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Cited 6 time in webofscience Cited 9 time in scopus
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Design of an Ideal Grain-Refiner Alloy for Al-7Si Alloy Using Artificial Neural Networks

Authors
Reddy, N. S.Rao, A. K. PrasadaKrishnaiah, J.Chakraborty, M.Murty, B. S.
Issue Date
Mar-2013
Publisher
ASM International
Keywords
Al-7Si alloy; artificial neural networks; grain refinement; grain refiners; sensitivity analysis
Citation
Journal of Materials Engineering and Performance, v.22, no.3, pp 696 - 699
Pages
4
Indexed
SCIE
SCOPUS
Journal Title
Journal of Materials Engineering and Performance
Volume
22
Number
3
Start Page
696
End Page
699
URI
https://scholarworks.gnu.ac.kr/handle/sw.gnu/20761
DOI
10.1007/s11665-012-0334-9
ISSN
1059-9495
1544-1024
Abstract
An ideal grain refiner has been designed for Al-7Si alloy by performing sensitivity analysis of trained artificial neural network (ANN) model. An ANNs model has been developed for solving these complex grain refinement phenomena in Al-7Si alloy. The model predictions and the analysis are well in agreement with the experimental results and existing metallurgical facts. Uncertainty in predictions helped in finding a new phenomenon at lower addition levels of grain refiner.
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공과대학 (나노신소재공학부금속재료공학전공)
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