Published October 2018 | Version v1
Journal article

A Multi-scale Mathematical Model of Growth and Coalescence of Bubbles Beneath the Anode in an Aluminum Reduction Cell

  • 1. Northeastern University, School of Metallurgy (China)
  • 2. Hohai University, College of Energy and Electricity (China)

Description

Modeling of bubble shapes is challenging because of the wide range of length scales in aluminum reduction cells. A 3D multi-scale mathematical model was developed to understand the nucleation, growth and coalescence of bubbles beneath the anode and to investigate the transition of bubbles from the micro- to macro level. The motion of micro-bubbles is examined using the discrete bubble model (DBM) within a Lagrangian reference. An algorithm for the transition from discrete micro-bubbles to large bubbles, which are fully resolved by the volume of fluid (VOF) approach, is achieved using a user-defined function. The two-way coupling between discrete bubbles and continuous fluids is achieved by inter-phase momentum exchange. The model involves three kinds of bubble coalescence: micro-bubble coalescence is taken into account by the DBM; large bubbles swallowing up micro-bubbles are solved by the discrete-continuum transition model; the coalescence between large bubbles is handled by the VOF method. Numerical results show that the coverage and thickness of bubbles agree well with the experimental data in the literature. Bubble thickness stops increasing when the bubble elongates with the anode bottom, which is 4.0 to 4.5 mm. Meanwhile, two asymmetrical thick heads can be observed under the anode. Bubble release frequency increases with increasing current density.

Additional details

Identifiers

Publishing Information

Journal Title
Metallurgical and Materials Transactions B, Process Metallurgy and Materials Processing Science
Journal Volume
49
Journal Issue
5
Journal Page Range
p. 2821-2834
ISSN
1073-5615
CODEN
MTBSEO

INIS

Country of Publication
United States
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
51019570
Subject category
S36: MATERIALS SCIENCE; S37: INORGANIC, ORGANIC, PHYSICAL AND ANALYTICAL CHEMISTRY;
Resource subtype / Literary indicator
Numerical Data
Descriptors DEI
ALGORITHMS; ALUMINIUM; ANODES; BUBBLES; COALESCENCE; CURRENT DENSITY; EXPERIMENTAL DATA; LAGRANGIAN FUNCTION; MATHEMATICAL MODELS; NUCLEATION; REDUCTION; SIMULATION; THICKNESS
Descriptors DEC
CHEMICAL REACTIONS; DATA; DIMENSIONS; ELECTRODES; ELEMENTS; FUNCTIONS; INFORMATION; MATHEMATICAL LOGIC; METALS; NUMERICAL DATA

Optional Information

Copyright
Copyright (c) 2018 The Minerals, Metals & Materials Society and ASM International
Notes
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