Dion Lukas, Lagacé Charles-Luc, Kiss László et Poncsák Sándor. (2016). Using artificial neural network to predict low voltage anode effect PFCs at the duct end of an electrolysis cell. Dans : 145th Annual Meeting & Exhibition, TMS Light Metals 2016 , February 14-18, 2016, Nashville, Tennessee.
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Résumé
Primary aluminum production is generating a significant amount of greenhouse gases. CO2 is the dominant compound but during anode effects, perfluorocarbons (PFCs) are released as well. Even when no generalized anode effects are present, intermittent emissions of PFC have been reported in small concentrations but the root causes of these emissions are hardly understood. Measurements were taken at “Aluminerie Alouette” plant using Fourier-transformed Infrared Spectroscopy on individual cells to analyze the evolution of the composition of the gas collected at the duct end. By correlating the variations of the concentration for the emitted gas with cell variables (voltage, intensity, and pseudo-resistivity) and individual anode currents, it was possible to develop a predictive model to quantify the tetrafluoromethane (CF4) emissions between 10 and 1000 ppb for individual cell emissions. By analyzing the time history of the resulting data and by applying a post treatment process accordingly, it is possible to reduce the number of false predictions and increase precision of the final results.
| Type de document: | Matériel de conférence (Non spécifié) |
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| Date: | 20 Décembre 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 |
| Liens connexes: | |
| Mots-clés: | tetrafluoromethane, perfluorocarbons, GHG emissions, predictive model, neural network, low voltage anode effect, tétrafluorométhane, perfluorocarbures, émissions de GES, modèle prédictif, réseau neuronal, effet anode basse tension |
| Déposé le: | 27 janv. 2021 23:10 |
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| Dernière modification: | 27 janv. 2021 23:10 |
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