Gaussian distribution-based modeling of cutting depth predictions of kerf profiles for ductile materials machined by abrasive waterjet

Abstract

This study proposes a model for the erosion cutting profile to predict the cutting depth under different process parameters for abrasive waterjet (AWJ) cutting. The model follows the Gaussian distribution and is experimentally validated. Additionally, the effects of the dimensional characteristics and process parameters on the kerf geometry were analyzed. It was found that the water pressure, abrasive flow rate, and focusing tube traverse speed changed the slope of the kerf wall without changing the kerf width. However, the standoff distance (SOD) changes the kerf width, whereas the slope of the kerf wall induces minor changes. Furthermore, based on the first-order derivation of the extracted kerf profile, the relationship between jet energy, cutting depth, and kerf width was analyzed. The experimental results revealed that: 1) the relationship between the reduction in the jet energy distribution and cutting depth is non-linear; 2) the jet energy distribution is smallest at the kerf top edge and bottom section. The predictive cutting depth model and jet energy distribution will enable the subsequent optimization of process parameters in the AWJ process.