Bösenhofer, M., Hauzenberger, F., Stocker, H., Feilmayr, C., & Harasek, M. (2023). An Eulerian-Based Reduction Model for Iron Ore Particle Reduction. In AISTech2023 Proceedings of the Iron & Steel Technology Conference (pp. 358–365). Association for Iron and Steel Technology (AIST). https://doi.org/10.33313/387/039
E166-02-2 - Forschungsgruppe Fluiddynamische Simulation (CFD) E166-02 - Forschungsbereich Thermische Verfahrenstechnik und Simulation E166 - Institut für Verfahrenstechnik, Umwelttechnik und technische Biowissenschaften
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Published in:
AISTech2023 Proceedings of the Iron & Steel Technology Conference
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ISBN:
9780930767204
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Date (published):
7-May-2023
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Event name:
AISTech 2023
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Event date:
8-May-2023 - 10-May-2023
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Event place:
Detroit, MI, USA, United States of America (the)
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Number of Pages:
8
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Publisher:
Association for Iron and Steel Technology (AIST)
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Keywords:
CFD; iron ore reduction; representative particle model (RPM); full-scale blast furnace model
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Abstract:
Reasonable iron ore reduction and melting prediction are critical issues for blast furnace modeling. The particle number required for full-scale blast furnace simulations exceeds the current capabilities of discrete element method (DEM) approaches. Continuum or Euler-based approaches can handle industry-scale equipment at reduced accuracy. This work explores the capabilities of a novel Eulerian-based reduction model based on a multi-fluid simulation framework. The reduction model uses a layer-like approach based on the representative particle assumption, and its performance is validated and evaluated against lab-scale experimental data.
