Secondary steelmaking process stream optimization - inclusions, clogging, and segregation

二次炼钢工艺流程优化 - 夹杂物、堵塞和偏析

• 批准号: 534082-2018
• 负责人: Phillion, AndréBernardAB
• 金额: $ 6.91万
• 依托单位: McMaster University
• 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=758229
• 关键词: Secondary; steelmaking; process; stream; optimization

Micro-particles in steel, also known as inclusions, are highly undesirable. Although modern steelmaking practices have been developed to mitigate most of the deleterious effects, inclusions are detrimental to the properties of the final product, they clog the submerged entry and metering nozzles that transfer molten steel from secondary steelmaking to the continuous casting process stages, and they affect solute segregation / microstructure evolution during casting. At present, these issues are dealt with by (a) dissolving inclusions in a liquid oxide system (slag) during ladle metallurgy, (b) calcium treatment for shape control and (c) frequent replacement of the SENs. Each of these mitigation strategies has their own consequences that negatively impact product quality. Given the impact of inclusions on steel quality, there is need to optimize the secondary steelmaking process stream from the Ladle Metallurgy Furnace (LMF) to the cast product.In this collaborative study with Gerdau and Laurel steel, a suite of fundamental models will be developed that predict steel cleanliness in a wide range of steelmaking practices and products in the LMF, nozzle clogging based on interactions between the melt and the inner surface of the SEN, and subsequent compositional segregation and microstructure development during continuous casting. The models will be verified against plant data and samples taken from the industrial sponsors. Long-term, this set of models will form the basis of an online tool for optimizing the secondary steelmaking process stream. As the models are based on the fundamentals of thermochemistry, transport phenomena, and solidification, a modification procedure will be developed enabling application for any Canadian steel mill.

钢中的微粒，也称为夹杂物，是高度不良的。尽管已经开发出现代的钢制造实践来减轻大多数有害影响，但包含物对最终产品的特性有害，但它们阻塞了被淹没的入口和计量喷嘴，这些喷嘴将熔融钢从次级钢制造转移到连续的铸造过程阶段，并且会影响溶质溶质分析 /微型结构 /微型结构 /微型结构 /微型结构演化。目前，通过（a）将夹杂物溶解在钢包冶金过程中的液体氧化物系统（炉渣）中，（b）钙处理以进行形状控制，（c）经常更换SENS。这些缓解策略中的每一个都有其自身的后果，会对产品质量产生负面影响。鉴于夹杂物对钢质质量的影响，需要优化从钢化冶金炉（LMF）到铸造产品的二级制造过程流。在与Gerdau和Laurel Steel的这项协作研究中，将开发出一组基本模型，可以预测钢层和材料之间的钢层型号的钢层层次，并在材料上进行融合的材料，摩尔在LMF上的融合，并预测LMF的摩尔套装， SEN，以及随后在连续铸造过程中的组成分离和微观结构的发展。这些模型将根据工厂数据和工业赞助商采集的样本进行验证。长期，这组模型将构成在线工具的基础，以优化二级钢制过程流。由于这些模型基于热化学，运输现象和固化的基本原理，因此将开发一种修改程序，从而为任何加拿大钢铁厂提供了应用。