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A method to predict effective case depth in ion nitrided steels

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dc.contributor.authors Genel, K; Demirkol, M;
dc.date.accessioned 2020-02-26T08:47:40Z
dc.date.available 2020-02-26T08:47:40Z
dc.date.issued 2005
dc.identifier.citation Genel, K; Demirkol, M; (2005). A method to predict effective case depth in ion nitrided steels. SURFACE & COATINGS TECHNOLOGY, 195, 120-116
dc.identifier.issn 0257-8972
dc.identifier.uri https://doi.org/10.1016/j.surfcoat.2004.07.051
dc.identifier.uri https://hdl.handle.net/20.500.12619/50061
dc.description.abstract Ion nitriding is one of the most promising thermochemical surface treatments to improve surface properties such as wear and corrosion resistance and fatigue strength. The prediction of effective case depth before nitriding treatment is very important and useful particularly from the perspective of the manufacturers in practice. In this study, ion nitriding parameter (INP), which is only a function of effective case depth and activation energy, has been suggested for the prediction of effective case depth in ion nitriding and the applicability of this approach has been verified. There is a good correlation between the progress of effective case depth and a proposed time-temperature compensated parameter. The results of proof tests have indicated that a reasonable agreement with 10% deviation was found between the experimental data and effective case depth values, which were predicted by using the parametric approach of INP for the steels AISI 4140, H13 and D3. (c) 2004 Elsevier B.V. All rights reserved.
dc.language English
dc.publisher ELSEVIER SCIENCE SA
dc.subject Physics
dc.title A method to predict effective case depth in ion nitrided steels
dc.type Article
dc.identifier.volume 195
dc.identifier.startpage 116
dc.identifier.endpage 120
dc.contributor.department Sakarya Üniversitesi/Mühendislik Fakültesi/Makine Mühendisliği Bölümü
dc.contributor.saüauthor Genel, Kenan
dc.relation.journal SURFACE & COATINGS TECHNOLOGY
dc.identifier.wos WOS:000228435100013
dc.identifier.doi 10.1016/j.surfcoat.2004.07.051
dc.contributor.author Genel, Kenan


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