The electric arc furnace operation at the Štore Steel company, one of the largest flat spring steel producers in Europe, consists of charging, melting, refining the chemical composition, adjusting the temperature, and tapping. Knowledge of the consumed energy within the individual electric arc operation steps is essential. The electric energy consumption during melting and refining was analyzed including the maintenance and technological delays. In modeling the electric energy consumption, 25 parameters were considered during melting (e.g., coke, dolomite, quantity), refining and tapping (e.g., injected oxygen, carbon, and limestone quantity) that were selected from 3248 consecutively produced batches in 2018. Two approaches were employed for the data analysis: linear regression and genetic programming model. The linear regression model was used in the first randomly generated generations of each of the 100 independent developed civilizations. More accurate models were subsequently obtained during the simulated evolution. The average relative deviation of the linear regression and the genetic programming model predictions from the experimental data were 3.60% and 3.31%, respectively. Both models were subsequently validated by using data from 278 batches produced in 2019, where the maintenance and the technological delays were below 20 minutes per batch. It was possible, based on the linear regression and the genetically developed model, to calculate that the average electric energy consumption could be reduced by up to 1.04% and 1.16%, respectively, in the case of maintenance and other technological delays.

ŠTORE STEEL Ltd. is one of the three steel plants in Slovenia. Continuous cast 180 mm × 180 mm billets can undergo cooling to room temperature using a turnover cooling bed. They can also be cooled down under hoods or heat treated to reduce residual stresses. Additional operations of heat treatment from 36 h up to 72 h and cooling of the billets for 24 h, with limited capacities (with only two heat treatment furnaces and only six hoods), drastically influence productivity. Accordingly, the casting must be carefully planned (i.e., the main thing is casting in sequences), while the internal quality of the billets (i.e., the occurrence of inner defects) may be compromised. Also, the stock of billets can increase dramatically. As a result, it was necessary to consider the abandoning of cooling under hoods and heat treatment of billets. Based on the collected scrap data after ultrasonic examination of rolled bars, linear regression and genetic programming were used for prediction of the occurrence of inner defects. Based on modeling results, cooling under hoods and heat treatment of billets were abandoned at the casting of several steel grades. Accordingly, the casting sequences increased, and the stock of billets decreased drastically while the internal quality of the rolled bars remained the same.

There is a continuously developing need for benchmarking of solidification simulations - from the theoretical as well as from the applied points of view. The history of related benchmarking shows differences of the results between different numerical methods, and differences in comparison with the experiments when solving even quite simple solidification situations. The present benchmark test proposes a three dimensional version of the recently developed two dimensional solidification benchmark of the continuous casting with turbulent fluid flow and solidification with macrosegregation. The macroscopic transport equations for mass, momentum, energy, species, turbulent kinetic energy and dissipation rate are considered. Turbulent effects are incorporated through the solution of a low-Re turbulence model. The solidification system is treated by the mixture-continuum model, where the mushy zone is modeled as a Darcy porous media with Kozeny-Karman permeability relation and columnar solid phase moving with the casting velocity. The Fe-C binary phase diagram and the lever rule microsegregation model are used to obtain the carbon segregation in the billet. The transport equations are solved by our newly developed and efficient meshless numerical technique, based on local collocation with radial basis functions and fractional step velocity- pressure coupling. The presented results represent first simulations of a three-dimensional solidification problem by a meshless method.

Continuous casting is the most widely used process in the steelmaking industry. Understanding the physical phenomena and modeling them is essential for mitigating casting defects. This study uses a mixture-continuum formulation in axisymmetry to model this process computationally. A physical model incorporating coupled mass, momentum, and energy equations for solidification with melt turbulence was employed, assuming Newtonian, incompressible behavior and the k-epsilon turbulence model. The model provides insights into the thermo-fluid dynamics during solidification. For the numerical simulation, the Local Radial Basis Function Collocation Method (LRBFCM), a meshless approach, is utilized and compared against the more traditional Finite Volume Method (FVM). The results demonstrate that the meshless LRBFCM offers comparable accuracy and convergence to the FVM while reducing the computational complexity associated with mesh generation. These findings suggest that LRBFCM is a viable alternative for simulating complex metallurgical processes, such as continuous casting, with competitive performance.