Scrap is the most important secondary raw material in the transformation to low carbon dioxide (CO<inf>2</inf>) steel. However, the suitable use of different scrap types for producing high quality steels with the right chemical composition is non-trivial. It requires process control and detailed knowledge of all input materials used. SHapley Additive exPlanations (SHAP), a game-theoretic approach, is often used to interpret machine learning models through visualizations and feature attributions. In this paper, we present a novel application of SHAP values. This enables more precise control of material composition in steel production without the need for additional sensors. This makes it extremely practical for real steel production environments and enables better control of the materials used in the steel production process. As a basis for this approach, various machine learning models were trained and the respective SHAP values computed. To validate the approach, the results were compared with the values from the steel plant. Comparing the calculated values with the historical estimates, the results agree for most input materials and target elements. The key innovation lies in using SHAP values not only for model interpretability, but also as a quantitative tool to estimate the chemical content of input materials (e.g., steel scrap) based on process data. The framework enables chemical composition estimation, relying solely on routinely collected process data. This is a novel application of SHAP and allows the back-calculation of predicted values and can be used in a wide range of applications in industry and academia.

Three chemically modified heat-resistant austenitic casting alloys were developed to improve the creep strength of rollers and beams used in rolling beam furnaces within the hot stamping industry. The microstructural features and creep performance of the newly designed alloys were evaluated in comparison to the currently employed casting alloy GX40CrNiSi25-20. The alloy design involved small additions of carbon (C), molybdenum Mo, tungsten (W), and niobium (Nb), along with adjustments in chromium (Cr) content, aimed at enhancing creep resistance while minimizing susceptibility to σ phase formation. Creep testing was conducted under two conditions: 930 °C at 48 MPa and 950 °C at 25 MPa. Notably, one of the modified alloys demonstrated superior creep performance, exhibiting a rupture life approximately six times longer than that of the reference alloy under both testing conditions. Microstructural analysis revealed the presence of M₂₃C₆-type secondary carbides in all alloys, with variations in composition reflecting the specific alloying element additions. Ageing experiments were performed at 950 °C for durations of 1, 120, 220 and 900 h to investigate the coarsening kinetics of these secondary carbides.

 Magnesia–carbon refractories are widely used as ladle lining materials in steelmaking due to their excellent thermal and chemical stability. Carbon retention is critical for extending refractory lifespan, as carbon loss significantly accelerates wear. Preheating-induced decarburization typically occurs in oxygen-rich atmospheres and in the presence of combustion byproducts from hydrocarbon fuels. This study investigates plasma heating as an alternative preheating method to mitigate initial decarburization. Full-scale industrial trials are conducted using 0.7 and 1.5 MW plasma torches with nitrogen as primary gas. For comparison, a ladle is also preheated using a conventional natural gas burner. Although all samples experience some decarburization, the plasma-heated samples demonstrate the lowest rate, at 0.14 mm h−1, compared to 0.20 mm h−1 for the gas-heated sample. The unexpectedly elevated decarburization in the plasma-treated bricks is attributed to residual oxygen within the ladle during the trials. Additionally, the plasma-heated bricks exhibit reduced surface disintegration and superior structural integrity, attributed to partial sintering at temperatures exceeding 1400 °C and enhanced retention of calcium silicates in intergranular regions. These findings indicate that plasma heating provides improved structural preservation of MgO–C linings, even under partially oxidizing conditions, compared to traditional preheating methods.

This study investigates the use of sustainable hydrochar-mill-scale briquettes for promoting slag foaming in the electric arc furnace (EAF) process. Two types of biochar are tested, namely, a pristine green waste hydrochar (GWH) and its pyrolyzed char (PGWH) produced at 873 K. Each briquette weighs ≈20 g and has Cfix/OFeOx molar ratios ranging from 0.07 up to 0.90. Briquettes are charged into a molten EAF slag (600 g) at 1923 K. Successful foaming is achieved for all seven briquette recipes developed. The maximum slag foaming height is 1.6–2.5 times of the initial slag height, and the slag foaming duration is in the range of 1.5–3.4 min. GWH briquettes promote rapid slag foaming through the abrupt release of volatile matter, while PGWH briquettes promote a more gradual and long-lasting foaming process through gas production (CO and CO2) from carbothermic reduction. It is estimated that 1 kg of anthracite applied for slag foaming should be replaced by 2.4 kg of GWH or 1.9 kg of PGWH added in composite briquette form. At the given briquette addition rate tested in this study (30 g per kg of slag), no appreciable impurity (sulfur, phosphorous) transfer from hydrochar to the slag is observed.

Vibration measurements are being conducted at an industrial ladle containing molten steel during vacuum degassing at Uddeholms AB, Hagfors, Sweden, using three highly sensitive accelerometers. The accelerometers are installed at different radial positions on the ladle-carrying car to record vibrations generated during argon gas injection under vacuum conditions, in order to study the vibrations generated in an industrial-scale ladle. To gain deeper fundamental knowledge and understanding, a similar methodology and measuring equipment are implemented at a laboratory-scale ladle operating with liquid Sn–40 wt% Bi alloy at 200 °C, integrated into the liquid metal model for steel casting facility at Helmholtz-Zentrum Dresden-Rossendorf (HZDR). The results indicate that bubble evolution events generate vibrations within comparable frequency ranges in both settings. A low-frequency band (100–300 Hz) is observed, associated with bubble generation at the stirring plugs and higher frequency signals (900–1600 Hz) are linked to bubble rupture at the slag-melt interface. The study demonstrates that analyzing the signals in those frequency bands can support the correct installation of gas flow rate and the assessment of gas injection conditions in steelmaking ladles. This study provides fundamental insights for interpreting vibration signals in an industrial setting.

Continuous casting of aluminum (Al) deoxidized steels demands careful inspection due to the occurrence of submerged entry nozzle (SEN) clogging, leading to unexpected production stops. Recognizing the castability of aspecific “cast” by monitoring the condition of the SEN is essential for uninterrupted casting. With this information prior to casting, operators can take preventive action against possible clogging occurrences, thus reducing unplanned downtimes. In response to the severe implications of SEN clogging, this work introduces a novel way to forecast castability of Al-killed steels. A hybrid model is proposed that integrates the adaptive neuro-fuzzy inference system (ANFIS) and long short-term memory (LSTM) networks. The output of the model helps to anticipate the event of clogging by analyzing both the past condition of the SEN and changes in the steel chemistry during the transport of the steel ladle from refining to the casting process. A comprehensive analysis of 150 casts helped to build the ANFIS algorithm for estimating the castability index (CI) parameter from steel chemistry. LSTM algorithm is used as asubsequent step to forecast castability in the next 20–25 min. Discrepancies between the predictive response and the actual conditions are reported. Although the real-time implementation of the proposed model is the ultimate goal, the focus of this work was to present the methodology and demonstrate its potential.

In this paper, we extend a recent asymptotic axisymmetric model for isothermal gas–solid flow in a countercurrent moving-bed reactor to a non-isothermal model for the heat transfer in an ironmaking blast furnace. The appended heat transfer model accounts for conduction, convection, thermal non-equilibrium between the gas and solid phases and the dominant endothermic chemical reaction in the bulk of the furnace, the Boudouard reaction. Asymptotic analysis is used to determine the leading-order heat balances and to interpret numerically obtained solutions for the phase temperatures. Although the model is considerably simpler than the many numerical models that already exist for blast-furnace operation, its future extension would form the basis of a computationally efficient approach for modelling the transient state of a blast furnace.

Vibration measurements provide a promising approach for regulating gas stirring intensity in metallurgical ladles. In this work, vibration measurements are conducted during argon injection into an experimental ladle filled with Sn–40 wt% Bi at 200 °C, integrated into the Liquid Metal Model for Steel Casting facility at Helmholtz-Zentrum Dresden Rossendorf, Germany. Three high-sensitivity accelerometers record vibrations during systematic changes in gas flow rate and pressure above the top free surface. The vibration signals are correlated with visual observations of the free surface to validate bubble behavior and surface disturbances. Results demonstrate that vibration signals qualitatively characterize bubble number and size, with specific frequency ranges associated with bubble formation and collapse. Furthermore, a reduction in pressure at the top free surface leads to an increase in the recorded root mean square vibration values, accompanied by a shift of single-bubble generation to lower frequencies and bubble bursting to higher frequencies. Signal analysis enables the distinction between single bubble flow and regimes where bubble–bubble interactions may occur. The study establishes a fundamental connection between evolving bubble dynamics and the vibrational response of two-phase flows. Data from this work can be used to develop more accurate vibration-based models for stirring monitoring in steelmaking processes.

Macroscopic interactions of liquid iron and solid oxides, such as alumina, calcia, magnesia, silica, and zirconia, manifest the behavior and efficiency of high-temperature metallurgical processes. The oxides serve dual roles, both as components of refractory materials in submerged entry nozzles and also as significant constituents of nonmetallic inclusions in the melt. It is therefore crucial to understand the physicochemical interplay between the liquid and the oxides in order to address the nozzle clogging challenges and thereby optimize cast iron and steel production. This paper presents a methodology for describing these interactions by combining the materials' dielectric responses, computed within the density functional theory, with the Casimir-Lifshitz dispersion forces to generate Hamaker constants. The approach provides a comprehensive understanding of the wettability of iron against these refractory oxides, revealing the complex relation between the molecular and macroscopic properties. Our theoretically determined crystalline structures are confirmed by room-temperature X-ray diffraction, and the contact angles of liquid iron on the oxides are validated with a sessile drop system at a temperature of 1823 K. For comparison, we also present the wettability of the oxides by a liquid tin-bismuth alloy. The findings are essential in advancing the fundamental understanding of interfacial interactions in metallurgical science and pivotal in driving the development of more efficient and reliable steelmaking processes.

In this paper, we investigate the Casimir-Lifshitz free energy mechanism that governs both ice growth and melting near metal surfaces, with a particular focus on the role of oxidation. Our study reveals that metals such as gold, iron, and aluminum induce incomplete premelting, resulting in micron-sized liquid water layers when in contact with ice. These layers could have significant implications for the defrosting of metallic surfaces. When exposed to water vapor at the triple point, aluminum and other metals can induce the formation of notably thick layers of either liquid water or ice, which can theoretically become infinitely thick if other interactions are disregarded. However, when aluminum undergoes oxidation to form alumina, its behavior changes dramatically. Alumina surfaces cause complete melting when in direct contact with bulk ice and result in only micron-sized layers of water or ice in vapor conditions. In contrast, magnetite, the oxidized form of iron, retains metalliclike behavior due to its high dielectric constant, similar to other metals, and continues to support thick layers of water or ice. This distinction highlights the significant influence of oxidation on the dynamics of ice growth and melting near different metal surfaces.