Electromagnetic stirring (EMS) is an efficient technology to control the flow structure in slab continuous casting mold. But there is still an important opened problem to be answered firstly, that is, what kind of flow structure is our goal by using electromagnetic stirring in order to get good casting products, and how to optimize the flow fields in slab continuous casting mold with EMS? Two kinds of research paradigms are proposed in this study. One is based on causal relationship between the flow field and its effects on the mold flux entrapment and solidification process. Two parameters, named Mold Flux Entrapment Index and Velocity Uniform Index were proposed in order to evaluate the flow field in the mold. Based on these two indexes, optimization stirring parameters were proposed under different casting situation. The other research paradigm is machine learning big data model based on correlation analysis of nearly all the input parameters of casting machine and slab quality as an output parameter. Data acquisition from the continuous casting machine, data mining by machine learning algorithms and online automatic control parameters output are three main aspects in the second research frame.
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