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dc.contributor.authorPustějovská, Pavlína
dc.contributor.authorBilík, Jiří
dc.contributor.authorJursová, Simona
dc.contributor.authorKardas, Edyta
dc.contributor.authorKonstanciak, Anna
dc.date.accessioned2023-11-22T10:56:04Z
dc.date.available2023-11-22T10:56:04Z
dc.date.issued2023
dc.identifier.citationProcesses. 2023, vol. 11, issue 1, art. no. 79.cs
dc.identifier.issn2227-9717
dc.identifier.urihttp://hdl.handle.net/10084/151771
dc.description.abstractThis article was conducted within the framework of project reg. no. CZ.11.4.120/0.0/0.0/ 16_013/0002594, programme, Interreg V-A Czech Republic-Poland, Microprojects Fund 2014–2020 in the Euroregion Silesia. It is focused in the area of modelling technological processes and the presentation of the main principles of these models. The modelling of technological processes is important in terms of its applicability to process prediction in industry. A complex of analytical and predictive metallurgical models was developed within VSB-TUO. The original mathematical model of coke degradation in a blast furnace makes it possible to calculate the minimum consumption of coke from the dynamic balance for different values of the ratio of direct and indirect reduction. As part of the graphic output, it determines the practically and theoretically achievable minimum coke consumption points. The use of the model enables the determination of a real reserve in reducing the amount of coke.cs
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofseriesProcessescs
dc.relation.urihttps://doi.org/10.3390/pr11010079cs
dc.rights© 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution.cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectthermodynamic and kinetic modelscs
dc.subjectblast furnace shaftcs
dc.titlePrediction of the consumption of raw materials and fuels for the blast furnacecs
dc.typearticlecs
dc.identifier.doi10.3390/pr11010079
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume11cs
dc.description.issue1cs
dc.description.firstpageart. no. 79cs
dc.identifier.wos000927311600001


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© 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution.
Except where otherwise noted, this item's license is described as © 2023 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution.