Prediction of Texture and Formability of Continuous Cast Aluminum Alloys

连铸铝合金的织构和成形性预测

• 批准号: 0413724
• 负责人: Tongguang Zhai
• 金额: $ 9.39万
• 依托单位: University of Kentucky Research Foundation
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0413724&HistoricalAwards=false
• 关键词: Prediction; Texture; Formability; Continuous; Cast

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.

肯塔基大学材料研究部授予的这一奖项旨在开发一种数学模型，用于量化连铸 (CC) 铝合金板中织构演变与加工参数的关系。 该模型将显示合金成分、热轧工艺和均匀化实践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铸AA 3000系列铝合金板冷轧及其退火过程中织构和微观结构的演变。 合金成分、初始织构和微观结构对这些铝合金织构演变的影响将被量化。 此外，还将研究描述铝合金板连续铸造加工过程中织构和微观结构演变的定量分析关系，以预测其成形性。 在织构和成形性研究中，如何以足够的精度预测金属板热机械加工过程中晶体织构的演变，并通过考虑织构和微观结构参数来量化其成形性，一直是织构和成形性研究中的一个挑战。 人们尝试使用基于物理的模型或经验方程来量化铝合金退火过程中的织构演变，但理论预测和实验结果之间仍然存在巨大差异。 改进的方法将通过在欧拉空间中唯一定义每个织构成分的区域来量化织构体积分数，并准确量化连铸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机械各向异性的角度以及极限应变的角度准确预测可成形性铺平道路，并且对于优化连铸铝合金的加工具有重要意义。该研究项目将通过分别量化热机械加工期间和之后的织构演变和板材成形性以及优化加工参数，帮助美国铝工业显着提高连铸铝合金的成形性。 通过该研究和教育计划培训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。 将研究融入教学和实验室项目将使学生受益，并为他们获得科学技术领域的职业或高等教育机会做好准备。