首页|New Machine Learning Research Has Been Reported by a Researcher at National Institute of Technology (Experimental Investigation of the Influence of Various Wear Parameters on the Tribological Characteristics of AZ91 Hybrid Composites and Their ...)
New Machine Learning Research Has Been Reported by a Researcher at National Institute of Technology (Experimental Investigation of the Influence of Various Wear Parameters on the Tribological Characteristics of AZ91 Hybrid Composites and Their ...)
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New study results on artificial intelligence have been published. According to news originating from Tamil Nadu, India, by NewsRx editors, the research stated, “In the current work, the AZ91 hybrid composites are fabricated through the utilization of the stir casting technique, incorporating aluminum oxide (Al2O3) and graphene (Gr) as reinforcing elements.” Our news journalists obtained a quote from the research from National Institute of Technology: “Wear behavior of the AZ91/Gr/Al2O3 composites was examined with the pin-on-disc setup under dry conditions. In this study, the factors such as reinforcement percentage ®, load (L), velocity (Ⅴ), and sliding distance (D) have been chosen to investigate their impact on the wear-rate (WR) and coefficient of friction (COF). This study utilizes a full factorial design to conduct experiments. The experimental data was critically analyzed to examine the impact of each wear parameter (i.e., R, L, V, and D) on the WR and COF of composites. The wear mechanisms at the extreme conditions of maximum and minimum wear rates are also investigated by utilizing the scanning electron microscope (SEM) images of specimen’s surface. The SEM study revealed the presence of delamination, abrasion, oxidation, and adhesion mechanisms on the surface experiencing wear.”
National Institute of TechnologyTamil NaduIndiaAsiaCyborgsEmerging TechnologiesMachine Learning
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NSTL
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