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Study of Mechanical and Sliding Wear Behavior of Al-25Zn alloy/SiC/Graphite Novel Hybrid Composites for Plain Bearing Application
by
Kharde, Y.R.
, Ritapure, P.P.
in
Abrasion
/ Abrasive cutting
/ Abrasive wear
/ Aluminum base alloys
/ Artificial neural networks
/ Cutting wear
/ Frictional wear
/ Graphite
/ Hybrid composites
/ Model accuracy
/ Parameters
/ Plain bearings
/ Regression models
/ Silicon carbide
/ Sliding friction
/ Tensile strength
/ Wear mechanisms
/ Wear resistance
/ Weight
2019
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Study of Mechanical and Sliding Wear Behavior of Al-25Zn alloy/SiC/Graphite Novel Hybrid Composites for Plain Bearing Application
by
Kharde, Y.R.
, Ritapure, P.P.
in
Abrasion
/ Abrasive cutting
/ Abrasive wear
/ Aluminum base alloys
/ Artificial neural networks
/ Cutting wear
/ Frictional wear
/ Graphite
/ Hybrid composites
/ Model accuracy
/ Parameters
/ Plain bearings
/ Regression models
/ Silicon carbide
/ Sliding friction
/ Tensile strength
/ Wear mechanisms
/ Wear resistance
/ Weight
2019
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Study of Mechanical and Sliding Wear Behavior of Al-25Zn alloy/SiC/Graphite Novel Hybrid Composites for Plain Bearing Application
by
Kharde, Y.R.
, Ritapure, P.P.
in
Abrasion
/ Abrasive cutting
/ Abrasive wear
/ Aluminum base alloys
/ Artificial neural networks
/ Cutting wear
/ Frictional wear
/ Graphite
/ Hybrid composites
/ Model accuracy
/ Parameters
/ Plain bearings
/ Regression models
/ Silicon carbide
/ Sliding friction
/ Tensile strength
/ Wear mechanisms
/ Wear resistance
/ Weight
2019
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Study of Mechanical and Sliding Wear Behavior of Al-25Zn alloy/SiC/Graphite Novel Hybrid Composites for Plain Bearing Application
Journal Article
Study of Mechanical and Sliding Wear Behavior of Al-25Zn alloy/SiC/Graphite Novel Hybrid Composites for Plain Bearing Application
2019
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Overview
In this investigations, sliding wear performance of Al-25Zn based novel hybrid composites added with fixed weight percentage of graphite (3 wt.%) and varying weight percentage of silicon carbide (10, 20 and 30 wt.%) was investigated for various process factors such as specimen temperature, applied load, sliding speed and sliding distance using a pin on disc with EN24 disc as per Taguchi L16 array. For similar test conditions, the composite with 10 wt.% of silicon carbide shows the highest wear resistance and tensile strength; whereas the composite with 20 wt.% of SiC shows highest hardness. The specimen temperature is recognized as the dominating parameter for the sliding wear performance of the materials. Artificial Neural network and Regression model developed was found competent for the forecasting of wear performance. Confirmation experiment conducted with the optimum parameter combination also confirmed the accuracy of developed model. The observed wear mechanism is abrasion and adhesion. The major mechanisms of abrasive wear are recognized as ploughing, micro cutting and delamination.
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