Abstract
Engine bearings are important in many mechanical systems applications; they reduce friction and loads in diverse operating environments. Thus, the material characteristics of these components are most important in determining higher performance levels, longer life cycles, and more efficient energy use. First, this paper will highlight several factors of the engine's bearings by providing a detailed description of the basic parameters of the bearings and their effect on friction and wear. Fundamental concepts of technical analysis, such as finite element analysis and CFD, are also described, along with contemporary optimization, such as genetic algorithms, machine learning, and multi-active optimization. The role of experimental validation as part of the procedure for moving from theoretical predictions to practical implementation is stressed. Evaluations of real-life automotive, aerospace, renewable energy, and heavy machinery applications indicate the effectiveness of using Bearing solitary components. Lastly, issues like multiple interactions of physics, the existing material's limitations, and the technology's high cost are also discussed; further, how to go for smart bearings, advanced material, and the product's sustainability are also tackled. These suggest that today's engines' ever-increasing role and application necessitate more research and development, innovation, and cooperation towards improving bearing structures.
Keywords
Engine Bearings, Optimization Techniques, Friction and Wear, Computational Modeling, Experimental Validation, Advanced Materials, Machine Learning
Citations
IRE Journals:
Vikrant Rayate
"Optimization of Engine Bearing Geometry for Reduced Friction and Wear" Iconic Research And Engineering Journals Volume 1 Issue 5 2017 Page 72-86
IEEE:
Vikrant Rayate
"Optimization of Engine Bearing Geometry for Reduced Friction and Wear" Iconic Research And Engineering Journals, 1(5)
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