NUMERICAL PREDICTIONS OF THE MECHANICAL PROPERTIES OF A356-SIC COMPOSITES FABRICATED BY POWDER METALLURGY

被引:4
|
作者
Nasser, Amal [1 ]
Nasser, Eman [1 ]
机构
[1] Higher Technol Inst, Dept Mech Engn, Tenth Of Ramadan City, Egypt
关键词
nano SiC; finite element method; artificial neural network; DRY SLIDING WEAR; BEHAVIOR;
D O I
10.21278/TOF.40407
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Pure aluminum nanocomposite reinforced with silicon carbide was produced by powder metallurgy process. The mechanical behavior of this composite was modelled and experimentally investigated. Measurements of density, tensile properties, and hardness showed that the tensile strength and the porosity of composites increased with an increase in the amount of nanoparticles; however, aluminum ductility decreased. On the other hand, the elongation percentage remains constant with an increase in the percentage of nanoparticles. Wear resistance of composite samples was higher than that of aluminium alloy. In the current research, a technique based on Artificial Neural Network (ANN) and Finite Element Method (FEM) was applied for the prediction of mechanical properties. It was observed that prediction results obtained in this study are consistent with the real measurements performed on composites.
引用
收藏
页码:83 / 94
页数:12
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