Use of a physical approach and artificial neural networks for the simulation of the relation between the yield strength of quenched Al-Si alloys and their structural characteristics

Models are developed to relate the yield strength of Al-Si alloys to their structural characteristics. The models are based on the physical theory of strength and artificial neural networks. The simulated and experimental yield strengths agree well. It is wise to use an artificial neural network to...

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Bibliographic Details
Published in:Russian metallurgy Metally 2007-12, Vol.2007 (6), p.524-528
Main Authors: Solonin, A. N., Churyumov, A. Yu, Malinin, R. Yu, Zolotorevskii, V. S.
Format: Article
Language:English
Subjects:
Alloys
Aluminum base alloys
Artificial neural networks
Computer simulation
Intermetallic compounds
Learning
Mathematical models
Neural networks
Quenching (cooling)
Studies
Yield strength
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Summary:Models are developed to relate the yield strength of Al-Si alloys to their structural characteristics. The models are based on the physical theory of strength and artificial neural networks. The simulated and experimental yield strengths agree well. It is wise to use an artificial neural network to predict the properties of alloys whose structural parameters fall in the range of the learning sample.[PUBLICATION ABSTRACT]
ISSN:0036-0295
1555-6255
1531-8648
DOI:10.1134/S0036029507060146