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Study of inclusion prediction model for Ladle Furnace process in secondary steelmaking

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dc.contributor.advisor이경우-
dc.contributor.author이형정-
dc.date.accessioned2017-07-13T05:47:25Z-
dc.date.available2017-07-13T05:47:25Z-
dc.date.issued2015-08-
dc.identifier.other000000067074-
dc.identifier.urihttps://hdl.handle.net/10371/118022-
dc.description학위논문 (박사)-- 서울대학교 대학원 : 재료공학부, 2015. 8. 이경우.-
dc.description.abstractStrict control over various elements is required for the production of high quality steel, which in turn necessitates an understanding of the secondary refining processes which make it possible to control the mixing of the alloy elements and inclusions. The secondary steelmaking process is the deoxidation process which contains argon bottom bubbling to inclusion removal. To make simulation, flow, mass transfer of deoxidizer and other alloys, reaction of dissolved oxygen ? deoxidizer in molten steel and its inclusion generation, inclusions collision ? agglomeration and removal should consider. Proper understating of the mixing of alloy elements and their transfer route is important to enhance operations of process. Especially when alloy (or deoxidizer) is added, the local area of alloy addition site soars up to over ten times of equilibrium concentration. Before the end of mass transfer, this high and low concentration region is mixed all over the ladle. Understanding of alloy transfer is important because the quantity of inclusion generation is depending on that.
Bottom argon blowing in the ladle leads to the melt being exposed. The injected gas bubble moves up by its buoyancy force and pushes slag away. The exposed area is known as the plume eye. In this study, the equation which is able to predict plume eye area is proposed. Through several experiments and simulations, relationship between plume eye ratio and gas flow rates is proportional to the square root of the gas flow rate and inversely proportional to the square root of the slag thickness. The proposed equation is able to apply various size of ladle and slag properties to predict plume eye area.
The local equilibrium reaction is made to reveal the deoxidation behavior in the ladle. To calculate equilibrium between deoxidizer and dissolved oxygen, associate model that is able to reduce interaction coefficients is applied. This feature is proper to calculate complicated reaction such as Calcium-Aluminum and Oxygen. The circulation point in the ladle is the lowest region of inclusion generation as a result of 10 minutes of process time. High Ca contents of Ca-aluminate is produced near the injection site of Ca. At the initial state of reaction, Al2O3 concentration decreases near the region of site of Ca injection. Independent on the Ca injection speed, CaAl4O7 and CaAl2O4 are produced after CaAl12O19 and Ca3Al2O6 inclusions are produced. Ca wire injection speed is inverse proportional to the time of reaching equilibrium.
To develop the model of inclusion agglomeration, its collision frequency and apparent density are defined. To simulate over billions of inclusion particles, algorithmic technic is added. Through this model, major inclusion growth site and size are predictable. The major site of agglomeration is the circulation point in the ladle which inclusions gather by flow. This circulation point has the longest residence time of inclusion. The region of plume has the highest collision frequency but agglomeration is effected more by the residence time. In this study, inclusions grow to 15 um when reaction between Al 1000ppm and O 300 ppm for 10 minutes of process under 30m3/hour.
In case of slag entrapment, the shape of slag is fixed as sphere. Entrapping of slag surface area and entrapping slag mass are calculated by the relationship between slag surface tension and turbulent kinetic energy. The range of slag droplet size is considered by turbulent and pressure difference. In this study, 5, 30, 70m3/hour flow rate of Argon bottom bubbling cases are calculated. The result for 10 minutes process, the residual quantity of slag droplet is 0.2ppm, 10ppm, 35ppm each. The possible entrapment diameter is from 5um to 40mm in case of 70m3/hour.
As mentioned above, this prediction program for ladle furnace (LD3D) can predict general phenomena such as bubbling process, deoxidation reaction, inclusion agglomeration behavior and slag entrapment. We hope to help designing secondary steelmaking process with this program.
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dc.description.tableofcontentsAbstract i
List of Figures iv
List of Tables x
Chapter 1. Deoxidation process in Ladle Furnace (LF) system 1
Chapter 2. Flow calculation model 4
2. 1 Plume eye phenomenon 4
2. 2 Experimental method and numerical model 6
2. 2. 1 Experimental apparatus of water model 6
2. 2. 2 Velocity measurement through particle image velocimetry 9
2. 2. 3 Ladle Furnace grid system 10
2. 2. 4 Flow module 12
2. 2. 5 Turbulence module 15
2. 2. 6 Boundary conditions 17
2. 2. 7 Calculation of driving force of gas bubble 18
2. 2. 8 Energy balance at plume eye boundary and its relationship 24
2. 3 Result and discussion 28
2. 3. 1 Velocity profiles in the water model 28
2. 3. 2 Effect of slag thickness on area of plume eye 31
2. 3. 3 Comparison with other studies 35
2. 3. 4 Application to industrial ladle 38
2. 3. 5 General equation for plume eye prediction 41
2. 4 Conclusion of flow calculation module 45
Chapter 3. Deoxidation reaction model 46
3. 1 Background study of oxide reaction 46
3. 2 Numerical model for deoxidation reaction 49
3. 2. 1 Reaction mechanism by Wagner formalism 49
3. 2. 2 Simple reaction by associate model 51
3. 2. 3 Formation of complex deoxidation inclusion 55
3. 2. 4 Assumption: Determining reaction speed and convergence 61
3. 2. 5 Algorithm of the module 62
3. 3 Result and discussion 65
3. 3. 1 Flow information 65
3. 3. 2 Reaction result of uniform distribution reaction 67
3. 3. 3 Simple deoxidation based on local reaction module 72
3. 3. 4 Ca-Aluminate reaction 76
3. 4 Conclusion of deoxidation reaction module 88
Chapter 4. Inclusion agglomeration model 90
4. 1 Background of inclusion agglomeration study 90
4. 2 Numerical model for inclusion agglomeration 90
4. 2. 1 Collision frequency of inclusions 90
4. 2. 2 Fractal dimension constant and apparent density 93
4. 2. 3 Inclusion agglomeration simplifications 96
4. 2. 4 Algorithm of inclusion agglomeration model 101
4. 3 Result and discussion 102
4. 3. 1 Comparing with Si-O reaction and Al-O reaction 102
4. 3. 2 Calculation result including inclusion removal 107
4. 4 Conclusion of inclusion agglomeration 112
Chapter 5. Slag entrapment model 114
5. 1 Background study of slag entrapment modeling 114
5. 2 Various theories of slag entrapment conditions 119
5. 3 Result of slag entrapment simulation and its condition 125
5. 4 Conclusion of slag entrapment 131

References 132
Korean abstract 136
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dc.formatapplication/pdf-
dc.format.extent5578061 bytes-
dc.format.mediumapplication/pdf-
dc.language.isoen-
dc.publisher서울대학교 대학원-
dc.subjectnumerical analysis-
dc.subjectladle furnace process-
dc.subjectplume eye-
dc.subjectinclusion generation-
dc.subjectinclusion agglomeration-
dc.subjectslag entrapment-
dc.subject.ddc620-
dc.titleStudy of inclusion prediction model for Ladle Furnace process in secondary steelmaking-
dc.typeThesis-
dc.description.degreeDoctor-
dc.citation.pagesxiii,138-
dc.contributor.affiliation공과대학 재료공학부-
dc.date.awarded2015-08-
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