Investigation on cutting deformation behavior of Al/SiCp composites considering particle feature distributions

Al/SiCp composite machining is considerably difficult owing to the presence of abrasive particles that results in weak synergetic deformation capacity during cutting. Therefore, to enhance the machinability of Al/SiCp composites, investigations on the cutting deformation behavior are imperative through finite element simulation. Aiming to address the limitations of conventional finite element models in accurately representing the actual microstructure of Al/SiCp composites, this study proposes a realistic microstructure-based finite element model to investigate the cutting deformation and damage behavior. The microstructural characteristics of the composites namely, particle feature distributions, including size distribution, aspect ratio distribution, and spatial aggregation of SiC particles, are analyzed and extracted based on the microstructure image of composite and the Gaussian stochastic model. Then, the particle feature distributions are incorporated into the microstructure-based model for the first time. Besides, all the failure mechanisms (i.e., the brittle fracture of SiC particles, the elastoplastic damage of Al matrix, as well as the particle-matrix decohesion) and the tool-chip contact behavior are comprehensively integrated into the modeling. The experimental results show that as the particle volume fraction and size increase, the chip radius and the number of chip curls decrease, the chips vary from little waviness to prominent saw-tooth type, and more particles are broken or debonded. According to the comparison with experimental results, the finite element model can effectively capture the deformation and failure process, as well as the characteristics of chip morphology, cutting force, and machined surface quality. In addition, the comparisons further demonstrate that SiC particles with large size, slender shape, and aggregation are prone to fracture and detachment in the cutting deformation. Finally, the influences of the particle feature distributions on the machinability of Al/SiCp composites are discussed in detail. It is found that decreasing the dispersion degree of particle size and aspect ratio distribution as well as minimizing the degree of particle clustering degree benefit the machinability of Al/SiCp composites.