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- Title
PREDICTION OF MECHANICAL PROPERTIES OF β-SiAlON CERAMICS BASED ON BP NEURAL NETWORK.
- Authors
LI, J.; ZHANG, C. F.; YIN, R. M.; ZHANG, W. H.
- Abstract
β-Si6-ZAlZOZN8-Z (0<Z≤2) ceramics with rod-like grain morphology were prepared by gas pressure sintering, and their mechanical properties (i.e., bulk density, hardness, fracture toughness, and flexural strength) were evaluated. A model to predict the mechanical properties of β-SiAlON ceramics was established by back propagation (BP) neural network, and the relationships between process parameters (i.e., Z-value and temperature) and mechanical properties were investigated. Results show that the model had good prediction accuracy and maximum relative error lower than 8 %. The model could reflect the complex nonlinear relationship between the process parameters and the mechanical properties of β-SiAlON ceramics. The model can provide an effective reference for optimizing the design of β-SiAlON ceramics.
- Subjects
CERAMIC materials; MECHANICAL behavior of materials; SILICON compounds; SINTERING; FRACTURE toughness; ARTIFICIAL neural networks
- Publication
Metalurgija, 2018, Vol 57, Issue 4, p265
- ISSN
0543-5846
- Publication type
Article