Study of Friction and Wear Behavior of Graphene-Reinforced AA7075 Nanocomposites by Machine Learning

被引:11
|
作者
Prasanth I.S.N.V.R. [1 ]
Jeevanandam P. [2 ]
Selvaraju P. [3 ]
Sathish K. [4 ]
Hasane Ahammad S.K. [5 ]
Sujatha P. [6 ]
Kaarthik M. [7 ]
Mayakannan S. [8 ]
Sasikumar B. [9 ]
机构
[1] Department of Mechanical Engineering Malla Reddy Engineering College, Hyderabad
[2] Department of Mechanical Engineering JCT College of Engineering and Technology, Pichanur Tamil Nadu, Coimbatore
[3] Department of Mathematics Rajalakshmi Institute of Technology, Tamil Nadu, Chennai
[4] Department of Mechanical Engineering Sri Eshwar College of Engineering, Tamil Nadu, Coimbatore
[5] Department of Electronics and Communication Engineering Koneru Lakshmaiah Education Foundation, Guntur
[6] Department of Information Technology Vels Institute of Science Technology and Advanced Studies Pallavaram, Tamil Nadu, Chennai
[7] Department of Civil Engineering Coimbatore Institute of Technology, Tamil Nadu, Coimbatore
[8] Department of Mechanical Engineering Vidyaa Vikas College of Engineering and Technology, Namakkal Tamil Nadu, Tiruchengode
[9] Faculty of Mechanical and Production Engineering Arba Minch University, Arba Minch
关键词
Compendex;
D O I
10.1155/2023/5723730
中图分类号
学科分类号
摘要
In this research, the friction and wear of AA7075 nanocomposites reinforced with graphene and graphite were studied. Graphene’s inclusion dramatically enhanced the material’s mechanical characteristics, friction, and wear resistance. AA7075 is strengthened with less graphene, and AA7075, reinforced with more graphite, exhibits similar wear and friction behavior. Wear rate and coefficient of friction predictions for AA7075-graphene nanocomposites were made using five machine learning (ML) regression models. ML simulations reveal that the wear and friction of AA7075-graphene composites are most sensitive to the proportion of graphene presence, the loadings, and the hardness. Copyright © 2023 I. S. N. V. R. Prasanth et al.
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