| Summary: | During the production of titanium products, the presence of aluminum-rich regions can cause Type II alpha stabilized defects which are deleterious to down-stream performance. Al-rich material can enter the melt via ballistic transfer from the melting hearth at various stages during electron beam cold hearth re-melting (EBCHR) of Ti-6Al-4V (Ti-6wt%Al-4wt%V) alloy. If this material is not fully dissolved and homogenized when solidification occurs, the ingot will contain Al-rich regions. Thus, in order to produce high-performance components for aerospace applications, titanium producers must understand the dissolution process for alloying elements entering the melt.
To study and characterize the phenomena associated with the dissolution and homogenization of alloying elements during EBCHR processing of Ti-6Al-4V, a water-ethanol physical analogue model has been developed to simulate the thermal, compositional and fluid flow behavior that are active in the dissolution process. The physical model consists of a hot water solvent contained in a transparent cell (beaker) in which solidified ethanol or ice solute is dipped. The data generated from the physical model was used to validate a coupled thermal- fluid flow-composition model (developed in the commercial CFD code ANSYS CFX).
The analogue model focuses on characterizing the effects of thermal and compositional variations on surface tension driven fluid flow (Marangoni flow) and buoyancy driven flow during the dissolution of a low density, low surface tension and low melting point solid material (frozen ethanol) in a high density, high surface tension and high melting point liquid (water), which was found to be analogous to the dissolution of solid Al in liquid Ti. In addition, the analogue model was also capable to predict the dissolution behavior when there was no compositional difference between the solute and the solvent. Based on a comparison of fluid flow pattern and interface shape, and temperature data obtained at discrete locations in the experimental and computational results, the numerical model has been shown to quantitatively and qualitatively predict the dissolution behavior observed in the physical process.
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