Artificial Neural Network Model: Prediction of Mechanical Properties in Beta-Titanium Biomaterial
Theoretical prediction of mechanical properties using Artificial Neural Network (ANN) of a new beta-titanium alloy was investigated and compared with the experimental results obtained as a function of heat treatment. The cold worked biomaterial was subjected to different thermal processing cycles. The experimental values of mechanical properties were determined using MTS Landmark-servo hydraulic UTS machine. The new beta-titanium alloy demonstrated an excellent combination of strength and ductility for β-annealing and solution treatment plus aging thermal processing treatments. This data was used to train an artificial neural network (ANN) model to predict hardness. The predicted hardness values were found to demonstrate very good agreement with the experimental values.