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

Evaluation of Viscosity of Mold Flux by Using Neural Network Computation

Hanao, Masahito; Kawamoto, Masayuki; Tanaka, Toshihiro et al.

ISIJ International, 2006, 46(3), 346-351

Number of Access:687（2025-08-14 03:09 Counts）

Identifier to cite or link to this item: https://hdl.handle.net/11094/26416

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Title	Evaluation of Viscosity of Mold Flux by Using Neural Network Computation
Creator	CreatorName Hanao, Masahito
	CreatorName Kawamoto, Masayuki
	NRID 1000010179773 1000010179773 researchmap permalink read0013978 read0013978 CreatorName Tanaka, Toshihiro
	NRID 1000080467539 1000080467539 ORCID 0000-0003-4684-0200 0000-0003-4684-0200 researchmap permalink read0090330 read0090330 Scopus Author ID 7102132238 7102132238 CreatorName Nakamoto, Masashi
Subject	viscosity
	solidification temperature
	slag
	mold flux
	neural network computation
	regression estimation
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.
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
Source Title	ISIJ International
Volume (Issue)	46(3)
Page	346-351
Date of Issued	2006
Language	English
Handle URL	https://hdl.handle.net/11094/26416
PISSN	09151559
NCID	AA10680712
Relation.isIdenticalTo	DOI (Publisher Version) https://doi.org/10.2355/isijinternational.46.346
Access Rights	open access
CopyRight	© 2006 ISIJ
oaire:version	Version of Record
Category	学術雑誌論文 Journal Article

Resource Type	journal article
Local Type	Journal Article
DCMI Type	Text
DCTERMS.bibliographicCitation	ISIJ International. 2006, 46(3), p. 346-351
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	English
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	26416
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
citation_language	English
citation_date	2006
citation_journal_title	ISIJ International
citation_volume	46
citation_issue	3
citation_firstpage	346
citation_lastpage	351
citation_doi	https://doi.org/10.2355/isijinternational.46.346
citation_public_url	https://hdl.handle.net/11094/26416

Evaluation of Viscosity of Mold Flux by Using Neural Network Computation

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