GOALI/IUCRP: Modeling, Simulation, and Optimization of Strip Casting Processes

9416304 萨海 不锈钢、普通碳钢和铝的薄带连铸工艺正在世界各地的公司中开发。 虽然工业成员已经证明了经验可行性，但对该工艺的理解还不足以提供稳健生产操作的工艺参数，以实现最大产量。 在这项研究中，将进行数值模拟，并验证与工业数据，从单辊以及双辊薄带连铸机在铝以及钢。 该模型可以预测冷却速度，冷却速度控制着铸带的显微组织，而显微组织又决定着铸带的最终机械性能。 这项研究将与坦普尔大学和德雷克塞尔大学的类似研究相结合。 在目前的制造实践中，用于制造车身的薄钢板和厨房中使用的薄铝箔，从大锭开始，经过多次轧制以降低厚度。 这一过程涉及多个制造步骤，消耗大量能源，增加在制品（库存）并减缓向客户交付的速度。 这种直接铸造带材的新方法如果被很好地理解并控制到高度可靠性而不牺牲产量，则具有显著降低制造成本的潜力。 国际竞争激烈，因为初级金属行业的风险很高。 在这项研究中，与国内钢铁和铝工业合作伙伴的合作将极大地帮助研究内容和制造相关性。

9416304 Sahai Thin Strip casting process for stainless and plain carbon steel, and aluminum are under development in companies around the world. While empirical feasibility has been demonstrated by industrial members, the process is not sufficiently well understood to provide the process parameters for robust manufacturing operation to achieve maximum yield. In this research, numerical simulation will be carried out and verified with industrial data from both Single Roller as well as Twin Roller Strip Casters in aluminum as well as steel. The ensuping model can predict the rate of cooling which controls the microstructure which in turn determines the final mechanical properties of the cast strip. This research will dove tail with similar effort at Temple University and Drexel University. In the current manufacturing practice, thin steel sheets used to build car bodies and thin aluminum foils used in the kitchen, start as large ingots and are rolled numerous times to bring the thickness down. This process involves several manufacturing steps consuming lots of energy, adding to work in process (inventory) and slowing delivery to customers. This novel approach of casting strips directly if well understood and controlled to a high degree of reliability without sacrificing yields has the potential to reduce the manufacturing cost significantly. International competition is intense since the stakes are high for primary metals industry. Proposed collaboration with domestic steel and aluminum industrial partners in this research will immensely help both research content and manufacturing relevance.