研究纳入教学和实验室项目将使学生受益，并为他们在科学和技术方面的职业或高等教育机会做好准备。

This award by the Division of Materials Research to University of Kentucky is to develop a mathematical model for quantification of texture evolution in continuous cast (CC) aluminum alloy sheets as a function of processing parameters. This model will show the effect of alloy composition, hot rolling procedure and homogenization practice on the evolution of texture during cold rolling and annealing. With this award, Professor Zhai will study quantitatively the evolution of texture and microstructure during cold rolling of continuous cast AA 3000 series aluminum alloy sheets, and during their annealing. The effect of alloy composition, initial texture and microstructure on the evolution of texture in these aluminum alloys will be quantified. In addition, quantitative analytical relations that describe the evolution of texture and microstructure during the continuous cast processing of aluminum alloy sheets, with a view to predicting their formability will be studied. It has been a challenge in texture and formability studies to predict with sufficient accuracy the evolution of crystallographic texture during thermomechanical processing of metal sheets, and to quantify their formability by taking into account texture and microstructure parameters. Attempts have been made to quantify texture evolution during annealing of aluminum alloys using a physically based model or an empirical equation, but large discrepancies between theoretical predictions and experimental results remained. Improved methods will be used to quantify texture volume fractions by uniquely defining the region of each texture component in Euler space, and accurately quantify the evolution of texture during annealing as well as cold rolling of continuous cast aluminum alloys. The success of this modeling project would pave the way to accurately predicting formability both from a mechanical anisotropy point of view as well as from a limit strain consideration, and would be valuable in the optimization of the processing of continuous cast aluminum alloys. This research project would help the U.S. aluminum industry to significantly improve the formability of continuous casting aluminum alloys by enabling the quantification of texture evolution and sheet formability during and after thermomechanical processing, respectively, and by optimization of processing parameters. Undergraduate and graduate students trained by this research and education program would prepare them for careers in aluminum industry. Integration of research into teaching and laboratory projects would benefit the students and prepare them for opportunities in careers or higher education in science and technology.