The main concept of this paper is to utilize advanced numerical modelling techniques with self-regulation algorithm in order to reach optimal casting conditions for real-time casting control. Fully 3-D macro-solidification model for the continuous casting (CC) process and an original fuzzy logic regulator are combined. The fuzzy logic (FL) regulator reacts on signals from two data inputs, the temperature field and the historical steel quality database. FL adjust the cooling intensity as a function of casting speed and pouring temperature. This approach was originally designed for the special high-quality high-additive steel grades such as higher strength grades, steel for acidic environments, steel for the offshore technology and so forth. However, mentioned approach can be also used for any arbitrary low-carbon steel grades. The usability and results of this approach are demonstrated for steel grade S355, were the real historical data from quality database contains approximately 2000 heats. The presented original solution together with the large steel quality databases can be used as an independent CC prediction control system.

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A supervision algorithm for controlling of continuous casting (CC) process is presented. The control strategy is based on the observation of temperature distribution through the casting strand. The algorithm is composed of two parts, an original 3D transient numerical model of the temperature field and the fuzzy‐regulation model. The numerical model calculates and predicts the temperature distribution while the fuzzy‐regulation model tracks the temperature in specific areas and tunes the casting parameters such as the casting speed, the cooling intensities in the secondary cooling, etc. The main goal is to keep surface and core temperatures in the specific ranges corresponding with the hot ductility of steel and adequately reacts on the variable casting conditions. The results show good and robust control behavior, fast response to dynamic system changes and general applicability for any CC process.

The fast and accurate modeling of phase change is of a significant importance in many processes from steel casting to latent heat thermal energy storage. The paper presents a numerical case study on the transient 3D heat diffusion problem with phase change. Three different approaches to modeling of the solid–liquid phase change in combination with four commonly used numerical schemes are compared for their efficiency, accuracy, applicability, simplicity of implementation, and robustness. The possibility of parallel decomposition of the approaches is also discussed. The results indicate that the best accuracy was achieved with the second-order implicit methods, and the best efficiency was reached with the simple explicit methods.

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