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Optimization of Steelmaking Processes in an Electric ARC Furnace.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Optimization of Steelmaking Processes in an Electric ARC Furnace./
作者:	Busa, Neel.
面頁冊數:	1 online resource (71 pages)
附註:	Source: Masters Abstracts International, Volume: 85-01.
Contained By:	Masters Abstracts International85-01.
標題:	Thermodynamics. -
電子資源:	click for full text (PQDT)
ISBN:	9798379874346

Optimization of Steelmaking Processes in an Electric ARC Furnace.
Busa, Neel.

Optimization of Steelmaking Processes in an Electric ARC Furnace. - 1 online resource (71 pages)

Source: Masters Abstracts International, Volume: 85-01.

Thesis (M.Sc.)--Purdue University, 2023.

Includes bibliographical references

The Electric Arc Furnace is being used quite frequently and significantly in today's environment due to its energy saving and improved product quality features. It is even more important to study more about optimizing the processes involved in the EAF in order to capitalize on its positive features and thus able to contribute to the world in our bid to fight global climate change.During the refining stage of the Electric Arc Furnace (EAF) operation, molten steel is stirred to facilitate steel/slag reactions and the removal of impurities, which determines the quality of the steel. The stirring process is driven by the injection of oxygen, which is carried out by burners operating in lance mode. In this study, a computational platform is used to analyze the flow dynamics produced during the stirring of the steel bath in an industry-scale EAF. Namely, nonreacting, three-dimensional, transient simulations of the liquid bath stirred by oxygen injection are carried out to analyze the mixing process. The CFD domain includes the liquid bath and the oxygen injected by three coherent jets. The study includes a baseline case, where the oxygen is injected at 1000 SCFM in all the burners. Two sets of cases are also included: first set considers cases where oxygen is injected at a reduced and at an increased uniform flow rate: 750 and 1250 SCFM, respectively. Second set considers cases with non-uniform injection rates in each burner, which keep the same total flow rate of the baseline case, 3000 SCFM. The analysis is also quantified by defining two variables: the mixing time and the standard deviation of the flow velocity. Results indicate that the mixing rate of the bath is determined by flow dynamics near the injection cavities, and that the formation of very low velocity regions or 'dead zones' at the center of the furnace and at the balcony regions prevent the flow mixing. All the non-uniform injection cases reduce the mixing time obtained in the baseline case. The melting of HBI/scrap in an electric arc furnace (EAF) is studied by using a computational fluid dynamics (CFD) platform. A previously developed scrap melting model is extended to investigate the different physical phenomena involved in melting of HBI/scrap charges. The CFD platform merges three computational models, namely a scrap/HBI melting model, an electric arc model and a coherent jet model. The simulation conditions were selected to match those typically seen in industry-scale EAFs.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798379874346Subjects--Topical Terms:

596513
Thermodynamics.
Index Terms--Genre/Form:

554714
Electronic books.

Optimization of Steelmaking Processes in an Electric ARC Furnace.
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504 $a Includes bibliographical references
520 $a The Electric Arc Furnace is being used quite frequently and significantly in today's environment due to its energy saving and improved product quality features. It is even more important to study more about optimizing the processes involved in the EAF in order to capitalize on its positive features and thus able to contribute to the world in our bid to fight global climate change.During the refining stage of the Electric Arc Furnace (EAF) operation, molten steel is stirred to facilitate steel/slag reactions and the removal of impurities, which determines the quality of the steel. The stirring process is driven by the injection of oxygen, which is carried out by burners operating in lance mode. In this study, a computational platform is used to analyze the flow dynamics produced during the stirring of the steel bath in an industry-scale EAF. Namely, nonreacting, three-dimensional, transient simulations of the liquid bath stirred by oxygen injection are carried out to analyze the mixing process. The CFD domain includes the liquid bath and the oxygen injected by three coherent jets. The study includes a baseline case, where the oxygen is injected at 1000 SCFM in all the burners. Two sets of cases are also included: first set considers cases where oxygen is injected at a reduced and at an increased uniform flow rate: 750 and 1250 SCFM, respectively. Second set considers cases with non-uniform injection rates in each burner, which keep the same total flow rate of the baseline case, 3000 SCFM. The analysis is also quantified by defining two variables: the mixing time and the standard deviation of the flow velocity. Results indicate that the mixing rate of the bath is determined by flow dynamics near the injection cavities, and that the formation of very low velocity regions or 'dead zones' at the center of the furnace and at the balcony regions prevent the flow mixing. All the non-uniform injection cases reduce the mixing time obtained in the baseline case. The melting of HBI/scrap in an electric arc furnace (EAF) is studied by using a computational fluid dynamics (CFD) platform. A previously developed scrap melting model is extended to investigate the different physical phenomena involved in melting of HBI/scrap charges. The CFD platform merges three computational models, namely a scrap/HBI melting model, an electric arc model and a coherent jet model. The simulation conditions were selected to match those typically seen in industry-scale EAFs.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Thermodynamics. $3 596513
650 4 $a Mechanics. $3 527684
650 4 $a Materials science. $3 557839
650 4 $a Industrial engineering. $3 679492
650 4 $a Fluid mechanics. $3 555551
650 4 $a Energy. $3 784773
650 4 $a Reynolds number. $3 839681
650 4 $a Carbon dioxide. $3 574401
650 4 $a Iron. $3 897875
650 4 $a Gases. $3 673055
650 4 $a Viscosity. $3 641960
650 4 $a Raw materials. $3 1113584
650 4 $a Furnaces. $3 596858
650 4 $a Heat transfer. $3 1085480
650 4 $a Climate change. $2 bicssc $3 1009004
650 4 $a Energy consumption. $3 571871
650 4 $a Heat conductivity. $3 1372522
650 4 $a Homogenization. $3 1437787
650 4 $a Electric rates. $3 1466223
650 4 $a Chemistry. $3 593913
650 4 $a Emissions. $3 1372626
650 4 $a Flow velocity. $3 1372583
650 4 $a Electrodes. $3 581312
650 4 $a Scrap. $3 1472743
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773 0 $t Masters Abstracts International $g 85-01.
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