Gary P. Tarcy

Corrosion and Passivation of Cermet Inert Anodes in Cryolite-Type Electrolytes

Cermets are a class of materials that offer promise as inert anodes in aluminum smelting because of the low solubilities of certain oxides in cryolite and high conductivities of the metal phase. Electrochemical dissolution of the metal phase in the cermets can lead to premature failure of the anode. The electrochemical corrosion of various metals and alloy candidate phases has been investigated with linear sweep voltammetry, galvanostatic polarizations and microprobe elemental dot map analysis. The investigation showed that nickel is an unacceptable metal for cermet anodes. Noble metals are cathodically protected from anodic dissolution while copper/nickel alloys undergo a passivation. The passivation is strictly valid with cermets only and dependent on the use of copper rich alloys and high alumina concentrations in the melt. The passivation is independent of microstructural size of the alloy particles, concentration of the alloy phase, current density, dissolved aluminum metal and time.

Effect of Open Holes in the Crust on Gaseous Fluoride Evolution from Pots

Changes in fluoride evolution from aluminum smelting pots have direct consequences on pot gas scrubber loads and resultant smelter emissions. Changes in fluoride evolution can also have dramatic implications on bath chemistry control and the resulting pot performance. Both of these factors motivate continuing efforts to quantify the effect of pot operating practices on fluoride evolution in order to prioritize the amount of effort to place on any given practice to minimize fluoride evolution. Gaseous fluoride evolution measurements were made at several smelters and demonstrate a strong correlation between the amount of gaseous fluoride evolved from an individual pot and the total area of open holes in the crust. Data from pots of different types suggest that it is possible to normalize the data to allow predictions for other pot sizes and geometries. In almost every case, the additional fluorides lost due to holes in the crust comprise the largest fraction of the total gaseous evolution.

Active Pot Control using Alcoa STARprobe

To run an aluminum smelting cell, routine bath sampling and subsequent chemistry analysis are required along with pot temperature measurement. The sampling and analytical process is lengthy, tedious, and very often results are delayed as long as 24 hours. In addition the results are not coupled to other critical information (e.g. noise, automatic resistance adjustments, etc) at the time of the sample. Alcoa STARprobe™, which was previously described (1), corrects these deficiencies while providing a means to more efficiently and effectively control a smelting pot. This paper presents the background philosophy for an advanced control that has been enabled by the new measurement technique. The control method has been applied in multiple plants and demonstration of improved performance will be shown.

Towards On-line Monitoring of Alumina Properties at a Pot Level

Aluminum reduction cells typically use about 1.9 kg of alumina in order to produce 1 kg of aluminum. Hence, for modern reduction cells operating in the 350 to 400 kA range, 5000 to 6000 kg of alumina is fed to reduction cells on a daily basis. However, no information is available in an on-line fashion about the alumina properties fed to the pot. Alumina feeding control systems assume that alumina properties are constant for all pots within a potroom and also over time. Therefore, these control systems aim at controlling alumina concentration dissolved in the bath without accounting for the time varying effects of alumina properties and/or pot condition on alumina dissolution. Based on sampling campaigns, this paper presents evidences of time varying alumina properties impacting its dissolution rate and also proposes a novel approach in order to measure on-line, at the pot, parameters that are related to alumina dissolution.

Multiblock Monitoring of Aluminum Reduction Cells Performance

Aluminum reduction cells performance are affected by many factors. In order to efficiently understand possible causes of performance upsets, all major sources of variations have to be monitored. This implies monitoring all anode and alumina properties, as well as pot state and manipulated variables, while also taking into account pot design or integrity after start-up. Considering the high number of variables involved in such a task, this is practically impossible using typical statistical process control tools. The problem is even worst when applied on a pot basis. This paper proposes the use of multiblock PLS (MBPLS) to build a monitoring scheme on a pot basis, simultaneously taking into account the influence of alumina and anode properties, of pot state and manipulated variables, as well as the pot state following its start-up. Derived from a regression model, the monitoring policy ensures that only variations relevant to pot performance variations are highlighted.

Improvement of Alumina Dissolution Rate through Alumina Feeder Pipe Modification

Aluminum reduction cells use about 1.9 kg of alumina in order to produce 1 kg of aluminum. That is, for modern reduction cells operating in the 350 to 400 kA range, 5000 to 6000 kg of alumina is fed daily. Considering that 5000 to 10000 kg of molten bath is available to dissolve the alumina, the dissolution rate is an important factor in order to avoid muck and enable alumina feed control system to operate within the 2 to 5% alumina concentration. However, on top of cell status, alumina properties have an impact on alumina dissolution rate. Hence, supplier changes and/or segregation of alumina within the delivery system may have negative impact on alumina dissolution rate leading to muck and/or anode effects. This paper discusses modification to an alumina feeder pipe promoting the dissolution rate. Promising results obtained during trial in a pilot plant section are presented and discussed.

Multivariate Specifications of Raw Materials: Application to Aluminum Reduction Cells

Abstract A metallurgical process generally processes some raw materials or ores into concentrates or primary metals using different technologies. However, the quality of the incoming raw materials has an effect on the process performance. Hence, engineers have to apply different set points in order to account or compensate for raw material quality variations. This is frequently performed using a set of univariate specifications. In this paper, a methodology to build multivariate specifications is presented and illustrated using a case study from an aluminum reduction smelter.