Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1705689 | Applied Mathematical Modelling | 2011 | 7 Pages |
Artificial neural network (ANN) is a nonlinear dynamic computational system suitable for simulations which are hard to be described by physical models where, rather than relying on a number of predetermined assumptions, data is used to form the model. In order to predict the mechanical properties of A356 including yield stress, ultimate tensile strength and elongation percentage, a relatively new approach that uses artificial neural network and finite element technique is presented which combines mechanical properties data in the form of experimental and simulated solidification conditions. It was observed that predictions of this study are consistent with experimental measurements for A356 alloy. The results of this research were also used for solidification codes of SUT CAST software.