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International Heat Transfer Conference 13
Graham de Vahl Davis (open in a new tab) School of Mechanical and Manufacturing Engineering, University of New South Wales, Kensington, NSW, Australia
Eddie Leonardi (open in a new tab) Computational Fluid Dynamics Research Laboratory, School of Mechanical and Manufacturing Engineering, The University of New South Wales, Sydney, Australia 2052

ISSN Online: 2377-424X

ISBN CD: 1-56700-226-9

ISBN Online: 1-56700-225-0

MODELLING AND NUMERICAL SIMULATION OF HEAT TRANSFER PHENOMENA IN THE SELF-INDUCED ION PLATING PROCESS (SIIP)

page 9
DOI: 10.1615/IHTC13.p13.60
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SINOPSIS

The present communication deals with the numerical simulation of heat transfer phenomena in a new physical vapour deposition process called self-induced ion plating (SIIP). SIIP has been developed in order to produce continuous coating of flat products in the steel industry. This coating process can be defined as the evaporation of a molten metallic target due to ions bombardment of a magnetron sputtering system. The thickness coating profile deposited on the flat substrate depends strongly on the target surface temperature field. So it seems essential to model heat transfer in the SIIP. The thermal phenomena taken into account in the SIIP heat transfer model are: the high energy argon ions bombardment of the target surface, the heat loss at the target surface due to the metal evaporation, the heat exchange by conduction, the radiative heat transfer and the convection heat exchange (free, Marangoni and electromagnetic convection) due to liquid target motion. Heat exchanges (conduction-convection-radiation) and velocity field are simultaneously computed using finite element software Comsol 3.2® . The Marangoni effect is of major importance in the SIIP. In fact it makes uniform the temperature field in the target. Thanks to the target surface temperature field and using the evaporation theory, we can compute the coating profile on the steel substrate. The computational results achieved are compared with measurements and show that our results are lower than measurements. We conclude that the SIIP model will have to be improved in the future.

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