We introduced the term "intelligent" digital twin in this article, as the approach combines fundamental-based models with data-driven methods. By merging the strengths of both, it creates models with significantly improved properties compared to existing ones.
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A significant advantage is the abundance of journals offering free access to science-based studies on the concept of digital twins. This easy, open access to relevant publications presents an excellent opportunity to explore the topic in greater detail.
Effective steelmaking modeling requires both practical knowledge and scientific fundamentals. This article outlines key disciplines, evaluates holistic models, and proposes a structured approach to model development.
We checked the results of 32 empirical equations for calculating the liquidus temperature on typical low alloyed and stainless steels. In addition, the voestalpine slide rule was used to determine the liquidus temperature and compared with the results of the formulas from the relevant literature.
Based on our software, quasi-binary Fe-C phase diagrams for steels are generated quickly and easily. Although the Fe-C diagram is crucial, additional elements and cooling rates alter phase areas, which is vital for preventing cracking during continuous casting.
It takes effort to understand data and information, it takes effort to know and derive skills from it and it takes effort to gain wisdom. When we part with linearity and recognize that the path to wisdom requires many learning loops, real added value can arise.