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Effect of coke granulometry on the properties of carbon anodes based on experimental study and ANN analysis

Sarkar Arunima, Kocaefe Duygu, Kocaefe Yasar S., Bhattacharyay Dipankar, Morais Brigitte et Coulombe Patrick. (2016). Effect of coke granulometry on the properties of carbon anodes based on experimental study and ANN analysis. Journal of Materials Science Research, 5, (4), p. 63-78.

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URL officielle: http://dx.doi.org/10.5539/jmsr.v5n4p63

Résumé

The available anode-quality petroleum coke is not sufficient to cover the need created by the increase in the world aluminum production. Understanding the consequences of varying calcined coke quality is necessary to possibly compensate for the reduction in coke quality and adjust the anode paste recipe in the subsequent use of coke in order to obtain economically viable production of aluminum. Different fractions of coke particles were mixed to optimize the anode recipe; however, it was laborious to find experimentally the suitable percentage of each fraction in anode paste which would give good anode properties. In this study, Artificial Neural Network (ANN) model was developed for adjusting the granulometry of the raw materials for anode production. Tapped bulk density of dry aggregates was used to predict the anode paste recipe using the ANN method. A new anode recipe (by adjusting the medium fraction in the paste) was proposed based on the predictions of an ANN model, which resulted in improved anode properties.

Type de document:Article publié dans une revue avec comité d'évaluation
Volume:5
Numéro:4
Pages:p. 63-78
Version évaluée par les pairs:Oui
Date:2016
Sujets: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:carbon anodes, coke, pitch, ANN, paste recipe
Déposé le:18 avr. 2019 21:11
Dernière modification:18 avr. 2019 21:11
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