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Prediction of low-voltage tetrafluoromethane emissions based on the operating conditions of an aluminium electrolysis cell

Dion Lukas, Kiss László, Poncsák Sándor et Lagacé Charles-Luc. (2016). Prediction of low-voltage tetrafluoromethane emissions based on the operating conditions of an aluminium electrolysis cell. Journal of The Minerals, Metals & Materials Society, 68, (9), p. 2472-2482.

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URL officielle: http://dx.doi.org/doi:10.1007/s11837-016-2043-6

Résumé

Greenhouse gas (GHG) generation is inherent in the production of aluminium by a technology that uses carbon anodes. Most of those GHG are composed of CO2 produced by redox reaction that occurs in the cell. However, a significant fraction of the annual GHG production is composed of perfluorocarbons (PFC) resulting from anode effects (AE). Multiple investigations have shown that tetrafluoromethane (CF4) can be generated under low-voltage conditions in the electrolysis cells, without global anode effect. The aim of this paper is to find a quantitative relationship between monitored cell parameters and the emissions of CF4. To achieve this goal, a predictive algorithm has been developed using seven cell indicators. These indicators are based on the cell voltage, the noise level and other parameters calculated from individual anode current monitoring. The predictive algorithm is structured into three different steps. The first two steps give qualitative information while the third one quantitatively describes the expected CF4 concentration at the duct end of the electrolysis cells. Validations after each step are presented and discussed. Finally, a sensitivity analysis was performed to understand the effect of each indicator on the onset of low-voltage PFC emissions. The standard deviation of individual anode currents was found to be the dominant variable. Cell voltage, noise level, and maximum individual anode current also showed a significant correlation with the presence of CF4 in the output gas of an electrolysis cell.

Type de document:Article publié dans une revue avec comité d'évaluation
Volume:68
Numéro:9
Pages:p. 2472-2482
Version évaluée par les pairs:Oui
Date:2 Août 2016
Sujets:Sciences naturelles et génie > Génie
Sciences naturelles et génie > Génie > Génie des matériaux et génie métallurgique
Département, module, service et unité de recherche:Départements et modules > Département des sciences appliquées > Module d'ingénierie
Mots-clés:Cell voltage, electrolysis cell, predictive algorithm, anode effect, aluminium industry, tension de cellule, cellule d'électrolyse, algorithme prédictif, effet d'anode, industrie de l'aluminium
Déposé le:22 janv. 2021 01:21
Dernière modification:26 janv. 2021 22:47
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Creative Commons LicenseSauf indication contraire, les documents archivés dans Constellation sont rendus disponibles selon les termes de la licence Creative Commons "Paternité, pas d'utilisation commerciale, pas de modification" 2.5 Canada.

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