Abstract
Microstructure characterization of the Al-4Cu-Mg alloys during the semi-solid compression has been investigated. A prediction model of microstructure evolution has been established based on the fuzzy-neural network. The present model uses deformation temperature, height reduction and strain rate as input parameters, and grain size or fractal dimension as output parameters. The results show that the prediction results are in excellent agreement with the experimental data. Therefore, the fuzzy-neural network model could be used to predict the microstructure evolution during the semi-solid forming of the Al-4Cu-Mg alloy and to optimize the deformation process parameters.
| Original language | English |
|---|---|
| Pages (from-to) | 7-11 |
| Number of pages | 5 |
| Journal | Cailiao Gongcheng/Journal of Materials Engineering |
| Issue number | 10 |
| State | Published - Oct 2004 |
Keywords
- Al-4Cu-Mg alloy
- Fractal dimension
- Fuzzy-neural network
- Grain size
- Semi-solid forming