Abstract

Overlapping adjacent passes of abrasive slurry jets can be used to fabricate micro-pockets or blind micro-slots. This study investigates the propagation of surfaces milled using overlapping passes of a high-pressure abrasive slurry jet on a ductile 6061-T6 target over a wide range of aspect ratios. Features such as shallow pockets with low aspect ratios to deep slots with aspect ratios ∼1.5 were fabricated to investigate the correlations between the aspect ratio, degree of pass overlap, and number of repeating passes with the machined surface evolution characteristics. A comprehensive model was presented that combined computational fluid dynamics (CFD) with surface evolution to predict the evolving machined feature topography after each of the overlapping and repeating passes, and to provide insights into experimental observations. The model explicitly considered the CFD-predicted local particle impact angles and velocities as well as effects due to secondary impacts, high sidewall slopes, and stagnation effects. For larger degrees of overlap, measurements revealed a more than linear rate of increase in depth after each repeat of two adjacent overlapped passes, as opposed to a linear depth increase for smaller overlaps and blind pockets. Large overlaps were found to result in asymmetric features. Up to a critical aspect ratio of ∼0.65, the model predicted the surface evolution of the features to within <8.6% of those measured. Beyond that, randomness in the machined feature shape and size made the process challenging to control and the surface evolution difficult to predict. Nevertheless, the model was able to elucidate the reasons for the randomness and other observed phenomena such as the more than linear growth in etch rate, and the occurrence of feature asymmetry. The findings emphasize that flow confinement, increases in the jet's turbulent kinetic energy, and the formation of vortices at the bottom of the machined features are critical factors influencing the machining process, and that in these cases explicit modeling approaches like the one presented in this study must be used.

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