Visualization of Slag Data for Efficient Monitoring and Improvement of Steelmaking Slag Operation in Electric Arc Furnaces, with a Focus on MgO Saturation

Visualization of Slag Data for Efficient Monitoring and Improvement of Steelmaking Slag Operation in Electric Arc Furnaces, with a Focus on MgO Saturation

Frequent slag sampling and analysis is still the most common method used to investigate and improve slag operation in electric arc furnaces (EAFs) for low-alloyed carbon steelmaking. An MgO saturation diagram for EAF slags was derived from phase equilibrium calculations in the system CaO–MgO–FeO–SiO...

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Bibliographic Details
Main Author: Marcus Kirschen
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Metals
Subjects:
electric arc furnace
process slag
saturation model
process improvement
Online Access:https://www.mdpi.com/2075-4701/11/1/17
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spelling doaj-a26f3457e3874639a0aa03c5fd3571cd2020-12-25T00:03:09ZengMDPI AGMetals2075-47012021-12-0111171710.3390/met11010017Visualization of Slag Data for Efficient Monitoring and Improvement of Steelmaking Slag Operation in Electric Arc Furnaces, with a Focus on MgO SaturationMarcus Kirschen0Thermal Process Engineering, University of Bayreuth, Universitätsstrasse 30, D-94557 Bayreuth, GermanyFrequent slag sampling and analysis is still the most common method used to investigate and improve slag operation in electric arc furnaces (EAFs) for low-alloyed carbon steelmaking. An MgO saturation diagram for EAF slags was derived from phase equilibrium calculations in the system CaO–MgO–FeO–SiO<sub>2</sub>–5%Al<sub>2</sub>O<sub>3</sub> to provide monitoring and interpretation of the slag data with respect to control of MgO saturation, FeO reduction, dissolution from the MgO-based refractory lining, and unusual losses of repair mixes. Examples from 14 industrial EAFs are given.https://www.mdpi.com/2075-4701/11/1/17electric arc furnaceprocess slagsaturation modelprocess improvement
collection DOAJ
language English
format Article
sources DOAJ
author Marcus Kirschen
spellingShingle Marcus Kirschen
Visualization of Slag Data for Efficient Monitoring and Improvement of Steelmaking Slag Operation in Electric Arc Furnaces, with a Focus on MgO Saturation
Metals
electric arc furnace
process slag
saturation model
process improvement
author_facet Marcus Kirschen
author_sort Marcus Kirschen
title Visualization of Slag Data for Efficient Monitoring and Improvement of Steelmaking Slag Operation in Electric Arc Furnaces, with a Focus on MgO Saturation
title_short Visualization of Slag Data for Efficient Monitoring and Improvement of Steelmaking Slag Operation in Electric Arc Furnaces, with a Focus on MgO Saturation
title_full Visualization of Slag Data for Efficient Monitoring and Improvement of Steelmaking Slag Operation in Electric Arc Furnaces, with a Focus on MgO Saturation
title_fullStr Visualization of Slag Data for Efficient Monitoring and Improvement of Steelmaking Slag Operation in Electric Arc Furnaces, with a Focus on MgO Saturation
title_full_unstemmed Visualization of Slag Data for Efficient Monitoring and Improvement of Steelmaking Slag Operation in Electric Arc Furnaces, with a Focus on MgO Saturation
title_sort visualization of slag data for efficient monitoring and improvement of steelmaking slag operation in electric arc furnaces, with a focus on mgo saturation
publisher MDPI AG
series Metals
issn 2075-4701
publishDate 2021-12-01
description Frequent slag sampling and analysis is still the most common method used to investigate and improve slag operation in electric arc furnaces (EAFs) for low-alloyed carbon steelmaking. An MgO saturation diagram for EAF slags was derived from phase equilibrium calculations in the system CaO–MgO–FeO–SiO<sub>2</sub>–5%Al<sub>2</sub>O<sub>3</sub> to provide monitoring and interpretation of the slag data with respect to control of MgO saturation, FeO reduction, dissolution from the MgO-based refractory lining, and unusual losses of repair mixes. Examples from 14 industrial EAFs are given.
topic electric arc furnace
process slag
saturation model
process improvement
url https://www.mdpi.com/2075-4701/11/1/17
work_keys_str_mv AT marcuskirschen visualizationofslagdataforefficientmonitoringandimprovementofsteelmakingslagoperationinelectricarcfurnaceswithafocusonmgosaturation
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