AN OPTIMIZATION AND PREDICTIVE MODELING TO ENHANCE THE WEAR AND MECHANICAL PERFORMANCE OF Al 5054 ALLOY FOR DEFENSE APPLICATIONS WITH TiO2 NANOPARTICLES
- Title
- AN OPTIMIZATION AND PREDICTIVE MODELING TO ENHANCE THE WEAR AND MECHANICAL PERFORMANCE OF Al 5054 ALLOY FOR DEFENSE APPLICATIONS WITH TiO2 NANOPARTICLES
- Creator
- Sahu S.K.; Bansod P.J.; Mohanasundaram S.; Vetrivel K.P.; Pandian P.P.; Rajendiran M.
- Description
- This study examines the effects of 2%, 4%, and 6% additions of TiO2 nanoparticles on the wear and mechanical characteristics of Al 5054 alloy reinforcement. The results demonstrate that the addition of TiO2 nanoparticles considerably increases the alloys tensile and impact strengths. Tensile strength reaches a peak of 221 MPa at 6% reinforcement and it rises gradually as the percentage of TiO2 reinforcement increases. Similarly, impact strength rises with time and, with TiO2 reinforcement, it reaches a maximum of 63 Joules at 6%. Wear analysis using Taguchi-based design determines the optimal combination of composition, disc rotation speed, load, and sliding distance to minimize a given wear rate and friction force. The SEM analysis validates that the composites exhibit enhanced wear resistance due to the uniform distribution of TiO2 nanoparticles. An Artificial Neural Network (ANN) model is also developed to predict the responses, and it achieves an overall accuracy of 83.549%. The mechanical properties and wear resistance of TiO2-reinforced Al 5054 composites can be enhanced, as it is demonstrated by these results. This information is crucial for material design and optimization across a range of engineering applications. 2024, Scibulcom Ltd.. All rights reserved.
- Source
- Journal of the Balkan Tribological Association, Vol-30, No. 1, pp. 67-80.
- Date
- 2024-01-01
- Publisher
- Scibulcom Ltd.
- Subject
- Artificial Neural Network; impact; Taguchi design of experiments; tensile; wear test
- Coverage
- Sahu S.K., Department of Mechanical Engineering, Veer Surendra Sai University of Technology, Odisha, Burla, India; Bansod P.J., Department of Mechanical Engineering, G H Raisoni College of Engineering & Management Wagholi, Maharashtra, Pune, India; Mohanasundaram S., Department of Mechanical Engineering, Karunya Institute of Technology and Sciences, Tamil Nadu, Coimbatore, India; Vetrivel K.P., Department of Mechanical Engineering, M. P. Nachimuthu M. Jaganathan Engineering College, Tamil Nadu, Erode, India; Pandian P.P., Department of Mechanical Engineering, School of Engineering and Technology, Christ University (Deemed to be University), Karnataka, Bangalore, India; Rajendiran M., Department of Computer Science and Engineering, Panimalar Engineering College, Poonamallee, Tamil Nadu, Chennai, India
- Rights
- Restricted Access
- Relation
- ISSN: 13104772
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Sahu S.K.; Bansod P.J.; Mohanasundaram S.; Vetrivel K.P.; Pandian P.P.; Rajendiran M., “AN OPTIMIZATION AND PREDICTIVE MODELING TO ENHANCE THE WEAR AND MECHANICAL PERFORMANCE OF Al 5054 ALLOY FOR DEFENSE APPLICATIONS WITH TiO2 NANOPARTICLES,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/13679.