An artificial neural network model of microstructural evolution, in particular grain size and volume fraction of α phase, has been established and trained with the help of experimental results obtained using Ti—6Al—4V alloy subjected to homogeneous deformation under high temperature. The measurement of microstructural variables was carried out using a Leica microscope. By comparison of the calculated results with the experimental data from training specimens and testing specimens, it has been verified that the proposed model can be applied to compute the microstructural evolution of formed Ti—6Al—4V alloy.
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