Abstract
Under a NASA (National Aeronautics and Space Agency)-ESA (European Space Agency) collaborative research project, MICAST (Microstructure formation in casting of technical alloys under a diffusive and magnetically controlled convection conditions), three Al-7wt% Si samples (MICAST-6, MICAST-7 and MICAST2-12) were directionally solidified at growth speeds varying from 10 to 50 µm s-1 aboard the International Space Station to determine the effect of mitigating convection on the primary dendrite array. The observed primary dendrite trunk diameters during steady-state growth of MICAST samples show a good agreement with predictions from a coarsening based model developed by the authors. The trunk diameters in the terrestrial-grown equivalent samples were larger than those predicted from the model. This suggest that thermosolutal convection increases the trunk diameter of primary dendrites, perhaps by increasing their tip radius due to compositional changes.
Highlights
During directional solidification (DS) of alloys in a positive thermal gradient (GL) a mushy-zone consisting of array of primary dendrite arms and interdendritic liquids in between, develops between the melt above and the solid below
Trunk diameters of primary dendrites on several such cross-sections along the length of the three MICAST samples were measured in the manner describes in Ref. 44
Following additional observations were made during this study, details of which are not included in this paper because of the lack of space
Summary
During directional solidification (DS) of alloys in a positive thermal gradient (GL) a mushy-zone consisting of array of primary dendrite arms and interdendritic liquids in between, develops between the melt above and the solid below. Given that mechanical properties depend upon the dendrite spacing and distribution, numerous experiments have been carried out to measure primary spacing as a function of solute content (Co,), growth speed (R), thermal gradient (GL) and the physical properties of the alloy to compare with model predictions [9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27].
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