4.3 Article

Multiple Performance Optimization in Wear Characteristics of Mg-SiC Nanocomposites Using Grey-Fuzzy Algorithm

期刊

SILICON
卷 12, 期 5, 页码 1177-1186

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SPRINGER
DOI: 10.1007/s12633-019-00196-4

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Magnesium; metal matrix composites; Wear; SiC nanoparticles; Scanning Electron microscopy; Grey-fuzzy algorithm

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The present investigation attempts to evaluate the effect of the SiC nano particles on the wear characteristics of Mg matrix nano composites. The wear tests on Mg matrix composites reinforced with SiC nanoparticles were carried out using the pin-on-disc tribometer under dry sliding conditions at various applied loads, sliding distance and speeds. The experiments were planned by adopting Taguchi L9 orthogonal array. The wear performances such as Specific wear rate and coefficient of friction were optimized by grey based fuzzy algorithm. The morphologies of the worn surfaces were observed by scanning electron microscopy (SEM) and important wear mechanisms were identified. The average compositions of the transfer layer formed at the worn surfaces were ascertained by EDX. Improved wear performances were exhibited by nano SiC reinforced composites at elevated conditions.

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