Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/13013
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dc.rights.licenserestrictedAccess-
dc.contributor.authorMiloradović, Nenad-
dc.contributor.authorVujanac, Rodoljub-
dc.contributor.authorStojanovic, Blaza-
dc.contributor.authorPavlović A.-
dc.date.accessioned2021-04-20T22:20:43Z-
dc.date.available2021-04-20T22:20:43Z-
dc.date.issued2021-
dc.identifier.issn0263-8223-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/13013-
dc.description.abstract© 2021 Elsevier Ltd Dry sliding wear behaviour of ZA27 alloy based hybrid composites, reinforced with silicon-carbide (SiC) and graphite (Gr) particles is analyzed in the paper. The objective was to analyze the influence of tested parameters (graphite content, contact load and sliding speed) on specific wear rate and to show which factor is dominant. Two hybrid composites produced by compocasting procedure were tested: ZA27/10%SiC/3%Gr and ZA27/10%SiC/5%Gr. The wear tests were performed on a block-on-disc tribometer under dry sliding test conditions at three different loads (10 N, 20 N and 30 N) and three different sliding speeds (0.25 m/s, 0.5 m/s and 1.0 m/s). The scanning electronic microscope (SEM) and energy dispersive spectrometry (EDS) were used for examination of the hybrid composites wear surface. The influence of various parameters on wear behaviour was investigated using Taguchi method. Contact load exerts the greatest influence on specific wear rate, followed by the sliding speed and graphite content. A review of available scientific literature shows that there are not many papers and research related to hybrid composite materials based on the ZA27 alloy. This research provides new information for further development of composite materials with ZA27 alloy reinforced by the SiC and graphite particles and for improvement of their dry sliding wear resistance.-
dc.rightsinfo:eu-repo/semantics/restrictedAccess-
dc.sourceComposite Structures-
dc.titleDry sliding wear behaviour of ZA27/SiC/Gr hybrid composites with Taguchi optimization-
dc.typearticle-
dc.identifier.doi10.1016/j.compstruct.2021.113658-
dc.identifier.scopus2-s2.0-85101684091-
Appears in Collections:Faculty of Engineering, Kragujevac

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