TY - GEN
T1 - Predicting dross formation in aluminium melt transfer operations
AU - Taylor, J. A.
AU - Prakash, M.
AU - Pereira, G. G.
AU - Rohan, P.
AU - Lee, M. J.
AU - Rinderer, B.
PY - 2010
Y1 - 2010
N2 - Aluminium melt transfer operations can lead to significant amounts of dross formation as a result of chemical oxidation and physical entrapment processes. It has been suggested that these activities may contribute up to 50% of the total metal loss of ∼1% in a typical primary aluminium smelter (i.e. 2,500 tonne/annum (tpa) in a smelter of 500,000tpa output). This is a large financial loss to any company, and also, in the new CO2-conscious era, it also represents a significant carbon footprint to ameliorate. A significant proportion of this metal loss may be prevented by adopting more efficient melt transfer strategies that reduce splashing and turbulence thereby resulting in reduced oxide and therefore dross formation. Optimisation of such systems is normally achieved by trial-and-error approaches, however a clear opportunity exists for rapid optimisation by employing computational modelling to explore the effects of changed equipment design and process conditions, such as tilt speed, spout height, spout geometry, etc. In the present paper, the Smoothed Particle Hydrodynamics (SPH) modeling method is used to predict the amount of oxide generated during molten metal transfers from a 500kg capacity tilting crucible furnace into a heated sow mould. Various conditions were tested. An oxidation model based on skimming trials performed in a laboratory-scale (8kg) oxidation rig is employed in the simulation. The predicted oxide from the simulations is compared against those of the experimental pours. It is anticipated that the validated model will be used for modifying the design and optimizing the operation of various melt transfer operations occurring in the aluminium industry.
AB - Aluminium melt transfer operations can lead to significant amounts of dross formation as a result of chemical oxidation and physical entrapment processes. It has been suggested that these activities may contribute up to 50% of the total metal loss of ∼1% in a typical primary aluminium smelter (i.e. 2,500 tonne/annum (tpa) in a smelter of 500,000tpa output). This is a large financial loss to any company, and also, in the new CO2-conscious era, it also represents a significant carbon footprint to ameliorate. A significant proportion of this metal loss may be prevented by adopting more efficient melt transfer strategies that reduce splashing and turbulence thereby resulting in reduced oxide and therefore dross formation. Optimisation of such systems is normally achieved by trial-and-error approaches, however a clear opportunity exists for rapid optimisation by employing computational modelling to explore the effects of changed equipment design and process conditions, such as tilt speed, spout height, spout geometry, etc. In the present paper, the Smoothed Particle Hydrodynamics (SPH) modeling method is used to predict the amount of oxide generated during molten metal transfers from a 500kg capacity tilting crucible furnace into a heated sow mould. Various conditions were tested. An oxidation model based on skimming trials performed in a laboratory-scale (8kg) oxidation rig is employed in the simulation. The predicted oxide from the simulations is compared against those of the experimental pours. It is anticipated that the validated model will be used for modifying the design and optimizing the operation of various melt transfer operations occurring in the aluminium industry.
KW - Aluminium
KW - Dross
KW - Modelling
KW - Oxidation
UR - http://www.scopus.com/inward/record.url?scp=73949090070&partnerID=8YFLogxK
U2 - 10.4028/www.scientific.net/MSF.630.37
DO - 10.4028/www.scientific.net/MSF.630.37
M3 - Conference contribution
SN - 0878493166
SN - 9780878493166
T3 - Materials Science Forum
SP - 37
EP - 44
BT - Aluminium Cast House Technology XI
PB - Trans Tech Publications Ltd.
T2 - Aluminium Cast House Technology, 11th Australasian Conference and Exhibition
Y2 - 13 September 2009 through 16 September 2009
ER -