Simulation of alumina dissolution and temperature response under different feeding quantities in aluminum reduction cell

Abstract

In the feeding process of aluminum electrolytic, feeding quantity of alumina affects eventually dissolved quantity at the end of a feeding cycle. Based on the OpenFOAM platform, dissolution model coupled with heat and mass transfer was established. Applying the Rosin-Rammler function, alumina particle size distribution under different feeding quantities was obtained. The temperature response of electrolyte after feeding was included and calculated, and the dissolution processes of alumina with different feeding quantities (0.6, 0.8, 1.0, 1.2, 1.4, 1.6 kg) after feeding were simulated in 300 kA aluminum reduction cell. The results show that with the increase of feeding quantity, accumulated mass fraction of dissolved alumina decreases, and the time required for the rapid dissolution stage extends. When the feeding quantity is 0.6 kg and 1.2 kg, it takes the shortest time for the electrolyte temperature dropping before rebounding back. With the increase of feeding quantity, the dissolution rate in the rapid dissolution stage increases at first and then decreases gradually. The most suitable feeding quantity is 1.2 kg. The fitting equation of alumina dissolution curve under different feeding quantities is obtained, which can be used to evaluate the alumina dissolution and guide the feeding quantity and feeding cycle.

Keywords

alumina dissolution / heat and mass transfer / particle size distribution / temperature response / numerical simulation

References

[1] YangY-j, GaoB-l, WangZ-w, ShiZ-n, HuX-wei. Effect of physiochemical properties and bath chemistry on alumina dissolution rate in cryolite electrolyte [J]. JOM, 2015, 67(5): 973-983

[2] YangZ-h, GaoB-l, XuN, QiuZ-x, LiuY-kuan. Dissolution of alumina in molten cryolite (photogrammetry) [J]. Journal of Northeastern University, 1999, 20(4): 398-400

[3] QiuZ-x, YangZ-h, GaoB-l, XuN, LiuY-kuan. Dissolution of alumina in molten cryolite (A video recording study) [C]. ECKERT CE Light Metals 1999, 1999, San Diego, CA, TMS: 467471

[4] XuJ-l, ShiZ-n, GaoB-l, QiuZ-xian. Dissolution of alumina in melted cryolite [J]. Journal of Northeastern University, 2003, 24(9): 832-834

[5] WalkerD IAlumina in aluminum smelting and its behaviour after addition to cryolite-based electrolytes [D], 1993, Toronto, University of Toronto

[6] WelchB J, KushelG I. Crust and alumina powder dissolution in aluminum smelting electrolytes [J]. JOM, 2007, 59(5): 50-54

[7] PoiN W, HaverkampR G, KublerS. Thermal effects associated with alumina feeding in aluminum reduction cells. MANNWEILER U. Light Metals 1994, 1994, San Francisco, CA, TMS: 219225

[8] VerhaegheF, BlanpainB, WollantsP. Dissolution of a solid sphere in a multi component liquid in a cubic enclosure[J]. Modelling and Simulation in Materials Science and Engineering, 2008, 164: 45007

[9] LillebuenB O R, BuggeM, HoieH. . Alumina dissolution and current efficiency in Hall-Heroult cells [C]. BEARNE G. Light Metals 2009, 2009, San Francisco, CA, TMS: 389-394

[10] BerezinA I, IsaevaL A, BelolipetskyV M, PoskazhovaT V, SinelnikovV V. A model of dissolution and heating of alumina charged by point-feeding system in “Virtual Cell” program [C]. KVANDE H. Light Metals 2005, 2005, San Francisco, CA, TMS: 151156

[11] TaylorM P, WelchB J, MckibbinR. Effect of convective heat transfer and phase change on the stability of aluminum smelting cells [J]. AICHE Journal, 1986, 32(9): 1459-1465.

[12] HouW-y, LiH-s, LiM, ZhangB, WangY-j, GaoY-t. Multi-physical field coupling numerical investigation of alumina dissolution [J]. Applied Mathematical Modelling, 2019, 67: 588-604

[13] ZhanS-q, LiM, ZhouJ-m, ZhouY-w, YangJ-hong. Numerical simulation of alumina concentration distribution in melt of aluminum reduction cell [J]. Chinese Journal of Nonferrous Metals, 2014, 24(10): 2658-2667

[14] ZhangH-huiNumerical simulation of melt vortex motion and alumina transport process in aluminum electrolysis cell [D], 2012, Changsha, Central South University

[15] FengY-q, CookseyM A, SchwarzM P. CFD modelling of alumina mixing in aluminum reduction cells [C]//. JOHNSON J A. Light Metals 2010, 2010, Seattle, WA, TMS: 455460

[16] ZhanS-q, LiM, ZhouJ-m, YangJ-h, ZhouY-wen. CFD simulation of dissolution process of alumina in an aluminum reduction cell with two-particle phase population balance model [J]. Applied Thermal Engineering, 2015, 73: 803-816

[17] AsanoKMass transfer: From fundamentals to modern industrial applications [M], 2006, Weinheim, Wiley-Vch Verlag GmbH & Co

[18] ZhangM-j, QiuZ-xian. Research on mathematical model of industrial aluminum electrolyte melting point [J]. Light Metal, 19811522

[19] HouW-yuanNumerical simulation of dissolution process of alumina particles in aluminum electrolysis cell [D], 2015, Changsha, Central South University

[20] FengN-xiangAluminum electrolysis [M], 2006, Beijing, Chemical Industry Press

[21] ZhanS-q, LiM, ZhouJ-m, YangJ-h, ZhouY-wen. CFD simulation of effect of anode configuration on gas-liquid flow and alumina transport process in an aluminum reduction cell [J]. Journal of Central South University, 2015, 22(7): 2482-2492

[22] PeterNEvolution of alpha phase alumina in agglomerates upon addition to cryolitic melts [D], 2002, Trondheim, Norwegian University of Science and Technology

[23] KobbeltvedtODissolution kinetics for alumina in cryolite melts [D], 1997, Trondheim, Department of Electrochemistry, Norwegian University of Science and Technology

[24] LiY-q, TangW, ChenY, LiuJ-w, LeeC F. Potential of acetone-butanol-ethanol (ABE) as a biofuel [J]. Fuel, 2019, 242: 673-686

[25] LiuG, LiM-s, ZhouB-j, Cheny-y, LiaoS-ming. General indicator for techno-economic assessment of renewable energy resources [J]. Energy Conversion and Management, 2018, 156: 416-426