Innovative Low Melting Liquid Metal Model for Optimizing Argon Injection Practices during Steelmaking and Continuous Casting for Productivity and Quality Improvements

创新的低熔点液态金属模型，用于优化炼钢和连铸过程中的吹氩实践，以提高生产率和质量

• 批准号: 522412-2017
• 负责人: Barati, MansoorM
• 金额: $ 3.75万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=758202
• 关键词: Innovative; Low; Melting; Liquid; Metal

Steelmakers are under constant pressure to increase productivity, and simultaneously maintain high quality of continuously cast steel slabs because of stringent quality demands imposed by their customers. However, increasing productivity has detrimental effects on slab quality, and defects and rejections have a major impact on the producers bottom-line. Controlling fluid flows in continuous casting is one of the key parameters to ensure cleaner steel and reduce defects. Physical and mathematical modeling is an essential tool to understand and optimize fluid flows in continuous casting. However, understanding bubbly and multiphase flows is not an easy task and traditional techniques like water modeling have certain limitations. The use of water models is reasonable and allows for applying a number of well-established measuring methods. However, a generalization of those results to liquid steel flows has to be considered carefully as the true values of flow parameters (Re, Pr, Gr, Ha, etc.) are difficult to meet. In many cases, e.g. for liquid metal flows with strong temperature gradients, for two-phase flows, and of course for applications of electromagnetic fields, the flow phenomena cannot be modeled correctly by means of water experiments. However, on using low melting point metals like (GaInSn alloys, Rose Metal, Field Metal etc.) these parameters are closer to the real steel/Ar system and hence the bubble dynamics and multiphase flow patterns are expected to be more realistic than water modeling. This project will deal with generating fundamental knowledge in the area of bubbly and multiphase flows in steelmaking continuous casting, and its application to improve product quality for AMDs flat products. This research program will utilize physical modeling approach to optimize argon injection during continuous casting and ladle stirring operations. At the caster, the project outcomes are expected to enable the increase of maximum casting speed of drawn & ironed (D&I) and ultra-low carbon (ULC) steel grades. The cost saving arising from improving both liquid and solid steel quality is expected to exceed $10 million/year.

由于客户对质量的严格要求，钢铁制造商在提高生产率的同时保持高质量的连铸板坯。然而，提高生产率对板坯质量有不利影响，缺陷和废品对生产商的底线有重大影响。连铸过程中的流动控制是保证钢水洁净度和减少缺陷的关键参数之一。物理和数学建模是理解和优化连铸中流体流动的重要工具。然而，了解泡状流和多相流并不是一件容易的事情，传统的技术如水模型有一定的局限性。水模型的使用是合理的，并允许应用一些公认的测量方法。然而，将这些结果推广到液态钢流动时，必须仔细考虑流动参数（Re，Pr，Gr，Ha等）的真实值。很难满足。在许多情况下，例如对于具有强温度梯度的液态金属流，对于两相流，当然对于电磁场的应用，流动现象不能通过水实验正确地建模。然而，在使用低熔点金属如（GaInSn合金、Rose Metal、Field Metal等）时，这些参数更接近于真实的钢/Ar系统，因此气泡动力学和多相流模式预期比水模拟更真实。 本项目将涉及在炼钢连铸中气泡和多相流领域的基础知识的产生，及其在提高AMD扁平产品质量方面的应用。本研究计画将利用物理模拟方法，以最佳化在连续铸造及钢包搅拌操作期间之氩气喷吹。在连铸机上，该项目的成果有望提高拉深（D&I）和超低碳（ULC）钢的最大铸造速度。 通过提高液态和固态钢的质量，预计每年可节省超过1000万美元的成本。