Evaluation of Viscosity of Mold Flux by Using Neural Network Computation
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概要
- 論文の詳細を見る
A new estimation method of viscosity or solidification temperature of mold fluxes was proposed by applying the neural network computation. In this evaluation system, the viscosity and the solidification temperature of mold fluxes can be evaluated from the analytical compositions in multi-component systems of SiO2–Al2O3–CaO–MgO–Na2O–F–T.Fe–ZrO2–TiO2–BaO–MnO–B2O3–S–C without any conversion of S or F to sulphide or fluoride. It was found that the calculated results of the dependence of viscosity on temperature and composition agree with the experimental results more precisely than some conventional physical models for viscosity. Furthermore, viscosity of mold fluxes can be estimated precisely in the wide range of SiO2 content.
- 2006-03-15
著者
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Kawamoto Masayuki
Corporate R&d Labs. Sumitomo Metal Industries Ltd.
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NAKAMOTO Masashi
Graduate School of Engineering, Osaka University
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Kawamoto Masayuki
Res. And Dev. Laboratories Sumitomo Metal Industries Ltd.
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HANAO Masahito
Research and Development Laboratories, Sumitomo Metal Industries, Ltd.
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Hanao Masahito
Res. And Dev. Laboratories Sumitomo Metal Industries Ltd.
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Hanao Masahito
Corporate Research And Development Laboratories Sumitomo Metal Industries Ltd.
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Tanaka Toshihiro
Graduate School Of Engineering Osaka University
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Tanaka Toshihiro
Division Of Materials And Manufacturing Science Osaka University
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Nakamoto Masashi
Graduate School Of Engineering Osaka University
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Nakamoto Masashi
Division Of Materials And Manufacturing Science Osaka University
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Tanaka Toshihiro
Division Of Materials And Manufacturing Science Graduate School Of Engineering Osaka University
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Tanaka Toshihiro
Graduate School Of Eng. Osaka Univ.
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TANAKA Toshihiro
Division of Materials and Manufacturing Science, Osaka University
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