Evaluation of Viscosity of Mold Flux by Using Neural Network Computation

Hanao, Masahito; Kawamoto, Masayuki; Tanaka, Toshihiro; Nakamoto, Masashi

doi:https://doi.org/10.2355/isijinternational.46.346

このアイテムのアクセス数:125件（2022-10-06 16:25 集計）

このアイテムへのリンクには次のURLをご利用ください: https://hdl.handle.net/11094/26416

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論文情報

タイトル	Evaluation of Viscosity of Mold Flux by Using Neural Network Computation
著者	著者名 Hanao, Masahito
	著者名 Kawamoto, Masayuki
	NRID 1000010179773 1000010179773 著者名 Tanaka, Toshihiro
	NRID 1000080467539 1000080467539 著者名 Nakamoto, Masashi
キーワード等	viscosity
	solidification temperature
	slag
	mold flux
	neural network computation
	regression estimation
抄録	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 SiO_2–Al_2O_3–CaO–MgO–Na_2O–F–T.Fe–ZrO_2–TiO_2–BaO–MnO–B_2O_3–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 SiO_2 content.
出版者	日本鉄鋼協会
	The Iron and Steel Institute of Japan
	ニホン　テッコウ　キョウカイ
収録物名	ISIJ International
巻	46
号	3
開始ページ	346
終了ページ	351
刊行年月	2006
言語	英語
ハンドルURL	https://hdl.handle.net/11094/26416
ISSN	09151559
NCID	AA10680712
関連情報 (isIdenticalTo)	DOI (出版社版) https://doi.org/10.2355/isijinternational.46.346
アクセス権	open access
権利情報	© 2006 ISIJ
出版タイプ	Version of Record
カテゴリ	学術雑誌論文 Journal Article

資源タイプ	学術雑誌論文
ローカル資源タイプ	学術雑誌論文
DCMI資源タイプ	text
DCTERMS.bibliographicCitation	ISIJ International.46(3) p.346-p.351
DC.title	Evaluation of Viscosity of Mold Flux by Using Neural Network Computation
DC.creator	Hanao, Masahito
	Kawamoto, Masayuki
	Tanaka, Toshihiro
	Nakamoto, Masashi
DC.publisher	日本鉄鋼協会
	The Iron and Steel Institute of Japan
	ニホン　テッコウ　キョウカイ
DC.language' scheme='DCTERMS.RFC1766	英語
DC.type' scheme='DCTERMS.DCMIType	text
DCTERMS.issued' scheme='DCTERMS.W3CDTF	2006
DC.identifier	https://doi.org/10.2355/isijinternational.46.346
DC.subject	viscosity
	solidification temperature
	slag
	mold flux
	neural network computation
	regression estimation
DCTERMS.abstract	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 SiO_2–Al_2O_3–CaO–MgO–Na_2O–F–T.Fe–ZrO_2–TiO_2–BaO–MnO–B_2O_3–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 SiO_2 content.
DC.rights	© 2006 ISIJ
DC.format	application/pdf
citation_title	Evaluation of Viscosity of Mold Flux by Using Neural Network Computation
citation_author	Hanao, Masahito
	Kawamoto, Masayuki
	Tanaka, Toshihiro
	Nakamoto, Masashi
citation_publisher	日本鉄鋼協会
	The Iron and Steel Institute of Japan
	ニホン　テッコウ　キョウカイ
citation_language	英語
citation_date	2006
citation_journal_title	ISIJ International
citation_volume	46
citation_issue	3
citation_firstpage	346
citation_lastpage	351
citation_issn	09151559
citation_doi	https://doi.org/10.2355/isijinternational.46.346
citation_public_url	https://hdl.handle.net/11094/26416

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