Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/11241
Title: Computational prediction of the refinement of oxide agglomerates in a physical conditioning process for molten aluminium alloy
Authors: Tong, M
Jagarlapudi, SC
Patel, JB
Stone, IC
Fan, Z
Browne, DJ
Keywords: Oxide clusters;High shear processing;Aggregation
Issue Date: 2015
Publisher: IOP Publishing
Citation: IOP Conference Series: Materials Science and Engineering, 84: 012092, (2015)
Abstract: Physically conditioning molten scrap aluminium alloys using high shear processing (HSP) was recently found to be a promising technology for purification of contaminated alloys. HSP refines the solid oxide agglomerates in molten alloys, so that they can act as sites for the nucleation of Fe-rich intermetallic phases which can subsequently be removed by the downstream de-drossing process. In this paper, a computational modelling for predicting the evolution of size of oxide clusters during HSP is presented. We used CFD to predict the macroscopic flow features of the melt, and the resultant field predictions of temperature and melt shear rate were transferred to a population balance model (PBM) as its key inputs. The PBM is a macroscopic model that formulates the microscopic agglomeration and breakage of a population of a dispersed phase. Although it has been widely used to study conventional deoxidation of liquid metal, this is the first time that PBM has been used to simulate the melt conditioning process within a rotor/stator HSP device. We employed a method which discretizes the continuous profile of size of the dispersed phase into a collection of discrete bins of size, to solve the governing population balance equation for the size of agglomerates. A finite volume method was used to solve the continuity equation, the energy equation and the momentum equation. The overall computation was implemented mainly using the FLUENT module of ANSYS. The simulations showed that there is a relatively high melt shear rate between the stator and sweeping tips of the rotor blades. This high shear rate leads directly to significant fragmentation of the initially large oxide aggregates. Because the process of agglomeration is significantly slower than the breakage processes at the beginning of HSP, the mean size of oxide clusters decreases very rapidly. As the process of agglomeration gradually balances the process of breakage, the mean size of oxide clusters converges to a steady value. The model enables formulation of the quantitative relationship between the macroscopic flow features of liquid metal and the change of size of dispersed oxide clusters, during HSP. It predicted the variation in size of the dispersed phased with operational parameters (including the geometry and, particularly, the speed of the rotor), which is of direct use to experimentalists optimising the design of the HSP device and its implementation.
URI: http://iopscience.iop.org/1757-899X/84/1/012092/
http://bura.brunel.ac.uk/handle/2438/11241
DOI: http://dx.doi.org/10.1088/1757-899X/84/1/012092
ISSN: 1757-8981
Appears in Collections:Brunel Centre for Advanced Solidification Technology (BCAST)

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