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2022 | OriginalPaper | Chapter

A Pragmatic Model for Alumina Feeding

Authors : Stein Tore Johansen, Kristian Etienne Einarsrud, Asbjørn Solheim, Kurian J. Vachaparambil

Published in: Light Metals 2022

Publisher: Springer International Publishing

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Abstract

In this paper, we demonstrate how we can develop a coarse-grained model for the alumina distribution in an aluminium reduction cell. The model is designed to have the potential of being a part of a control system or play the role of a Digital Twin. The modelling work is applying the concepts of Pragmatism in Industrial Modelling [5]. The task is to be able to dynamically keep track of where dissolved and undissolved alumina are inside the cell. The numerical grid is the coarsest possible, and special numerical techniques are applied to support fast simulations. The bath (electrolyte) flow is obtained from detailed CFD simulations and imported into the coarse-grained model. A method to deal with dispersion in such a coarse-grained model is developed. The physics of particulate alumina dissolution and the electrochemical consumption of dissolved alumina at the anodes are represented. A simple model for the current distribution through the anodes is applied. The model is typically running much faster than real time. In demonstration simulations, the model runs 50–500 times faster than real time. From these, it can be observed how alumina particles and dissolved alumina distribute in time and space. Regions where anode effects are expected to initiate can be observed as well as the impacts of changing the feeding pattern and positions for the alumina. The numerical approach is inspired by previous works [9, 10]. The possibilities and limitations of the approach are discussed.

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previous chapter Statistical Model for Forecasting the Cell Replacement Rate in an Aluminum Smelter

next chapter Stabilizing a Low-Dimensional Model of Magnetohydrodynamic Instabilities in Aluminum Electrolysis Cells

The Schiller-Naumann drag coefficient (\(C_D\)) is calculated based on the following equation: \(C_D = \frac{24}{Re_p}\left( 1.0 + 0.15Re_p^{0.657} \right) + \frac{0.407}{1.0+\frac{8710}{Re_p}}\).

The mass imbalance is determined as the difference between the difference in the Numerically accumulated alumina mass between \({t=0s}\) and the last time step. The mass imbalance should theoretically be equal to zero at any time step to ensure that the framework conserves mass.

Winix Technologies. https://medium.com/@winix/industry-4-0-the-digital-technology-transformation-b23ba02a7dd2. Accessed 27 August 2021

Wikipedia. https://en.wikipedia.org/wiki/Digitization. Accessed 27 August 2021

Lin Y-W, Tang TLE, Spanos CJ (2021) Hybrid Approach for Digital Twins in the Built Environment. In e-Energy ’21: Proceedings of the Twelfth ACM International Conference on Future Energy Systems. Italy, pp. 450–457. https://doi.org/10.1145/3447555.3466585

Abburu S, Berre AJ, Jacoby M, Roman D, Stojanovic L, Stojanovic N (2020) COGNITWIN – Hybrid and Cognitive Digital Twins for the Process Industry. In 2020 IEEE International Conference on Engineering, Technology and Innovation (ICE/ITMC). Cardiff, United Kingdom, June 2020, pp. 1–8. https://ieeexplore.ieee.org/document/9198403

Zoric J, Johansen ST, Einarsrud KE, and Solheim A (2015) On pragmatism in industrial modeling. In Progress in Applied CFD; Selected papers from 10th International Conference on Computational Fluid Dynamics in the Oil & Gas, Metallurgical and Process Industries. Trondheim, Norway 2015, pp. 9–24. http://hdl.handle.net/11250/2464595. Accessed 25 August 2021

Zoric J, Busch A, Meese EA, Khatibi M (2015) On pragmatism in industrial modeling - part II: workflows and associated data and metadata. Presented at the 11th International Conference on CFD in the Minerals and Process Industries. Melbourne, Australia, 7–9 December, 2015. https://www.cfd.com.au/cfd_conf15/PDFs/032JOH.pdf. Accessed 25 August 2021

Johansen ST, Messe EA, Zoric J, Islam A, Martins DW (2017) On pragmatism in industrial modeling part iii: application to operational drilling. In Progress in Applied CFD – CFD2017 Proceedings of the 12th International Conference on Computational Fluid Dynamics in the Oil & Gas, Metallurgical and Process Industries. Trondheim, Norway, 30 May-1 June, 2017. http://hdl.handle.net/11250/2465068. Accessed 25 August 2021

Johansen ST, Ringdalen E (2018) Reduced metal loss to slag in HC FeCr production - by redesign based on mathematical modelling. In: Steenkamp JD & Cowey A (eds) Furnace Tapping 2018 Conference. Kruger National Park, South Africa, 14–17 October 2018, pp. 29–38. http://www.saimm.co.za/Conferences/FurnaceTapping2018/029-Johansen.pdf. Accessed 25 August 2021

Meese EA, Johansen ST (2017) A simulation concept for generic simulation of multi-material flow using staggered cartesian grids. In Progress in Applied CFD – CFD2017 Proceedings of the 12th International Conference on Computational Fluid Dynamics in the Oil & Gas, Metallurgical and Process Industries. Trondheim, Norway, 30 May-1 June, 2017. pp. 253–263. http://hdl.handle.net/11250/2480173. Accessed 25 August 2021

10.

Dang ST, Meese EA, Morud JC, Johansen ST (2019) Numerical approach for generic three-phase flow based on cut-cell and ghost fluid methods. Int J Numer Meth Fluids 91:419–447. https://doi.org/10.1002/fld.4758.

11.

Lavoie P, Taylor MP and Metson JB (2016) A Review of Alumina Feeding and Dissolution Factors in Aluminum Reduction Cells, Metall and Materi Trans B, 47(4):2690–2696. https://doi.org/10.1007/s11663-016-0680-3.

12.

Lavoie P, Taylor MP (2016) Alumina Concentration Gradients in Aluminium Reduction Cells, In: Reddy RG, Chaubal P, Pistorius PC, Pal U (eds) Advances in Molten Slags, Fluxes, and Salts: Proceedings of the 10th International Conference on Molten Slags, Fluxes and Salts 2016. Springer, Cham. https://doi.org/10.1007/978-3-319-48769-4_84

13.

Kaszas C, Kiss L, Poncsak S, Guerard S, Bilodeau JF (2017) Spreading of Alumina and Raft Formation on the Surface of Cryolitic Bath, Light Metals 2017, pp. 473–478. https://doi.org/10.1007/978-3-319-51541-0_59

14.

Alarie J, Roger T, Kiss LI, Poncsak S, Guerard S, Bilodeau JF (2020) Validation of the Gravimetric Method to Properly Follow Alumina Dissolution in Cryolitic Bath Light Metals 2020, pp. 680–687. https://doi.org/10.1007/978-3-030-36408-3_92

15.

Yang Y, Gao B, Wang Z, Shi Z, Hu X (2015) Study on the Dissolution of Alumina in Cryolite Electrolyte Using the See-Through Cell, Light Metals 2015, pp. 583–588. https://doi.org/10.1002/9781119093435.ch97

16.

Gylver SE, Omdahl NH, Prytz AK, Meyer AJ, Lossius LP, Einarsrud KE (2019) Alumina Feeding and Raft Formation: Raft Collection and Process Parameters, Light Metals 2019, pp. 659–666. https://doi.org/10.1007/978-3-030-05864-7_81

17.

Gylver SE, Omdahl NH, Rørvik S, Hansen I, Nautnes A, Neverdal SN, Einarsrud KE (2019) The Micro- and Macrostructure of Alumina Rafts, Light Metals 2019, pp. 689–696. https://doi.org/10.1007/978-3-030-05864-7_85

18.

Gylver SE, Solheim A, Gudbrandsen H, Follo ÅH, Einarsrud KE (2020) Lab Scale Experiments on Alumina Raft Formation, Light Metals 2020, pp. 659–663. https://doi.org/10.1007/978-3-030-36408-3_89

19.

Roger T, Kiss L, Fraser K, Poncsak S, Guerard S, Bilodeau JF (2019) Development of a Mathematical Model to Follow Alumina Injection, Light Metals 2019, pp. 683–688. https://doi.org/10.1007/978-3-030-05864-7_84

20.

Roger T, Kiss L, Fraser K, Poncsak S, Guerard S, Bilodeau JF. Bonneau G (2020) Development of a Mathematical Model to Simulate Raft Formation, Light Metals 2020, pp. 688–695. https://doi.org/10.1007/978-3-030-36408-3_93.

21.

Feng Y, Cooksey MA, Schwarz MP (2011) CFD Modelling of Alumina Mixing in Aluminium Reduction Cells, Light Metals 2011, pp. 543–548. https://doi.org/10.1007/978-3-319-48160-9_96

22.

Einarsrud KE, Eick I, Bai W, Feng Y, Hua J, Witt PJ (2017) Towards a coupled multi-scale, multi-physics simulation framework for aluminium electrolysis, Appl Math Model 44:3–24. https://doi.org/10.1016/j.apm.2016.11.011

23.

Zhan S, Li M, Zhou J, Yang J, Zhou Y (2014) CFD simulation of dissolution process of alumina in an aluminum reduction cell with two-particle phase population balance model, Appl Therm Eng 73(1):805–818. https://doi.org/10.1016/j.applthermaleng.2014.08.040

24.

Zhan S, Li M, Zhou J, Yang J, Zhou Y (2015) Analysis and modeling of alumina dissolution based on heat and mass transfer, Trans Nonferrous Met Soc China 25(5):1648–1656. https://doi.org/10.1016/S1003-6326(15)63770-0

25.

Bardet B, Foetisch T, Renaudier S, Rappaz J, Flueck M, Picasso M (2016) Alumina Dissolution Modeling in Aluminium Electrolysis Cell Considering MHD Driven Convection and Thermal Impact, Light Metals 2016, pp. 315–319. https://doi.org/10.1002/9781119274780.ch52

26.

Bojarevics V, Dynamic Modelling of Alumina Feeding in an Aluminium Electrolysis Cell, Light Metals 2019, pp. 675–682. https://doi.org/10.1007/978-3-030-05864-7_83

27.

Haverkamp RG, Welch BJ (1998) Modelling the dissolution of alumina powder in cryolite, Chem Eng Process 37(2):177–187. https://doi.org/10.1016/S0255-2701(97)00048-2.

28.

ParaView. www.paraview.org. Accessed on 24 July 2021.

Title: A Pragmatic Model for Alumina Feeding
Authors: Stein Tore Johansen
Kristian Etienne Einarsrud
Asbjørn Solheim
Kurian J. Vachaparambil
Publisher: Springer International Publishing
Book: Light Metals 2022
Print ISBN: 978-3-030-92528-4

Electronic ISBN: 978-3-030-92529-1

Copyright Year: 2022
DOI: https://doi.org/10.1007/978-3-030-92529-1_67

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