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JOM

, Volume 66, Issue 2, pp 235–244 | Cite as

Cathode Characterization with Steel and Copper Collector Bars in an Electrolytic Cell

  • Subrat DasEmail author
  • Yos Morsi
  • Geoffrey Brooks
Article

Abstract

This article presents finite-element method simulation results of current distribution in an aluminum electrolytic cell. The model uses one quarter of the cell as a computational domain assuming longitudinal (along the length of the cell) and transverse axes of symmetries. The purpose of this work is to closely examine the impact of steel and copper collector bars on the cell current distribution. The findings indicated that an inclined steel collector bar (φ = 1°) can save up to 10–12 mV from the cathode lining in comparison to a horizontal 100 mm × 150-mm steel collector bar. It is predicted that a copper collector bar has a much higher potential of saving cathode voltage drop (CVD) and has a greater impact on the overall current distribution in the cell. A copper collector bar with 72% of cathode length and size of 100 mm × 150 mm is predicted to have more than 150 mV savings in cathode lining. In addition, a significant improvement in current distribution over the entire cathode surface is achieved when compared with a similar size of steel collector bar. There is a reduction of more than 70% in peak current density value due to the higher conductivity of copper. Comparisons between steel and copper collector bars with different sizes are discussed in terms CVD and current density distribution. The most important aspect of the findings is to recognize the influence of copper collector bars on the current distribution in molten metal. Lorentz fields are evaluated at different sizes of steel and copper collector bars. The simulation predicts that there is 50% decrease in Lorentz force due to the improvement in current distribution in the molten metal.

Keywords

Molten Metal Current Distribution Cathode Surface Cryolite Horizontal Current 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© The Minerals, Metals & Materials Society 2013

Authors and Affiliations

  1. 1.Faculty of Science and Technology, School of EngineeringDeakin UniversityWaurn PondsAustralia
  2. 2.Faculty of Engineering and Industrial Sciences, FEISSwinburne University of TechnologyHawthornAustralia

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