Study of Characterization, Mechanical Properties, and Tribological Behavior of Magnesium-Silver Alloy

Badiger Pradeep V.,Vinyas M.,Prabhu T. Ram,Kumar N. V. Naveen, Nargund Nikhil B., Gouda P. K. Ramesh

Recent Advances in Mechanical Engineering(2022)

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摘要
Magnesium alloys are being rapidly used in automobile and aerospace industries due to their low density, high specific strength, high specific stiffness, good damping characteristics, and excellent machinability and castability. Despite their appealing range of mechanical qualities, Mg alloys’ low strength at ambient and elevated temperatures, as well as poor resistance to wear and corrosion, pose a substantial hurdle to their widespread use, which is keeping them from being as commonly employed as Al alloys. This study looks at the characterization, mechanical characteristics, and tribological behavior of a magnesium-silver alloy. Microstructural analysis and phase analysis are used to characterize the material. The material was subjected to tensile test and Vickers hardness test, and it was observed that the tensile strength and hardness of magnesium had been increased due to the addition of silver. Microstructure analysis showed a reduction in the grain size of alloy which in turn can be considered responsible for heightening the mechanical properties of the material. L9 Taguchi orthogonal array was used in designing experiments for the pin-on-disk wear test considering the input parameter sliding distance (500, 750, and 1000 m), normal load (50, 75, and 100 N), and speed (500, 1000, and 1500 rpm). The findings were analyzed using analysis of variance (ANOVA) to determine the impact of each parameter on volume wear, wear rate, and wear loss. The analysis portrayed that speed has the highest influence on the output characters. Finally, ANN and regression mathematical models were used to develop a predictive model to know the effectiveness of results and if the models showed any deviation before predicting an adequate model.
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关键词
Mg-Ag alloy, Tribology, ANN, ANOVA, Regression model
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