Wear Prediction of Functionally Graded Composites Using Machine Learning
Reham Fathi,
Minghe Chen,
Mohammed Abdallah
et al.
Abstract:This study focuses on the production of functionally graded composites by utilizing magnesium matrix waste chips and cost-effective eggshell reinforcements through centrifugal casting. The wear behavior of the produced samples was thoroughly examined, considering a range of loads (5 N to 35 N), sliding speeds (0.5 m/s to 3.5 m/s), and sliding distances (500 m to 3500 m). The worn surfaces were carefully analyzed to gain insights into the underlying wear mechanisms. The results indicated successful eggshell par… Show more
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