## 4 Conclusions  
Water-cooling is an important component of steelmaking technology. The purpose of cooling is not to only remove as much amount of heat as possible in the shortest possible time, but also carry out this operation in a controlled manner. This ensures obtaining a product with the searched properties. As part of this work, three cooling systems used for high-temperature processes were assessed: AAS, WS and JET. The assessment was made by identifying the HTC and HF on the surface of the sensor cooled with water. The identification of the boundary condition of heat transfer was performed using the inverse method. The solution of the heat conduction equation was obtained using the finite element method. The obtained results of the calculations indicate that the accuracy of the inverse solution is high, and the average temperature error ranged from 0.1 K to 0.9 K. The accuracy of the heat conduction model was tested based on the reference boundary condition model similar to the experimental conditions. The average error of the solution was 0.17 K.  
Based on the results of the analysis, the following conclusions were defined:  
* The analyzed systems did not allow for obtaining a homogeneous distribution of the HTC on the surface. The smallest maximum differences in HTC distribution were obtained for the AAS system (11,200 W/m\({}^{2}\)K). * The ability of the fluid to dissipate heat from the surface was the highest for the AAS system and it increased with increasing water pressure (the increase in pressure from 0.1 MPa to 0.2 MPa caused an over 47% increase in the ability of water to dissipate heat). For the other considered systems, the relationship was reversed. * The highest amount of heat dissipating from the surface in the boiling range was obtained for the WS cooling system. A 17.55% increase in the amount of heat dissipating from the surface at a pressure of 0.05 MPa, a 16% increase at a pressure of 0.1 MPa and a 12.28% increase at a pressure of 0.2 MPa were achieved compared to the amount of heat dissipating during AAS-cooling. The obtained result was influenced by the low thermal conductivity of the tested material and material thickness. Further research is necessary to investigate the effect of material conductivity on the amount of energy dissipating from a cooled surface and the change in material temperature depending on the used cooling system. This approach will allow for verification if the impact of the adopted cooling system is noticeable for materials with different thermal conductivities, and indicates which cooling systems are suitable for cooling materials with specific properties. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Type of Cooling**} & \multirow{2}{*}{**Pressure, MPa**} & \multirow{2}{*}{\(\tau_{S}\), **s**} & \multicolumn{2}{c}{**Temperature at**} & \multicolumn{2}{c}{**Temperature at**} \\  & & & **Point P4 Obtained at** & \multirow{2}{*}{\(\tau_{E}\), **s**} & **Point P4 Obtained at** \\  & & & & **Time \(\tau_{E}\), \({}^{\circ}\)C** & **Time \(\tau_{E}\), \({}^{\circ}\)C** \\ \hline \multirow{3}{*}{AAS} & 0.05 & 34 & 422.3 & 59 & 237.6 \\ \cline{2-6}  & 0.1 & 30 & 447.8 & 56 & 254.5 \\ \cline{2-6}  & 0.2 & 29 & 423.0 & 53 & 253.9 \\ \hline \multirow{3}{*}{WS} & 0.05 & 36 & 390.3 & 65 & 214.2 \\ \cline{2-6}  & 0.1 & 36 & 391.9 & 62 & 213.8 \\ \cline{2-6}  & 0.2 & 30 & 430.7 & 56 & 242.1 \\ \hline \multirow{3}{*}{JET} & 0.05 & 39 & 372.4 & 68 & 197.9 \\ \cline{2-6}  & 0.1 & 32 & 417.9 & 57 & 245.2 \\ \cline{1-1} \cline{2-6}  & 0.2 & 30 & 433.4 & 54 & 252.0 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Temperature reached at point P4 at times \(\tau_{S}\) and \(\tau_{E}\). **Author Contributions:** E.J. : Formal analysis, investigations, writing--original draft, visualization. B.H. : Conceptualization, validation, formal analysis, investigations, writing, supervision. A.C.-R.: Writing--review and editing, formal analysis. Z.M. : Software. K.J. : Investigation, visualization. D.S. : supervision, visualization.