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

9416304萨海薄带连铸不锈钢、普通碳钢和铝的工艺在世界各地的公司都在开发中。虽然工业成员已经证明了经验上的可行性，但对该过程的理解还不够充分，无法为稳健的制造操作提供实现最大产量的过程参数。在本研究中，将进行数值模拟，并用铝和钢的单辊和双辊薄带连铸机的工业数据进行验证。消耗模型可以预测冷却速度，冷却速度控制着铸带的组织，进而决定了铸带的最终力学性能。这项研究将在坦普尔大学和德雷克塞尔大学进行类似的研究。在目前的生产实践中，用于制造汽车车身的薄钢板和用于厨房的薄铝箔，一开始是大钢锭，然后被多次轧制，以降低厚度。这一过程涉及几个制造步骤，消耗大量能源，增加在制品(库存)，并减缓向客户交付。这种直接浇铸薄带的新方法，如果得到很好的理解和控制，在不牺牲产量的情况下达到高度可靠性，就有可能显着降低制造成本。由于初级金属行业的风险很高，国际竞争非常激烈。在这项研究中，建议与国内钢铁和铝工业合作伙伴合作，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.