Abstract
The present research focuses on the tribological behavior of the AA5083 alloy-based hybrid surface composite using aluminosilicate and multi-walled-carbon nanotube through friction stir processing for automotive applications. The friction stir processing parameters (tool rotation and traverse speed) are varied based on full factorial design to understand their influence on the tribological characteristics of the developed hybrid composite. The surface morphology and composition of the worn hybrid composite are examined using a field-emission scanning electron microscope and an energy-dispersive x-ray spectroscope. No synergistic interaction is observed between the wear rate and friction coefficient of the hybrid composite plate. Also, adhesive wear is the major wear mechanism in both base material and hybrid composite. The influence of friction stir process parameters on wear rate and the friction coefficient is analyzed using the hybrid polynomial and multi-quadratic radial basis function. The models are utilized to optimize the friction stir processing parameters for reducing the rate of wear and friction coefficient using multi-quadratic RBF algorithm optimization.
Original language | English |
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Pages (from-to) | 2363-2377 |
Number of pages | 15 |
Journal | Carbon Letters |
Volume | 33 |
Issue number | 7 |
DOIs | |
Publication status | Published - Dec 2023 |
Keywords
- AlSiO
- CNT
- FSP
- Optimization
- RBF algorithm
- Wear
ASJC Scopus subject areas
- Ceramics and Composites
- Renewable Energy, Sustainability and the Environment
- Energy Engineering and Power Technology
- Process Chemistry and Technology
- Organic Chemistry
- Inorganic Chemistry
- Materials Chemistry