Characterization of EAF and LF Slags Through an Upgraded Stationary Flowsheet Model of the Electric Steelmaking Route
Open Access
Abstract
The current, continuous increase in attention toward preservation of the environment and natural resources is forcing resource-intensive industries like steelworks to investigate new solutions to improve resource efficiency and promote the growth of a circular economy. In this context, electric steelworks, which inherently implement circularity principles, are spending efforts to enhance valorization of their main by-product, namely slags. A reliable characterization of the slag’s composition is crucial for the identification of the best valorization pathway, but, currently, slag monitoring is often discontinuous. Furthermore, in the current period of transformation of steel production, preliminary knowledge of the effect of modifications of operating practices on slags composition is crucial to assessing the viability of these modifications. In this paper, a stationary flowsheet model of the electric steelmaking route is presented; this model enables joint monitoring of key variables related to process, steel and slags. For the estimation of the content of most compounds in slags, the average relative percentage error is below 20% for most of the considered steel families. Thus, the tool can be considered suitable for scenario analyses supporting slag valorization. Higher performance is achievable by exploiting more reliable data for model tuning. These data can be obtained via novel devices that gather more numerous and representative data on the amount and composition of slags.Keywords
Funding Information
- Research Fund for Coal and Steel (899164)
This publication has 33 references indexed in Scilit:
- Progress Toward Biocarbon Utilization in Electric Arc Furnace Steelmaking: Current Status and Future ProspectsJournal of Sustainable Metallurgy, 2024
- Rapid quantitative analysis of slag acidity by laser induced breakdown spectroscopy combined with random forestChinese Journal of Analytical Chemistry, 2022
- Future Scenarios for Reducing Emissions and Consumption in the Italian Steelmaking IndustrySteel Research International, 2022
- Effect of Slag Composition on Dephosphorization and Foamability in the Electric Arc Furnace Steelmaking Process: Improvement of Plant OperationMetallurgical and Materials Transactions B, 2021
- A Deep Learning-based approach for forecasting off-gas production and consumption in the blast furnaceNeural Computing and Applications, 2021
- Scenario Analyses for By‐Products Reuse in Integrated Steelmaking Plants by Combining Process Modeling, Simulation, and Optimization TechniquesSteel Research International, 2019
- Improving the Modeling of Slag and Steel Bath Chemistry in an Electric Arc Furnace Process ModelMetallurgical and Materials Transactions B, 2019
- Internal Slags Reuse in an Electric Steelmaking Route and Process Sustainability: Simulation of Different Scenarios Through the EIRES Monitoring ToolWaste and Biomass Valorization, 2018
- Comprehensive Electric Arc Furnace Model for Simulation Purposes and Model-Based ControlSteel Research International, 2016
- Process integration analysis and some economic-environmental implications for an innovative environmentally friendly recovery and pre-treatment of steel scrapApplied Energy, 2016