PDF

Simulation of the Dynamic Response of Aluminum Reduction Cells

Imad Tabsh, Marc Dupuis

1994enaluminumsimulationdynamicreductioncells

Abstract

Language:

A comprehensive program known as ARC/DYNAMIC was developed to simulate the dynamic behavior of aluminum reduction cells during operation. The primary objective was to use this tool to determine the transient evolution of over 60 process variables through the application of mass and energy balance equations. This paper details the implementation of ARC/DYNAMIC, focusing particularly on its application to study the sensitivity of cell dynamic responses to back electro-motive force (BEMF). The methodology includes modeling of various operational and control policies and leveraging 13 differential equations that characterize mass and heat balance in the cells. Results demonstrated that the pseudo-resistance calculated using BEMF efficiently filters amperage fluctuations caused by anode effects. In conclusion, the findings suggest that PBF cell technology exhibits greater tolerance than side break cells when incorrect BEMF values are applied. The study also highlights the significance of accurately calculating BEMF values, particularly when utilizing experimental data.

Download

Cite This Work

@article{f73c0bbc-a02d-4a76-8221-fcc5177e325d,
  title={Simulation of the Dynamic Response of Aluminum Reduction Cells},
  author={Imad Tabsh and Marc Dupuis},
  year={1994},
  language={en}
}
TY  - JOUR
TI  - Simulation of the Dynamic Response of Aluminum Reduction Cells
AU  - Imad Tabsh
AU  - Marc Dupuis
PY  - 1994
LA  - en
ER  -

Similar Items

ETUDE DE DIMENSIONNEMENT ET SIMULATION D’UN BRAS A COMMANDE HYDRAULIQUE A FIXER SUR UN CAMION DE COLLECTE DES DECHETS

TSHIJIKA MUNENGE Olivier, MUSASA KABEYA

La ville de Kolwezi fait face à une croissance démographique et industrielle rapide, entraînant une augmentation considérable de la production des déc

2025frPDF

Metal Casting Processes

Unknown, Unknown

This chapter discusses metal casting processes, highlighting the diversity and common characteristics among them. The objective is to elucidate the fu

2023enPDF

Artificial intelligence-aided materials design: AI-algorithms and case studies on alloys and metallurgical processes

Rajesh Jha, Bimal Kumar Jha

This book describes the application of artificial intelligence (AI) and machine learning (ML) concepts to develop predictive models that can be used t

2022enPDF

Metallurgical Plant Design and Operating Strategies

The Australasian Institute of Mining and Metallurgy

This conference, held in Perth, Western Australia, focuses on the latest advancements in metallurgical processing plant design and operational strateg

2006enPDF

Metallurgical Plant Design and Operating Strategies

David Pollard, Geoff Dunlop

The MetPlant 2008 conference focused on advancements in metallurgical processing of ores, emphasizing plant design, operation strategies, and innovati

2008enPDF

Metallurgical Plant Design and Operating Strategies

P Card, J Canterford

This document presents a collection of papers from the METPLANT 2011 conference focusing on metallurgical plant design and operating strategies. The o

2011enPDF