Simulators for the AOD and CAS-OB processescc.oulu.fi/~kamahei/u/res_materials/poster_Visuri... ·...
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Introduction Process simulators enable testing of new steelmaking practices with less time and costs. The objective of this work was to develop thermodynamic- kinetic simulators for the Argon-Oxygen Decarburisation (AOD) and Composition Adjustment by Sealed argon blowing – Oxygen Bubbling (CAS-OB) processes. Both simulators employ a Law of Mass Action based kinetic approach [1]. Converter Process Simulator The Converter Process Simulator (CPS) is a modular thermodynamic- kinetic model for the AOD and similar converter processes (Fig. 1). The studied process stage and the modules required for calculation are determined based on inputs from the graphical user interface (Fig. 2). The simulator consists of three main reaction models: 1. The side-blowing model [2–3] assumes that the reactions take place in the gas plume, which is treated as a three-phase plug flow reactor. 2. In the top-blowing model [4–5] reactions take place simultaneously on the cavity and on the surface of the splashed metal droplets. 3. The reduction model [6–7] is based on the assumption that reactions take place between steel bath and slag droplets. CAS-OB Simulator The CAS-OB process simulator is divided into two main reaction models: 1. The heat-up model [8] considers chemical heating of steel bath by oxidation of aluminium with an oxygen jet (Fig. 3). The heat and mass transfer coefficients of the gas jet were determined with separate Computational Fluid Dynamics (CFD) simulations [9]; an illustration is shown in Fig. 4. 2. The reduction model [10] considers reactions and heat transfer between steel bath and top slag during the reduction stage. The development of the reduction model was preceded by a CFD study on the generation of slag droplets during bottom-blowing [11]. Simulators for the AOD and CAS-OB processes Ville-Valtteri Visuri *) , Petri Sulasalmi and Aki Kärnä Process Metallurgy Research Unit, University of Oulu, PO Box 4300, FI-90014 University of Oulu, Finland. *) Corresponding author. E-mail: [email protected]. Benefits The simulators can predict the dynamic changes in the compositions and temperatures of the metal, slag and gas phases (Figs. 5 and 6). Hence, the simulators are well-suited for decision support and process optimisation. They can be employed for optimising several process parameters including • composition and temperature of the material inputs, • composition and injection rate of gas, and • types of material additions and their feed rates. At Outokumpu Stainless Oy, the length of the AOD treatment of certain steel grades was reduced by 10% with the help of simulations with CPS and automation system [12]. The annual savings were valued at EUR 3 million in the case of full production. Summary The objective of this work was to develop computational simulation tools for the AOD and CAS-OB processes. Results from validation of the models suggest that the models yield reliable predictions for the composition and temperature of the steel produced. The simulators are powerful support tools for decisionmaking and process optimisation. As illustrated by the reduced length of the AOD process at Outokumpu Stainless, the potential financial benefits of mathematical modelling can be considerable. Acknowledgements This research has been conducted within the DIMECC SIMP research program. The Finnish Funding Agency for Innovation (TEKES), Outokumpu Stainless Oy and SSAB Europe Oy are acknowledged for funding this work. References [1] M. Järvinen, V.-V. Visuri, E.-P. Heikkinen, A. Kärnä, P. Sulasalmi, C. De Blasio and T. Fabritius, ISIJ Int., 56(9): 1543–1552, 2016. [2] M. P. Järvinen, S. Pisilä, A. Kärnä, T. Ikäheimonen, P. Kupari and T. Fabritius, Steel Res. Int., 82(6): 638–649, 2011. [3] S. E. Pisilä, M. P. Järvinen, A. Kärnä, T. Ikäheimonen, T. Fabritius and P. Kupari, Steel Res. Int., 82(6): 650–657, 2011. [4] V.-V. Visuri, M. Järvinen, A. Kärnä, P. Sulasalmi, E.-P. Heikkinen, P. Kupari and T. Fabritius, ”A Mathematical Model for Reactions during Top-Blowing in the AOD Process: Validation and Results”, under review. [5] V.-V. Visuri, M. Järvinen, A. Kärnä, P. Sulasalmi, E.-P. Heikkinen, P. Kupari and T. Fabritius, ”A Mathematical Model for Reactions during Top-Blowing in the AOD Process: Derivation of the Model”, under review. [6] V.-V. Visuri, M. Järvinen, P. Sulasalmi, E.-P. Heikkinen, J. Savolainen and T. Fabritius, ISIJ Int., 53(4): 603–612, 2013 [7] V.-V. Visuri, M. Järvinen, J. Savolainen, P. Sulasalmi, E.-P. Heikkinen and T. Fabritius, ISIJ Int., 53(4): 613–621, 2013. [8] M. Järvinen, A. Kärnä, V.-V. Visuri, P. Sulasalmi, E. P. Heikkinen, K. Pääskylä, C. De Blasio, S. Ollila, T. Fabritius, ISIJ Int., 54(10): 2263–2272, 2014 [9] A. Kärnä, M. P. Järvinen andT. Fabritius, Steel Res. Int., 86(11): 1370–1378, 2015. [10] P. Sulasalmi, V.-V. Visuri, A. Kärnä, M. Järvinen, S. Ollila and T. Fabritius, Metall. Mater. Trans. B, 2016, DOI: 10.1007/s11663-016-0769-8. [11] P. Sulasalmi, V.-V. Visuri,A. Kärnä and T. Fabritius, Steel Res. Int., 86(3): 212–222, 2015. [12] V. Kivelä, Master’s thesis, University of Oulu, 2016. Fig. 3. Schematic illustration of the CAS-OB process; heat-up (left) and reduction of slag (right). Fig. 6. Dimensionless steel composition after the reduction stage in the CAS-OB process [10]. Fig. 1. Structure of the CPS. Fig. 5. Carbon and chromium content during top-blowing in the AOD process. Fig. 4. Supersonic oxygen jet inside the CAS-OB bell [9]. Fig. 2. Graphical user interface of the CPS.
Transcript of Simulators for the AOD and CAS-OB processescc.oulu.fi/~kamahei/u/res_materials/poster_Visuri... ·...
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IntroductionProcess simulators enable testing of new steelmaking practices with lesstime and costs. The objective of this work was to develop thermodynamic-kinetic simulators for the Argon-Oxygen Decarburisation (AOD) andComposition Adjustment by Sealed argon blowing – Oxygen Bubbling(CAS-OB) processes. Both simulators employ a Law of Mass Action basedkinetic approach [1].
Converter Process SimulatorThe Converter Process Simulator (CPS) is a modular thermodynamic-kinetic model for the AOD and similar converter processes (Fig. 1). Thestudied process stage and the modules required for calculation aredetermined based on inputs from the graphical user interface (Fig. 2). Thesimulator consists of three main reaction models:
1. The side-blowing model [2–3] assumes that the reactions take place inthe gas plume, which is treated as a three-phase plug flow reactor.
2. In the top-blowing model [4–5] reactions take place simultaneously onthe cavity and on the surface of the splashed metal droplets.
3. The reduction model [6–7] is based on the assumption that reactionstake place between steel bath and slag droplets.
CAS-OB SimulatorThe CAS-OB process simulator is divided into two main reaction models:
1. The heat-up model [8] considers chemical heating of steel bath byoxidation of aluminium with an oxygen jet (Fig. 3). The heat and masstransfer coefficients of the gas jet were determined with separateComputational Fluid Dynamics (CFD) simulations [9]; an illustration isshown in Fig. 4.
2. The reduction model [10] considers reactions and heat transferbetween steel bath and top slag during the reduction stage. Thedevelopment of the reduction model was preceded by a CFD study onthe generation of slag droplets during bottom-blowing [11].
Simulators for the AOD and CAS-OB processes
Ville-Valtteri Visuri*), Petri Sulasalmi and Aki KärnäProcess Metallurgy Research Unit, University of Oulu, PO Box 4300, FI-90014 University of Oulu, Finland.*) Corresponding author. E-mail: [email protected].
BenefitsThe simulators can predict the dynamic changes in the compositions andtemperatures of the metal, slag and gas phases (Figs. 5 and 6). Hence, thesimulators are well-suited for decision support and process optimisation. Theycan be employed for optimising several process parameters including
• composition and temperature of the material inputs,• composition and injection rate of gas, and• types of material additions and their feed rates.
At Outokumpu Stainless Oy, the length of the AOD treatment of certain steelgrades was reduced by 10% with the help of simulations with CPS andautomation system [12]. The annual savings were valued at EUR 3 million inthe case of full production.
SummaryThe objective of this work was to develop computational simulation tools forthe AOD and CAS-OB processes. Results from validation of the modelssuggest that the models yield reliable predictions for the composition andtemperature of the steel produced. The simulators are powerful support toolsfor decisionmaking and process optimisation. As illustrated by the reducedlength of the AOD process at Outokumpu Stainless, the potential financialbenefits of mathematical modelling can be considerable.
AcknowledgementsThis research has been conducted within the DIMECC SIMP researchprogram. The Finnish Funding Agency for Innovation (TEKES), OutokumpuStainless Oy and SSAB Europe Oy are acknowledged for funding this work.
References[1] M. Järvinen, V.-V. Visuri, E.-P. Heikkinen, A. Kärnä, P. Sulasalmi, C. De Blasio and T. Fabritius,
ISIJ Int., 56(9): 1543–1552, 2016.[2] M. P. Järvinen, S. Pisilä, A. Kärnä, T. Ikäheimonen, P. Kupari and T. Fabritius, Steel Res.
Int., 82(6): 638–649, 2011.[3] S. E. Pisilä, M. P. Järvinen, A. Kärnä, T. Ikäheimonen, T. Fabritius and P. Kupari, Steel Res.
Int., 82(6): 650–657, 2011.[4] V.-V. Visuri, M. Järvinen, A. Kärnä, P. Sulasalmi, E.-P. Heikkinen, P. Kupari and T. Fabritius,
”A Mathematical Model for Reactions during Top-Blowing in the AOD Process: Validationand Results”, under review.
[5] V.-V. Visuri, M. Järvinen, A. Kärnä, P. Sulasalmi, E.-P. Heikkinen, P. Kupari and T. Fabritius,”A Mathematical Model for Reactions during Top-Blowing in the AOD Process: Derivationof the Model”, under review.
[6] V.-V. Visuri, M. Järvinen, P. Sulasalmi, E.-P. Heikkinen, J. Savolainen and T. Fabritius, ISIJ Int.,53(4): 603–612, 2013
[7] V.-V. Visuri, M. Järvinen, J. Savolainen, P. Sulasalmi, E.-P. Heikkinen and T. Fabritius, ISIJInt., 53(4): 613–621, 2013.
[8] M. Järvinen, A. Kärnä, V.-V. Visuri, P. Sulasalmi, E. P. Heikkinen, K. Pääskylä, C. De Blasio,S. Ollila, T. Fabritius, ISIJ Int., 54(10): 2263–2272, 2014
[9] A. Kärnä, M. P. Järvinen and T. Fabritius, Steel Res. Int., 86(11): 1370–1378, 2015.[10] P. Sulasalmi, V.-V. Visuri, A. Kärnä, M. Järvinen, S. Ollila and T. Fabritius, Metall. Mater.
Trans. B, 2016, DOI: 10.1007/s11663-016-0769-8.[11] P. Sulasalmi, V.-V. Visuri, A. Kärnä and T. Fabritius, Steel Res. Int., 86(3): 212–222, 2015.[12] V. Kivelä, Master’s thesis, University of Oulu, 2016.
Fig. 3. Schematic illustration of the CAS-OB process;heat-up (left) and reduction of slag (right).
Fig. 6. Dimensionless steel compositionafter the reduction stage in the CAS-OBprocess [10].
Fig. 1. Structure of the CPS.
Fig. 5. Carbon and chromium content duringtop-blowing in the AOD process.
Fig. 4. Supersonic oxygen jetinside the CAS-OB bell [9].
Fig. 2. Graphical user interface of the CPS.
