Abstract
Titanium alloy exhibits an excellent combination of bio-compatibility, corrosion resistance, strength and toughness. The microstructure of an alloy influences the properties. The microstructures depend mainly on alloying elements, method of production, mechanical, and thermal treatments. The relationships between these variables and final properties of the alloy are complex, non-linear in nature, which is the biggest hurdle in developing proper correlations between them by conventional methods. So, we developed artificial neural networks (ANN) models for solving these complex phenomena in titanium alloys.
In the present work, ANN models were used for the analysis and prediction of the correlation between the process parameters, the alloying elements, microstructural features, beta transus temperature and mechanical properties in titanium alloys. Sensitivity analysis of trained neural network models were studied which resulted a better understanding of relationships between inputs and outputs. The model predictions and the analysis are well in agreement with the experimental results. The simulation results show that the average output-prediction error by models are less than 5% of the prediction range in more than 95% of the cases, which is quite acceptable for all metallurgical purposes.
In the present work, ANN models were used for the analysis and prediction of the correlation between the process parameters, the alloying elements, microstructural features, beta transus temperature and mechanical properties in titanium alloys. Sensitivity analysis of trained neural network models were studied which resulted a better understanding of relationships between inputs and outputs. The model predictions and the analysis are well in agreement with the experimental results. The simulation results show that the average output-prediction error by models are less than 5% of the prediction range in more than 95% of the cases, which is quite acceptable for all metallurgical purposes.
Original language | English |
---|---|
Title of host publication | 2010 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC 2010) |
Subtitle of host publication | Proceedings of a meeting held 28-29 December 2010, Coimbatore, India |
Editors | N. Krishnan |
Place of Publication | Piscataway, NJ |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 645-648 |
Number of pages | 4 |
Publication status | Published - Dec 2010 |
Event | 2010 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC 2010) - Coimbatore, India Duration: 01 Dec 2010 → 01 Dec 2010 |
Conference
Conference | 2010 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC 2010) |
---|---|
Country/Territory | India |
City | Coimbatore |
Period | 01/12/2010 → 01/12/2010 |
Keywords
- Neural Networks
- Titanium alloys
- Beta transus temperature
- Prediction