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Optimization of an electron beam ingot casting process
The final stage of a Cold Hearth Electron Beam Refining process is solidification of the molten material in a water-cooled mold to
produce ingots used for making high-performance parts of aeroengines and land-based power turbines. The refined metal pours into a cylindrical mold. The top surface of the metal pool is heated using an
electron beam gun. The molten metal cools due to radiative losses from the exposed surface and by transferring heat to the mold. The progressive solidification of the metal gives rise to a pool and a
mushy region at the top of the solidified and growing ingot. The flow induced in the pool due to buoyancy forces strongly influences the heat transfer to the mold and hence the shape and the size of the
pool. The resulting solidification rates determine the microstructure of the ingot produced.
At Innovative Research, we have developed a model for the ingot casting process during remelting and
refining of superalloys and Titanium alloys. It analyzes the underlying physical phenomena – namely fluid flow, energy transport, and phase change, for predicting the resulting pool shape and
solidification rates. It uses an accurate model for calculating the heat transfer to the mold in presence of shrinkage and for treatment of turbulence decay in the mushy region. The size of the pool and
the pool profile is strongly affected by the magnitude and distribution of the heat flux on the top surface of the pool. In the present study, the model for the ingot solidification process was first
validated against data from actual production runs of the EB process. The model was then used to perform a parametric study of the effect of casting rates and heat flux distribution on the resulting pool
shape and the solidification rates. The insights gained and quantitative predictions obtained from the analysis were used to determine the optimum processing conditions. Final processing conditions were
determined by refining the optimum range of conditions determined in the analysis. A trial-and-error based design for such processes is very expensive because of the hostile environment involved, and the
material and operational costs. Use of model allowed design of the process in a scientific and a cost-effective manner.
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