The Effect of Sn (0, 0.5, 1 and 3 wt.%) on the Mechanical Properties of Gravity Casting Mg-3Al Alloy and a Neural Network Application for Prediction

In this study, the influence of Sit (0, 0,5, 1 and 3 wt.%) addition on the yield and ultimate tensile strength (UTS) and elongation values of Mg-3Al alloy was investigated. The alloys were produced under a controlled atmosphere by a gravity-casting process. The results show that yield and ultimate tensile strength of based alloy increased by adding Sn up to 1 wt. %. These ultimate tensile tests and casting process are taking a lot time and cost. So, a neural network (NN) model was developed for prediction these mechanical effects using varied Sn additions. At the end of the testing whether the NN model is suitable for this case, it was seemed that results checked the system accuracy.