An adaptive prediction model of grain size for the forging of Ti–6Al–4V alloy based on fuzzy neural networks

In this paper, an adaptive model of grain size, has been established with the help of the fuzzy neural networks (FNNs), based on experimental results for Ti–6Al–4V titanium alloy with homogeneous deformation under various process technological parameters. The data of Teacher’s samples has been obtained from the experimental results. By the comparison of the calculated results with the experimental data of the Teacher’s samples and the testing samples, it has been verified that the model proposed in this paper can be applied to compute the grain size evolution during the deformation of Ti–6Al–4V titanium alloy.