Estimation of the γ and γ' Lattice Parameters in Nickel-base Superalloys Using Neural Network Analysis
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概要
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The lattice constants of the γ and γ phases of nickel base superalloys have been modelled using a neural network within a Bayesian framework. The analysis is based on datasets compiled from new experiments and the published literature, the parameters being expressed as a non-linear function of some eighteen variables which include the chemical composition and temperature. The analysis permits the estimation of error bars whose magnitude depends on their position in the input space. Of the many models possible, a "committee of models" is found to give the most reliable estimate. The method is demonstrated to be consistent with known metallurgical trends and has been applied towards the study of some experimental alloys.
- 社団法人 日本鉄鋼協会の論文
- 1998-05-15
著者
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Mackay D.
Mathematical And Physical Sciences Group Darwin College
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Bhadeshia H
Univ. Cambridge
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HARADA H.
National Research Institute for Metals
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NARAYAN V.
Department of Materials Science and Metallurgy, University of Cambridge
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BHADESHIA H.
Mathematical and Physical Sciences Group, Darwin College
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YOSHITAKE S.
Department of Materials Science and Metallurgy, University of Cambridge
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Narayan V.
Department Of Materials Science And Metallurgy University Of Cambridge
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Harada H
Nippon Steel Corp. Chiba Jpn
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