Influence of applied pressures and casting section thicknesses on interfacial heat transfer in squeeze casting of magnesium alloy AZ91

The estimation for interfacial heat transfer coefficient (IHTC) between casting and mold is paramount to predict solidification phenomena. In this study, three hydraulic pressures of 30, 60, and 90 MPa were applied to indirectly squeeze cast magnesium alloy AZ91 in a P20 steel mold with five casting...

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Veröffentlicht in:Heat and mass transfer 2021, Vol.57 (7), p.1107-1120
Hauptverfasser: Ren, Luyang, Hu, Anita, Fu, Yintian, Hu, Henry
Format: Artikel
Sprache:eng
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Zusammenfassung:The estimation for interfacial heat transfer coefficient (IHTC) between casting and mold is paramount to predict solidification phenomena. In this study, three hydraulic pressures of 30, 60, and 90 MPa were applied to indirectly squeeze cast magnesium alloy AZ91 in a P20 steel mold with five casting section thicknesses of 2, 4, 8, 12, and 20 mm, named steps 1, 2, 3, 4 and 5, by using a 75-ton hydraulic press machine. For comparison, the AZ91 alloy was also cast without the applied pressure (0 MPa). K-type thermocouples were utilized to measure temperatures simultaneously on the casting surface and at three different depths from the mold surface inward. Based on the temperature measurements, the IHTCs at the five steps were calculated by the inverse method. Despite of the differences in their peak values, the IHTC variation for the three applied pressures at the five steps during the squeeze casting process was similar to that of 0 MPa, in which the IHTC values abruptly rose to an apex first, and then declined slowly. The overall IHTC values of step 5 were higher than those of the other four steps, while the lowest peak IHTC value was present at step 1. When the applied pressure was increased, the IHTC peak value of each step became large accordingly. The empirical equations relating the IHTCs to the pressures, section thicknesses, and temperatures at the casting/mold interface were derived based on the multivariate linear and polynomial regression.
ISSN:0947-7411
1432-1181
DOI:10.1007/s00231-020-03012-7