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Multi-Parameter Characteristics of Electric Arc Furnace Melting

The article presents the results of analyses of numerical modelling of selected factors in electric arc furnace melts. The aim of the study was to optimise the melting process in an electric arc furnace using statistical-thermodynamic modelling based on, among other things, multiple linear regressio...

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Autores principales: Moskal, Michał, Migas, Piotr, Karbowniczek, Mirosław
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8878267/
https://www.ncbi.nlm.nih.gov/pubmed/35208138
http://dx.doi.org/10.3390/ma15041601
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author Moskal, Michał
Migas, Piotr
Karbowniczek, Mirosław
author_facet Moskal, Michał
Migas, Piotr
Karbowniczek, Mirosław
author_sort Moskal, Michał
collection PubMed
description The article presents the results of analyses of numerical modelling of selected factors in electric arc furnace melts. The aim of the study was to optimise the melting process in an electric arc furnace using statistical-thermodynamic modelling based on, among other things, multiple linear regression (MLR). The article presents tools and methods which make it possible to identify the most significant indicators of the process carried out on the analysed unit from the point of view of improvement. The article presents the characteristics of the process and creation of the MLR model and, by applying its numerical analyses and results of calculations and simulations for selected variables and indicator, identifying the operation of a selected furnace. Developed model to demand of electric energy identification was used for calculations of energy balances, the distribution of the energy used in the furnace was presented.
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spelling pubmed-88782672022-02-26 Multi-Parameter Characteristics of Electric Arc Furnace Melting Moskal, Michał Migas, Piotr Karbowniczek, Mirosław Materials (Basel) Article The article presents the results of analyses of numerical modelling of selected factors in electric arc furnace melts. The aim of the study was to optimise the melting process in an electric arc furnace using statistical-thermodynamic modelling based on, among other things, multiple linear regression (MLR). The article presents tools and methods which make it possible to identify the most significant indicators of the process carried out on the analysed unit from the point of view of improvement. The article presents the characteristics of the process and creation of the MLR model and, by applying its numerical analyses and results of calculations and simulations for selected variables and indicator, identifying the operation of a selected furnace. Developed model to demand of electric energy identification was used for calculations of energy balances, the distribution of the energy used in the furnace was presented. MDPI 2022-02-21 /pmc/articles/PMC8878267/ /pubmed/35208138 http://dx.doi.org/10.3390/ma15041601 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Moskal, Michał
Migas, Piotr
Karbowniczek, Mirosław
Multi-Parameter Characteristics of Electric Arc Furnace Melting
title Multi-Parameter Characteristics of Electric Arc Furnace Melting
title_full Multi-Parameter Characteristics of Electric Arc Furnace Melting
title_fullStr Multi-Parameter Characteristics of Electric Arc Furnace Melting
title_full_unstemmed Multi-Parameter Characteristics of Electric Arc Furnace Melting
title_short Multi-Parameter Characteristics of Electric Arc Furnace Melting
title_sort multi-parameter characteristics of electric arc furnace melting
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8878267/
https://www.ncbi.nlm.nih.gov/pubmed/35208138
http://dx.doi.org/10.3390/ma15041601
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