材料科学
芳纶
表面粗糙度
分类
分层(地质)
机械加工
遗传算法
机械工程
复合材料
计算机科学
纤维
算法
工程类
机器学习
古生物学
生物
俯冲
冶金
构造学
作者
Müge Kahya,Emre Doğankaya,Ömer Refet Çaylan,Zarife Göknur Büke,Hakkı Özgür Ünver
标识
DOI:10.1177/09544089221085325
摘要
The secondary operations of composite parts are performed following thermal cure processes, which generate the final dimensions with desired tolerance and quality specifications. High-strength composites, on the other hand, especially aramid fiber-reinforced polymers (AFRP), are not suitable for conventional machining operations due in part to high operational costs and limited surface quality characterized by fuzziness and delamination. Abrasive Water Jet (AWJ) has been recently shown promising results in obtaining improved surface quality while ensuring significant cost advantages. This study investigates the AWJ processing of AFRP by implementing the analysis of variance and response surface methods. The effects of the control parameters (sand ratio, pressure, stand-off-distance, and feed rate) on the surface quality metrics (surface roughness, kerf angle, and dimensional error) are identified and comparatively evaluated. The surface quality of the AWJ processed AFRP specimens are investigated using Scanning Electron Microscopy (SEM). The trade-offs between the measured tolerances and surface roughness values are identified via a new genetic algorithm approach: Non-dominated Sorting Genetic Algorithm (NSGA-III). Also, operation regions are determined using the generated Pareto curves while improving the quality of various features of an AFRP component, critical to its functional performance during extended service life. As a result, the lowest Ra values obtained were 4.135 µm for trimming, 5.962 µm for pocketing, and 4.696 µm for the hole-making operation. The maximum error in the accuracy of operating regions yields to 7% with independent measurements for validation.
科研通智能强力驱动
Strongly Powered by AbleSci AI