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Abstract

Modern metal forming processes of non-ferrous metals, particularly aluminum and its alloys, are increasingly based on integrated technologies combining numerous operations in one process line. The subject of this paper focuses on the possibility of using materials after mould casting (simulating a continuous casting process between cylindrical crystallizers – Twin Roll Casting method) for the direct cold rolling process. As a part of this research a pilotage study on metallurgical synthesis and mould casting process of Al-Mg alloys with the magnesium contents of 5%-10%, testing their mechanical, electrical and structural properties as well as susceptibility to cold plastic deformation. This process was carried out with the measurement of strength parameters and confirmed the possibility of cold rolling alloys with a casting structure without prior hot deformation.

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Authors and Affiliations

W. Ściężor
A. Mamala
R. Kowal
P. Kwaśniewski
ORCID: ORCID
K. Franczak
ORCID: ORCID
P. Strzępek
ORCID: ORCID
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Abstract

Production of near net shape thin strips using vertical twin roll casting method has been studied. In a typical VTRC process, the simultaneous action of solidification and rolling makes the process quite attractive as well as complicated. An industrially popular alloy A356 has been chosen for the VTRC processing. It is challenging to identify VTRC processing parameters for the alloy to produce thin strips because of its freezing range and complex composition. In the present work processing parameters of VTRC like roll speed, roll gap, melt superheat and the interface convective heat transfer coefficient have been investigated through modelling of the process. The mathematical model was developed which simultaneously solves the heat transfer, fluid flow and solidification, using commercial software COMSOL Multiphysics 5.4. VTRC sheets of alloy A356 were produced in an experimental set up and attempts were made to correlate the microstructures of VTRC A356 alloy to that predicted from the numerical studies to validate the model.

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Authors and Affiliations

B. Dhindaw
S. Singh
A. Mandal
A. Pandey

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