Applications of the artificial intelligence methods for modeling of the ACAlSi7Cu alloy crystallization process

In this work the derivation analysis techniques is applied for the preparation of ACAlSi7Cu alloy thermal characteristic, and assessed influence of cooling rate for characteristic transformations during the crystallizations. Alloys were cooled with three cooling rate: 0.2, 0.5 and 1 °C/s. Rise of the cooling rate is influenced on a dendrite phase nucleation point which has an effect on a solid fraction. In this case alloys are much more uniform. The changes of crystallization temperature at the end of the process are not observed during the rise of the cooling rate. The neural networks were used for modeling of the ACAlSi7Cu alloy crystallization process cooled with different cooling rate.