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Measurements and modelling of dendritic growth velocities of pure Fe with thermoelectric magnetohydrodynamics convection

Measurements and modelling of dendritic growth velocities of pure Fe with thermoelectric magnetohydrodynamics convection

Zhao, Rijie, Gao, Jianrong, Kao, Andrew ORCID: 0000-0002-6430-2134 and Pericleous, Koulis ORCID: 0000-0002-7426-9999 (2017) Measurements and modelling of dendritic growth velocities of pure Fe with thermoelectric magnetohydrodynamics convection. Journal of Crystal Growth, 475. pp. 354-361. ISSN 0022-0248 (doi:https://doi.org/10.1016/j.jcrysgro.2017.07.020)

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Abstract

Dendritic growth velocities of pure Fe under static magnetic fields of intensity ranging from B = 0 T to B = 6 T were measured using a high speed camera. The data measured at undercoolings up to T = 190 K show a depression followed by a recovery of the growth velocities as the magnetic field intensity increased from a low range, B = 1 ~ 3 T to a high range, B = 4 ~ 6 T. These magnetic field effects are similar to those previously observed for pure Ni and can be attributed to competing thermoelectric magnetohydrodynamic (TEMHD) convection patterns in the local liquid. The experimental measurements for the two metals were modelled using a three-dimensional dendritic growth theory taking into account convection to estimate the effective flow velocities in the tip growth direction. The calculated effective flow velocities identify two undercooling dependences and a distinct type of magnetic field intensity dependence in common for the two metals. In comparison, the calculated effective flow velocities for pure Fe are generally smaller in magnitude. This difference between the two metals can be related to their differences in material-dependent properties as is revealed by a simple model proposed for a transverse TEMHD flow.

Item Type: Article
Uncontrolled Keywords: Dendrites, Solidification, Magnetic fields, Convection
Subjects: Q Science > QA Mathematics
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Centre for Numerical Modelling & Process Analysis (CNMPA) > Computational Science & Engineering Group (CSEG)
Faculty of Architecture, Computing & Humanities > Department of Mathematical Sciences
Last Modified: 02 Mar 2019 15:53
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/17520

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