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Meeting MS&T24: Materials Science & Technology
Symposium Application of ICME Methods to Advance Sustainable Metallurgy and Metals Processing
Presentation Title Quantifying Pyrometallurgy Process Options with Low-Dimensional Models
Author(s) Petrus C. Pistorius
On-Site Speaker (Planned) Petrus C. Pistorius
Abstract Scope Mass and energy balances, incorporating relevant reaction equilibria, constitute the first hurdle that any proposed process improvement – or a radically new process – must clear. Such balances are also the basis of figures of merit for process changes; the example that will be shown is the use of injectants for partial replacement of coke in blast furnace ironmaking. The relevant values are the oxygen-carrying capacity of the injectant, and the enthalpy change, for system boundaries at the tuyères and the wüstite reserve zone with the blast furnace. Process fundamentals also aid feature engineering in the analysis of large datasets: examples are fitting rate constants to steel refining kinetics (used to analyze the efficacy of ladle stirring), and relating the electricity consumption in electric arc furnace steelmaking to slag volume and the consumption of carbon and oxygen.

OTHER PAPERS PLANNED FOR THIS SYMPOSIUM

A Thermodynamic Analysis of Red Mud Usage for Sustainable Iron and Steel Production
Application of CALPHAD-Based Tools to Develop More Sustainable Alloys and Processing Methods
Application of ICME Methods in Aerospace Applications
CALPHAD Simulations to Assist Sustainable Metal Processing
Green Ironmaking via Ammonia-Based Direct Reduction of Iron Ores
ICME Approaches Towards Sustainable Metal Additive Manufacturing
Pathways for Decarbonizing Steel
Quantifying Pyrometallurgy Process Options with Low-Dimensional Models
Scheil-Gulliver Constituent Diagrams for Designing Recycled Al-Alloys
Screening LCA for Rapid Assessment of Sustainable Production
The Road to Sustainable Steelmaking Technologies: Linking Fundamental and Applied Research Activities
Validation of the Coupled Random Cellular Automata Finite Element Model of Dynamic Recrystallization

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