Development Towards Sustainable Ironmaking
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(2) Development Towards Sustainable Ironmaking The IronArc Process JONAS SVANTESSON. Academic Dissertation which, with due permission of the KTH Royal Institute of Technology, is submitted for public defence for the Degree of Licentiate of Engineering on Friday the 18th of December 2020, at 14:00 a.m. in Säfströmrummet, Brinellvägen 23, Stockholm.. Licentiate Thesis in Material Science KTH Royal Institute of Technology Stockholm, Sweden 2020.
(3) © Jonas Svantesson © Mikael Ersson, Björn Glaser, Pär G. Jönsson, Matej Imris, Maria Swartling, Jesse F. White ISBN 978-91-7873-711-6 TRITA-ITM-AVL 2020:45 Printed by: Universitetsservice US-AB, Sweden 2020.
(4) Abstract The IronArc process is a novel process for a more sustainable production of liquid pig iron using electricity for heating and hydrocarbons for reduction. This thesis aims to facilitate its use by investigating possible refractory solutions and the gas blowing in the process which is done by a plasma generator. The process involves a slag with a high FeO content of 90 wt % and gangue content of approximately 5 wt % SiO2 and 5 wt % CaO. The interaction between such a slag and refractories of MgO, Al2 O3 , Cr2 O3 , SiC, ASZ, and C was investigated by high temperature experiments at 1700 K and by thermodynamic calculations in Thermo-calc and FactSage. In the high temperature experiments it was found that all of the studied refractory materials experienced significant wear after 3 h, but the MgO-Al2 O3 spinel refractories were the least affected. The thermodynamic calculations show fair agreement to the experiments, with the exception for the Cr2 O3 -spinel refractory which performed much worse than predicted by thermodynamic equilibrium calculations. It was concluded that the thermodynamic equilibrium calculations in Thermo-calc and Factsage can be used as an indicator for the stability of a refractory material, but with varying accuracy depending on the quality of the data in the database used. Since industrial refractory materials are not viable as refractory for the IronArc process a freeze-lining approach was evaluated by using CFD in ANSYS Fluent. The flow of a slag was simulated through two different designs of slag runner to investigate how well a freeze-lining protects the walls in a region with rapid flow and the cooling required to form and maintain said freeze-lining. It was found that the enthalpy porosity model in ANSYS Fluent in combination with the RSM turbulence model accurately predicts the thickness of a freeze lining when validated against experiments in the CaCl2 -H2 O system. For optimal protection of the refractory walls the reactor and runner should be designed to minimize the movement close to the walls as high near-wall turbulence will reduce the thickness and stability of the freeze-lining, leading to greater cooling requirements to maintain a freeze-lining. The IronArc process uses a plasma generator to supply heat to the reactor using electricity. By blowing gas and hydrocarbons through an electric arc, superheated gas is formed which when injected into the reactor provides both stirring and heating for the process. To study the behavior of the injected gas a simulation model was developed in OpenFOAM. The model for i.
(5) simulating gas blowing was tested in both incompressible and compressible simulations in the air-water system which were verified against an experimental study in the air-water system and found good agreement. The simulations of the plasma generator blowing were done in the compressible model to account for the high temperature and pressure present in the IronArc process. It was found that the stability of the gas blowing is dependent on the Froude number where low values cause an unstable and pulsating plume and higher values produce a more stable jet. It was also found that the empirical equation for penetration length is only valid for gas blowing with sufficiently high Froude numbers to produce a jetting behavior. It was found that the transition from pulsating to steady jetting in the IronArc system occurred around Froude numbers of 300 and higher values further increased the stability of the jet. For gas blowing below the transition region, the penetration length of the unstable and pulsating jet will be severely underpredicted by the empirical equation. This behavior must be considered when designing the gas blowing system for the IronArc process as the gas penetration length will significantly influence the stirring in the reactor. Additionally, a pulsating and unstable jet produces large bubbles which risk coming in contact with the refractory walls which in previous studies has been shown to be very detrimental to the refractory lifetime. A decrease of the inlet diameter for the gas blowing increases the Froude number and the stability of the jet. By implementing the proposed refractory protection by freeze-lining and the small changes to the plasma generator inlet diameter the IronArc process can be developed into a promising industrial process capable of producing liquid pig iron in a more sustainable way.. Keywords: IronArc, Refractory wear, Plasma generator, Freezelining. ii.
(6) Sammanfattning IronArc processen ¨ ar en nyt¨ ankande metod f¨or att producera flytande r˚ aj¨arn p˚ a ett mer h˚ allbart s¨ att genom att anv¨anda elektricitet f¨ or uppv¨armning och kolv¨ aten f¨or reduktion. Denna avhandling a¨mnar att utv¨ ardera m¨ ojliga metoder f¨or att skydda infordingen i processen och unders¨oka gasbl˚ asningen i processesen som g¨ ors med en plasma generator. Ett av huvudstegen av IronArc processen ¨ar tillverkningen av en slagg med upp till 90 vikts % j¨arnoxid samt 5 vikts % kiseldioxid och 5 vikts % kalciumoxid fr˚ an g˚ angarten. Interaktionen mellan en s˚ adan slagg och olika infodringar baserade p˚ a MgO, Al2 O3 , Cr2 O3 , SiC, ASZ, och C unders¨oktes i h¨ ogtemperaturexperiment vid 1700 K samt med termodynamiska ber¨aknar i Thermo-calc och FactSage. Experimenten visade att alla de unders¨okta infodringsmaterialen br¨ots ned under de 3 timmar de var i kontakt med slaggen, men de tv˚ a MgO-Al2 O3 spinel baserade infodringarna visade h¨ogst motst˚ andskraft mot slitaget. De termodynamiska ber¨akningarna o¨verrensst¨ amde bra med de experimentella resultaten f¨or alla infodringsmaterial f¨ orutom den kromoxid baserade infodringen som br¨ots ned fullst¨andigt trots att de termodynamiska ber¨akningarna p˚ avisade viss stabilitet. Slutsatsen ¨ ar att inget av de studerade infodringsmaterialen ¨ar bra anpassat f¨ or IronArc processen men att metoden som anv¨andes f¨or de termodynamiska ber¨ akningarna i Thermo-calc och FactSage kan anv¨andas f¨ or att ge en indikation om stabiliteten f¨or olika infodringsmaterial i kontakt med slagg. Dock s˚ a kommer resultaten av de termodynamiska ber¨ akningarna vara beroende av kvalit´en av databasen som anv¨ ands f¨ or ber¨akningen. Eftersom infodringsmaterialen inte kunde motst˚ a slitaget fr˚ an slaggen unders¨ oktes en dynamisk infodring f¨ or slaggr¨annan i IronArcprocessen. Detta gjordes genom att simulera fl¨odet och stelningen av slagg i fl¨odesber¨akningar i ANSYS Fluent i tv˚ a olika typer av slaggr¨annor. Studien visade att enthalpy-porosity modellen f¨ or stelning samt RSM modelled f¨ or turbulens kunde f¨ orutsp˚ a stelningsf¨ orloppet i slaggr¨annan samt beskriva hur v¨al den dynamiska infodringen skyddar v¨aggen och vilken kyleffekt som kr¨ avs f¨ or att bibeh˚ alla den. Denna modell validerades mot experimentella studier i CaCl2 -H2 O systemet med god ¨overrensst¨ ammelse. F¨ or optimalt skydd av v¨ aggarna i IronArcprocessen borde reaktorn och slaggr¨annan utformas s˚ a att fl¨ odet n¨ ara v¨aggarna minimeras d˚ a ett turbulent fl¨ode n¨ ara v¨ aggen ¨ar negativt f¨ or stabiliteten och tjockleken hos den dynamiska infodringen. IronArcproceesen anv¨ ander sig av en plasmagenerator f¨ or att f¨orse processen med v¨ arme via elektricitet. Genom att bl˚ asa gas och kolv¨aten genom iii.
(7) en ljusb˚ age v¨ arms gasblandningen och trycks in i reaktorn vilket ger b˚ ade v¨ arme och omr¨ orning till processen. F¨or att unders¨oka hur den varma gasen beter sig i reaktorn utvecklades en simuleringsmodell i OpenFOAM. Modellen utformades som b˚ ade inkompressibel och kompressibel f¨or bl˚ asning av luft i vatten och j¨amf¨ ordes med experiment d¨ar gas bl˚ astes i vatten. De b˚ ada modellerna o¨verrensst¨amde bra med de experimentella resultaten och kunde d¨ arf¨or anv¨andas f¨ or att studera gasfl¨odet i IronArcprocessen. F¨ or simuleringen av IronArcprocessen valdes den kompressibla versionen av simuleringen d˚ a den tar h¨ ansyn till de h¨oga temperaturer och tryck som uppst˚ ar i reaktorn. Simuleringarna visade att den inbl˚ asta gasen kan ge en stabil gas-jet om Froude-talet f¨or inbl˚ aset ¨ar tillr¨ ackligt h¨ogt. Om Froude-talet f¨ or gasbl˚ asningen ¨ ar f¨ or l˚ agt s˚ a kommer gasen pulsera p˚ a ett instablit s¨att och skapa stora bubblor som kommer i kontakt med infodringsmaterialet, vilket tidigare har p˚ avisats orsaka ¨ okat slitage p˚ a infodringsmaterialet. F¨ or IronArc processen kr¨ avdes ett Froude tal p˚ a ca 300 eller h¨ogre f¨or att skapa en stabil jet av gas, d¨ ar h¨ ogre v¨ arden vidare ¨okar gas-jettens stabilitet. Studien visade ocks˚ a att den empiriska ekvationen som anv¨ ands f¨ or att ber¨akna penetrationsl¨angden vid gasbl˚ asning endast ¨ar korrekt om gasen ¨ar en stabil jet. Om ekvationen anv¨ ands f¨ or att ber¨ akna penetrationsl¨ angden f¨or gasbl˚ asning med mindre ¨an det kr¨ avda Froude talet kommer penetrationsl¨ angden kraftigt underskattas vilket kan medf¨ ora att fel beslut tas n¨ar en process utformas. Genom att minska diametern p˚ a dysan som anv¨ands f¨ or gasbl˚ asningen ¨okas Froudetalet och d¨ armed stabiliteten av ga jetten, vilket g¨ or den mer f¨ oruts¨agbar och b¨ attre f¨ or processen. F¨ or att vidare utveckla IronArcprocessen s˚ a b¨or den unders¨ okta dynamiska infodringen samt de f¨oreslagna modifieringarna till gasbl˚ asningen anv¨andas. D˚ a kan en lovande industriell process utformas som har m¨ ojlighet att producera flytande r˚ aj¨arn p˚ a ett mer h˚ allbart s¨att.. Keywords: IronArc, infodringsslitage, plasmagenerator, dynamisk infodring. iv.
(8) Acknowledgements I would like to express my sincerest gratitude to my main supervisor Mikael Ersson, with whom I have had many fruitful discussions to help me understand the mysteries of fluid dynamics and to help guide and motivate me throughout my thesis. Even when workloads were high and deadlines approaching he has taken the time to answer my questions, however trivial, about everything from linux commands to CFD theory. I would also like to thank my co-supervisors Bj¨orn Glaser and P¨ ar J¨onsson for supporting me in my work and teaching me a lot about proper experimental technique and article writing. Thanks to you I feel well equipped to carry on as a researcher and engineer in further projects. Also, I would like to thank ScanArc Plasma Technologies for being a great collaborator during the project. Many thanks to my contacts Matej Imris and Maria Swartling for helping me during my visits in Hofors for experiments and for answering all my questions about the IronArc process. I am grateful for the funding from Energimyndigheten (Swedish energy agency) which made the project possible and allowed me to travel to Toronto for the Steelsim 2019 conference. Additionally I would like to thank Jernkontoret for the grant i received to fund my travel to the Molten2020 conference even though the trip was cancelled and the grant I recieved which allowed me to finish this thesis. I would like to thank my colleagues in the unit of processes for keeping me company during these two years and for the many fun, weird, interesting, and informative discussions in the break room. And last but not least I would like to thank my friends and family for supporting me throughout the entire process and keeping interest in my work. Without you I would not have persisted and finished my thesis. Jonas Svantesson The 1st of October 2020. v.
(9) List of Supplements Supplement 1 Numerical Analysis of Slag Transfer in the IronArc Process - Jonas L. Svantesson, Mikael Ersson, Matej Imris and P¨ar J¨ onsson, Metallurgical and Materials Transactions B vol 51. pp. 2171-2186, ISSN 1073-5615 Supplement 2 Study of Dynamic Refractory Wear by Slags Containing Very High FeO Contents under Steelmaking Conditions - Jonas L. Svantesson, Bj¨orn Glaser, Mikael Ersson, Jesse F. White, Matej Imris, P¨ar G. J¨onsson, Ironmaking and Steelmaking (Preprint) Supplement 3 Effect of Froude number on Submerged Gas blowing Characteristics - Jonas L. Svanteeson, Mikael Ersson, P¨ar G. J¨onsson, Manuscript Contribution to supplements Supplement 1 All of the literature study, all of the simulations, most of the analysis, all of the writing Supplement 2 All of the literature study, all of the experiments, most of the thermodynamic calculations, most of the analysis, all of the writing Supplement 3 All of the literature study, all of the simulations, all of the analysis, all of the writing. vi.
(10) List of Tables 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21. Composition of Refractory Materials . . . . . . . . . . . . . Composition of Refractory Systems . . . . . . . . . . . . . Slagrunner Mesh Analysis . . . . . . . . . . . . . . . . . . . Stagnated Bath Mesh Analysis . . . . . . . . . . . . . . . . Boundary Conditions . . . . . . . . . . . . . . . . . . . . . . Material Properties . . . . . . . . . . . . . . . . . . . . . . . Ambient Temperature Mesh Sensitivity Analysis . . . . . . IronArc System Mesh Sensitivity Analysis . . . . . . . . . . Boundary Conditions for the Incompressible Air-Water System Transport Properties for the Incompressible Air-Water System Boundary Conditions for the Compressible Air-Water System Transport Properties for Gasses and Liquids . . . . . . . . . Material Parameters in Solidification Validation . . . . . . . EDS Area Analysis of Adhered Slag (spectrum 1) and Bulk Refractory (spectrum 2) . . . . . . . . . . . . . . . . . . . . EDS Area Analysis of Adhered Slag (Spectrum 1) and Bulk Refractory (spectrum 2) . . . . . . . . . . . . . . . . . . . . Slag Composition before and after Refractory Finger Experiments in wt% . . . . . . . . . . . . . . . . . . . . . . . . . Composition of Refractory Systems . . . . . . . . . . . . . Summary of Thermodynamic Calculations . . . . . . . . . . Measured and Calculated Penetration Length in the AirWater System . . . . . . . . . . . . . . . . . . . . . . . . . . Simulated and Calculated Penetration Length in the AirWater System . . . . . . . . . . . . . . . . . . . . . . . . . . Simulated and Calculated Penetration Length in the IronArc System for Varying Pressure . . . . . . . . . . . . . . . . . .. vii. 11 13 20 20 21 21 25 25 26 26 27 27 29 35 36 36 37 41 54 56 58.
(11) List of Figures 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28. Schematic Image of the Demonstration Scale IronArc Reactor The Rapidly Flowing Slagrunner (SR) Design and the Slower Flowing Stagnated Bath (SB) Design . . . . . . . . . . . . . Connectivity of the Three Supplements . . . . . . . . . . . Schematic Image of Furnace and Experimental Setup . . . . The Slagrunner (SR) Design . . . . . . . . . . . . . . . . . . The Stagnated Bath (SB) Design . . . . . . . . . . . . . . . Simulation Domain for Ambient Temperature . . . . . . . . Simulation Domain for the IronArc System . . . . . . . . . Solidification Profile after 5 hours of 50 ◦ C Flow in Side View Solidification Profile after 5 hours of 50 ◦ C Flow in Top View Refractory Fingers Before and after 3 h Rotation in IronArc Slag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MgO-Spinel1550◦ C Cross Section in LOM (a) and SEM (b) . MgO-Spinel1750◦ C Cross Section in LOM (a) and SEM (b) . Phase Distribution of the SiC Refractory System over Temperature in Thermo-calc Calculations in the TCOX8 Database Phase Distribution of the SiC Refractory System over Temperature in FactSage Calculations . . . . . . . . . . . . . . . Liquid Surface and Solidified Material in the SR Design . . Liquid Surface and Solidified Material in the SB Design . . Liquid Surface and Solidified Material in the SR Design with 1cm Steel Insulation . . . . . . . . . . . . . . . . . . . . . . Average Freeze-lining Thickness with Varying Viscosity . . Average Freeze-lining Coverage with Varying Viscosity . . . Average and Maximum Wall Shear Stress with Varying Viscosity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Heatflux Through Different Parts of the Wall as Function of Heat Conductivity of Slag . . . . . . . . . . . . . . . . . . . Freeze-lining Thickness as Function of Heat Conductivity of Slag . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Freeze-lining Thickness as Function of Inlet Mass Flow . . . Freeze-lining Coverage as Function of Inlet Mass Flow . . . Heatflux Through Different Parts of the Wall as Function of Mushy Zone Parameter . . . . . . . . . . . . . . . . . . . . Degree of Freeze-lining Coverage as Function of Mushy Zone Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . Gas Plume in the Incompressible Simulation of Air-Water System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. viii. 4 7 9 12 19 19 23 24 29 30 33 34 35 38 38 42 43 43 45 46 47 48 49 50 51 52 53 54.
(12) 29 30 31 32. Gas Plume in the Compressible Simulation of Air-Water System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Deviation of Simulated Results from Calculated Results as a factor of Froude number and Density Ratio . . . . . . . . Gas Plume the IronArc System with 177 kPa Inlet Pressure Gas Plume in the IronArc System with 300 kPa Inlet Pressure. ix. 55 56 57 58.
(13) List of Symbols ρ u, v, w m α µ p g E kef f T h J τef f Sh , Sb C β γ hs Cp ∆H φ d0 Mw R σ. Density [kg · m-3 ] Velocity [m · s-1 ] Mass Transfer [kg · s-1 ] Phase Fraction Viscosity [P a · s] Pressure [P a] Gravity [m · s-2 ] Energy [J] Effective Heat Conductivity [W · m-1 · K -1 ] Temperature [K] Enthalpy [J · kg -1 ] Species Diffusion [kg · m-2 · s-1 ] Effecive Shear Stress [P a] Source Terms Mushy Zone Parameter Porosity Thermal Expansion Sensible Heat [J · kg -1 ] Specific Heat [J · kg -1 · K] Latent Heat [J · kg -1 ] A general property Inlet diameter [cm] Molecular Weigth [g · mol-1 Fluid Constant [J · mol-1 · K -1 ] Surface tension [N · m-1 ]. x.
(14) List of Abbreviations EAF HBI DRI LNG LPG BF SR SB PG NF r Pr number CFD AZS FeO Fe2 O3 Fe3 O4 SiO2 CaO Al2 O3 Cr2 O3 MgO ZrO2 C Mo LOM SEM FVM VOF GCI Lp , PL. Electric Arc Furnace Hot Briketted Iron Direct Reduced Iron Liquid Natural Gas Liquid Petroleum Gas Blast Furnace SlagRunner StagnatedBath Plasma generator Froude number Prandtl number Computational Fluid Dynamics Alumina Stabilized Zirconia Iron Oxide, W¨ ustite Iron Oxide, Haematite Iron Oxide, Magnetite Silicon Oxide Calcium Oxide Aluminum Oxide Chromium Oxide Magnesium Oxide Zirconium Oxide Carbon, Graphite Molybdenum Light Optical Microscope Scanning Electron Microscope Finite Volume Method Volume of Fluid Grid Convergence Index Penetration Length. xi.
(15) Contents 1 Introduction 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Present Work . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Objective of the Work . . . . . . . . . . . . . . . . . . . . . 2 Methodology 2.1 Experimental Methods . . . . . . 2.2 Thermodynamic Calculations . . 2.3 Numerical Models . . . . . . . . 2.3.1 CFD Theory . . . . . . . 2.3.2 Turbulence Models . . . . 2.3.3 Slagrunner Simulations . 2.3.4 Gas Blowing Simulations 2.3.5 Validation Study . . . . .. 1 1 8 9. . . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . . .. 11 11 13 14 14 17 18 22 28. 3 Results 3.1 Experimental Results (Supplement 2) . . . . . . . . 3.2 Thermodynamic Results (Supplement 2) . . . . . . . 3.2.1 SiC Refractory . . . . . . . . . . . . . . . . . 3.2.2 MgO-C . . . . . . . . . . . . . . . . . . . . . 3.2.3 MgO-Spinel . . . . . . . . . . . . . . . . . . . 3.2.4 Al2 O3 -Spinel . . . . . . . . . . . . . . . . . . 3.2.5 Cr2 O3 -Spinel . . . . . . . . . . . . . . . . . . 3.2.6 ZrO2 . . . . . . . . . . . . . . . . . . . . . . . 3.2.7 Graphite . . . . . . . . . . . . . . . . . . . . 3.2.8 Molybdenum in Experimental Systems . . . . 3.2.9 Expected Experimental Results . . . . . . . . 3.3 Results of Freeze-lining Simulations (Supplement 1) 3.3.1 Viscosity . . . . . . . . . . . . . . . . . . . . 3.3.2 Heat Conductivity . . . . . . . . . . . . . . . 3.3.3 Mass Flow . . . . . . . . . . . . . . . . . . . . 3.3.4 Mushy Zone Parameter . . . . . . . . . . . . 3.4 Results of Gas Blowing Simulations (Supplement 3) 3.4.1 Air-Water System . . . . . . . . . . . . . . . 3.4.2 Density variations . . . . . . . . . . . . . . . 3.4.3 IronArc System . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . .. 33 33 37 37 39 39 39 40 40 40 40 41 42 44 47 49 51 53 53 55 57. . . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . . .. . . . . . . . .. 4 Discussion. 59. 5 Conclusions. 67. xii.
(16) 6 Future Work and Sustainability 6.1 Further work . . . . . . . . . . . . . . . . . . . . . . . . . . 6.2 Sustainability . . . . . . . . . . . . . . . . . . . . . . . . . .. xiii. 69 69 70.
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(18) 1 1.1. Introduction Introduction. Ironmaking is a well established technology and a requirement for modern civilization, but the technology used today is very different from when it emerged. Modern blast furnaces are the result of centuries of development which for the longest time focused on increasing productivity and the quality of the product which has resulted in a finely tuned process with close to optimized operation. In modern time the focus of the development has shifted to also include considerations of sustainability for the development of ironmaking [1]. The focus on lessening environmental impacts by reducing the production of harmful by-products and the emissions of greenhouse gasses has been very successful and with the best available technology the emissions of CO2 are significantly lower than 40 years ago [2]. However, the iron and steelmaking industry still accounts for 4-7 % of the worlds CO2 emissions, of which the majority originates from the blast furnace [3]. The average blast furnace requires 400-500 kg of coke per tonne of produced iron, which leads to an average emission of 1.9 tonnes of CO2 per tonne of iron [4]. Using the best available technology it is possible to reduce the emissions somewhat, but this is fairly close to the theoretical lower limit for how low the emissions of CO2 can be from the blast furnace process without fundamentally changing the process. The total reaction for reduction of iron oxide to metallic iron by carbon is shown in Equation 1, with which it is simple to calculate that the minimum CO2 emissions for iron oxide reduction by carbon is approximately 590 kg of CO2 per tonne of liquid iron. However, in the blast furnace this process occurs in a set of reactions where the actual reduction of iron oxide is mainly done by carbon monoxide (CO). 2F e2 O3 (s) + 3C(s) → 4F e(l) + 3CO2 (g). (1). To facilitate these reactions a very high temperature must be maintained in the blast furnace. Since the total reduction reaction of iron oxide is endothermic a significant amount of heat needs to be added to the system to maintain the temperature, and in the Blast Furnace this is mainly done by oxidation (burning) of coke together with injected oxygen. Additionally, the blast furnace loses large amounts of heat through the walls of the reactor, through off gasses, and to heat up the new material which is added. A large fraction of the coke added to the Blast furnace does not contribute to the actual reduction reaction, but still produces CO2 emissions. This is the reason for the large differance between the calculated emissions for the 1.
(19) reduction and the actual emissions from the blast furnace [4]. To further reduce the environmental impact associated with ironmaking, and eventually make it a carbon neutral process, other process routes are required. Many different approaches have been proposed as alternatives to the Blast Furnace with the goal to reduce the emissions from ironmaking. The most common and widely used alternate route for iron and steelmaking is the Electric Arc Furnace (EAF) which is used to remelt scrap which can then be used to produce new iron and steel products. By using electric energy to melt the scrap rather than chemical energy the CO2 emissions can be reduced, given that the electricity is produced in a carbon neutral way. However, the EAF is not designed to produce virgin pig iron from iron ore, as it does not involve a reduction step [5]. For primary production of iron the most common alternate routes to the blast furnace are the direct reduction processes based on natural gas or hydrogen which account for almost 10 % of the total primary produced iron [6]. For example the Midrex and HyL 3 processes both utilize a shaft furnace with natural gas to reduce iron ore to metallic iron. With optimal use, these processes can produce iron with 40-60 % lower CO2 emissions as compared to the blast furnace. The reduced emissions can largely be credited to the lower operating temperature (900◦ C vs 1800◦ C) which reduces energy lost as heat, and the use of hydrogen from the reformed natural gas used for reduction which does not directly contribute to CO2 emissions [7][8]. Additionally, there are many ongoing development projects for a reduction process using only hydrogen as a reductant, which would further reduce the necessary emissions associated with ironmaking. These projects are for example developments of the Midrex process or the Hybrit initiative [9]. However, such hydrogen based reduction processes are still in development and not expected to be commercially used for many years. All of these direct reduction technologies produce solid material in the form of pellets or hot-briketted iron (HBI). To use these materials for steelmaking, further processing in EAF is required to produce molten pig iron. The novel IronArc process is being developed to reduce the emissions associated with ironmaking while still producing liquid pig iron without the need for additional process steps. This type of process is called a smelting reduction process and has previously been attempted in many processes, for example the Corex process, the plasmared process, the Elred process, and the COIN-process. However, none of these processes became established techniques with any significant use [10]. The main difference between the. 2.
(20) IronArc process and the previous processes is that it utilizes plasma generators to supply all the heat needed for the process by superheating gas with electric arcs and injecting said gas into the reactor. The heat carried by the gas will heat the iron ore and form a slag which is very rich in iron, with some residual amounts of gangue elements of Si and Ca from the ore. By adding reductants in the form of hydrogen and carbon to the injected gas in the form of LPG or LNG the hot gas will also reduce the Hematite and Magnetite in the slag to W¨ ustite. If more carbon is added to the system the reduction from W¨ ustite to liquid iron can be done. To improve the thermodynamic conditions for the final reduction the molten W¨ ustite slag will be transferred to a second reactor where the addition of carbon is done and the liquid iron can be tapped. The CO which is formed from this reaction can then be recycled for reduction of Hematite and Magnetite in the first reactor to further increase the efficiency of the process. The use of plasma generators combined with modern gas recycling has the possibility of creating a very efficient process with lower emissions than the blast furnace [11]. If this is done optimally it is possible to reach a 88 % use of all CO produced for reduction purposes. This would result in carbon use as low as 0.172 kg C/kg Fe as was calculated by J.O Edstr¨ om et al. based on the work of Rist and Maysson for smelting reduction processes [10][12]. If this process is then done in a large reactor to minimize heat losses the final CO2 emissions associated with the process can be significantly lower than even the direct reduction processes. The IronArc process is capable of working with either coke, carbon, LPG, LNG, or even possibly hydrogen as a reductant. Depending on the reductant used the estimated CO2 emissions for the process as compared to the blast furnace is 45-70 % when using coke, 40-60 % when using carbon, 30-40 % when using LPG, 25-35 % when using LNG, and 0 % when using hydrogen [11]. The next step in the development of the IronArc process is to scale up the reactor from the batchwise pilot plant with a capacity of 200 kg·h-1 to a demonstration scale plant capable of continuous production of iron at a capacity of 150 000 tonne/year. To facilitate the continuous process the process is split into two reactors, the first one with the main purpose of melting the incoming iron ore and reducing it to w¨ ustite by injection of CO and LNG and a second reactor where the final reduction to liquid iron takes place. A schematic image of the demonstration-scale reactor is presented in Figure 1.. 3.
(21) Figure 1: Schematic Image of the Demonstration Scale IronArc Reactor The two reactors in the demonstration-scale plant use separate atmospheres to facilitate the thermodynamic conditions required in the separate reactors. For the transfer of the FeO rich slag between these reactors a slagrunner is required which can transport the slag without transferring the atmosphere between the reactors. This isolation of the atmospheres can be achieved by using a system of submerged dams which allows the liquid to flow out of the smelting reactor, but not the gas. Compared to the Blast Furnace the IronArc process has the potential to significantly reduce the CO2 emissions associated with ironmaking since all the heat for the process can be supplied by electricity rather than the burning of coke. If the electricity is produced with low CO2 emissions, the total emissions associated with the process will be significantly lower for the IronArc process. Additionally, the use of natural gas in the IronArc process further reduces the CO2 emissions since the hydrogen in the natural gas will contribute to the reduction of the iron oxide. The IronArc process also has the benefit of working on a smaller scale than the blast furnace which makes it more fitting for smaller specialized steelplants in need of primary iron. This is especially important when scrap use increases and the competition for scrap is high. In comparison with scrap the primary iron has the benefit of lower amounts of Cu and other contaminants which 4.
(22) is an increasing problem in recycled steel scrap [13]. Compared to the DRI processes the IronArc process will slightly reduce the associated CO2 emissions due to the increased use of electricity for heating [14]. However, the main benefit of the IronArc process over the direct reduction route is that the IronArc process produces molten iron as a final product as compared to the pellets or hot brikettes produced by direct reduction. This means that the IronArc reactor can be integrated in the established blast furnace process route without the need for an additional melting step in an EAF. Ultimately, the usefullness of developing a novel process such as the IronArc process has to be weighted against possible improvements in the BF, DRI techniques, or other novel techniques which employ pure hydrogen reduction with the possibility of reducing the CO2 emissions even more. The IronArc process is a promising possibility which can be implemented fairly soon if development is continued as the reactor design can be based on the already existing zinc refinement reactor in use by Nyrstar Hoyanger which works in a similar way [14]. However, to adapt the reactor design and technique from zinc refining to ironmaking some modification of the process is required. One explicit worry with the IronArc process is the handling and transport of a high FeO slag between the melting and reduction reactor in the IronArc reactor. The molten slag which is produced in the first reactor in the IronArc process is expected to contain approximately 90 % FeO , 5 % CaO and 5 % SiO2 . Such a slag is infamous for being very corrosive to most types of industrial refractory materials as the FeO content is significantly higher than in conventional iron and steelmaking applications [15][16][17]. Previous studies on the wear of refractory by slag with high FeO contents have mainly studied compositions in the range of 50 % [18][19]. The compatibility between such a slag and different refractory materials must be evaluated in order to make an informed decision on the construction of the reactor. Such a study must be done experimentally to determine what refractories are resistant to the slag in a lab environment. Additionally, thermodynamic equilibrium calculations can be used to predict the stability of different refractories to the IronArc slag. If no refractory materials with satisfactory resistance to the slag can be found another proposed solution to contain the corrosive slag is to use a freeze-lining. A freeze-lining (or dynamic refractory lining) protects the. 5.
(23) reactor walls by forming a frozen layer of slag or metal on the inside of the reactor. This is done by intense cooling on the outside of the reactor and a highly conductive wall and refractory material which removes sufficient heat to allow solidification on the walls of the reactor. Since the solidified material on the refractory wall has the same composition as the bulk material it will not be affected by chemical wear and therefore works regardless of the slag composition [20]. The formation of a freeze-lining is however dependent on the flow behavior in the reactor and the cooling used. In areas where the flow is very turbulent close to the walls a greater cooling is required to maintain the freeze-lining and in areas of low turbulence only very low cooling is required. For this reason it is very important to study the flow behavior in the different parts of the reactor and how the intensity of cooling affects the thickness and stability of the freeze-lining. For an optimized process with a freeze-lining it is very important that the cooling is tuned correctly as too low cooling increases the risk for breakthrough of the refractory and too high cooling increases the energy consumption of the process and may cause excessive solidification and clogging of the process [20]. The runner connecting the two reactors is of special interest since it will experience a continuous flow of the slag and must thus be designed to minimize the near wall turbulence and cannot be allowed to clog by excessive solidification. By considering the design of the reactor the cooling required to maintain a freeze-lining can be reduced which in turn reduces the energy requirements for both heating of the reactor and cooling of the walls. Two different designs for the runner between the two reactors has been constructed to investigate the shear stress and freeze-lining behavior in the runner. The first design of the runner was designed for a fast moving slag and formed as a half-pipe and tilted 15 degrees drive the flow of the slag, this design was named the Slagrunner (SR). The second design of the runner was designed for a slow moving slag but with a greater cross section of the flow to enable equal volume flowrate. The second runner is not tilted and the flow is instead driven by the height difference between inlet and outlet, this design was named the Stagnated Bath (SB). Both designs can be seen in Figure 2. The flow pattern inside the IronArc pilot plant has previously been studied by B¨ olke et al. where it was found that significant sloshing is present during the process [21]. The intense stirring provided by the submerged gas blowing is beneficial for the kinetics of the process as the mixing is. 6.
(24) Figure 2: The Rapidly Flowing Slagrunner (SR) Design and the Slower Flowing Stagnated Bath (SB) Design very fast, but detrimental to the lifetime of the reactor as rapid movement causes both significant vibrations of the reactor, as well as increased erosion of wall material or stress on a freeze-lining. However, this previous study considered the gas blowing from the PG as an incompressible isothermal system to simplify the calculations. For an accurate modelling of the flow behaviour in the IronArc reactor the gas blowing from a PG must be further investigated to see if this assumption is correct. The high temperature of the inlet gas causes a very large difference in density between the injected gas and the liquid slag. It is not established if gas blowing at such conditions follows the empirical equation for penetration length as established by Hoefele and Brimacombe based on the Froude number [22]. This empirical equation for the penetration length of a gas jet in liquid is presented in Equation 2 Lp = 10.7d0 (NF r0 )0.46 (. ρg 0.35 ) ρl. (2). The flow behavior of the PG blowing in the IronArc reactor is also important to study to ensure that the gas plume which is formed does not have too much contact with the walls as such interactions have been found to be very detrimental to the refractory lifetime in conventional metallurgical processes [23]. According to Heofele and Brimacombe there may be a lower limit to the dimensionless Froude number (Equation 3) associated with submerged blowing to ensure that the gas has a jetting behavior instead of a bubbling behavior. The Froude number limit is dependent on the system and increases with increasing density ratios between gas and liquid and is somewhere in the range of 100-2000 [22]. NF r =. ρg u20 g(ρl − ρg )d0 7. (3).
(25) If the limit for the IronArc system is established the empirical equation in Equation 2 can be used to calculate the penetration length for different PG settings and thus avoid gas bubbles close to the walls.. 1.2. Present Work. In this work different refractory materials have been investigated in contact with the IronArc slag using high temperature experiments. The flow and solidification behavior in the runner between the two reactors of the IronArc process has been studied using CFD simulations in ANSYS Fluent. And the gas blowing behavior from a PG in the IronArc system has been studied in CFD simulations using OpenFOAM. The thesis and work consists of 3 supplements, which are interconnected as is illustrated in Figure 3. Specifically, the work is divided as follows: Supplement 1 In the first supplement two different designs of runner were investigated in CFD simulations. The main purpose of this work was to investigate the behavior of a dynamic refractory lining (freeze-lining) for different process parameters and material parameters, and to see if it could be accurately modelled using the enthalpy-porosity model. Additionally, these simulations were used to determine the shear stress on the refractory walls from a flowing slag if no freeze-lining was used. Validation of the model was done by comparison to previously published research on solidification. Supplement 2 The second supplement investigates a set of common and uncommon refractory materials in high temperature experiments to determine their resistance to wear from the IronArc slag. Additionally a thermodynamic analysis of the experimental systems was performed in Thermo-calc and FactSage to evaluate if thermodynamic equilibrium calculations can be used to accurately predict the wear of the refractory materials when in contact with a slag. Supplement 3 The third supplement investigates the submerged blowing of a PG in the IronArc process using CFD simulations in OpenFOAM. The work investigated the importance of considering compressibility effects when simulating gas blowing in systems with high temperature, velocity and density differ8.
(26) ences. The simulated penetration lengths of gas for different systems were compared with empirical equations and experimental results in published research for calculating the penetration length in systems based on the modified Froude number.. Figure 3: Connectivity of the Three Supplements. 1.3. Objective of the Work. The objective of the work is to help facilitate the realization of the IronArc process by investigating parts of the process which have not yet been thoroughly investigated. This is required as an assurance that the design of the process is sound. This thesis focuses on how to contain the high FeO slag as well as the behavior of a submerged jet in metallurgical processes. In supplement 1 the objective was to design a runner with a long lifetime in the process either by low shear stress on the refractory walls or by forming a stable freeze-lining. In supplement 2 the objective was to evaluate the resistance to wear from the IronArc slag for a set of refractories, as well as 9.
(27) determine if thermodynamic calculations could be used to screen for refractories with high resistance to certain slags. In supplement 3 the objective was to develop a model for predicting the gas flow from a PG under process conditions to aid in design of the reactor and future flow simulations.. 10.
(28) 2. Methodology. This thesis includes both experimental work, numerical flow modeling, and thermodynamic modeling. The methods employed for each part of the study are described in the following sections as well as in the corresponding supplement.. 2.1. Experimental Methods. The experimental work was carried out at KTH Royal institute of technology in the high temperature laboratory. This work had the objective of investigating if any of the studied common and uncommon industrial refractory materials listed in Table 1 show resistance to the high FeO IronArc slag. This was done using the rotating refractory finger technique where a finger of refractory material is lowered into molten slag and rotated for a set time to study the dissolution of the refractory as a function of time. This technique has been used extensively in literature for studies of refractory wear [24][25][26]. This type of experimental study will show the combined mechanical and chemical wear of the refractory material, which is more similar to the actual industrial conditions than a purely chemical wear study. Table 1: Composition of Refractory SiO2 Al2 O3 MgO Cr2 O3 Al2 O3 -Spinel 1 88 11 Cr2 O3 -Spinel 6 91 SiC 55 MgO-Spinel1550◦ C 1 9 87 AZS 20 40 MgO-C 97 ◦ MgO-Spinel1750 C 1 16 81 Graphite. Materials ZrO2 C. SiC. CaO. 45 1. 2. 3. 40 3 2 100. The refractory materials were shaped to 10x10x80 mm fingers using a diamond sawblade and a dremel bit. After shaping the refractory fingers were dried in a table furnace at 150 °C for 2 h to remove moisture. The finished refractory fingers had an approximate weight of 20 g with slight differences depending on the size and density of the material. The IronArc slag was prepared by mixing lab grade SiO2 and CaO powder with FeO to a slag composition of 90 % FeO, 5 % SiO2 and 5 % CaO by weigth. The FeO was manufactured by mixing Fe2 O3 powder and Fe pow11.
(29) der to a molar composition of 51 % Fe [18]. The iron mixture was heated to 900 °C for 60 h under an argon atmosphere to cause the reduction of Fe2 O3 to FeO, after which it was extracted and crushed to a fine powder. The experiments were performed in a vertical tube furnace as depicted in Figure 4. For each experiment 100 g of the premixed slag was poured into a Mo crucible which in turn was placed in a Mo holder. The holder was lowered into the sealed alumina tube to the hotzone of the furnace and the system was purged from oxygen by cycling vacuum and high purity argon 5.0 gas three times. The refractory finger was attached to a sliding steel rod and placed inside the furnace at a height of approximately 20 cm above the crucible. To start the experiment the furnace was heated to 1700 K at a rate of 2 K·min-1 and held for 2 h to homogenize the temperatures in the furnace. Once the temperature was homogenized the tip of the refractory finger was lowered into the liquid slag and rotated at 100 RPM for 3 h. After the experimental time the refractory finger was pulled up from the slag and the furnace was cooled at 3 K·min-1 down to room temperature.. Figure 4: Schematic Image of Furnace and Experimental Setup 12.
(30) The crucible and refractory fingers were extracted from the furnace and their wear was documented. The fingers which were still intact were cut to reveal the cross section to closer study the wear in LOM and SEM.. 2.2. Thermodynamic Calculations. The thermodynamic equilibrium calculations were performed in Thermocalc using the TCFE9 and TCOX8 databases, as well as in FactSage using the FactPS, FTmisc and FToxid databases. These thermodynamic equilibrium calculations were performed to determine if thermodynamic equilibrium calculations can be used to predict the stability of refractory materials in high temperature experiments. The calculations were performed by calculating the equilibrium phase distribution at temperatures from 1000 K to 2000 K in a system with 100 g of IronArc slag composition, and 20 g of refractory material composition. The system pressure is set to 100 kPa and all available phases in the databases are enabled. The oxygen potential in the system is not specified but rather imposed by the amount of oxygen introduced in the system by the slag and refractory material. The specific composition of the systems used for the thermodynamic calculations are listed in Table 2. Table 2: Composition of Refractory Systems FeO SiO2 CaO Si Al2 O3 MgO Cr2 O3 ZrO2 Al2 O3 -Spinel 90 5 5 18 2 Cr2 O3 -Spinel 90 5 5 1.5 18.5 SiC 90 5 5 6 11 MgO-Spinel 90 5 5 4 16 AZS 90 9 5 8 8 MgO-C 90 5 5 19 Graphite 90 5 5. C. 3. 1 20. The results were then plotted for the amount of phase at different temperatures to allow for comparison between the refractory materials. Additionally, since the experimental slags are melted in a molybdenum crucible the thermodynamic systems were run again with 5 g of molybdenum added to the composition of the system. This was done to evaluate if partial dissolution of the crucible material would affect the thermodynamic equilibrium in the slag-refractory systems. Since thermodynamic modelling only considers the equilibrium state the accuracy of the conclusions which can be drawn from such calculations is 13.
(31) dependent on how far the experimental system is from equilibrium. In industry a process will never go to equilibrium as it takes a very long time. But this can also be used to our advantage when designing the process. Concentration and temperature gradients can be promoted by reducing mixing or movement in certain areas which reduces the convective aspect of mass and heat transport.. 2.3. Numerical Models. Numerical CFD models were used to simulate the flow and solidification in the runner between the two reactors in the IronArc process as well as to investigate the blowing from a plasma generator under compressible conditions in the IronArc process. To validate that the simulations are independent of the mesh used in the simulations a mesh sensitivity analysis was done for each type of simulation and domain. Additionally, to validate that the models are representative of reality the simulations are compared to physical experiments as validation. The simulations of the slag runner were performed in ANSYS Fluent 2019 R1 and the simulations of the gas blowing were performed in OpenFOAM v7. All simulations were run on either Linux mint 18.3 with an Intel Core i9-7940X processor and 32GB of RAM, or on a computer running Ubuntu 18.04 with two AMD EPYC 7301 processors and 128GB of RAM. 2.3.1. CFD Theory. The CFD softwares used for this work employ the finite volume method (FVM) which is based on solving a set of conservation equations in each computational volume/mesh element and pairing it with all surrounding mesh elements. The conservation equations are employed to solve the behavior of all properties in the domain and can be stated in a general form as Equation 4. This describes the transport of a property Φ depending on the spatial coordinate (xi ) and velocity (ui ) considering the influence of density (ρ). Additionally, the effect of diffusivity (Γ) and generation of said property (SΦ ) is considered [27]. ∂ ∂ ∂ ∂Φ (ρΦ) + (ρΦui ) = (ΓΦ ) + SΦ ∂t ∂xi ∂xi ∂xi. (4). The CFD simulations were performed using the VOF (Volume of Fluid) multiphase model in both Fluent and OpenFOAM to calculate the interface between gas and liquid phases. The Volume of Fluid model achieves. 14.
(32) continuity by controlling the volume fraction of the phase in each mesh element as described by Equation 5 where αq is the fraction of phase q, (m) ˙ is the mass transfer from element 1 to element 2, and (Sαq ) is the source term [28][29]. n X 1 ∂ (m ˙ pq − m ˙ qp ) (αq ρq ) + ∇ · (αq ρq v~q ) = Sαq + ρq ∂t. (5). p=1. The VOF method is also dependent on the momentum equations, which are solved for each direction as in Equation 6 with the forcing term defined in Equation 7 [30][29]. ∂ (ρ~v ) + ∇ · (ρ~v~v ) = −∇p + ∇ · µ ∇~v + ∇~v T + ρ~g + F~ ∂t Sx Sy F~ = Sz + Sb. (6). (7). The momentum equation is dependent on the density, velocity, gravity, and pressure of the system, but also on the viscosity (µ) of the fluid. The generalised momentum equation also contains a forcing term (F) which is replaced by a different source term depending on the direction of the momentum equation. This is done to include the generation of momentum from buoyancy in the z-direction of the momentum equation. The source term in the momentum equation also contains the formulations for the surface tension between the phases. When calculating the momentum the density used is based on the phase fraction in the particular cell which is calculated by Equation 8. ρ = αρ1 + (1 − α)ρ2. (8). The momentum and conservation equations calculate the volume of fluid in each cell without consideration for the actual interface of between the phases. To track the interface additional interface tracking is required. In ANSYS Fluent this is done by the geo-reconstruct method which applies a piecewise-linear approach based on the work of Youngs [31]. In OpenFOAM a MULES based interface advection scheme is used instead for tracking of the interface [32]. For the compressible formulation of the Volume of Fluid model as used by OpenFOAM in the compressibleInterFoam model the density of the gas needs to be defined as a function of pressure and temperature according to 15.
(33) the perfect gas law in Equation 9. ρ=. p. (9). R Mw T. Where ρ is the density, p is the pressure T is the temperature, R is a material constant (j·mol-1 ·K-1 ) which is 8.314 for perfect gasses and 3000 for a generic liquid, and Mw (g·mol-1 ) is the molecular weight of the fluid which is 29 for air, 18 for water, and 70 for the IronArc slag [32]. The energy equation for the VOF method is used to calculate the transfer of heat within the simulations. This is required for the solidification simulations as well for the compressible simulations of the penetration length and is implemented as Equation 10. X ∂ (ρE) + ∇ · (~v (ρE + p)) = ∇ · kef f ∇T − hj J~j + (τ¯ef f · ~v ) + Sh (10) ∂t J. This formulation of the energy equation considers conduction (kef f ) of heat, as well as species diffusion flux (Jj) and viscous dissipation from the effective shear stress (τef f ). Since only two discrete phases, and no species are used, the summation term for the species diffusion flux can be disregarded. The source term from the latent heat of solidification (Sh ) is defined further in Equation 10. The energy is defined as Equation 11, where (hq ) is based on the specific heat of the considered phase and (ν) is the kinematic viscosity. p ν2 Eq = hq − + (11) ρq 2 The model for solidification is based on the work of Voller et al. on the enthalpy-porosity model and is applied using a sink term [33][30]. The sink term (Sx ) is applied to all the conservation equations discussed above, but in separate ways depending on the equation. For the momentum equations the sink term is defined as shown in Equation 12 Sx,y,z = C ·. (1 − β)2 ·u (β 3 + 0.001). (12). where (C) is the Mushy-zone parameter, (u) is the velocity of the flow in the x, y, or z direction, and (β) is the liquid fraction which is 0 below solidus and 1 above liquidus. In the mushy zone region β varies depending on the current temperature, as in Equation 13. β=. T − Tsolidus Tliquidus − Tsolidus 16. (13).
(34) The sink term represents the changing flow behavior when the fluid partially solidifies. In the momentum equations this is done by lowering the velocity in proportion to the liquid fraction. When the liquid fraction reaches zero the material is considered fully solidified. For a 3D case, the momentum sink term is applied for all three momentum equations with an additional term in the z-direction, which is indicated in the forcing term in Equation 6. The additional term accounts for the buoyancy force caused by natural convection in the temperature gradient close to the solidification front and is defined in Equation 14 [34]. The buoyancy sink term is calculated based on the density (ρ), gravity (g), thermal expansion coefficient (γ), sensible heat (hs ), and the specific heat of the fluid (c). ρgγ(hs − hs,ref ) (14) c When using the solidification model the energy equation is modified by the source term described in Equation 15, which accounts for the energy released by latent heat during solidification (ΔH), as defined by Voller and Prakash. The latent heat is defined as a function of temperature over the mushy zone as shown in Equation 16, which is a requirement for a dispersed interface between liquid and solid [34]. Sb =. Sh =. ∂ρ∆H + div(ρu∆H) ∂t ∆H = f (T ). 2.3.2. (15) (16). Turbulence Models. For many boundary layer simulations the k-ω SST model is the most common choice. It performs similarly to the k-ω BSL but with a better experimental agreement for boundary-layer flows with adverse pressure gradients [35]. In the current simulations high pressure gradients are present in the gas blowing simulations but not in the runner simulations. For this reason the kOmegaSSTDES model is used for the gas blowing simulations, which is an SST approach, and the RSM BSL model is used for the runner simulations. After the simulations were complete additional simulations were done in the runner simulations with the k-ω and SST type turbulence models and found that the results were very similar to the used RSM BSL turbulence model. However, the k-ε turbulence model resulted in vastly different results than the ω based turbulence models with for example twice as much solidified material. With this in mind the RSM BSL turbulence may not 17.
(35) have been the best choice of turbulence model for the runner simulations due to the larger computational power required for the simulations, but the results can be considered to be a conservative estimation of the actual behaviour. 2.3.3. Slagrunner Simulations. The simulations of the runner in the IronArc process used the VOF multiphase model in ANSYS Fluent together with the energy equation, enthalpyporosity solidification model, and a turbulent flow. The VOF model can be used with many different turbulence models depending on the simulation. For the simulations in the two designs of the runner the Baseline Reynolds Stress Model (RSM BSL) was used as it experienced the least problems when initializing the simulations. The choice of turbulence model and simulation setup was studied in further detail in the validation study where the runner simulations were compared to published experimental work. Two different runner designs were developed for the slag transfer system in the IronArc process and constructed using SpaceClaim in ANSYS. Both designs are 1 m long with 20 mm thick insulation and in the shape of a half-pipe with a symmetry line in the x-z axis as can be seen in Figure 5 and 6. The Slagrunner (SR) domain was designed with a low inlet at 16 mm above the insulation with the intention of promoting a fast and smooth flow driven by a 15 degree angle. The Stagnated Bath (SB) domain was designed with a high inlet at 181 mm above the insulation and an outlet 120 mm above the insulation with the intention of promoting a slow flow once the lower part of the domain was filled with mostly stagnant slag. The simulations were initialized at the operational temperature of 1650 K to prevent immediate solidification and clogging the domains. Additionally, the SB domain was initialized as filled with molten slag moving at 0.05 m·s-1 to remove the computational time required to simulate the filling process of the bath. The simulations were run as transient simulations with 0.01 s timesteps and up to 100 s of flow time for the SR design and 300 s for the SB design. This long flowtime was required to allow the solidified layer to form and stabilize, but that does not necessarily mean that the simulations had reached a steady state for all the parameter combinations in the parameter study as some settings vastly decreased the speed at which the slag solidified. The domains were meshed using the mosaic meshing function in Fluent meshing which creates a poly-hexcore mesh with an inflation layer near the 18.
(36) Figure 5: The Slagrunner (SR) Design. Figure 6: The Stagnated Bath (SB) Design walls to properly resolve the thermal and viscous boundary layers. Such an approach allowed for coarser mesh elements in the bulk of the domain as the main focus of the simulation was on the shear stress and solidification behaviour in the near wall region. The mesh sensitivity of the simulations of the runners was studied using the GCI procedure as established by Richardson and further developed by Celik et al.[36][37]. By investigating how the value of some important parameters change with refinements in the mesh, a Grid Convergence Index (GCI) can be established as a measurement of the mesh independence of the simulation. The parameters considered for the mesh analysis of the runners was the heat flux through different sections of the cooled wall (denoted Heat 19.
(37) Table 3: Slagrunner Mesh Analysis Slagrunner Mesh 1 Mesh 2 Mesh 3 Elements 14015 75249 474366 Heat Flux 1 (kW) -21.01 -20.99 -20.93 Heat Flux 2 (kW) -18.14 -18.27 -18.46 Heat Flux 3 (kW) -18.91 -19.01 -19.21 3 -5 -5 Volume of Solid Slag (m ) 3.87·10 5.27·10 4.8·10-5 Wall Coverage (%) 0.09 92.07 85.40 Timestep (s) 0.005 0.005 0.005. GCI 0.003 0.038 0.016 0.055 0.006 -. Table 4: Stagnated Bath Stagnated Bath Mesh 1 Elements 141698 Heat Flux 1 (kW) -35.64 Heat Flux 2 (kW) -34.04 Heat Flux 3 (kW) -27.14 Volume of Solid Slag (m3 ) 8.59·10-4 Wall Coverage (%) 99.40 Timestep (s) 0.01. GCI 0.039 0.047 0.012 0.003 0.045 -. Mesh Analysis Mesh 2 Mesh 3 329976 751264 -38.58 -39.93 -37.86 -39.57 -30.07 -30.85 8.56·10-4 9.31·10-4 99.64 99.86 0.01 0.002. Flux 1, 2, and 3), the volume of solidified slag in the domain, as well as the wall coverage of solidified slag. The amount of solidified material in the domain was calculated using the custom field function in Equation 17. Solidif ied material = (1 − Slag liquid f raction) · slag V OF · cell volume. (17). The studied mesh sizes, resulting parameter values and calculated GCI for the SR design is listed in Table 3 and for the SB design in Table 4. From these tables we can see that the maximum GCI for the SR is in the volume of solidified slag at 5.5 % and for the SB it is the Heat Flux 2 at 4.7 %. This is considered a sufficiently low GCI to say that ”Mesh 2” is fine enough to produce a mesh independent solution for both the SR and SB design. The boundary conditions used for the runner simulations are mostly the same for both runner designs and are listed in Table 5. For the insulation area in the domains the material properties of alumina are used to represent a refractory lining with higher than usual thermal conductivity. Outside of the insulation domain the boundary conditions on the walls are imposed by a thermal boundary condition of 1 cm of steel shell for the SB design. For the SR design a 2 cm thick steel shell is imposed in the first third of the domain and 5 cm for the remaining two thirds. This difference in boundary 20.
(38) conditions was done to prevent clogging of the runner in the SR domain. Additional simulations in the SR design were done with a 1 cm thick steel shell for a more direct comparison between the two designs. Table 5: Boundary Conditions Boundary Condition Value Mass-flow-inlet 1.25 (kg·s-1 ) Inlet Slag Temperature 1650 (K) Backflow Air Temperature 300 (K) Mushy Zone Parameter 10000 Cooling water temp 300 (K). The exact material properties of the IronArc slag have not been experimentally established and were thus approximated based on existing data for similar slags with slightly lower FeO contents. The material properties of the IronArc slag and the other materials used in the simulations are presented in Table 6 [38][39][40]. Table 6: Material Properties IronArc Slag Alumina Density 3500 3000 Specific Heat 2000 600 Thermal Conductivity 2 20 Heat of Melting 250 Solidus Temperature 1550 Liquidus Temperature 1600 Viscosity 0.1 -. Air 1.225 1006 0.024 1.7·10-5. Steel 8030 502 16 -. Due to the uncertain value of the viscosity and thermal conductivity of the IronArc slag a parameter study was performed to study the impact of changing these material parameters as well as the impact of changing the value of the boundary conditions of Mass Flow Inlet and Mushy Zone parameter. The mass flow determines the maximum production rate of the IronArc reactor and by varying it between 0.5 and 5 kg·s-1 allows for production capacities of 15000-150000 tons per year. The effect of the Mushy Zone parameter was studied from 100 up to 200 000 to evaluate how the freeze-lining is affected. The parameter study mainly focused on how the freeze-lining coverage and thickness was affected by the variations in these parameters.. 21.
(39) The freeze-lining coverage on the walls of the runners was determined by establishing a histogram of the slag liquid fraction on the mesh elements on the walls. All cells with a slag liquid fraction below 0.1 (10 %) are considered solidified and since all the elements on the wall are of the same size, the fraction of cells covered in slag is equal to the fraction of wall area covered in solidified slag. The freeze-lining thickness was calculated by dividing the total amount of solidified material in the domain by the wall area in contact with the slag. 2.3.4. Gas Blowing Simulations. The gas blowing simulations were performed in OpenFOAM v7 by using the VOF model interFoam for the incompressible simulations and the compressibleInterFoam model for the compressible simulations in both the air-water system and the IronArc system. These simulations were performed in order to study the gas behavior in submerged gas blowing with varying Froude number to determine the penetration length of the gas into the liquid. The interFoam and compressibleInterFoam solvers in OpenFOAM can be used with many different turbulence models depending on the simulation. For the submerged gas-blowing simulations the k-ω SST DES turbulence model was used. This turbulence model combines the accuracy of a LES turbulence model in the areas of fine mesh with the efficiency of the k-ω model in the coarse areas of the mesh. The refinement area close to the inlet in the gas blowing simulations uses a small element size and can be solved using the LES model, while the bulk of the domain uses a coarse mesh which is solved by the k-ω turbulence model. Additionally, the GaussSeidel solver is used for the pressure calculations and the PBiCGStab solver is used for all other properties in the simulation. The maximum courant number for the simulations was set to 0.5 to increase the stability of the simulation. However, this caused the timesteps to be very small in the range of 10-6 to 10-5 depending on the mesh element size and inlet velocity. The simulations in the study were run to 2 s of flow time to ensure that the jet had developed fully and to allow for measurement of the standard deviation of the velocity and penetration length. The finest meshes used for the mesh sensitivity analysis and the high pressure simulations were not run for the full 2 s due to time constraints and very large computational demand for such fine meshes and high velocities. The domains used in the Gas blowing simulations were constructed using ANSYS SpaceClaim as rectangular boxes with circular inlets. Two different 22.
(40) domains were constructed for the study, one for the ambient temperature simulations which is used as a verification when compared to physical experiments in the air-water system, and one for the IronArc system. The domain for the ambient temperature simulations is 1x0.4x0.75 m with a liquid surface patched in at 0.55 m. The circular inlet is 4.6 mm and extends 16 mm into the domain at 98 mm above the bottom of the domain, this domain is depicted in Figure 7.. Figure 7: Simulation Domain for Ambient Temperature. The domain for the IronArc system is 2x1x2 m with a liquid surface patched in at 1.6 m. The circular inlet is 30 mm and extends 16 mm into the domain at 98 mm above the bottom, this domain is depicted in Figure 8. The inlet size was chosen to reflect the 3 MW plasma generator used by ScanArc which is proposed for the IronArc reactor. The larger domain was required to reduce the sloshing of the surface from the powerful gas jet which affected the measurement of the penetration length.. 23.
(41) Figure 8: Simulation Domain for the IronArc System. The domains were meshed using the cutcell approach in ANSYS Meshing with a refinement region in the small box close to the inlet to properly resolve the penetrating gas jet. The mesh was transformed to an OpenFOAM compatible mesh by the fluent3DMeshToFoam command. Similarly to the runner simulations the GCI of the gas blowing simulations was investigated by comparing three different meshes in both domains to determine if the solutions to the simulations were independent of the mesh. The chosen parameter for the mesh sensitivity analysis was the penetration length of the gas into the liquid. For the compressible simulations the average velocity at the inlet was also studied as it varied with mesh size for the pressure driven inlet. The mesh sensitivity analysis for the air-water system is shown in Table 7 for both the incompressible and compressible simulations. The listed cell size is the size in the refinement zone which is considerably smaller than in the bulk of the domain. Here it is apparent that the simulation is not fully independent of the mesh, but a finer mesh is not viable for the study as it would require too much computational power and time.. 24.
(42) Table 7: Ambient Waterlab Domain Elements Cell Size Incompressible Lp (cm) Compressible Lp (cm) Velocity. Temperature Mesh 1 257000 2 mm 11.34 ± 2.3 9.49 ± 2.1 204. Mesh Sensitivity Analysis Mesh 2 Mesh 3 631000 1128000 1.4 mm 0.8 mm 14.3 ± 2.5 16.48 ± 3.56 12.16 ± 2.5 14.47 ± 3.93 216 223. GCI 0.0244 0.1808 0.015. The mesh sensitivity analysis for the compressible system at high temperature in the IronArc system is significantly better for both the velocity and the penetration length as can be seen in Table 8. The low GCI for both the penetration length and velocity shows that the medium mesh can be used for the study as it produces very similar results to the much finer mesh. Table 8: IronArc System Mesh Sensitivity Analysis IronArc Domain Mesh 1 Mesh 2 Mesh 3 Elements 141k 285k 991k Cell Size 8 mm 6 mm 4 mm Lp (cm) 9.7 ± 6 16.4 ± 8.7 17.36 ± 10.13 Velocity 204 ± 187 393 ± 131 396 ± 165. GCI 0.0042 2.7·10-5. The penetration length used for the mesh sensitivity analysis and for comparison with the empirical equations is measured through the nozzle centerline to the point where the fraction of gas is lower than 10 %. This is equal to a value of alpha.liquid of 0.9, but the choice of 0.9 as a cutoff is arbitrary and different values will affect the measured penetration length. Due to the fluctuations in the jet the standard deviation of the penetration length is important for the study. The mesh sensitivity analysis for the IronArc system was done at a low inlet pressure of 177 kPa which was not sufficient to produce stable jetting, instead a pulsating behavior is observed. For the IronArc process the gas blowing must produce a jetting behavior to provide the necessary stirring for the process. Therefore a parameter study was done on the relationship between the inlet pressure and the velocity and penetration length for the gas jet in the IronArc system. This was also used to determine at what Froude number the transition regime from pulsating to jetting is to allow for the use of the empirical equation for penetration length. The boundary conditions for the incompressible simulation in the air-water system are chosen to closely replicate the experimental study done by 25.
(43) Chanouian and Ahlin in the air water system [41]. The experimental study used a gas flow rate of 240 l·min-1 to blow gas through a 4.6 mm inlet nozzle into water at room temperature which resulted in an approximate inlet velocity of 240 m·s-1 . The complete boundary conditions for the incompressible simulations are listed in Table 9. Table 9: Boundary Conditions for the Incompressible p rgh U Inlet fixedFluxPressure fixedValue (240 0 0) Outlet. fixedValue uniform 0. Walls Symmetry. fixedFluxPressure symmetry. pressureInlet OutletVelocity (0 0 0) noSlip symmetry. Air-Water System alpha.water inletOutlet inletValue 0 phi rhoPhi fixedValue uniform 0 zeroGradient symmetry. These boundary conditions were combined with the transport properties for air and water as listed in Table 10. Table 10: Transport Properties for the Incompressible Air-Water System Density (kg·m-3 ) Viscosity (m2 ·s-1 ) Surface Tension (N·m-1 ) Water 1000 1 · 10-6 0.07 Air 1.2 1.5 · 10-5. For the compressible simulations using the compressibleInterFoam solver the boundary conditions had to be modified to facilitate the pressure controlled inlet. For these simulations the pressure is controlled by p rgh which represents the static pressure minus the dynamic pressure. The static pressure (p) is also included in the simulation but is set with the ”calculated” boundary condition. The velocity boundary condition is set as the ”pressureInletOutletVelocity” condition with a zero value for both the inlet and the outlet boundary. The remaining boundary conditions for the compressible simulations are listed in Table 11.. 26.
(44) Table 11: Boundary Conditions for the Compressible Air-Water System p rgh T alpha.water Internal 101325 300 Inlet prghTotalPressure inletOutlet inletOutlet P0 150k Value 300 Phi rhoPhi Value 150k uniform 0 Outlet prghTotalPressure inletOutlet fixedValue P0 100k Value 300 uniform 0 Value 100k Walls fixedFluxPressure fixedValue 300 zeroGradient Symmetry symmetry symmetry symmetry. The values for the boundary conditions are modified when used in the IronArc system to reflect the conditions of the IronArc reactor. The temperature of the inlet gas is set to 3000 K and the inlet pressure set by p rgh is set to 177 kPa for the base case. The process temperature of 1700 K is set on the walls and outlet boundaries as well as in the internal field. To study the effect of the Froude number in the IronArc system, simulations were run with increasing inlet pressures up to 300 kPa. This increased inlet pressure causes higher inlet velocity and thus higher Froude number of the gas blowing. The thermophysical properties of the fluids for the compressible simulations require the molecular weight, specific heat, viscosity, Pr number and base density of the fluids since the density is calculated as a perfect fluid. The properties used in the compressible simulations and for the density variation simulations are listed in Table 12. Table 12: Transport Properties for Gasses and Mw Cp ν Pr (g·mol-1 ) (J·kg-1 ·K-1 ) (m2 ·s-1 ) number Air 29 1005 1.5 · 10-5 0.70 Helium 4 5200 1.0 · 10-4 0.71 Argon 40 520 1.2 · 10-6 0.68 Water 18 4191 1.0 · 10-6 2.28 Slag 70 2000 3.3 · 10-6 10 ZnCl 100 1840 6.3 · 10-6 Mercury 200 139 1.2 · 10-6 0.025. Liquids ρ0 (kg·m-3 ) 1.2 0.177 1.6 1000 3500 1900 13600. σ (N·m-1 ) 0.07 0.5 0.07 0.465. To compare the simulations to the empirical equation for different cases a 27.
(45) set of different liquids and gasses with varying densities were prepared and tested. Simulations were run with all combinations of the three gasses: air, helium and argon to the three liquids: water, ZnCl-solution, and mercury. The simulations for the density variations were run with the same boundary conditions as the incompressible simulations in the air-water system as listed in Table 9. 2.3.5. Validation Study. To study the accuracy of the CFD simulations the results were validated against physical experiments in published research which studied similar problems. The cases studied in the physical experiments were set up in simulations using the same solvers and turbulence models as used in the studies for the IronArc process. The runner simulations using the solidification model, the VOF model, and the RSM-BSL turbulence model were validated by comparison with the experimental work by Crivits et. al. in the CaCl-H2 O system [42]. The experimental work studies how a CaCl-H2 O solution solidifies on a cooled wall while the bulk of the material is flowing. The experimental domain of 300 x 100 x 50 mm was constructed in ANSYS Fluent according to the descriptions in the experimental work. The cooled wall was simulated using a mixed thermal boundary condition at 290 K with a 1 mm thick copper wall. The inlet into the domain was set as a mass flow inlet at 0.023 kg·s-1 with a temperature of 323 K to match the 854 ml·min-1 of 50 °C liquid used by Crivits et. al. in case 6. In the experimental work this case produced a 6.5 mm thick freeze-lining after 10 h. The material properties for the liquid in the verification simulation were taken from the work of Guevara et.al for a 53 % CaCl-H2 O solution [43] and the solidified phase was modelled with the material properties of CaCl-6H2 O from Samanta et.al.[44]. All density and viscosity variations due to temperature were disregarded to simplify the simulation, and as these factors are partially considered in the solidification model. The material parameters used for the solid and liquid phase in the simulation are listed in Table 13. In the mushy zone the parameters are interpolated between the solid and liquid values based on the temperature.. 28.
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