Search Results (158)

Accurate endpoint control in basic oxygen furnace (BOF) steelmaking is essential for reducing production costs and improving steel quality. To overcome the limited mechanism support and poor transparency of purely data-driven models, this study proposes a physics-aware and interpretable framework for cumulative decarburization prediction based on real industrial data. Historical multi-heat data from the same converter were integrated, and an averaged full-spectrum cross-correlation method was used to estimate and correct the transport delay of off-gas signals, thereby constructing a heat-wise large-sample dataset. Key elemental features with clear physical significance were then extracted from high-dimensional flame spectra by incorporating their underlying radiation mechanisms. On this basis, a Stacking-based ensemble model was developed for cumulative decarburization prediction, and SHAP was introduced to interpret the model decision logic. Results show that the proposed framework outperforms conventional single models and purely data-driven dimensionality reduction methods. SHAP analysis further indicates that model decisions are mainly dominated by four core elemental spectral features, namely Fe, C, O, and Mn. Overall, the proposed method combines predictive performance, physical constraints, and interpretability, and provides a new solution for auxiliary soft sensing and decision support in BOF endpoint control. Full article

Carryover slag (COS) entrained from the basic oxygen furnace (BOF) during tapping is highly oxidizing and affects secondary steelmaking by increasing deoxidizer consumption, refractory wear, P reversion, and decreasing steel cleanliness. A kinetic COS amount estimation model was developed by using the effective equilibrium reaction zone (EERZ) method. The amount of COS was determined by iteratively adjusting the carryover slag coefficient (CSC) until predicted steel and slag compositions approached industrial measurements. Validation with four industrial heats confirmed that the model effectively predicts COS under both complete and incomplete deoxidation conditions. Further simulation results show that increasing the CSC from 2 to 4 kg per tonne of steel leads to 9.3 ppm P reversion. The calculations also confirmed that larger COS amounts accelerate refractory wear due to the higher input of readily reducible components, particularly FeO and MnO. Full article

Reducing the carbon footprint of cement based materials requires approaches beyond replacing cement alone. Mineral carbonation of aggregates offers a simple route to store carbon dioxide permanently while improving material performance. In this study, four steel slag aggregates were evaluated as sand replacements in mortar after pre carbonation, including basic oxygen furnace slag, blast furnace slag, skim slag, and Rockport slag. The aggregates were treated using moisture assisted carbonation with carbon dioxide and then used in mortar made under the same mix design and curing conditions. Bulk chemistry was determined by X-ray fluorescence, carbon uptake was quantified by thermogravimetric analysis, and performance was evaluated using compressive strength, ultrasonic pulse velocity, chemical soundness, freeze thaw resistance, and scanning electron microscopy. Pre-carbonation stored approximately 14–19 wt% CO₂ relative to the dry mass of the slag aggregates, depending on slag type. Mortars with carbonated basic oxygen furnace slag and carbonated blast furnace slag showed clear strength gains at 28 days, along with higher ultrasonic pulse velocity and improved chemical durability. Rockport slag showed modest improvement, while skim slag showed a reduction in strength after carbonation. Microstructural observations indicate that carbonate precipitation filled pores and densified the aggregate paste interface, which explains the strength and durability improvements in the more responsive slags. These laboratory-scale results show that, under the specific moisture-assisted pre-carbonation conditions investigated, pre-carbonation of slag aggregates can combine permanent CO₂ storage with improved mortar performance. However, the magnitude of these benefits depends strongly on slag chemistry and particle structure, highlighting the need for slag-specific carbonation design and further validation under practical conditions. Full article

In this study, CaO-SiO₂-Al₂O₃-MgO-TiO₂ slag was used as the research object to simulate the blast furnace ironmaking process. Based on the experimental data, the influences of basicity (R(w(CaO)/w(SiO₂))) and the magnesia–alumina ratio (w(MgO)/w(Al₂O₃)) on desulfurization ability are discussed. Additionally, the influences of dissimilarity, basicity, and the magnesia–alumina ratio on slag structure were analyzed using Fourier transform infrared spectroscopy (FT-IR). The results show that when w(Al₂O₃) = 20% and w(MgO)/w(Al₂O₃) = 0.50, sulfide capacity (lgC_s) accretion with the increment in R. Moreover, when w(Al₂O₃) = 20% and R = 1.30, sulfide capacity accretion with the increment in w(MgO)/w(Al₂O₃). Fourier transform infrared spectroscopy was used to confirm that, with increasing basicity and the magnesia–alumina ratio, the concentration of dissociated free oxygen ions (O²⁻) in slag increases, and these ions interact with the bridging oxygen (O⁰) of silicate to depolymerize the complex Si-O structure into simpler units. Full article

Vanadium–titanium magnetite is a strategically important resource for iron, vanadium, and titanium production, yet its utilization in conventional blast furnace–basic oxygen furnace routes is limited by the dilution of titanium into low-value slag. This study investigates an integrated process route combining pellet preparation, hydrogen-based shaft furnace reduction conducted in the temperature range of 800–1000 °C, and subsequent electric furnace smelting for efficient recovery of Fe, V, and Ti. Pellets prepared from 100 wt.% vanadium–titanium magnetite exhibited sufficient mechanical strength but showed poor reducibility and severe low-temperature reduction disintegration, rendering them unsuitable for hydrogen-based shaft furnace operation. To overcome these limitations, systematic ore blending was applied. An optimized pellet composition comprising 40 wt.% vanadium–titanium magnetite, 50 wt.% high-grade iron ore, and 10 wt.% titanium concentrate achieved reduction degrees above 90%, acceptable swelling and bonding behavior, and low reduction disintegration indices meeting industrial HYL requirements. Industrial trials in a hydrogen-based shaft furnace demonstrated stable operation and consistent product quality, producing direct reduced iron with controlled metallization and enrichment of titanium and vanadium. Subsequent electric furnace smelting achieved clear slag–metal separation, yielding hot metal with high iron and vanadium recovery and a TiO₂-rich slag containing approximately 45 wt.% TiO₂. Recovery rates of Fe, V, and Ti exceeded 90%, confirming the technical feasibility of the proposed process route. Full article

Accurately predicting molten steel carbon content plays a crucial role in improving productivity and energy efficiency during the Basic Oxygen Furnace (BOF) steelmaking process. However, current data-driven methods primarily focus on endpoint carbon content prediction, while lacking sufficient investigation into real-time curve forecasting during the blowing process, which hinders real-time closed-loop BOF control. In this article, a novel Transformer-based framework is presented for real-time carbon content prediction. The contributions include three main aspects. First, the prediction paradigm is reconstructed by converting the regression task into a sequence classification task, which demonstrates superior robustness and accuracy compared to traditional regression methods. Second, the focus is shifted from traditional endpoint-only forecasting to long-term prediction by introducing a Transformer-based model for continuous, real-time prediction of carbon content. Last, spatial–temporal feature representation is enhanced by integrating an optical flow channel with the original RGB channels, and the resulting four-channel input tensor effectively captures the dynamic characteristics of the converter mouth flame. Experimental results on an independent test dataset demonstrate favorable performance of the proposed framework in predicting carbon content trajectories. The model achieves high accuracy, reaching 84% during the critical decarburization endpoint phase where carbon content decreases from 0.0829 to 0.0440, and delivers predictions with approximately 75% of errors within ±0.05. Such performance demonstrates the practical potential for supporting intelligent BOF steelmaking. Full article

Scrap steel is known to influence the fluid flow characteristics of the melt pool in converter steelmaking. However, few studies have considered the effects of the scrap steel charging structure. In this study, a physical model of a 1:8.8 steel–scrap–gas three-phase flow converter was established to investigate the effects of scrap steel state, distribution, material type and shape on the fluid flow characteristics of the converter melt pool. The velocity distribution within the molten pool was measured using particle image velocimetry, while mixing time under various operating conditions was determined using the stimulus–response method. Considering the melting behaviour of scrap steel and the gas utilisation rate comprehensively, the results indicate that when scrap steel is arranged in a uniform position at the bottom of the converter—comprising 90% medium scrap in rectangular scrap and 10% heavy scrap in thin-plate form—and the gas flow rate is 750 m³/h, the overall dynamic conditions of the melt pool are optimal. At this time, the mixing time is 68.2 s (a reduction of up to 45.4%), average velocity is 0.117 m/s (a maximum increase of 207.9%) and turbulent energy dissipation rate is 0.0266 m²/s³ (a maximum increase of 141.8%). Finally, a relationship was established between stirring power and mixing time at different scrap steel charging structures, providing a methodological reference and data support for optimising the charging structure of scrap steel and efficiently using scrap steel in converters. Full article

The global transition toward a low-carbon economy has intensified the interest in green hydrogen as a key enabler of industrial decarbonization. In particular, the steel sector, one of the most carbon-intensive industries, offers significant opportunities for emissions reduction through H₂-based technologies. This study presents a techno-economic assessment of alternative green hydrogen supply pathways, namely alkaline electrolysis and ammonia cracking, and evaluates their integration into hydrogen-based direct reduction (HyDR) routes. Process simulations are performed using Aspen Plus^® V14 to quantify the energy consumption, hydrogen demand, and associated CO₂ emissions across multiple configurations and case studies. A comprehensive 3E (energy, economics, and environmental) evaluation framework is applied to compare system performance and assess the suitability of each pathway for large-scale deployment. The results indicate that ammonia cracking represents a technically viable and potentially competitive hydrogen supply option for steel decarbonization under the assumed operating conditions, highlighting its relevance as a transitional pathway toward low-carbon steel production. Full article

The steel industry contributes to approximately 7%–9% of global anthropogenic CO_2(g) emissions, with traditional blast furnace–basic oxygen furnace (BF–BOF) routes emitting up to 1.8 t_CO2 per ton of steel. In contrast, Electric Arc Furnace (EAF) steelmaking, especially when integrated with hydrogen direct-reduced iron (DRI), can reduce emissions by over 40%, positioning EAFs as a key enabler of low-carbon metallurgy. However, despite its lower direct emissions, the EAF process still depends on fossil carbon sources for slag foaming and FeO reduction, which are essential for arc stability and energy efficiency. Slag foaming plays a critical role in controlling the thermal efficiency of the EAF by shielding the electric arc, reducing radiative heat losses, and stabilizing the arc’s behavior. This review examines the mechanisms of slag foaming, discussed through empirical models that consider the foaming index (Σ) and slag foaming rate as critical parameters, and highlights the influence of physical properties such as slag viscosity, surface tension, and density on gas bubble retention. Also, the work embraces the potential use of alternative carbon sources including biochar, biomass, and waste-derived materials such as plastics and rubber to replace fossil-based reductants and foaming agents in EAF operations. Finally, it discusses the use of new materials with a biological base, such as nanocellulose, to serve as reactive templates for producing nanohybrid materials, containing both oxides, which can contribute to slag basicity (MgO and/or CaO, for example), together with a reactive carbonaceous phase, derived from the organic fiber’s thermal degradation, which could contribute to slag foaming, and could replace part of the fossil fuel charge to be employed in the EAF process. In this context, the development and characterization of renewable carbonaceous materials capable of simultaneously reducing FeO and promoting slag foaming are essential to achieving net-zero steel production and enhancing the sustainability of EAF-based steelmaking. Full article

This paper analyses the factors that affect CO₂ emissions in the BF-BOF steelmaking process using a dynamic econometric approach based on annual data from the Polish steel industry. The analysis commences with the estimation of a baseline dynamic model that describes the relationship between CO₂ emissions in the industry and investment allocations, crude steel production, and lagged CO₂ emissions. The baseline analysis illustrates the dominant feature of strong emission level persistence and poor tracking of selected conventional production-related factors. The analysis proceeds by extending the baseline results through additional consideration of technological factors, material composition factors, and resource use factors in the generation of CO₂ emissions. The additional factors include the use of coke, electricity consumption, fixed asset value, and the scrap ratio. The analysis indicates that these additional factors are essential in improving the accuracy of the modeling process and in clarifying the significance of material composition in CO₂ emissions in particular. The analysis further illustrates the critical result that increased use of electricity leads to high CO₂ emissions in the BF-BOF process. Further analysis indicates that increasing the use of steel scrap leads to substantial CO₂ reductions in the BF-BOF route and other steelmaking technologies. The results also show that CO₂ emissions in the BF-BOF process depend not only on production volume, but also on material composition and the technological structure of the process. In the context of the WFESF project, these findings provide evidence-based guidance for metal industry research by identifying priority levers for mitigation, particularly through improvements in process technology and scrap-based material substitution. Full article

The Turkish steel industry aims to reduce its sectoral carbon dioxide (CO₂) emissions by 55% by 2030, in line with Türkiye’s Paris Agreement commitments and the European Green Deal (EGD), and consistent with the ambition of the European Union’s economy-wide ‘Fit for 55’ emissions-reduction target. Türkiye faces significant challenges in achieving net-zero greenhouse gas (GHG) emissions, particularly as a developing country confronting the impacts of climate change and in the market situation, such as the effects of the ongoing Russia-Ukraine conflict, limited access to affordable raw materials, and rising operational costs. This study serves as a guideline for the Turkish steel sector’s roadmap towards modernization and eventual compliance with net-zero targets. The consideration and integration of new technologies planned for the Turkish steel industry, in both electric arc furnace (EAF) and blast furnace-basic oxygen furnace (BF-BOF) facilities, have been outlined in conjunction with green hydrogen and with Carbon Capture and Storage (CCS) technologies. Four different scenarios were analysed to understand the reduction in CO₂ emissions: (1) In a Business-As-Usual (BAU) scenario without any reduction, (2) 39.9% CO₂ emission reduction with the Moderate scenario, (3) 59.6% reduction with the Advanced scenario, and (4) 82.9% reduction in CO₂ emissions from the Turkish steel sector with the Net-Zero scenario. To quantify the uncertainty in these long-term projections, a Monte Carlo simulation was conducted, generating probabilistic confidence intervals that reinforce the robustness and credibility of the net-zero pathway. The official roadmap for the sector is not available as of today; however, an in-depth discussion with a policy innovation leading to it is the objective of this study. Full article

Nitrogen control in steel production critically influences mechanical properties and product quality, yet traditional mechanistic models struggle to capture complex multivariable interactions across the complete steelmaking chain. This study developed and validated automated machine learning (AutoML) models using Microsoft Azure Machine Learning Studio to predict nitrogen content at four critical stages: desulfurization of pig iron (Stage 1), basic oxygen furnace prior to tapping (Stage 2), secondary steelmaking initiation (Stage 3), and secondary steelmaking finishing (Stage 4). Industrial data from 291 metal samples across 76 heats were collected and processed, with stage-specific models employing stack ensemble architectures combining 4–7 algorithms with feature sets ranging from 12 to 35 variables. The models achieved normalized root mean squared errors between 0.112–0.149, mean absolute percentage errors of 14.6–21.1%, and Spearman correlations of 0.310–0.587, with secondary steelmaking models demonstrating superior performance due to more controlled thermodynamic conditions. All models achieved sub-second prediction latencies suitable for real-time industrial implementation. This research demonstrates that AutoML effectively captures complex physicochemical relationships governing nitrogen behavior throughout the steelmaking process, providing practical solutions for Industry 4.0 applications in steelmaking process control and quality optimization. Full article

This study investigates sustainable alternatives for thermal regulation in building materials by incorporating modified basic oxygen furnace slag (MBOFS) as a partial replacement for natural aggregates in concrete. MBOFS was produced by injecting oxygen and silica sand into molten BOF slag to reduce free CaO and MgO, enhancing stability and suitability for cementitious composites. Characterization revealed high mid-infrared emissivity (up to 95.92% in the 8–13 μm range), low solar reflectivity, and high absorptance—properties favorable for passive radiative cooling. Optical, physical, mechanical, and thermal evaluations included spectral analysis, tests for density, porosity, compressive strength, and indoor irradiation with heat flux and temperature monitoring. Increasing MBOFS content raised thermal resistance from 0.034 to 0.069 m²·K/W and lowered thermal transmittance from 3.644 to 3.235 W/m²·K. Higher heat storage capacity and higher emissivity (thermal radiation) suppress the thermal transmittance, thus improving the thermal resistance of the building walls. The 60% replacement showed the most balanced surface thermal response, whereas higher ratios yielded greater energy retention. These results demonstrate that MBOFS can enhance insulation, radiative cooling, and mechanical performance, advancing climate-responsive concrete for urban heat island mitigation. Full article

Intensive calcination, selection and metallurgical joint comprehensive utilization of solid waste blast furnace gas ash generated by a Chinese iron and steel plant. The main valuable elements in the gas ash are Fe, Pb, Zn, and C, with contents of 22.46%, 3.22%, 10.57%, and 27.02%, respectively. The iron minerals are mainly magnetite and hematite/limonite. Lead exists primarily in the form of lead vanadate and basic lead chloride. Zinc is associated with oxygen, sulfur, and iron in the form of zinc ferrite crystals. The effects of calcination temperature, calcination time, and reducing agent dosage on gasification and reduction indices were investigated. Results showed that using a gasification and reduction calcination–magnetic separation process with weak magnetism, at a calcination temperature of 1150 °C, with 20% anthracite as the reducing agent and a calcination time of 2 h, the volatilization rates of lead and zinc reached 96.70% and 98.26%, respectively. When the roasted ore was ground to a particle size of D₉₀ = 0.085 mm, high-quality iron concentrate with 65.61% iron grade and low lead and zinc contents of 0.08% and 0.17% was obtained, meeting the quality requirements for iron concentrate. The tailings from iron selection can be used as additives in cement and other construction materials. This integrated process combining pyrometallurgy and mineral processing enables the efficient and comprehensive utilization of blast furnace gas dust. Full article

Basic oxygen furnace slag (BOFS) is one of the major by-products of the steelmaking industry. Its limited utilization as a construction material is primarily attributed to its chemical properties, which hinder its stability and hydraulic activity due to its high free lime (f-CaO) content. This paper explores the performance of supplementary cementitious material (SCM) synthesized with ground granulated blast furnace slag (GGBFS), freshly produced BOFS (f-BOFS), and stockpiled BOFS (s-BOFS). A total of 10 mixtures with ordinary Portland cement (OPC) replacement percentages were assessed, maintaining a total replacement of 50% OPC, incorporating 15%, 25%, and 35% of each material by weight. The laboratory experimental program encompassed material characterization, fresh and hardened properties, pozzolanic activity, and durability assessment, with comparative studies conducted for each evaluation item. Test results indicate that f- or s-BOFS, when used with GGBFS, can be a viable alternative SCM with the potential for hydraulic activities and pozzolanic reaction. The newly synthesized SCMs demonstrated improved strength development in mortar mixtures. The mixture containing [15% f-BOFS + 35% GGBFS] achieved a 28-day compressive strength of 20.6 MPa, while the [25% BOFS + 25% GGBFS] blend reached a compressive strength of 19.7 MPa. These mixtures meet Grade 80 criteria as per ASTM C989/C989M Standard Specification for Slag Cement for Use in Concrete and Mortars. A performance-based ranking system was developed by integrating results from flowability, air content, strength activity index, drying shrinkage, alkali–silica reaction, and sulfate attack. The novelty of this work lies in assessing BOFS–GGBFS blends as SCMs using this multi-criteria approach to identify the most sustainable and technically viable mixtures. Moreover, the study highlights the influence of storage-induced weathering by directly comparing the reactivity and performance of f- and s-BOFSs in ternary blends, providing new insights into optimizing the utilization of slag. Notably, regardless of f- and s-BOFSs, proportions of [15% BOFS + 35% GGBFS] demonstrated superior strength development and achieved an excellent overall ranking. These findings confirm the potential of such slag blends as suitable SCMs for mortar and concrete applications, thereby advancing the sustainability and efficiency of cementitious materials. Full article