Physical and Mechanical Properties Estimation of Ti/HAP Functionally Graded Material Using Artificial Neural Network
This study presents the effort in applying neural network-based system identification techniques by using Back- propagation algorithm to predict somephysical mechanical properties of functionally graded and compositesamples from Ti/HAP, these samples were fabricated by powder metallurgy method at va...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Unviversity of Technology- Iraq
2016-12-01
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| Series: | Engineering and Technology Journal |
| Subjects: | |
| Online Access: | https://etj.uotechnology.edu.iq/article_120066_a87727dbc7d9df42ad007739857663e9.pdf |
| Summary: | This study presents the effort in applying neural network-based system identification techniques by using Back- propagation algorithm to predict somephysical mechanical properties of functionally graded and compositesamples from Ti/HAP, these samples were fabricated by powder metallurgy method at various volume fraction of hydroxyapatite and at n equal (0.8, 1, and 1.2). Because of important of advanced materials such as FGMs as alternative industrial material, it is necessary to measure the physical properties of these materials such as porosity, density, hardness, compression …etc. Therefore the ANN will be used to estimate these properties and give a good performance to the network. |
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| ISSN: | 1681-6900 2412-0758 |