Modeling the Density and Hardness of AA2024-SiC NanocompositesModeling the Density and Hardness of AA2024-SiC Nanocomposites
- Other Titles
- Modeling the Density and Hardness of AA2024-SiC Nanocomposites
- 전아현; 김홍인; 성효경; 수바레디
- Issue Date
- AA2024-SiC nanocomposite; Prediction; Sensitvity analysis; Density; Hardness
- 한국분말재료학회지, v.26, no.4, pp.275 - 281
- Journal Title
- Start Page
- End Page
- An artificial neural network (ANN) model is developed for the analysis and simulation of correlation between flake powder metallurgy parameters and properties of AA2024-SiC nanocomposites. The input parameters of the model are AA 2024 matrix size, ball milling time, and weight percentage of SiC nanoparticles and the output parameters are density and hardness. The model can predict the density and hardness of the unseen test data with a correlation of 0.986 beyond the experimental data. A user interface is designed to predict properties at new instances.
We have used the model to simulate the individual as well as the combined influence of parameters on the properties.
Moreover, we have analyzed the calculated results from the powder metallurgical point of view. The developed model can be used as a guide for further composite development.
- Files in This Item
- There are no files associated with this item.
- Appears in
- 공과대학 > 나노신소재공학부금속재료공학전공 > Journal Articles
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.