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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

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dc.contributor.authorReddy, N. S.-
dc.contributor.authorRao, A. K. Prasada-
dc.contributor.authorKrishnaiah, J.-
dc.contributor.authorChakraborty, M.-
dc.contributor.authorMurty, B. S.-
dc.date.accessioned2022-12-27T00:36:04Z-
dc.date.available2022-12-27T00:36:04Z-
dc.date.issued2013-03-
dc.identifier.issn1059-9495-
dc.identifier.issn1544-1024-
dc.identifier.urihttps://scholarworks.gnu.ac.kr/handle/sw.gnu/20761-
dc.description.abstractAn 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.-
dc.format.extent4-
dc.language영어-
dc.language.isoENG-
dc.publisherASM International-
dc.titleDesign of an Ideal Grain-Refiner Alloy for Al-7Si Alloy Using Artificial Neural Networks-
dc.typeArticle-
dc.publisher.location미국-
dc.identifier.doi10.1007/s11665-012-0334-9-
dc.identifier.scopusid2-s2.0-84878535911-
dc.identifier.wosid000314899800006-
dc.identifier.bibliographicCitationJournal of Materials Engineering and Performance, v.22, no.3, pp 696 - 699-
dc.citation.titleJournal of Materials Engineering and Performance-
dc.citation.volume22-
dc.citation.number3-
dc.citation.startPage696-
dc.citation.endPage699-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaMaterials Science-
dc.relation.journalWebOfScienceCategoryMaterials Science, Multidisciplinary-
dc.subject.keywordPlusALUMINUM-
dc.subject.keywordAuthorAl-7Si alloy-
dc.subject.keywordAuthorartificial neural networks-
dc.subject.keywordAuthorgrain refinement-
dc.subject.keywordAuthorgrain refiners-
dc.subject.keywordAuthorsensitivity analysis-
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공과대학 (나노신소재공학부금속재료공학전공)
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