Sharath Ballupete Nagaraju, Venkatesh Channarayapattana Venkataramaiah, Afzal Asif, Aslfattahi Navid, Aabid Abdul, Baig Muneer, Saleh Bahaa
Department of Mechanical Engineering, Malnad College of Engineering, Hassan, Affiliated to Visvesvaraya Technological University, Belagavi 573201, India.
Department of Mechanical Engineering, P. A. College of Engineering, Affiliated to Visvesvaraya Technological University, Belagavi, Mangaluru 574153, India.
Materials (Basel). 2021 May 28;14(11):2895. doi: 10.3390/ma14112895.
Lightweight composite materials have recently been recognized as appropriate materials have been adopted in many industrial applications because of their versatility. The present research recognizes the inclusion of ceramics such as Gr and BC in manufacturing AMMCs through stir casting. Prepared composites were tested for hardness and wear behaviour. The tests' findings revealed that the reinforced matrix was harder (60%) than the un-reinforced alloy because of the increased ceramic phase. The rising content of BC and Gr particles led to continuous improvements in wear resistance. The microstructure and worn surface were observed through SEM (Scanning electron microscope) and revealed the formation of mechanically mixed layers of both BC and Gr, which served as the effective insulation surface and protected the test sample surface from the steel disc. With the rise in the content of BC and Gr, the weight loss declined, and significant wear resistance was achieved at 15 wt.% BC and 10 wt.% Gr. A response surface analysis for the weight loss was carried out to obtain the optimal objective function. Artificial neural network methodology was adopted to identify the significance of the experimental results and the importance of the wear parameters. The error between the experimental and ANN results was found to be within 1%.
轻质复合材料近年来因其多功能性而被公认为适用于许多工业应用的材料。目前的研究认可通过搅拌铸造将诸如Gr和BC等陶瓷纳入制造先进金属基复合材料（AMMCs）的过程。对制备的复合材料进行了硬度和磨损行为测试。测试结果表明，由于陶瓷相增加，增强基体比未增强合金更硬（硬60%）。BC和Gr颗粒含量的增加导致耐磨性不断提高。通过扫描电子显微镜（SEM）观察了微观结构和磨损表面，发现形成了BC和Gr的机械混合层，该混合层作为有效的绝缘表面，保护测试样品表面免受钢盘磨损。随着BC和Gr含量的增加，重量损失下降，在BC含量为15 wt.%和Gr含量为10 wt.%时实现了显著的耐磨性。对重量损失进行了响应面分析以获得最优目标函数。采用人工神经网络方法来确定实验结果的显著性以及磨损参数的重要性。发现实验结果与人工神经网络结果之间的误差在1%以内。
