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<p>Aluminium 7075 alloy-based composites have higher strength, which enhances the tribological properties which making them highly desirable for advanced technological applications. In this study, the combination of SiC, Fly ash and glass powder into the Al 7075 alloy to investigate the wear performance. The wear test on samples was examined using a POD machine under various sliding distances, load, and %wt of reinforcement. Best wear performance was achieved at a distance of sliding of 1000&#xa0;m under load 60&#xa0;N by using the reinforcement with 9 wt%, which exhibits the lowest wear rate and the coefficient of friction (COF). SEM analysis of this optimum sample indicated that the worn surface was smooth with low wear debris and that strong mechanical interlocking, uniform particle distribution, and small voids were formed, which verified the enhanced structural stability caused by hybrid reinforcement. An ANN model using the Levenberg-Marquardt algorithm was used for the prediction of wear rate and COF with good accuracy 0.99726 for training, 0.99258 for validation and 0.99395 for testing and an overall correlation of 0.99544 was achieved. The best validation performance was obtained at epoch 2 with a Mean Squared Error of 0.0010773. This novel hybrid reinforcement approach is a significant refinement through the addition of ceramic-glass particulates for enhanced wear performance, and its applicability to high-strength next-generation automotive, aerospace, and marine components of the future, which require longer life and reduction of material wastage.</p>

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Mechanistic wear performance and high-accuracy Levenberg–Marquardt algorithm prediction in Al 7075 reinforced with Sic/Fly ash/glass powder particles

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月20日

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  • Vijayakumar Sivasundar,
  • Anusha Peyyala,
  • Bandi Maheswara Rao,
  • Ramya Maranan,
  • Anand Rajendran,
  • Akanksha Mishra,
  • Hari Prasadarao Pydi,
  • N. Dhasarathan

摘要

Aluminium 7075 alloy-based composites have higher strength, which enhances the tribological properties which making them highly desirable for advanced technological applications. In this study, the combination of SiC, Fly ash and glass powder into the Al 7075 alloy to investigate the wear performance. The wear test on samples was examined using a POD machine under various sliding distances, load, and %wt of reinforcement. Best wear performance was achieved at a distance of sliding of 1000 m under load 60 N by using the reinforcement with 9 wt%, which exhibits the lowest wear rate and the coefficient of friction (COF). SEM analysis of this optimum sample indicated that the worn surface was smooth with low wear debris and that strong mechanical interlocking, uniform particle distribution, and small voids were formed, which verified the enhanced structural stability caused by hybrid reinforcement. An ANN model using the Levenberg-Marquardt algorithm was used for the prediction of wear rate and COF with good accuracy 0.99726 for training, 0.99258 for validation and 0.99395 for testing and an overall correlation of 0.99544 was achieved. The best validation performance was obtained at epoch 2 with a Mean Squared Error of 0.0010773. This novel hybrid reinforcement approach is a significant refinement through the addition of ceramic-glass particulates for enhanced wear performance, and its applicability to high-strength next-generation automotive, aerospace, and marine components of the future, which require longer life and reduction of material wastage.